MDPI - Publisher of Open Access Journals

14 pages, 6982 KiB

Open AccessArticle

Deep Learning Integration for Normal Breathing Classification Using a Flexible Fiber Sensor

by Jiseon Kim and Jooyong Kim

Processes 2024, 12(12), 2644; https://doi.org/10.3390/pr12122644 (registering DOI) - 24 Nov 2024

Measuring respiratory parameters is crucial for clinical decision making and detecting abnormal patterns for disease prevention. While deep learning methods are commonly used in respiratory analysis, the image-based classification of abnormal breathing remains limited. This study developed a stitched sensor using silver-coated thread, [...] Read more.

Measuring respiratory parameters is crucial for clinical decision making and detecting abnormal patterns for disease prevention. While deep learning methods are commonly used in respiratory analysis, the image-based classification of abnormal breathing remains limited. This study developed a stitched sensor using silver-coated thread, optimized for the knit fabric’s course direction in a belt configuration. By applying a Continuous Wavelet Transform (CWT) and a two-dimension Convolutional Neural Network (2D-CNN), the model achieved 96% accuracy, with potential for further improvement through data expansion. Full article

(This article belongs to the Special Issue Research on Intelligent Fault Diagnosis Based on Neural Network)

► Show Figures

Figure 1

21 pages, 6640 KiB

Open AccessArticle

Combining Network Pharmacology and Transcriptomic Strategies to Explore the Pharmacological Mechanism of Total Ginsenoside Ginseng Root and Its Impact on Antidepressant Effects

by Weijia Chen, Pengli Guo, Lili Su, Xiangjuan Guo, Meiling Shi, Jianan Geng, Ying Zong, Yan Zhao, Rui Du and Zhongmei He

Int. J. Mol. Sci. 2024, 25(23), 12606; https://doi.org/10.3390/ijms252312606 (registering DOI) - 24 Nov 2024

Abstract

Depression is one of the most common neurological diseases, which imposes a substantial social and economic burden on modern society. The purpose of this study was to explore the mechanism of total ginsenoside ginseng root (TGGR) in the treatment of depression through a [...] Read more.

Depression is one of the most common neurological diseases, which imposes a substantial social and economic burden on modern society. The purpose of this study was to explore the mechanism of total ginsenoside ginseng root (TGGR) in the treatment of depression through a comprehensive strategy combining network pharmacology, transcriptomics, and in vivo experimental validation. The Traditional Chinese Medicine Systematic Pharmacology (TCMSP) database and literature were used to collect the main components and targets of TGGR. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were applied to explore the underlying mechanisms. In addition, the chronic unpredictable mild stress (CUMS)-induced C57BL/6 mouse model was used to evaluate the antidepressant activity of TGGR. The results showed that TGGR improved depression-like behavior in mice and increased the decrease in serum 5-hydroxytryptamine (5-HT) and brain-derived neurotrophic factor (BDNF) levels caused by CUMS. Combined network pharmacology and transcriptomic analysis showed that the AMP-activated kinase (AMPK) signaling pathway mainly enriched the core target. Immunohistochemistry, Western blotting, and reverse transcription quantitative polymerase chain reaction (RT-qPCR) were used to confirm whether TGGR exerts antidepressant effects by regulating this pathway. The results showed that TGGR has a regulatory impact on related proteins in the AMPK pathway, and the regulatory effect of TGGR on proteins was inhibited after the administration of related pathway inhibitors. In summary, total ginsenosides may regulate the AMPK signaling pathway and activate the sirtuin 1 (SIRT1) peroxisome proliferator-activated receptor-gamma coactivator 1-alpha (PGC-1α) pathway to have therapeutic effects on depression. Full article

(This article belongs to the Special Issue Pathophysiology and Pharmacology in Psychiatry)

► Show Figures

Figure 1

11 pages, 2800 KiB

Open AccessArticle

A Data-Assisted and Inter-Symbol Spectrum Analysis-Based Speed Estimation Method for Radiated Signals from Moving Sources

by Gaohui Liu and Boquan Chen

Appl. Sci. 2024, 14(23), 10869; https://doi.org/10.3390/app142310869 (registering DOI) - 24 Nov 2024

Abstract

Aiming at the problem of estimating the speed of M-ary Phase Shift Keying (MPSK) communication radiated sources and their carrying platform targets, this paper proposes a data-assisted and inter-symbol spectrum analysis-based speed estimation method for MPSK communication radiated sources. The method first demodulates [...] Read more.

Aiming at the problem of estimating the speed of M-ary Phase Shift Keying (MPSK) communication radiated sources and their carrying platform targets, this paper proposes a data-assisted and inter-symbol spectrum analysis-based speed estimation method for MPSK communication radiated sources. The method first demodulates a signal-carrying message symbol from the received MPSK signal; then segments the signal according to the symbol synchronization information and the symbol period; and then compensates the phase of the symbol waveform corresponding to the message data according to the demodulated message symbol; finally combines the phase-compensated symbol waveform data into a two-dimensional matrix and finds the Doppler frequency of the data at the same sampling moment of different symbols using the vertical Fourier transform to obtain the moving target speed. The speed measurement accuracy and anti-noise performance of the method are analyzed through simulation experiments, and the simulation results show that the speed measurement accuracy of the method is 98.5%. Full article

► Show Figures

Figure 1

11 pages, 408 KiB

Open AccessArticle

Munich cCT Rule for Patients with Recreational Drug and Ethanol Poisoning

by Tobias Zellner, Felix Wegscheider, Michael Dommasch, Florian Eyer, Rebecca Dieminger and Sabrina Schmoll

J. Clin. Med. 2024, 13(23), 7096; https://doi.org/10.3390/jcm13237096 (registering DOI) - 24 Nov 2024

Abstract

Background: Patients with recreational drug and ethanol poisoning often present with reduced consciousness, coma, or disorientation. It is often unclear if there was recent head trauma. Algorithms to perform cranial computed tomography (cCT) like the Canadian CT Head Rule (CCHR), the National Emergency [...] Read more.

Background: Patients with recreational drug and ethanol poisoning often present with reduced consciousness, coma, or disorientation. It is often unclear if there was recent head trauma. Algorithms to perform cranial computed tomography (cCT) like the Canadian CT Head Rule (CCHR), the National Emergency X-Radiography Utilization Study Head CT Decision Instrument (NEXUS DI), or the New Orleans Criteria (NOC) exist for patients with head trauma. It is unclear whether these algorithms can be applied to this patient collective. Methods: This is a retrospective data analysis of patients admitted to our emergency department with drug or ethanol poisoning in 2019. Minors < 16 years were excluded. The primary outcome was fracture/bleeding in cCT, the secondary outcome was neurosurgical intervention. These results were calculated: 1. Sensitivity and negative predictive value (NPV) of the CCHR, NEXUS DI, and NOC. 2. Uni- and multivariate analysis of risk factors for critical findings. 3. The Munich cCT Rule sensitivity and NPV. Results: A total of 420 patients were included. cCT was performed in 120 patients. Eight patients had fracture/bleeding in cCT, two required neurosurgical intervention. The number of patients at risk, sensitivity, and NPV for critical cCT findings were as follows: CCHR 57/25%/98.3%, NEXUS DI 239/100%/100%, NOC 420/100%/100%. The sensitivity and NPV for neurosurgical intervention were as follows: CCHR 50%/99.7%, NEXUS DI 100%/100%, NOC 100%/100%. In univariate analysis, these findings correlated significantly with the following critical findings: accident, injury, injury above clavicle, head wound, anisocoria, ethanol in serum > 2 g/L, hypotension, drug ingestion, GCS < 8, focal neurological deficit, age > 60, and cerebellar symptoms. Via chi-square recursive partitioning analysis, we created the Munich cCT Rule which is positive for intoxicated patients if both an accident and an ethanol level > 2 g/L are present. This identified 70 patients at risk. It excluded fracture/bleeding and neurosurgical intervention with a sensitivity and NPV of 100%. Conclusions: Fracture/bleeding in cCT in intoxicated patients is rare. Performing unnecessary cCTs should be avoided. The Munich cCT Rule for patients with recreational drug and ethanol poisoning may help rule out critical findings and is superior to the NEXUS DI and NOC. It also has a 100% sensitivity which the CCHR (25%) is lacking. Full article

(This article belongs to the Special Issue Clinical Advances in Trauma and Emergency Medicine)

► Show Figures

Figure 1

14 pages, 4106 KiB

Open AccessArticle

Quantitative Classification and Prediction of Starkrimson Pear Maturity by Near-Infrared Spectroscopy

by Ruitao Lu, Linqian Qiu, Shijia Dong, Qiyang Xue, Zhaohui Lu, Rui Zhai, Zhigang Wang, Chengquan Yang and Lingfei Xu

Foods 2024, 13(23), 3761; https://doi.org/10.3390/foods13233761 (registering DOI) - 24 Nov 2024

Abstract

Scientific evaluation of pear maturity is important for commercial reasons. Near-infrared spectroscopy is a non-destructive method that could be used for rapid assessment of pear maturity. The aim of this study was to develop a reasonable and effective method for the assessment of [...] Read more.

Scientific evaluation of pear maturity is important for commercial reasons. Near-infrared spectroscopy is a non-destructive method that could be used for rapid assessment of pear maturity. The aim of this study was to develop a reasonable and effective method for the assessment of Starkrimson pear maturity using near-infrared technology. Partial least squares regression and five classification methods were used for analysis of the data. Among the indices used with the competitive adaptive reweighting–partial least squares regression method for quantitation, the visual ripeness index had the best modeling effect (Rp2: 0.87; root mean square error of prediction: 0.39). The classification model constructed with the visual ripeness index and post-ripeness score gave a cross-validation neural network model with the best classification effect and the highest accuracy (classification accuracy: 88.7%). The results showed that combination of quality indices with near-infrared spectroscopy was effective for rapidly evaluating the maturity of Starkrimson pears. Full article

(This article belongs to the Section Food Analytical Methods)

► Show Figures

Figure 1

15 pages, 10816 KiB

Open AccessArticle

Naphthalene-Containing Epoxy Resin: Phase Structure, Rheology, and Thermophysical Properties

by Svetlana O. Ilyina, Irina Y. Gorbunova, Anastasiya Y. Yadykova, Anna V. Vlasova, Michael L. Kerber and Sergey O. Ilyin

Polymers 2024, 16(23), 3264; https://doi.org/10.3390/polym16233264 (registering DOI) - 24 Nov 2024

Abstract

Naphthalene is a fungicide that can also be a phase-change agent owing to its high crystallization enthalpy at about 80 °C. The relatively rapid evaporation of naphthalene as a fungicide and its shape instability after melting are problems solved in this work by [...] Read more.

Naphthalene is a fungicide that can also be a phase-change agent owing to its high crystallization enthalpy at about 80 °C. The relatively rapid evaporation of naphthalene as a fungicide and its shape instability after melting are problems solved in this work by its placement into a cured epoxy matrix. The work’s research materials included diglycidyl ether of bisphenol A as an epoxy resin, 4,4′-diaminodiphenyl sulfone as its hardener, and naphthalene as a phase-change agent or a fungicide. Their miscibility was investigated by laser interferometry, the rheological properties of their blends before and during the curing by rotational rheometry, the thermophysical features of the curing process and the resulting phase-change materials by differential scanning calorimetry, and the blends’ morphologies by transmission optical and scanning electron microscopies. Naphthalene and epoxy resin were miscible when heated above 80 °C. This fact allowed obtaining highly concentrated mixtures containing up to 60% naphthalene by high-temperature homogeneous curing with 4,4′-diaminodiphenyl sulfone. The initial solubility of naphthalene was only 19% in uncured epoxy resin but increased strongly upon heating, reducing the viscosity of the reaction mixture, delaying its gelation, and slowing cross-linking. At 20–40% mass fraction of naphthalene, it almost entirely retained its dissolved state after cross-linking as a metastable solution, causing plasticization of the cured epoxy polymer and lowering its glass transition temperature. At 60% naphthalene, about half dissolved within the cured polymer, while the other half formed coarse particles capable of crystallization and thermal energy storage. In summary, the resulting phase-change material stored 42.6 J/g of thermal energy within 62–90 °C and had a glass transition temperature of 46.4 °C at a maximum naphthalene mass fraction of 60% within the epoxy matrix. Full article

(This article belongs to the Special Issue Epoxy Resins and Epoxy-Resins-Based Polymer Materials II)

► Show Figures

Figure 1

13 pages, 7571 KiB

Open AccessArticle

The Coupling Characteristics of Vapor Pressure Deficit and Soil Moisture in China

by Chong Nie, Chunxu Hao, Xingan Chen, Juan Zhou, Rui Xu, Chenning Deng, Zeqian Zhang, Yanzhong Zhu and Lijing Wang

Remote Sens. 2024, 16(23), 4387; https://doi.org/10.3390/rs16234387 (registering DOI) - 24 Nov 2024

Abstract

Vapor pressure deficit (VPD) and soil moisture (SM) are the two main parameters related to ecosystem water stresses. They are tightly coupled through land–atmosphere interactions and have large impacts on terrestrial ecosystems and global water and carbon cycles. However, the coupling characteristics between [...] Read more.

Vapor pressure deficit (VPD) and soil moisture (SM) are the two main parameters related to ecosystem water stresses. They are tightly coupled through land–atmosphere interactions and have large impacts on terrestrial ecosystems and global water and carbon cycles. However, the coupling characteristics between the two have not been thoroughly studied, particularly in the context of climate warming. In this study, based on remote sensing and reanalysis datasets, spatial and temporal variations in the VPD and SM and their correlation coefficients in the growing season in China from 1982 to 2018 were evaluated. Then, the probabilities of compound water stress (high VPD and low SM) were investigated under three scenarios based on a copula analysis. The results show that, over the 37 years, the VPD significantly increased during the growing season, while the SM significantly decreased. The coupling relationship between the VPD and SM was relatively weak in extreme arid and arid regions. In contrast, this relationship was stronger in semi-arid and semi-humid regions, where the probabilities of compound water stress were significantly higher (p < 0.05). The probabilities of compound water stress (high VPD and low SM) were significantly higher than the probabilities when the VPD and SM were independent, and this difference increased with the severity of the water stress in the same region. The obtained results can be further applied to improve Earth system models and formulate agricultural irrigation schemes. Full article

(This article belongs to the Special Issue Global Monitoring of Inland Water Using Remote Sensing and Artificial Intelligence)

► Show Figures

Figure 1

13 pages, 4516 KiB

Open AccessArticle

Anti-Inflammatory Effects of Aptamin C in Pulmonary Fibrosis Induced by Bleomycin

by Seulgi Shin, Hyejung Jo, Tomoyo Agura, Seoyoun Jeong, Hyovin Ahn, Soyoung Pang, June Lee, Jeong-Ho Park, Yejin Kim and Jae Seung Kang

Pharmaceuticals 2024, 17(12), 1577; https://doi.org/10.3390/ph17121577 (registering DOI) - 24 Nov 2024

Abstract

Background/Objectives: Vitamin C is a well-known antioxidant with antiviral, anticancer, and anti-inflammatory properties. However, its therapeutic applications are limited by rapid oxidation due to heat and light sensitivity. Aptamin C, which employs aptamers to bind vitamin C, has demonstrated enhanced stability and [...] Read more.

Background/Objectives: Vitamin C is a well-known antioxidant with antiviral, anticancer, and anti-inflammatory properties. However, its therapeutic applications are limited by rapid oxidation due to heat and light sensitivity. Aptamin C, which employs aptamers to bind vitamin C, has demonstrated enhanced stability and efficacy. This study investigates the potential of Aptamin C to inhibit the progression of pulmonary fibrosis, a prominent inflammatory lung disease with no effective treatment. Methods: Mice bearing bleomycin-induced pulmonary fibrosis were administered vitamin C or Aptamin C, and their weight changes and survival rates were monitored. Inflammatory cell infiltration was assessed in the bronchoalveolar lavage fluid (BALF), and the degree of alveolar fibrosis was measured by H&E and Masson’s trichrome staining. To elucidate the mechanism of action of Aptamin C, Western blot analysis was performed in HaCaT and lung tissues from bleomycin-induced pulmonary fibrosis mice. Results: The Aptamin C-treated group showed a notably higher survival rate at 50%, whereas all subjects in the vitamin C-treated group died. Histological examination of lung tissue showed that inflammation was significantly suppressed in the Aptamin C-supplemented group compared to the vitamin C-supplemented group, with a 10% greater reduction in cell infiltrations, along with noticeably less tissue damage. Additionally, it was observed that Aptamin C increased SVCT-1 expression in the HaCaT cells and the lung tissues. Conclusions: Taken together, Aptamin C not only increases the stability of vitamin C but also induces an increase in SVCT-1 expression, facilitating greater vitamin C absorption into cells and tissues, thereby inhibiting the progression of symptoms and associated inflammatory responses in pulmonary fibrosis. Full article

(This article belongs to the Section Pharmacology)

► Show Figures

Figure 1

12 pages, 566 KiB

Open AccessArticle

Chronic Total Occlusions in Non-Infarct-Related Coronary Arteries and Long-Term Cardiovascular Mortality in Patients Receiving Percutaneous Coronary Intervention in Acute Coronary Syndromes

by Irzal Hadžibegović, Ivana Jurin, Mihajlo Kovačić, Tomislav Letilović, Ante Lisičić, Aleksandar Blivajs, Domagoj Mišković, Anđela Jurišić, Igor Rudež and Šime Manola

J. Clin. Med. 2024, 13(23), 7094; https://doi.org/10.3390/jcm13237094 (registering DOI) - 24 Nov 2024

Abstract

Background and aim: Patients with non-infarct-related artery chronic total occlusion (non-IRA CTO) found during percutaneous coronary intervention (PCI) in acute coronary syndromes (ACSs) are not rare and have worse clinical outcomes. We aimed to analyze their long-term clinical outcomes in regard to [...] Read more.

Background and aim: Patients with non-infarct-related artery chronic total occlusion (non-IRA CTO) found during percutaneous coronary intervention (PCI) in acute coronary syndromes (ACSs) are not rare and have worse clinical outcomes. We aimed to analyze their long-term clinical outcomes in regard to clinical characteristics, revascularization strategies, and adherence to medical therapy. Patients and methods: The dual-center ACS registry of patients treated from Jan 2017 to May 2023 was used to identify 1950 patients with timely PCI in ACS who survived to discharge with documented adequate demographic, clinical, and angiographic characteristics, treatment strategies, and medical therapy adherence during a median follow-up time of 49 months. Results: There were 171 (9%) patients with non-IRA CTO. In comparison to patients without non-IRA CTO, they were older, with more diabetes mellitus (DM), higher Syntax scores (median 27.5 vs. 11.5), and lower left ventricular ejection fraction (LVEF) at discharge (median LVEF 50% vs. 55%). There was also a lower proportion of patients with high adherence to medical therapy (32% vs. 46%). Patients with non-IRA CTO had significantly higher cardiovascular mortality during follow-up (18% vs. 8%, RR 1.87, 95% CI 1.27–2.75). After adjusting for relevant clinical and treatment characteristics in a multivariate Cox regression analysis, only lower LVEF, worse renal function, the presence of DM, and lower adherence to medical therapy were independently associated with higher cardiovascular mortality during follow-up, with low adherence to medical therapy as the strongest predictor (RR 3.18, 95% CI 1.76–5.75). Time to cardiovascular death was significantly lower in patients who did not receive non-IRA CTO revascularization, although CTO revascularization did not show independent association with survival in the multivariate analysis. Conclusions: Patients with non-IRA CTO found during ACS treatment have more unfavorable clinical characteristics, worse adherence to medical therapy, and higher cardiovascular mortality. They need a more scrutinized approach during follow-up to increase adherence to optimal medical therapy and to receive revascularization of the non-IRA CTO whenever it is clinically indicated and reasonably achievable without excess risks. Full article

(This article belongs to the Special Issue Research Advances in Coronary Revascularization)

► Show Figures

Figure 1

9 pages, 3259 KiB

Open AccessReview

Lung Cancer Associated with Cystic Airspaces: Current Insights into Diagnosis, Pathophysiology, and Treatment Strategies

by Kun Wang, Xuechun Leng, Hang Yi, Guochao Zhang, Zhongwu Hu and Yousheng Mao

Cancers 2024, 16(23), 3930; https://doi.org/10.3390/cancers16233930 (registering DOI) - 24 Nov 2024

Abstract

Lung cancer associated with cystic airspaces (LCCA) is a rare subtype of non-small-cell lung cancer (NSCLC), accounting for 1–4% of cases. LCCA is characterized by the presence of cystic airspaces within or at the periphery of the tumor on imaging. LCCA poses significant [...] Read more.

Lung cancer associated with cystic airspaces (LCCA) is a rare subtype of non-small-cell lung cancer (NSCLC), accounting for 1–4% of cases. LCCA is characterized by the presence of cystic airspaces within or at the periphery of the tumor on imaging. LCCA poses significant clinical challenges due to its high risk of misdiagnosis or missed diagnosis, often leading to a worse prognosis compared to other forms of lung cancer. While previous studies have identified correlations between the pathological features and imaging characteristics of LCCA, research on its associated driver gene mutations and responses to chemotherapy and immunotherapy remains limited. Furthermore, the development of an appropriate T-staging system is necessary to improve prognostic outcomes. This review provides an overview of the current research on the definition, imaging classification, pathological and molecular mechanisms, and prognosis of LCCA, aiming to provide a reference for clinical decision-making. Full article

(This article belongs to the Section Systematic Review or Meta-Analysis in Cancer Research)

► Show Figures

Figure 1

18 pages, 3925 KiB

Open AccessArticle

Novel PCR-Based Technology for the Detection of Sunflower in Edible and Used Cooking Oils

by Tamara Kutateladze, Kakha Karchkhadze, Kakha Bitskinashvili, Boris Vishnepolsky, Tata Ninidze, David Mikeladze and Nelly Datukishvili

Foods 2024, 13(23), 3760; https://doi.org/10.3390/foods13233760 (registering DOI) - 24 Nov 2024

Abstract

Reliable detection of sunflower (Helianthus annuus) in edible and used cooking oil (UCO) is crucial for the sustainable production of food and biodiesel. In this study, a variety of sunflower oils (crude, cold pressed, extra virgin, refined, and UCO) were examined [...] Read more.

Reliable detection of sunflower (Helianthus annuus) in edible and used cooking oil (UCO) is crucial for the sustainable production of food and biodiesel. In this study, a variety of sunflower oils (crude, cold pressed, extra virgin, refined, and UCO) were examined using different methods of DNA extraction and PCR amplification to develop an efficient technology for the identification of sunflower in oils. DNA extraction kits such as NucleoSpin Food, DNeasy mericon Food, and Olive Oil DNA Isolation as well as modified CTAB method were found to be able to isolate amplifiable genomic DNA from highly processed oils. Novel uniplex, double, and nested PCR systems targeting the sunflower-specific helianthinin gene were developed for efficient identification of sunflower. New sunflower DNA markers were revealed by uniplex PCRs. The combination of modified CTAB and nested PCR was demonstrated as a reliable, rapid, and cost-effective technology for detecting traces of sunflower in 700 μL of highly processed oil, including refined and used cooking oil. The study will contribute to both the food industry and the energy sector as developed methods can be used for oil authenticity testing in food and biodiesel production. Full article

(This article belongs to the Special Issue The 4th International Electronic Conference on Foods—"Focus on Sustainable Food Systems: Current Trends and Advances" (Foods2023))

► Show Figures

Figure 1

15 pages, 7711 KiB

Open AccessArticle

Development of Automated 3D LiDAR System for Dimensional Quality Inspection of Prefabricated Concrete Elements

by Shuangping Li, Bin Zhang, Junxing Zheng, Dong Wang and Zuqiang Liu

Sensors 2024, 24(23), 7486; https://doi.org/10.3390/s24237486 (registering DOI) - 24 Nov 2024

Abstract

The dimensional quality inspection of prefabricated concrete (PC) elements is crucial for ensuring overall assembly quality and enhancing on-site construction efficiency. However, current practices remain heavily reliant on manual inspection, which results in high operator dependency and low efficiency. Existing Light Detection and [...] Read more.

The dimensional quality inspection of prefabricated concrete (PC) elements is crucial for ensuring overall assembly quality and enhancing on-site construction efficiency. However, current practices remain heavily reliant on manual inspection, which results in high operator dependency and low efficiency. Existing Light Detection and Ranging (LiDAR)-based methods also require skilled professionals for scanning and subsequent point cloud processing, thereby presenting technical challenges. This study developed a 3D LiDAR system for the automatic identification and measurement of the dimensional quality of PC elements. The system consists of (1) a hardware system integrated with camera and LiDAR components to acquire 3D point cloud data and (2) a user-friendly graphical user interface (GUI) software system incorporating a series of algorithms for automated point cloud processing using PyQt5. Field experiments comparing the system’s measurements with manual measurements on prefabricated bridge columns demonstrated that the system’s average measurement error was approximately 5 mm. The developed system can provide a quick, accurate, and automated inspection tool for dimensional quality assessment of PC elements, thereby enhancing on-site construction efficiency. Full article

(This article belongs to the Topic 3D Computer Vision and Smart Building and City, 2nd Volume)

► Show Figures

Figure 1

11 pages, 875 KiB

Open AccessArticle

Unraveling the Relationship Between English Learning Burnout and Academic Achievement: The Mediating Role of English Learning Resilience

by Honggang Liu, Ling Jin, Xiaoyu Han and Haoyue Wang

Behav. Sci. 2024, 14(12), 1124; https://doi.org/10.3390/bs14121124 (registering DOI) - 24 Nov 2024

Abstract

Although burgeoning research has been conducted on the role of negative emotions (e.g., English learning burnout) in affecting students’ academic achievement, there are limited studies on the intricate working mechanism between these two factors. Academic resilience is an adaptive response to academic adversity [...] Read more.

Although burgeoning research has been conducted on the role of negative emotions (e.g., English learning burnout) in affecting students’ academic achievement, there are limited studies on the intricate working mechanism between these two factors. Academic resilience is an adaptive response to academic adversity and might therefore offer protection against negative emotions (e.g., English learning burnout). Hence, this study focused on the complex interplay among students’ English learning burnout, English learning resilience, and academic achievement. A total of 334 senior high school students were recruited in the current study. The findings displayed that students’ English learning resilience mediated the relationship between English learning burnout and English academic achievement. This study may generate suggestions and implications for English teaching and learning. Full article

(This article belongs to the Section Educational Psychology)

► Show Figures

Figure 1

23 pages, 9861 KiB

Open AccessArticle

A Synergistic Framework for Coupling Crop Growth, Radiative Transfer, and Machine Learning to Estimate Wheat Crop Traits in Pakistan

by Rana Ahmad Faraz Ishaq, Guanhua Zhou, Aamir Ali, Syed Roshaan Ali Shah, Cheng Jiang, Zhongqi Ma, Kang Sun and Hongzhi Jiang

Remote Sens. 2024, 16(23), 4386; https://doi.org/10.3390/rs16234386 (registering DOI) - 24 Nov 2024

Abstract

The integration of the Crop Growth Model (CGM), Radiative Transfer Model (RTM), and Machine Learning Algorithm (MLA) for estimating crop traits represents a cutting-edge area of research. This integration requires in-depth study to address RTM limitations, particularly of similar spectral responses from multiple [...] Read more.

The integration of the Crop Growth Model (CGM), Radiative Transfer Model (RTM), and Machine Learning Algorithm (MLA) for estimating crop traits represents a cutting-edge area of research. This integration requires in-depth study to address RTM limitations, particularly of similar spectral responses from multiple input combinations. This study proposes the integration of CGM and RTM for crop trait retrieval and evaluates the performance of CGM output-based RTM spectra generation for multiple crop traits estimation without biased sampling using machine learning models. Moreover, PROSAIL spectra as training against Harmonized Landsat Sentinel-2 (HLS) as testing was also compared with HLS data only as an alternative. It was found that satellite data (HLS, 80:20) not only consistently performed better, but PROSAIL (train) and HLS (test) also had satisfactory results for multiple crop traits from uniform training samples in spite of differences in simulated and real data. PROSAIL-HLS has an RMSE of 0.67 for leaf area index (LAI), 5.66 µg/cm² for chlorophyll ab (Cab), 0.0003 g/cm² for dry matter content (Cm), and 0.002 g/cm² for leaf water content (Cw) against the HLS only, with an RMSE of 0.40 for LAI, 3.28 µg/cm² for Cab, 0.0002 g/cm² for Cm, and 0.001 g/cm² for Cw. Optimized machine learning models, namely Extreme Gradient Boost (XGBoost) for LAI, Support Vector Machine (SVM) for Cab, and Random Forest (RF) for Cm and Cw, were deployed for temporal mapping of traits to be used for wheat productivity enhancement. Full article

(This article belongs to the Section Remote Sensing in Agriculture and Vegetation)

► Show Figures

Figure 1

18 pages, 9911 KiB

Open AccessArticle

Agri-Food and Food Waste Lignocellulosic Materials for Lipase Immobilization as a Sustainable Source of Enzyme Support—A Comparative Study

by Bartłomiej Zieniuk, Jolanta Małajowicz, Karina Jasińska, Katarzyna Wierzchowska, Şuheda Uğur and Agata Fabiszewska

Foods 2024, 13(23), 3759; https://doi.org/10.3390/foods13233759 (registering DOI) - 24 Nov 2024

Abstract

Enzyme immobilization is a crucial method in biotechnology and organic chemistry that significantly improves the stability, reusability, and overall effectiveness of enzymes across various applications. Lipases are one of the most frequently applied enzymes in food. The current study investigated the potential of [...] Read more.

Enzyme immobilization is a crucial method in biotechnology and organic chemistry that significantly improves the stability, reusability, and overall effectiveness of enzymes across various applications. Lipases are one of the most frequently applied enzymes in food. The current study investigated the potential of utilizing selected agri-food and waste materials—buckwheat husks, pea hulls, loofah sponges, and yerba mate waste—as carriers for the immobilization of Sustine^® 121 lipase and Yarrowia lipolytica yeast biomass as whole-cell biocatalyst and lipase sources. Various lignocellulosic materials were pretreated through extraction processes, including Soxhlet extraction with hexane and ethanol, as well as alkaline and acid treatments for loofah sponges. The immobilization process involved adsorbing lipases or yeast cells onto the carriers and then evaluating their hydrolytic and synthetic activities. Preparations’ activities evaluation revealed that alkaline-pretreated loofah sponge yielded the highest hydrolytic activity (0.022 U/mg), while yerba mate leaves under brewing conditions demonstrated superior synthetic activity (0.51 U/mg). The findings underscore the potential of lignocellulosic materials from the agri-food industry as effective supports for enzyme immobilization, emphasizing the importance of material selection and pretreatment methods in optimizing enzymatic performance through giving an example of circular economy application in food processing and waste management. Full article

(This article belongs to the Special Issue Sustainable Food Waste Management: Recovery, Recycling and Valorization)

► Show Figures

Figure 1

13 pages, 1570 KiB

Open AccessArticle

Assessment of the Aging State for Transformer Oil-Barrier Insulation by Raman Spectroscopy and Optimized Support Vector Machine

by Deliang Liu, Biao Lu, Wenping Wu, Wei Zhou, Wansu Liu, Yiye Sun, Shilong Wu, Guolong Shi and Leiming Yuan

Sensors 2024, 24(23), 7485; https://doi.org/10.3390/s24237485 (registering DOI) - 24 Nov 2024

Abstract

Accurate assessment of the aging state of transformer oil-barrier insulation is crucial for ensuring the safe and reliable operation of power systems. This study presents the development of indoor accelerated thermal aging experiments to simulate the degradation of oil-immersed barrier insulation within transformers. [...] Read more.

Accurate assessment of the aging state of transformer oil-barrier insulation is crucial for ensuring the safe and reliable operation of power systems. This study presents the development of indoor accelerated thermal aging experiments to simulate the degradation of oil-immersed barrier insulation within transformers. A series of samples reflecting various aging states was obtained and categorized into six distinct groups. Raman spectroscopy analytical technology was employed to characterize the information indicative of different aging states of the oil-immersed barrier insulation. The raw Raman spectra were processed using asymmetric reweighted penalty least squares to correct baseline shifts, Savitzky–Golay (S-G) smoothing to eliminate fluctuation noise, and principal component analysis (PCA) to reduce data dimensionality by extracting principal components. A support vector machine (SVM) classifier was developed to discriminate between the Raman spectra and category labels. The SVM parameters were optimized using grid search, particle swarm optimization (PSO), and genetic algorithm (GA), yielding the optimal parameters (C and gamma). Notably, the grid search method demonstrated high efficiency in identifying the best combination of SVM parameters (c and g). Comparative analyses with varying numbers of principal components in SVM classifiers revealed that incorporating an optimal subset of PCA features achieved the highest classification accuracy of 94.44% for external validation samples, with only eight samples being misclassified into adjacent categories. This study offers technical support and a theoretical foundation for the effective assessment of the aging state of oil-barrier type insulation in transformers, contributing to the advancement of condition monitoring and maintenance strategies in power systems. Full article

(This article belongs to the Section Physical Sensors)

► Show Figures

Figure 1

15 pages, 767 KiB

Open AccessArticle

A Model to Strengthen the Quality of Midwifery Education: A Grounded Theory Approach

by Waleola B. Ige and Winnie B. Ngcobo

Int. Med. Educ. 2024, 3(4), 473-487; https://doi.org/10.3390/ime3040036 (registering DOI) - 24 Nov 2024

Abstract

A well-educated midwifery workforce is critical to providing quality health services. However, the quality of midwifery education in Nigeria is identified as a factor contributing to the country’s poor maternal and neonatal health outcomes and inability to meet global development goals. This study [...] Read more.

A well-educated midwifery workforce is critical to providing quality health services. However, the quality of midwifery education in Nigeria is identified as a factor contributing to the country’s poor maternal and neonatal health outcomes and inability to meet global development goals. This study aimed to analyse the process used to strengthen the quality of midwifery education with the aim of generating a middle-range model to prepare competent and confident midwifery graduates. The Strauss and Corbin version of the Grounded Theory approach that is underpinned by the Social Constructivism Paradigm was adopted for this qualitative study. Strengthening the quality of midwifery education (SQME) emerged as the model’s core phenomenon. Major concepts, including the midwifery education context, nature of the curriculum, SQME process, pillars, and outcomes, supported the core phenomenon. Strengthening the quality of midwifery education can be achieved over a long time provided the pillars of SQME are deep-rooted to sustain the process of strengthening the quality of midwifery education. The model can be used to strengthen the quality of midwifery education and may be adapted to nursing/allied health programmes in Nigeria and other developing countries. Full article

► Show Figures

Figure 1

21 pages, 329 KiB

Open AccessArticle

The Strength Within: CSR Governance as an Environmental Performance Driver in Weak Institutional Contexts

by Eun-jung Hyun and Si Yu

Systems 2024, 12(12), 515; https://doi.org/10.3390/systems12120515 (registering DOI) - 24 Nov 2024

Abstract

This study investigates how the relationship between firm-level corporate social responsibility (CSR) governance and corporate environmental performance (CEP) varies across diverse national contexts. Drawing on institutional theory, organizational adaptation theory, and the concept of institutional voids, we analyze an extensive dataset of 5326 [...] Read more.

This study investigates how the relationship between firm-level corporate social responsibility (CSR) governance and corporate environmental performance (CEP) varies across diverse national contexts. Drawing on institutional theory, organizational adaptation theory, and the concept of institutional voids, we analyze an extensive dataset of 5326 firms from 26 OECD countries over a seven-year period (2013–2019). Employing panel data analysis, we examine the moderating effects of country-level factors on the CSR governance–CEP relationship. Our findings reveal a significant positive association between a firm’s CSR governance quality and environmental performance, which is notably stronger in countries characterized by weaker environmental governance, less prominent societal environmental values, and fewer climate mitigation laws and policies. These results suggest that firms with strong CSR governance effectively fill institutional voids in environmental governance, going beyond mere compliance to drive environmental performance improvements where external pressures are weak. Our study contributes to the literature by advancing the current understanding of the contextual nature of CSR, extending the application of institutional void theory to environmental governance landscapes in developed economies, and providing a more nuanced perspective on when and where CSR governance matters most for environmental outcomes. These insights offer valuable implications for managers in diverse institutional contexts and for policymakers seeking to enhance corporate environmental performance through complementary governance mechanisms. Full article

(This article belongs to the Special Issue Business Innovation: From Management Systems to Corporate Social Responsibility)

14 pages, 2109 KiB

Open AccessSystematic Review

Antibiotic Residues in Raw Cow’s Milk: A Systematic Review of the Last Decade

by Lucyana Vieira Costa, Clarice Gebara, Ozana de Fátima Zacaroni, Natylane Eufransino Freitas, Adriele Nascimento da Silva, Cristiano Sales Prado, Iolanda Aparecida Nunes, Valéria Quintana Cavicchioli, Francine Oliveira Souza Duarte, Moacir Evandro Lage, Fabiane Rodrigues de Alencar, Bruna Aparecida Souza Machado, Katharine Valéria Saraiva Hodel and Cíntia Minafra

Foods 2024, 13(23), 3758; https://doi.org/10.3390/foods13233758 (registering DOI) - 24 Nov 2024

Abstract

The inappropriate use of antimicrobials in dairy animals can lead to residues in raw milk and in dairy products. Foods containing residues of this nature, whether in the short, medium, or long term, cause serious health harm. Absence of these compounds in foods [...] Read more.

The inappropriate use of antimicrobials in dairy animals can lead to residues in raw milk and in dairy products. Foods containing residues of this nature, whether in the short, medium, or long term, cause serious health harm. Absence of these compounds in foods should be a premise for declaring safety. This systematic review aimed to identify the antibiotic residues most frequently found in raw bovine milk and the methodologies used to detect such residues over the ten years from 2013 to 2023. PRISMA guidelines for systematic reviews were followed, by searching the Web of Science, PubMed Central, Scopus, and Springer databases. The search strategy identified 248 articles, and after applying the selection and quality assessment criteria, 16 studies were selected. The number of samples analyzed was 411,530, of which 0.21% tested positive for some type of antibiotic. Eight classes and 38 different types of antibiotics were identified. The most common class was tetracycline, with emphasis on sulfonamides and quinolones, which have shown increasing prevalence among residues in milk in recent years. A total of 56.25% of the studies employed rapid kits to detect residues, 18.75% chromatography, and 25% both techniques. Antibiotic residues in bovine raw milk should be a great concern for animal, environmental, and human health. Full article

(This article belongs to the Special Issue The Analysis and Risk Assessment of Organic Pollutants in Food Products)

► Show Figures

Graphical abstract

18 pages, 3841 KiB

Open AccessArticle

The New Interpretation of the Photothermal Spectra of CdTe Samples After Different Surface Treatments

by Jacek Zakrzewski, Mirosław Maliński, Mohammed Boumhamdi, Janusz Strzelecki and Karol Strzałkowski

Crystals 2024, 14(12), 1019; https://doi.org/10.3390/cryst14121019 (registering DOI) - 24 Nov 2024

Abstract

This article presents new research on the surface condition of bulk crystal samples after the following stages of surface treatment: grinding, polishing, and etching. Furthermore, it shows how the surface condition affects the photothermal signal’s spectral amplitude and phase characteristics (PZE). A new [...] Read more.

This article presents new research on the surface condition of bulk crystal samples after the following stages of surface treatment: grinding, polishing, and etching. Furthermore, it shows how the surface condition affects the photothermal signal’s spectral amplitude and phase characteristics (PZE). A new theoretical interpretation of the photothermal spectra of CdTe samples after different surface treatments is proposed. We demonstrate that the piezoelectric method is susceptible to the surface condition, and it allows for the estimation of the thickness of surface-damaged layers of samples, and for the analysis of their thermal parameters. The roughness of surfaces obtained from the AFM pictures is estimated and compared to the photothermal results. Full article

(This article belongs to the Section Inorganic Crystalline Materials)

► Show Figures

Figure 1

20 pages, 31755 KiB

Open AccessArticle

An Improved 2D Pose Estimation Algorithm for Extracting Phenotypic Parameters of Tomato Plants in Complex Backgrounds

by Yawen Cheng, Ni Ren, Anqi Hu, Lingli Zhou, Chao Qi, Shuo Zhang and Qian Wu

Remote Sens. 2024, 16(23), 4385; https://doi.org/10.3390/rs16234385 (registering DOI) - 24 Nov 2024

Abstract

Phenotypic traits, such as plant height, internode length, and node count, are essential indicators of the growth status of tomato plants, carrying significant implications for research on genetic breeding and cultivation management. Deep learning algorithms such as object detection and segmentation have been [...] Read more.

Phenotypic traits, such as plant height, internode length, and node count, are essential indicators of the growth status of tomato plants, carrying significant implications for research on genetic breeding and cultivation management. Deep learning algorithms such as object detection and segmentation have been widely utilized to extract plant phenotypic parameters. However, segmentation-based methods are labor-intensive due to their requirement for extensive annotation during training, while object detection approaches exhibit limitations in capturing intricate structural features. To achieve real-time, efficient, and precise extraction of phenotypic traits of seedling tomatoes, a novel plant phenotyping approach based on 2D pose estimation was proposed. We enhanced a novel heatmap-free method, YOLOv8s-pose, by integrating the Convolutional Block Attention Module (CBAM) and Content-Aware ReAssembly of FEatures (CARAFE), to develop an improved YOLOv8s-pose (IYOLOv8s-pose) model, which efficiently focuses on salient image features with minimal parameter overhead while achieving a superior recognition performance in complex backgrounds. IYOLOv8s-pose manifested a considerable enhancement in detecting bending points and stem nodes. Particularly for internode detection, IYOLOv8s-pose attained a Precision of 99.8%, exhibiting a significant improvement over RTMPose-s, YOLOv5s6-pose, YOLOv7s-pose, and YOLOv8s-pose by 2.9%, 5.4%, 3.5%, and 5.4%, respectively. Regarding plant height estimation, IYOLOv8s-pose achieved an RMSE of 0.48 cm and an rRMSE of 2%, and manifested a 65.1%, 68.1%, 65.6%, and 51.1% reduction in the rRMSE compared to RTMPose-s, YOLOv5s6-pose, YOLOv7s-pose, and YOLOv8s-pose, respectively. When confronted with the more intricate extraction of internode length, IYOLOv8s-pose also exhibited a 15.5%, 23.9%, 27.2%, and 12.5% reduction in the rRMSE compared to RTMPose-s, YOLOv5s6-pose, YOLOv7s-pose, and YOLOv8s-pose. IYOLOv8s-pose achieves high precision while simultaneously enhancing efficiency and convenience, rendering it particularly well suited for extracting phenotypic parameters of tomato plants grown naturally within greenhouse environments. This innovative approach provides a new means for the rapid, intelligent, and real-time acquisition of plant phenotypic parameters in complex backgrounds. Full article

(This article belongs to the Special Issue Intelligent Extraction of Phenotypic Traits in Agroforestry)

► Show Figures

Figure 1

21 pages, 1846 KiB

Open AccessFeature PaperArticle

Analytical Models of Experimental Artefacts in an Ill-Posed Nonlinear ODE System

by Andreas Henrici and Marcello Robbiani

Mathematics 2024, 12(23), 3675; https://doi.org/10.3390/math12233675 (registering DOI) - 24 Nov 2024

Abstract

We discuss different approaches for the analytical description of a mechanical system used in control theory, aiming at the analytical modelling of experimental artefacts observed in the implementation of ideal searched trajectories. Starting from an established analytical solution, we develop an alternative analytical [...] Read more.

We discuss different approaches for the analytical description of a mechanical system used in control theory, aiming at the analytical modelling of experimental artefacts observed in the implementation of ideal searched trajectories. Starting from an established analytical solution, we develop an alternative analytical model for this solution with minimal deviations and then extend this starting point to a more flexible toolbox that incorporates a variety of phenomena that typically occur in real implementations of this mechanical system, thus providing an important step towards bridging the gap between theoretical models and experimental reality. Full article

(This article belongs to the Section Mathematical Physics)

► Show Figures

Figure 1

12 pages, 1837 KiB

Open AccessArticle

Modifying the Resistant Starch Content and the Retrogradation Characteristics of Potato Starch Through High-Dose Gamma Irradiation

by Zhangchi Peng, Xuwei Wang, Zhijie Liu, Liang Zhang, Linrun Cheng, Jiahao Nia, Youming Zuo, Xiaoli Shu and Dianxing Wu

Gels 2024, 10(12), 763; https://doi.org/10.3390/gels10120763 (registering DOI) - 24 Nov 2024

Abstract

Potato starch is widely utilized in the food industry. Gamma irradiation is a cost-effective and environmentally friendly method for starch modification. Nevertheless, there is a scarcity of comprehensive and consistent knowledge regarding the physicochemical characteristics of high-dose gamma-irradiated potato starch, retrogradation properties in [...] Read more.

Potato starch is widely utilized in the food industry. Gamma irradiation is a cost-effective and environmentally friendly method for starch modification. Nevertheless, there is a scarcity of comprehensive and consistent knowledge regarding the physicochemical characteristics of high-dose gamma-irradiated potato starch, retrogradation properties in particular. In this study, potato starch was exposed to gamma rays at doses of 0, 30, 60, 90, and 120 kGy. Various physicochemical properties, including retrogradation characteristics, were investigated. Generally, the apparent amylose content (AAC), water absorption, gel viscosity, gel hardness, and gumminess decreased as the doses of gamma irradiation increased. Conversely, the resistant starch (RS), amylose content evaluated by the concanavalin A precipitation method, water solubility, and enthalpy of gelatinization were increased. Additionally, swelling power, crystalline structure, and amylopectin branch chain length distribution either remained stable or exhibited only minor changes. Notably, the degree of retrogradation of potato starches on day 7 was positively correlated with the doses of gamma irradiation. Full article

(This article belongs to the Special Issue Natural Bioactive Compounds and Gels)

► Show Figures

Figure 1

16 pages, 4225 KiB

Open AccessArticle

Impact of Ga, Sr, and Ce on Ni/DSZ95 Catalyst for Methane Partial Oxidation in Hydrogen Production

by Salma A. Al-Zahrani, Omer Bellahwel, Ahmed Aidid Ibrahim, Mohammed F. Alotibi, Najat Masood, Sahar Y. Rajeh, Ahmed Al Otaibi, Hessah Difallah A. Al-Enazy and Ahmed S. Al-Fatesh

Catalysts 2024, 14(12), 851; https://doi.org/10.3390/catal14120851 (registering DOI) - 24 Nov 2024

Abstract

The greenhouse gas CH₄ is more potent than CO_2, although both these gases are solely responsible for global warming. The efficient catalytic conversion of CH₄ into hydrogen-rich syngas, which also demonstrates economic viability, can deplete the concentration of CH₄ [...] Read more.

The greenhouse gas CH₄ is more potent than CO_2, although both these gases are solely responsible for global warming. The efficient catalytic conversion of CH₄ into hydrogen-rich syngas, which also demonstrates economic viability, can deplete the concentration of CH₄. This study examines the partial oxidation of methane (POM) prepared by the wetness impregnation process using 5% Ni supported over DSZ95 (93.3% ZrO₂ + 6.7% Sc₂O₃) and promoted with 1% Ga (gallium), 1% Sr (strontium), and 1% Ce (cerium). These catalysts are characterized by surface area porosity, X-ray diffraction, FT-Infrared spectroscopy, Raman infrared spectroscopy, temperature programmed reduction, CO₂ temperature-programmed techniques, desorption techniques, thermogravimetry, and transmission electron microscopy. The characterization results demonstrate that Ni is appropriate for the POM because of its crystalline structure, improved metal support contact, and increased thermal stability with Sr, Ce, and Ga promoters. The synthesized catalyst 5Ni+1Ga-DSZ95 maintained stability for 240 min on stream during the POM at 700 °C. Adding a 1% Ga promoter and active metal Ni to the DSZ95 improved the CH₄ conversion from 70.00% to 75.90% and raised the H₂ yield from 69.21% to 74.80%, while maintaining the reactants’ stoichiometric ratio of (CH₄:O₂ = 2:1). The 5Ni+1Ga-DSZ95 catalyst is superior to the other catalysts, given its rich catalyst surface, strong metal support interaction, high surface area and low amount of carbon deposit. The high H₂/CO ratio (>2.6) and H₂ yield close to 75% indicate that 5Ni+1Ga-DSZ95 is a potent industrial catalyst for hydrogen-rich syngas production through partial oxidation of methane. Full article

(This article belongs to the Special Issue Advances in Catalytic Dry Reforming of Methane)

► Show Figures

Figure 1

Recent Articles

Open Access Journals

Highly Accessed Articles

Latest Books

News

Blog Posts

Topics

Selected Special Issues

Selected Collections

Journals by Subject

Further Information

Guidelines

MDPI Initiatives

Follow MDPI