Search Results (62)

Since 2013, the World Health Organization has recommended the use of rapid molecular tests as the initial diagnostic step for Mycobacterium tuberculosis (MTB) infection to enhance the control of tuberculosis. In recent years, the prevalence of infections by non-tuberculous mycobacteria (NTM) in humans has also risen, particularly in countries with low tuberculosis incidence, such as Italy. Therefore, the rapid differentiation between NTM and Mycobacterium tuberculosis complex is crucial for timely therapeutic decisions. This study evaluates a new rapid molecular assay, Standard M10 MTB/NTM, designed to detect MTB, NTM, or co-detection in Mycobacteria Growth Indicator Tube cultures from different biological matrices. The assay was validated using 100 positive and 50 negative liquid mycobacteria cultures, already confirmed by specific real-time PCR and Sanger sequencing. Following optimization of assay conditions for culture sample processing and assessment of potential interference, Standard M10 demonstrated excellent sample stability, high specificity, and good sensitivity, identifying all 50 MTB and 49 NTM samples. Some limitations included the non-detection of M. celatum in one case and false positive results (MTB co-infection) in two NTB cases. Nevertheless, overall, the adoption of this test could be considered for laboratory management to enable rapid and effective sample targeting for subsequent diagnostic evaluation and treatment decision-making. Full article

In the past three years, electric vehicle (EV) sales in Indonesia have increased significantly, reflecting a positive trend in the country’s efforts to reduce carbon emissions. However, EV adoption in developing countries may not always lead to effective carbon emission reductions. The environmental benefits of EVs are highly dependent on the electricity generation mix of a given country. Since Indonesia still relies heavily on fossil fuel-based power plants, the positive impact of EV usage on emission reduction needs to be critically assessed. This paper examines the adoption of EVs as a strategic pathway to reduce fossil fuel import dependency and carbon emissions. Using emissions data provided by the Google Environmental Insights Explorer (EIE) in West Nusa Tenggara Province (NTB), this study adopts a System Dynamics approach to explore various policy and energy transition scenarios that could maximize the environmental benefits of EV use. This study aims to analyze the impact of EV development on CO₂ emissions, fossil fuel dependency, and cross-sectoral sustainability trade-offs in Indonesia. These insights can inform the formulation of more integrated and effective policies to guide the national transition toward sustainable transportation. Full article

In this study, we employed density functional theory (DFT), a standard method in quantum chemistry, to investigate the structural intricacies of thioether-linked naphthalene-based liquid-crystal dimers. The theoretical analysis included the calculation of the molecular bend angle, a crucial factor influencing the formation of the twist–bend nematic (N_TB) phase, as well as other molecular parameters such as transition dipole moments, bond lengths, and bond energies. These calculations allowed for the determination of the probable conformations and the computation of their vibrational spectra, which are essential for interpreting experimental spectra. Connecting these insights, we identified stable conformations and observed differences in the spectra between the conventional nematic (N) and N_TB phases. The combined DFT calculations and infrared absorbance measurements allowed us to investigate the structure and intermolecular interactions of molecules in the N and N_TB phases of the dimers. Notably, significant changes in average absorbance were detected in the experimental spectra in the N_TB phase. During the transition from the N phase to the N_TB phase, a clear decrease in absorbance for longitudinal dipoles and an increase for transverse dipoles were observed. This phenomenon suggests that longitudinal dipoles are antiparallel, while transverse dipoles are parallel. To verify the influence of nearest-neighbor interactions, DFT calculations were conducted on a system comprising several neighboring molecules. Full article

In this paper, a novel method for estimating high-resolution isotropic broadband albedo is proposed, by downscaling satellite-derived albedo using an optimization approach. At first, broadband albedo is calculated from the lower-resolution multispectral satellite image using standard narrow-to-broadband (NTB) conversion, where the surfaces are considered Lambertian with isotropic reflectance. The high-resolution true orthophoto for the same location is segmented with the deep learning-based Segment Anything Model (SAM), and the resulting segments are refined with a classified digital surface model (cDSM) to exclude small transient objects. Afterwards, the remaining segments are grouped using K-means clustering, by considering orthophoto-visible (VIS) and near-infrared (NIR) bands. These segments present surfaces with similar materials and underlying reflectance properties. Next, the Differential Evolution (DE) optimization algorithm is applied to approximate albedo values to these segments so that their spatial aggregate matches the coarse-resolution satellite albedo, by proposing two novel objective functions. Extensive experiments considering different DE parameters over an 0.75 km² large urban area in Maribor, Slovenia, have been carried out, where Sentinel-2 Level-2A NTB-derived albedo was downscaled to 1 m spatial resolution. Looking at the performed spatiospectral analysis, the proposed method achieved absolute differences of 0.09 per VIS band and below 0.18 per NIR band, in comparison to lower-resolution NTB-derived albedo. Moreover, the proposed method achieved a root mean square error (RMSE) of 0.0179 and a mean absolute percentage error (MAPE) of 4.0299% against ground truth broadband albedo annotations of characteristic materials in the given urban area. The proposed method outperformed the Enhanced Super-Resolution Generative Adversarial Networks (ESRGANs), which achieved an RMSE of 0.0285 and an MAPE of 9.2778%, and the Blind Super-Resolution Generative Adversarial Network (BSRGAN), which achieved an RMSE of 0.0341 and an MAPE of 12.3104%. Full article

The temperature-based crop water stress index (CWSI) is the most robust metric among precise techniques that assess the severity of crop water stress, particularly in susceptible crops like maize. This study used a unmanned aerial vehicle (UAV) to remotely collect data, to use in combination with the random forest regression algorithm to detect the maize CWSI in smallholder croplands. This study sought to predict a foliar temperature-derived maize CWSI as a proxy for crop water stress using UAV-acquired spectral variables together with random forest regression throughout the vegetative and reproductive growth stages. The CWSI was derived after computing the non-water-stress baseline (NWSB) and non-transpiration baseline (NTB) using the field-measured canopy temperature, air temperature, and humidity data during the vegetative growth stages (V5, V10, and V14) and the reproductive growth stage (R1 stage). The results showed that the CWSI (CWSI < 0.3) could be estimated to an R² of 0.86, RMSE of 0.12, and MAE of 0.10 for the 5th vegetative stage; an R² of 0.85, RMSE of 0.03, and MAE of 0.02 for the 10th vegetative stage; an R² of 0.85, RMSE of 0.05, and MAE of 0.04 for the 14th vegetative stage; and an R² of 0.82, RMSE of 0.09, and MAE of 0.08 for the 1st reproductive stage. The Red, RedEdge, NIR, and TIR UAV-bands and their associated indices (CCCI, MTCI, GNDVI, NDRE, Red, TIR) were the most influential variables across all the growth stages. The vegetative V10 stage exhibited the most optimal prediction accuracies (RMSE = 0.03, MAE = 0.02), with the Red band being the most influential predictor variable. Unmanned aerial vehicles are essential for collecting data on the small and fragmented croplands predominant in southern Africa. The procedure facilitates determining crop water stress at different phenological stages to develop timeous response interventions, acting as an early warning system for crops. Full article

We report the first homologous series of methylene-linked cyanobiphenyl- and cyanoterphenyl-based liquid crystal (LC) dimers (CBnCT). To induce the heliconical twist-bend nematic (N_TB) phase through bent molecular shapes, the CBnCT homologs have an odd-numbered flexible alkylene spacer (n) ranging from 1 to 17. Polarized optical microscopy and differential scanning calorimetry are used to identify phases and analyze the phase-transition behavior. Except for n = 1, all the CBnCT homologs exhibit the conventional nematic (N) and N_TB phases. The CBnCT dimers with n = 3 and 5 show a monotropic N_TB phase, while those with n = 7, 9, 11, 13, 15, and 17 demonstrate an enantiotropic N_TB phase below the conventional N phase temperature. The N_TB phases of the CBnCT dimers (n = 7, 9, and 11) remain stable down to room temperature and vitrify without crystallization. Compared with cyanobiphenyl-based LC dimer homologs (CBnCB), the CBnCT dimers show significantly broader N and N_TB phase temperature ranges with higher isotropic and N_TB–N phase-transition temperatures. The N_TB phase temperature ranges of CBnCT (n = 7, 9, 11, and 13) are over 100 °C. Additionally, more CBnCT homologs exhibit the enantiotropic N_TB phase than the CBnCB ones. These enhancements result from increased π-conjugation and asymmetric molecular structures. Furthermore, CB9CT exhibits higher birefringence than CB9CB owing to its longer π-conjugated terphenyl moiety. Full article

Background: Current research highlights the importance of addressing multiple risk factors concurrently to tackle the complex etiology of dementia. However, limited evidence exists on the efficacy of technology-driven, multidomain community-based interventions for preventing cognitive decline. Objectives: To evaluate the efficacy of ADL+, an artificial intelligence (AI)-enabled digital toolkit integrating cognitive assessments and multidomain interventions, on outcomes of cognitive function, activity levels, and quality of life in older adults at risk of cognitive decline. Adherence and usability were also evaluated. Methods: We conducted a quasi-experimental study including community-dwelling older adults aged 60 years and above without dementia, but with subjective memory complaints (AD8 score ≥ 2). Participants received a six-month intervention (app-based cognitive training, personalized nutritional, physical, and social activities recommendations) or a control group treatment (cognitive health educational package). The primary outcome was a change in neuropsychological test battery (NTB) Z-scores (NTB composite and its individual domains: attention, processing speed, memory, and executive function). Secondary outcomes were activity levels (Frenchay Activities Index, FAI), and quality of life (EQ-5D). Outcomes were assessed at the end of the intervention and three months post-intervention using linear mixed-effects models. Results: 96% of participants in the intervention and 89% in the control group completed the study. At six months, the intervention group showed a significant NTB composite score improvement (mean change: 0.086 (95% CI 0.020 to 0.15)), with a between-group difference of 0.17 (95% CI 0.071 to 0.27). Significant differences in attention, processing speed, and memory domains were observed, with benefits sustained in the processing speed domain at nine months. The control group’s FAI scores declined at six months (mean change: −1.04 (95% CI −1.83 to −0.26)), while the intervention group’s scores remained stable. The intervention group’s EQ-5D visual analogue scale (VAS) scores improved at both six and nine months, with between-group differences of 4.06 (95% CI 0.23 to 7.90) at six months and 5.12 (95% CI 0.81 to 9.43) at nine months. Adherence was high, while average usability scores were obtained. Conclusions: The ADL+ toolkit shows potential beneficial effects on cognitive function, activity levels, and quality of life for older adults at risk of cognitive decline. Findings will guide future randomized controlled trials and implementation efforts. Full article

Nitrogen (N) fertilizer is essential for agricultural production as it is the main nutrient driving crop growth. However, in China, only one-third of applied N fertilizer is effectively absorbed by crops, while the rest leads to significant environmental impacts. In this study, we introduced a nitrogen threshold boundary (NTB) approach to establish different thresholds for N use efficiency (NUE) and N surplus without affecting crop yield. We also developed an integrated assessment framework to systematically evaluate the potential for improving N utilization and reducing environmental impacts in the production of grain crops (rice, wheat, maize, and soybeans) and cash crops (tea, fruits, and vegetables) at the county level in Fujian Province. Three N management strategies were evaluated: a scenario with reduced N surplus (S1), a scenario with increased NUE (S2), and a combined scenario that simultaneously reduces N surplus and increases NUE (S3). The predictions indicate that, under the aforementioned scenarios, there will be a decrease of 66%, 58%, and 71% in N application without affecting crop yields, respectively. Correspondingly, N surplus will decrease by 65%, 56%, and 67%, while greenhouse gas (GHG) emissions will decrease by 54%, 48%, and 57%. In addition, NUE will increase by 23%, 17% and 25%, respectively. It is notable that scenario S3 demonstrated the greatest potential for improvement. For cash crops, N application will decrease by 65–78%, NUE will increase by 13–21%, N surplus will decrease by 63–74%, and GHG emissions will reduce by 66–78%. In contrast, for grain crops, N application will decrease by 27–38%, NUE will increase by 9–13%, N surplus will decrease by 26–37%, and GHG emissions will reduce by 24–28%. Overall, the potential for improvement is greater for cash crops compared to grain crops. The application of the assessment framework in this study demonstrates its effectiveness as a valuable tool for promoting green and sustainable development in conventional agricultural regions. Full article

This work aims to determine how the nematic twist-bend phase (N_TB) of bismesogens containing two rigid parts of cyanobiphenyls connected with a linking chain containing n = 7, 9, and 11 methylene groups behaves in mixtures with structurally similar cyanobiphenyls nCB, n = 4–12, 14. The whole phase diagrams are presented for the CB7CB-nCB system. For the other systems, CB9CB-nCB and CB11CB-nCB, only curves corresponding to N_TB-N phase transition are presented. Based on the temperature-concentration range of the existence of N_TB phase, it was established that an increase in the alkyl chain length of CBnCB causes an increase in the stability of the N_TB phase. But surprisingly, an increase in the alkyl chain length of nCB compounds does not change the slope of the N_TB-N equilibrium line on phase diagrams. It is slightly bigger when the nCB compound has the same length of alkyl chain as the length of the linking group of a bismesogen. XRD studies were carried out for two mixtures. Full article

Natural Killer (NK) cells have the potential to eliminate HIV-1-infected cells by antibody-dependent cellular cytotoxicity (ADCC). NK cell activation is tightly regulated by the engagement of its inhibitory and activating receptors. The activating receptor CD16 drives ADCC upon binding to the Fc portion of antibodies; NK cell activation is further sustained by the co-engagement of activating receptors NTB-A and 2B4. During HIV-1 infection, Nef and Vpu accessory proteins contribute to ADCC escape by downregulating the ligands of NTB-A and 2B4. HIV-1 also evades ADCC by keeping its envelope glycoproteins (Env) in a “closed” conformation which effectively masks epitopes recognized by non-neutralizing antibodies (nnAbs) which are abundant in the plasma of people living with HIV. To achieve this, the virus uses its accessory proteins Nef and Vpu to downregulate the CD4 receptor, which otherwise interacts with Env and exposes the epitopes recognized by nnAbs. Small CD4-mimetic compounds (CD4mc) have the capacity to expose these epitopes, thus sensitizing infected cells to ADCC. Given the central role of NK cell co-activating receptors NTB-A and 2B4 in Fc-effector functions, we studied their contribution to CD4mc-mediated ADCC. Despite the fact that their ligands are partially downregulated by HIV-1, we found that both co-activating receptors significantly contribute to CD4mc sensitization of HIV-1-infected cells to ADCC. Full article

Photoisomerizable molecules in liquid crystals (LCs) allow for photoinduced phase transitions, facilitating applications in a wide variety of photoresponsive materials. In contrast to the widely investigated azobenzene structure, research on the photoinduced phase-transition behavior of imine-based LCs is considerably limited. We herein report the thermal and photoinduced phase-transition behaviors of photoisomerizable imine-based LC dimers with twist–bend nematic (N_TB) phases. We synthesize two homologous series of ester- and thioether-linked N-(4-cyanobenzylidene)aniline-based bent-shaped LC dimers with an even number of carbon atoms (n = 2, 4, 6, 8, and 10) in the central alkylene spacers, namely, CBCOOnSBA(CN) and CBOCOnSBA(CN), possessing oppositely directed ester linkages, C=OO and OC=O, respectively. Their thermal phase-transition behavior is examined using polarizing optical microscopy and differential scanning calorimetry. All dimers form a monotropic N_TB phase below the temperature of the conventional nematic (N) phase upon cooling. Remarkably, the N_TB phases of CBCOOnSBA(CN) (n = 2, 4, 6, and 8) and CBOCOnSBA(CN) (n = 6 and 8) supercool to room temperature and vitrify without crystallization. In addition, the phase-transition temperatures and entropy changes of CBCOOnSBA(CN) are lower than those of CBOCOnSBA(CN) at the same n. Under UV light irradiation, the N_TB and N phases transition to the N and isotropic phases, respectively, and reversibly return to their initial LC phases when the UV light is turned off. Full article

Pre-flight inspection and maintenance are essential prerequisites for aviation safety. This study focused on developing a real-time monitoring system designed to assess the condition of composite material structures on the exterior of aircraft. Implementing such a system can reduce operational costs, enhance flight safety, and increase aircraft availability. This study aims to detect defects in aircraft fuselages manufactured from composite materials by applying image visual recognition technology. This study integrated a drone and an infrared camera for real-time image transmission to ground stations. MATLAB image analysis software (MATLAB 2020b) was used to analyze infrared (IR) images and detect structural defects in the aircraft’s appearance. This methodology was based on the inspection of damaged engine cowlings. The developed approach compares composite material conditions with known defects before and after repair, considering mechanical performance, defect size, and strength. Simultaneously, tests were conducted on various composite material panels with unknown defects, yielding favorable results. This study underscores an integrated system offering rapid detection, real-time feedback, and analysis, effectively reducing time, and potential hazards associated with high-altitude operations. Furthermore, it addresses blind spots in aircraft inspections, contributing to effective flight safety maintenance. Full article

The impact of cancer cachexia on the colonic microbiota is poorly characterized. This study assessed the effect of two cachectic-producing tumor types on the gut microbiota to determine if a similar dysbiosis could be found. In addition, it was determined if a diet containing an immunonutrient-rich food (walnuts) known to promote the growth of probiotic bacteria in the colon could alter the dysbiosis and slow cachexia. Male Fisher 344 rats were randomly assigned to a semi-purified diet with or without walnuts. Then, within each diet group, rats were further assigned randomly to a treatment group: tumor-bearing ad libitum fed (TB), non-tumor-bearing ad libitum fed (NTB-AL), and non-tumor-bearing group pair-fed to the TB (NTB-PF). The TB group was implanted either with the Ward colon carcinoma or MCA-induced sarcoma, both transplantable tumor lines. Fecal samples were collected after the development of cachexia, and bacteria species were identified using 16S rRNA gene analysis. Both TB groups developed cachexia but had a differently altered gut microbiome. Beta diversity was unaffected by treatment (NTB-AL, TB, and NTB-PF) regardless of tumor type but was affected by diet. Also, diet consistently changed the relative abundance of several bacteria taxa, while treatment and tumor type did not. The control diet increased the abundance of A. Anaeroplasma, while the walnut diet increased the genus Ruminococcus. There were no common fecal bacterial changes characteristic of cachexia found. Diet consistently changed the gut microbiota, but these changes were insufficient to slow the progression of cachexia, suggesting cancer cachexia is more complex than a few gut microbiota shifts. Full article

This research work highlights significant achievements in the domain of intrusion detection systems (IDSs) for autonomous vehicles, which are crucial in enhancing their safety, reliability, and cybersecurity. This study introduces an approach that leverages non-tree-based machine learning algorithms, such as K-nearest neighbors and ensemble learning, to develop an IDS tailored for autonomous vehicles. These algorithms were employed because of their ability to process complex and large datasets with less likeliness for overfitting, their scalability, and their ability to adapt to changing conditions in real time. These algorithms effectively handle imbalanced data, enhancing the detection accuracy of both normal and intrusive instances. The IDS’s performance was validated through the utilization of three real-world datasets, CAN intrusion, CICIDS2017, and NSL-KDD, where the proposed non-tree-based IDS (NTB-MTH-IDS) was measured with the standard measurement metrics: accuracy, precision, F1-score, and recall, including specificity and sensitivity. Notably, the results indicate that K-nearest neighbors and stacking, as part of NTB-MTH-IDS, has an accuracy of 99.00%, 98.57%, and 97.57%, and F1-scores of 99.00%, 98.79%, and 97.54% in the CICIDS2017, NSL-KDD, and CAN datasets, respectively. The results of this research can lead to establishing a robust intrusion detection framework, thereby ensuring the safety and reliability of autonomous vehicles. Through this achievement, road users, passengers, and pedestrians are safeguarded against the consequences of potential cyber threats. Full article

Small-scale tropical fisheries are complex systems that utilize multiple fishing gears to target various species. In this study, we investigated small-scale reef and demersal fisheries in Saleh Bay, Indonesia, using catch and effort data from 2016 to 2019, where 57.7 percent of the catch was grouper (serranids) and snapper (lutjanids). Despite the complexity (75 documented species and eight fishing methods), this fishery is characterized by the catches of four dominant species: leopard coral grouper (Plectropomus leopardus), orange-spotted-grouper (Epinephelus coioides), spotted coral grouper (P. maculatus), and malabar blood snapper (Lutjanus malabaricus). The species caught varied among fishing methods. Over 90% of the catch was attributed to three primary fishing methods: bottom longline, speargun, and handline. Multivariate analyses found that fishing depth, season, and/or year significantly influenced the catch composition for each of these fishing methods. Fishing activities exhibit a temporal pattern influenced by monsoonal seasons. Results also suggest that fishers employ specialized fishing tactics by targeting high-value species to maximize their profits. This study recommends a management strategy of focusing on monitoring and managing the three main fishing gears and four important species during their peak seasons to reduce some of the complexity and management costs. Full article