Search Results (10)

Fast fashion is a rapidly expanding sector characterized by high production volumes, low costs, and short product lifecycles. While recent efforts have focused on improving sustainability within supply chains, consumer behavior remains a critical yet underexplored driver of environmental impacts. This study presents a web-based calculator tool designed to estimate both the carbon and plastic footprints associated with individual fast fashion consumption, with a particular focus on shopping behaviors, garment disposal, and laundry habits. Adopting a geographical perspective, the analysis explicitly considers the spatial dynamics of consumption and logistics within the urban context of Milan (Italy), a dense metropolitan area representative of high fashion activity and mobility. By incorporating user-reported travel patterns, logistics routes, and localized emission factors, the tool links consumer habits to place-specific environmental impacts. By involving over 360 users, the tool not only quantifies emissions and plastic waste (including microfibers) but also serves an educational function, raising awareness about the hidden consequences of fashion-related choices. Results reveal high variability in environmental impacts depending on user profiles and behaviors, with online shopping, frequent use of private vehicles, and improper garment disposal contributing significantly to emissions and plastic pollution. Our findings highlight the importance of integrating consumer-focused educational tools into broader sustainability strategies. The tool’s dual function as both calculator and awareness-raising platform suggests its potential value for educational and policy initiatives aimed at promoting more sustainable fashion consumption patterns. Full article

The fast fashion industry significantly impacts the environment at every stage of a product’s life cycle. The transport of products to wholesalers and stores, as one of the stages of the product life cycle, is often overlooked during the analysis of their carbon footprint. Therefore, research is needed on the impact of fast fashion on the environment through its logistics and transport, especially in relation to air emissions. This article attempts to determine how extensively fast fashion companies disclose the impact of their transport operations on their overall corporate carbon footprint, determine the proportion of total emissions attributed to transport, and evaluate the effectiveness of companies’ efforts to mitigate their transport-related environmental impact. This research used a case study method on selected brands (H&M Group, Inditex, Shein), using secondary data available in non-financial reports for 2023. As a result of the analysis of their non-financial reports on transport emissions, several key findings have been presented. Companies predominantly rely on external frameworks and standards, particularly the Global Reporting Initiative. However, the level of detail of the data presented varies. The priority for the surveyed companies is to reduce emissions from significant sources, such as production processes. The data disclosed in the reports (scope 1, 2, 3) must be clearly formulated and can be used to calculate the level of their CO₂ emission reduction or increase. Companies should improve their environmental reporting by including indicators of their transport-related emissions. This approach provides a comprehensive view of their environmental impact, highlighting absolute values and efficiency metrics. Full article

The kinetics and mechanism of drug binding to its target are critical to pharmacological efficacy. A high throughput (HTS) screen often results in hundreds of hits, of which usually only simple IC₅₀ values are determined during reconfirmation. However, kinetic parameters such as residence time for reversible inhibitors and the k_inact/K_I ratio, which is the critical measure for evaluating covalent inactivators, are early predictive measures to assess the chances of success of the hits in the clinic. Using the promising cancer target human histone deacetylase 8 as an example, we present a robust method that calculates concentration-dependent apparent rate constants for the inhibition or inactivation of HDAC8 from dose–response curves recorded after different pre-incubation times. With these data, hit compounds can be classified according to their mechanism of action, and the relevant kinetic parameters can be calculated in a highly parallel fashion. HDAC8 inhibitors with known modes of action were correctly assigned to their mechanism, and the binding mechanisms of some hits from an internal HDAC8 screening campaign were newly determined. The oxonitriles SVE04 and SVE27 were classified as fast reversible HDAC8 inhibitors with moderate time-constant IC₅₀ values of 4.2 and 2.6 µM, respectively. The hit compound TJ-19-24 and SAH03 behave like slow two-step inactivators or reversible inhibitors, with a very low reverse isomerization rate. Full article

We present synthetic experiments of lactic acid (LA) polycondensation to produce poly(lactic acid) (PLA) as well as kinetic modeling calculations that capture the polymer molecular weight increase with time, given the initial concentrations. Tin-octoate-catalyzed polycondensation of (D,L)- or L-lactic acid was carried out in pre-dried toluene after azeotropic dehydration for 48–120 h at 130–137 °C. The polymerization was optimized by varying lactic acid and catalyst concentrations as well as the temperature. Gel permeation chromatography was used to experimentally follow the evolution of molecular weights and the products were characterized by NMR, TGA, DSC and IR. Under optimal conditions, PLLA with weight-average molecular weight (M_w) of 161 kDa could be obtained. The rate equations that describe polycondensation kinetics were recast in a condensed form that allowed very fast numerical solution and calculation of the number-average molecular weight with time. Deviations with respect to the experiment were minimized in a least-squares fashion to determine rate constants. The optimized kinetics parameters are shown to reproduce the experimental data accurately. Full article

Monitoring tumor growth dynamics is crucial for understanding cancer. To establish an in vitro method for the continuous assessment of patient-specific tumor growth, tumor organoids were generated from patients with intrahepatic CCA (iCCA). Organoid growth was monitored for 48 h by label-free live brightfield imaging. Growth kinetics were calculated and validated by MTS assay as well as immunohistochemistry of Ki67 to determine proliferation rates. We exposed iCCA organoids (iCCAOs) and non-tumor intrahepatic cholangiocyte organoids (ICOs) to sub-therapeutic concentrations of sorafenib. Monitoring the expansion rate of iCCAOs and ICOs revealed that iCCAO growth was inhibited by sorafenib in a time- and dose-dependent fashion, while ICOs were unaffected. Quantification of the proliferation marker Ki67 confirmed inhibition of iCCAO growth by roughly 50% after 48 h of treatment with 4 µM sorafenib. We established a robust analysis pipeline combining brightfield microscopy and a straightforward image processing approach for the label-free growth monitoring of patient-derived iCCAOs. Combined with bioanalytical validation, this approach is suitable for a fast and efficient high-throughput drug screening in tumor organoids to develop patient-specific systemic treatment options. Full article

LED illumination-based multispectral imaging has a fast switching ability, high cost-effectiveness, and a simple structure. It has been used in some applications, especially color recognition. In this paper, we introduce an efficient and portable LED multispectral imaging system for human tongue detection. The spatial pixels are categorized based on cosine similarity to reduce the optimization calculation times. Further, segment linear calibration is used to improve the recovery quality. Simulation results show that this method greatly improves the reconstruction speed and that recovered images maintain a high spatial and spectral quality. This LED multispectral imaging system captures images quickly and obtains multispectral images in a timely fashion. We also built a small prototype for human tongue detection in traditional Chinese medicine. The recovered spectra were used to calculate the tongue body color and fur color. By combining these with the spatial information, the fur distribution and fur thickness were analyzed. The results of this study verified the effectiveness of this LED multispectral imaging system. Further experiments will be undertaken for the quantitative analysis of tongue features. The study was approved by the Institutional Review Board (or Ethics Committee) of Shenzhen Institute of Advanced Technology Chinese Academy of Sciences. Full article

Berberine is a natural alkaloid used to improve glycemia but displays poor bioavailability and increased rates of gastrointestinal distress at higher doses. Recently, dihydroberberine has been developed to combat these challenges. This study was designed to determine the rate and extent to which berberine appeared in human plasma after oral ingestion of a 500 mg dose of berberine (B500) or 100 mg and 200 mg doses of dihydroberberine (D100 and D200). In a randomized, double-blind, crossover fashion, five males (26 ± 2.6 years; 184.2 ± 11.6 cm; 91.8 ± 10.1 kg; 17.1 ± 3.5% fat) completed a four-dose supplementation protocol of placebo (PLA), B500, D100, and D200. The day prior to their scheduled visit, participants ingested three separate doses with breakfast, lunch, and dinner. Participants fasted overnight (8–10 h) and consumed their fourth dose with a standardized test meal (30 g glucose solution, 3 slices white bread) after arrival. Venous blood samples were collected 0, 20, 40, 60, 90, and 120 minutes (min) after ingestion and analyzed for BBR, glucose, and insulin. Peak concentration (C_Max) and area under the curve (AUC) were calculated for all variables. Baseline berberine levels were different between groups (p = 0.006), with pairwise comparisons indicating that baseline levels of PLA and B500 were different than D100. Berberine C_Max tended to be different (p = 0.06) between all conditions. Specifically, the observed C_Max for D100 (3.76 ± 1.4 ng/mL) was different than PLA (0.22 ± 0.18 ng/mL, p = 0.005) and B500 (0.4 ± 0.17 ng/mL, p = 0.005). C_Max for D200 (12.0 ± 10.1 ng/mL) tended (p = 0.06) to be different than B500. No difference in C_Max was found between D100 and D200 (p = 0.11). Significant differences in berberine AUC were found between D100 (284.4 ± 115.9 ng/mL × 120 min) and PLA (20.2 ± 16.2 ng/mL × 120 min, p = 0.007) and between D100 and B500 (42.3 ± 17.6 ng/mL × 120 min, p = 0.04). Significant differences in D100 BBR AUC (284.4 ± 115.9 ng/mL×120 min) were found between PLA (20.2 ± 16.2 ng/mL × 120 min, p = 0.042) and B500 (42.3 ± 17.6 ng/mL × 120 min, p = 0.045). Berberine AUC values between D100 and D200 tended (p = 0.073) to be different. No significant differences in the levels of glucose (p = 0.97) and insulin (p = 0.24) were observed across the study protocol. These results provide preliminary evidence that four doses of a 100 mg dose of dihydroberberine and 200 mg dose of dihydroberberine produce significantly greater concentrations of plasma berberine across of two-hour measurement window when compared to a 500 mg dose of berberine or a placebo. The lack of observed changes in glucose and insulin were likely due to the short duration of supplementation and insulin responsive nature of study participants. Follow-up efficacy studies on glucose and insulin changes should be completed to assess the impact of berberine and dihydroberberine supplementation in overweight, glucose intolerant populations. Full article

Image registration is among the most popular and important problems of remote sensing. In this paper we propose a fully unsupervised, deep learning based multistep deformable registration scheme for aligning pairs of satellite imagery. The presented method is based on the expression power of deep fully convolutional networks, regressing directly the spatial gradients of the deformation and employing a 2D transformer layer to efficiently warp one image to the other, in an end-to-end fashion. The displacements are calculated with an iterative way, utilizing different time steps to refine and regress them. Our formulation can be integrated into any kind of fully convolutional architecture, providing at the same time fast inference performances. The developed methodology has been evaluated in two different datasets depicting urban and periurban areas; i.e., the very high-resolution dataset of the East Prefecture of Attica, Greece, as well as the high resolution ISPRS Ikonos dataset. Quantitative and qualitative results demonstrated the high potentials of our method. Full article

Background: Skeletal muscle has been implicated in the pathogenesis of type 2 diabetes but it has never been investigated in diabetes after pancreatitis. The aim was to investigate the relationship between psoas muscle volume (PMV) and diabetes in individuals after pancreatitis, as well as its associations with ectopic fat phenotypes and insulin traits. Methods: Individuals after an attack of pancreatitis and healthy individuals were studied in a cross-sectional fashion. All participants underwent magnetic resonance imaging, based on which PMV, skeletal muscle fat deposition (SMFD), as well as liver and intra-pancreatic fat depositions were derived. Fasting and postprandial blood samples were collected to calculate indices of insulin sensitivity and secretion. Linear regression analyses were conducted, adjusting for possible confounders (age, sex, body composition, comorbidities, use of insulin, and others). Results: A total of 153 participants were studied. PMV was significantly decreased in the diabetes group compared with healthy controls (β = −30.0, p = 0.034 in the most adjusted model). SMFD was significantly inversely associated with PMV (β = −3.1, p < 0.001 in the most adjusted model). The Matsuda index of insulin sensitivity was significantly directly associated with PMV (β = 1.6, p = 0.010 in the most adjusted model). Conclusions: Diabetes in individuals after pancreatitis is characterized by reduced PMV. Reduced PMV is associated with increased SMFD and decreased insulin sensitivity in individuals after pancreatitis. Full article

The integral image, an intermediate image representation, has found extensive use in multi-scale local feature detection algorithms, such as Speeded-Up Robust Features (SURF), allowing fast computation of rectangular features at constant speed, independent of filter size. For resource-constrained real-time embedded vision systems, computation and storage of integral image presents several design challenges due to strict timing and hardware limitations. Although calculation of the integral image only consists of simple addition operations, the total number of operations is large owing to the generally large size of image data. Recursive equations allow substantial decrease in the number of operations but require calculation in a serial fashion. This paper presents two new hardware algorithms that are based on the decomposition of these recursive equations, allowing calculation of up to four integral image values in a row-parallel way without significantly increasing the number of operations. An efficient design strategy is also proposed for a parallel integral image computation unit to reduce the size of the required internal memory (nearly 35% for common HD video). Addressing the storage problem of integral image in embedded vision systems, the paper presents two algorithms which allow substantial decrease (at least 44.44%) in the memory requirements. Finally, the paper provides a case study that highlights the utility of the proposed architectures in embedded vision systems. Full article