Malawi has the potential to explore the utilization of biogas technology. The technology has existed in the country for decades. However, the uptake has been lower than expected. Further, there has been a high rate of dis-adoption of the installed systems. To deal with the problem, this study explored the opportunities and barriers to biogas technology to enhance biogas adoption and utilization in Malawi. Qualitative research methods using key informant interviews were employed to collect the data from biogas adopters, dis-adopters, potential adopters, and experts. A total of 22 households and 6 experts were interviewed. The findings of the study show that the country has opportunities for biogas adoption and utilization. The most mentioned opportunities were livestock farming practices, constraints to access to reliable energy sources, associated benefits of biogas technology, and land holding. However, the adoption of the technology has faced several challenges. Commonly cited barriers were the high installation and maintenance costs, inadequate feedstock, inappropriate dissemination approaches, lack of training after installation services and expertise, lack of reliable water sources, absence of ownership, lack of cooperation amongst institutions involved in biogas promotion, lack of a coordinating body for institutions involved in biogas dissemination, lack of standards, and socio-cultural factors. To overcome the challenges, strategies were identified, and these include the provision of incentives, loans and subsidies, provision of technical support services, having demonstration sites, employing suitable dissemination approaches, co-digestion or diversification of raw materials, awareness campaigns, and collaboration amongst sectors involved in biogas dissemination. Full article

In modern agricultural production, where a small number of commercial cultivars dominate, the collection, evaluation, and preservation of germplasm are important tasks to reduce the erosion of genes and preserve biodiversity. The aim of this study is to characterize the morphological and fruit chemical properties of the pomegranate germplasm grown on the East Adriatic coast, including the commercial cultivars ‘Hicaznar’, ‘Granada’, and ‘Wonderful’, and to highlight the characteristics with the greatest discriminating power. The characterization of the tree, leaf, flower, arils, seed, and juice was carried out using the UPOV descriptor. The colors of the peel, arils, and juice were analyzed according to the CIEL*a*b* method, total soluble solids were measured using refractometers, and total acidity was determined by titration with 0.1 M NaOH. The research results showed significant diversity between the cultivars, which were grouped into several clusters using an unsupervised analysis technique. Factors such as plant vigor, plant growth habit, predominant number of leaves per node on young shoots, crown type, fruit shape, fruit shape in cross-section, peel weight, total aril weight, aril weight, number of arils per fruit, seed length and width, seed yield, total acidity, TSS/TA ratio, and color parameters of the peel, arils, and juice showed high variability, indicating their strong discriminating power in determining the phenotypic diversity of pomegranate. Full article

Keloids, marked by abnormal cellular proliferation and excessive extracellular matrix (ECM) accumulation, pose significant therapeutic challenges. Ethyl pyruvate (EP), an inhibitor of the high-mobility group box 1 (HMGB1) and TGF-β1 pathways, has emerged as a potential anti-fibrotic agent. Our research evaluated EP’s effects on keloid fibroblast (KF) proliferation and ECM production, employing both in vitro cell cultures and ex vivo patient-derived keloid spheroids. We also analyzed the expression levels of ECM components in keloid tissue spheroids treated with EP through immunohistochemistry. Findings revealed that EP treatment impedes the nuclear translocation of HMGB1 and diminishes KF proliferation. Additionally, EP significantly lowered mRNA and protein levels of collagen I and III by attenuating TGF-β1 and pSmad2/3 complex expression in both human dermal fibroblasts and KFs. Moreover, metalloproteinase I (MMP-1) and MMP-3 mRNA levels saw a notable increase following EP administration. In keloid spheroids, EP induced a dose-dependent reduction in ECM component expression. Immunohistochemical and western blot analyses confirmed significant declines in collagen I, collagen III, fibronectin, elastin, TGF-β, AKT, and ERK 1/2 expression levels. These outcomes underscore EP’s antifibrotic potential, suggesting its viability as a therapeutic approach for keloids. Full article

Few-shot object detection is a challenging task aimed at recognizing novel classes and localizing with limited labeled data. Although substantial achievements have been obtained, existing methods mostly struggle with forgetting and lack stability across various few-shot training samples. In this paper, we reveal two gaps affecting meta-knowledge transfer, leading to unstable performance and forgetting in meta-learning-based frameworks. To this end, we propose sample normalization, a simple yet effective method that enhances performance stability and decreases forgetting. Additionally, we apply Z-score normalization to mitigate the hubness problem in high-dimensional feature space. Experimental results on the PASCAL VOC data set demonstrate that our approach outperforms existing methods in both accuracy and stability, achieving up to +4.4 [email protected] and +5.3 mAR in a single run, with +4.8 [email protected] and +5.1 mAR over 10 random experiments on average. Furthermore, our method alleviates the drop in performance of base classes. The code will be released to facilitate future research. Full article

Land formation seriously disturbs coastal salt marsh wetland ecosystems, while its influences on soil organic carbon (SOC) under chronosequences remain unclear. In this study, the impacts of the land formation time (from one to fourteen years) and soil properties on the chronosequences changes of SOC in the nascent wetland of Hengsha Island were investigated. The study results showed the following. (1) As the land-formation time extended, the SOC experienced a significant increase, tripling after a period of 14 years. The changes in SOC occurred mainly in the surface layer but not in the deep soil layer. Specifically, the surface layer’s average SOC reached 5.52 g·kg⁻¹, markedly higher than 3.17 g·kg⁻¹ in the deeper layer. (2) Spearman correlation analysis revealed that the ammonium nitrogen (${\mathrm{NH}}_4^{+}$-N), aboveground biomass (AGB), and soil water content (SWC) were positively correlated with the SOC. Methane emissions (CH₄) and SOC exhibited a negative correlation. (3) The structural equation model (SEM) illustrated that the duration of soil deformation directly impacted the vegetation growth and affected the distribution characteristics of the SOC by modifying the soil environmental conditions. Changes in SOC following land formation influenced the rapid succession of soil properties and vegetation, with the modification of carbon sinks in the ecosystems. Full article

Lacticaseibacillus rhamnosus is applied as a probiotic to alleviate various metabolic, gastrointestinal, and psychological symptoms and diseases, and its probiotic effectiveness is strain-specific. In this study, we obtained 21 strains of Ls. rhamnosus, and their genomes were sequenced. We defined the pan- and core-genomes of Ls. rhamnosus. Phenotypes such as the assimilation of carbohydrates and antibiotic resistance were experimentally characterized and associated with genome annotations. Nine strains were selected and tested for growth rates, tolerance to acidity/alkalinity and bile acids, the production of short-chain fatty acids, and competition with pathogenic microbes. Strains WL11 and WL17 were targeted as potential probiotics and were applied in mouse model tests for the alleviation of chronic fatigue syndrome (CFS) and irritable bowel syndrome (IBS). The results showed that WL11 and WL17 effectively alleviated slow body weight gain, anxiety, poor memory, and cognitive impairment in CFS mouse models. They also reduced the expression of pro-inflammatory factors, such as TNF-α and IL-6, and alleviated intestinal peristalsis, visceral hypersensitivity, and anxiety-like behavior in IBS mouse models. This study reports new Ls. rhamnosus strain resources and their effect on alleviation of both IBS and CFS symptoms with mouse models; the probiotic functions of those strains in human patients remain to be further tested. Full article

Existing methods for inverse synthetic aperture radar (ISAR) target recognition typically rely on a single high-resolution radar signal type, such as ISAR images or high-resolution range profiles (HRRPs). However, ISAR images and HRRP data offer representations of targets across different aspects, each containing valuable information crucial for radar target recognition. Moreover, the process of generating ISAR images inherently facilitates the acquisition of HRRP data, ensuring timely data collection. Therefore, to fully leverage the different information from both HRRP data and ISAR images and enhance ISAR ship target recognition performance, we propose a novel deep fusion network named the Separation-Decision Recognition network (SDRnet). First, our approach employs a convolutional neural network (CNN) to extract initial feature vectors from ISAR images and HRRP data. Subsequently, a feature separation module is employed to derive a more robust target representation. Finally, we introduce a weighted decision module to enhance overall predictive performance. We validate our method using simulated and measured data containing ten categories of ship targets. The experimental results confirm the effectiveness of our approach in improving ISAR ship target recognition. Full article

For developing novel photosensitizers with therapeutic potential in non-malignant and malignant cutaneous disorders, the unsymmetrical porphyrin, 5-(2-hydroxy-3-methoxyphenyl)-10, 15, 20-tris-(4-carboxymethylphenyl) porphyrin, was evaluated in silico and in vitro. The cellular uptake of the investigated porphyrin and its ability to perform photodynamic therapy were investigated in terms of the viability, proliferation, and necrosis of human HaCaT keratinocytes and human Hs27 skin fibroblasts, in correlation with the predictions regarding diffusion through cell membranes, ADMET profile (absorption, distribution, metabolism, elimination, toxicity), and potential pharmacological mechanism. Molecular docking and 250 ns molecular dynamics simulations revealed that P5.2 has the potential to form a relatively stable complex with the carbonic anhydrase IX catalytic site, the lowest predicted free energy of binding (MM/PBSA) being −39.097 kcal/mol. The results of the in vitro study showed that P5.2 is incorporated within 24 h in the investigated cells, especially in HaCaT keratinocytes, indicating its photosensitizing ability. Nevertheless, P5.2 does not exert significant cytotoxicity in “dark” conditions. In turn, PDT induced a decrease in the number of metabolically active HaCaT keratinocytes within 24 h, accompanied by a 4-fold increase in lactate dehydrogenase release, indicating its ability to perform PDT in human skin cells. The experimental results suggest that the asymmetrical porphyrin is a promising candidate theranostics agent for skin disorders. Full article

This paper discusses the time-fractional nonlinear Schrödinger model with optical soliton solutions. We employ the $\left(f+\left(\frac{G^{\prime }}{G}\right)\right)$-expansion method to attain the optical solution solutions. An important tool for explaining the particular explosion of brief pulses in optical fibers is the nonlinear Schrödinger model. It can also be utilized in a telecommunications system. The suggested method yields trigonometric solutions such as dark, bright, kink, and anti-kink-type optical soliton solutions. Mathematica 11 software creates 2D and 3D graphs for many physically important parameters. The computational method is effective and generally appropriate for solving analytical problems related to complicated nonlinear issues that have emerged in the recent history of nonlinear optics and mathematical physics. Furthermore, we venture into uncharted territory by subjecting our model to chaotic and sensitivity analysis, shedding light on its robustness and responsiveness to perturbations. The proposed technique is being applied to this model for the first time. Full article

Shallow geothermal or ground source heat pump (GSHP) energy systems offer efficient space heating and cooling, reducing greenhouse gas emissions and electrical consumption. Incorporating ground heat exchangers (GHEs) within pile foundations, as part of these GSHP systems, has gained significant attention as it can reduce capital costs. The design and optimisation of GHEs connected in parallel within energy piles have been researched widely, considering symmetrical placement, while the potential misplacement due to construction errors and the optimal placement remain mostly unexplored. This study utilises 3D finite element numerical methods, analysing energy piles with diameters from 0.5 m to 1.4 m, equipped with parallelly connected U-tube and W-tube GHEs. The impact of GHE loop placement is analysed, considering the influence of the ground and concrete thermal conductivities, pile length, fluid flow rate, GHE pipe diameter, and pile spacing. Results indicate a marginal impact, less than 3%, on the overall heat transfer when loops deviate from symmetry and less than 5% on the total heat transfer shared by each loop, except for highly non-symmetric configurations. Symmetrical and evenly spaced loop placement generally maintains favourable thermal performance and ease of installation. This study underscores the flexibility in GHE design and construction with a low risk of thermal yield variations due to uncertainties, particularly with a separation-to-shank distance ratio between 0.5 and 1.5 in a symmetrical distribution. Full article

The Guangdong historical trail comprises two ancient trails, known as Yile (宜乐) and Xijing (西京); can be found within the borders of Lechang (乐昌); and is an integral part of the northern section of the Guangdong historical trail, connecting Hunan and Guangdong. Along these routes, there are various types of ancestral halls. The objectives of this study include analyzing various levels of information about ancestral hall architecture, determining their respective importance through AHP hierarchical analysis, classifying architectural features via cluster analysis using SPSS, and exploring the geographical distribution trajectories of ancestral halls along the ancient paths using GIS technology. Ultimately, this study seeks to shed light on the influence of different cultures brought by the ancient road on the distribution of architectural types and identify three distinct types of ancestral halls. Full article

This paper focuses on improving automated approaches to glaucoma diagnosis, a severe disease that leads to gradually narrowing vision and potentially blindness due to optic nerve damage occurring without the patient’s awareness. Early diagnosis is crucial. By utilizing advanced deep learning technologies and robust image processing capabilities, this study employed four types of input data (retina fundus image, region of interest (ROI), vascular region of interest (VROI), and color palette images) to reflect structural issues. We addressed the issue of data imbalance with a modified loss function and proposed an ensemble model based on the vision large language model (VLLM), which improved the accuracy of glaucoma classification. The results showed that the models developed for each dataset achieved 1% to 10% higher accuracy and 8% to 29% improved sensitivity compared to conventional single-image analysis. On the REFUGE dataset, we achieved a high accuracy of 0.9875 and a sensitivity of 0.9. Particularly in the ORIGA dataset, which is challenging in terms of achieving high accuracy, we confirmed a significant increase, with an 11% improvement in accuracy and a 29% increase in sensitivity. This research can significantly contribute to the early detection and management of glaucoma, indicating potential clinical applications. These advancements will not only further the development of glaucoma diagnostic technologies but also play a vital role in improving patients’ quality of life. Full article

The integration of target capture systems with next-generation sequencing has emerged as an efficient tool for exploring specific genetic regions with a high resolution and facilitating the rapid discovery of novel alleles. Despite these advancements, the application of targeted sequencing methodologies, such as the myBaits technology, in polyploid oat species remains relatively unexplored. In this study, we utilized the myBaits target capture method offered by Daicel Arbor Biosciences to detect variants and assess their reliability for variant detection in oat genomics and breeding. Ten oat genotypes were carefully chosen for targeted sequencing, focusing on specific regions on chromosome 2A to detect variants. The selected region harbors 98 genes. Precisely designed baits targeting the genes within these regions were employed for the target capture sequencing. We employed various mappers and variant callers to identify variants. After the identification of variants, we focused on the variants identified via all variants callers to assess the applicability of the myBaits sequencing methodology in oat breeding. In our efforts to validate the identified variants, we focused on two SNPs, one deletion and one insertion identified via all variant callers in the genotypes KF-318 and NOS 819111-70 but absent in the remaining eight genotypes. The Sanger sequencing of targeted SNPs failed to reproduce target capture data obtained through the myBaits technology. Similarly, the validation of deletion and insertion variants via high-resolution melting (HRM) curve analysis also failed to reproduce target capture data, again suggesting limitations in the reliability of the myBaits target capture sequencing using short-read sequencing for variant detection in the oat genome. This study shed light on the importance of exercising caution when employing the myBaits target capture strategy for variant detection in oats. This study provides valuable insights for breeders seeking to advance oat breeding efforts and marker development using myBaits target capture sequencing, emphasizing the significance of methodological sequencing considerations in oat genomics research. Full article

Team coaching has been found to increase group effort, improve interpersonal processes, and increase team knowledge and learning. However, the team coaching literature is renowned for its inability to define team coaching itself—making it difficult to solidify its place in the world of team science. So far, there is no consensus on what specific training would serve internal leaders best, and how they would connect to the team coaching literature. We know leadership and team training are effective in improving organizational outcomes, but the gap in the literature lies in identifying what specific competencies internal team coaches need, and what training could fulfill these. In this piece, we seek to (1) identify what competencies internal team leaders need based on the outcomes we know team coaching yields, (2) identify specific behaviors that can fulfill these competencies, and (3) integrate the literature to form an evidence-based guide on what training to provide to internal team coaches. By doing so, we hope to provide a definitive understanding of what internal team coaches need to be successful. Full article

Polysaccharides from Dendrobium officinale have garnered attention for their diverse and well-documented biological activities. In this study, we isolated three ethanol-fractionated polysaccharides from Dendrobium officinale (EPDO) and investigated their digestive properties and effects on gut microbiota regulation in vitro. The results indicated that after simulating digestion in saliva, gastric, and small intestinal fluids, three EPDOs, EPDO-40, EPDO-60 and EPDO-80, with molecular weights (Mw) of 442.6, 268.3 and 50.8 kDa, respectively, could reach the large intestine with a retention rate exceeding 95%. During in vitro fermentation, the EPDOs were broken down in a “melting” manner, resulting in a decrease in their Mw. EPDO-60 degraded more rapidly than EPDO-40, likely due to its moderate Mw. After 24 h, the total production of short-chain fatty acids (SCFAs) for EPDO-60 reached 51.2 ± 1.9 mmol/L, which was higher than that of EPDO-80. Additionally, there was an increase in the relative abundance of Bacteroides, which are capable of metabolizing polysaccharides. EPDO-60 also promoted the growth of specific microbiota, including Prevotella 9 and Parabacteroides, which could potentially benefit from these polysaccharides. Most notably, by comparing the gut microbiota produced by different fermentation carbon sources, we identified the eight most differential gut microbiota specialized in polysaccharide metabolism at the genus level. Functional prediction of these eight differential genera suggested roles in controlling replication and repair, regulating metabolism, and managing genetic information transmission. This provides a new reference for elucidating the specific mechanisms by which EPDOs influence the human body. These findings offer new evidence to explain how EPDOs differ in their digestive properties and contribute to the establishment of a healthy gut microbiota environment in the human body. Full article

The atmospheric flow field and weather processes exhibit complex and variable characteristics at small scales, involving interactions between terrain features and atmospheric physics. To investigate the mechanisms of these process further, this study employs a Lagrangian particle motion model combined with a Euler background field approach to construct a small-scale atmospheric flow field model. The model streamlines the modeling process by combining the benefits of the Lagrangian dynamics model and the Eulerian integration scheme. To verify the effectiveness of the Euler–Lagrange hybrid model, experiments using the Fluent wind field model were conducted for comparison. The results show that both models have their advantages in handling terrain-induced wind fields. The Fluent model excels in simulating the general characteristics of wind fields under specific terrain, while the Euler–Lagrange hybrid model is better at capturing the upstream and downstream disturbances of the terrain on the atmospheric flow field. These findings provide powerful tools for in-depth diagnostic analysis of atmospheric flow simulation and convective precipitation processes. Notably, the Euler–Lagrange hybrid model demonstrates excellent computational efficiency, with an average computation time of approximately 2 s per time step in a Python environment, enabling rapid simulation of 40 time steps within approximately 90 s. Full article

Those with visual impairments, including complete blindness or partial sight loss, constitute a significant global population. According to estimates by the World Health Organization (WHO), there are at least 2.2 billion people worldwide who have near or distance vision disorders. Addressing their needs is crucial. Introducing a smart cane tailored for the blind can greatly improve their daily lives. This paper introduces a significant technical innovation, presenting a smart cane equipped with dual ultrasonic sensors for obstacle detection, catering to the visually impaired. The primary focus is on developing a versatile device capable of operating in diverse conditions, ensuring efficient obstacle alerts. The strategic placement of ultrasonic sensors facilitates the emission and measurement of high-frequency sound waves, calculating obstacle distances and assessing potential threats to the user. Addressing various obstacle types, two ultrasonic sensors handle overhead and ground-level barriers, ensuring precise warnings. With a detection range spanning 2 to 400 cm, the device provides timely information for user reaction. Dual alert methods, including vibrations and audio signals, offer flexibility to users, controlled through intuitive switches. Additionally, a Bluetooth-connected mobile app enhances functionality, activating audio alerts if the cane is misplaced or too distant. Cost-effective implementation enhances accessibility, supporting a broader user base. This innovative smart cane not only represents a technical achievement but also significantly improves the quality of life for visually impaired individuals, emphasizing the social impact of technology. The research underscores the importance of technological research in addressing societal challenges and highlights the need for solutions that positively impact vulnerable communities, shaping future directions in research and technological development. Full article

Thunderstorms are a common natural phenomenon posing significant hazards to power systems, structures, and humans. With technological advancements, protection against lightning is gradually shifting from passive to active measures, which require the prediction of thunderstorm occurrences. Current research on lightning warning relies on various data sources, such as satellite data and atmospheric electric field data. However, these studies have placed greater emphasis on the process of warning implementation, overlooking the correlation between parameters used for lightning warning and lightning phenomena. This study relied on the ERA5 dataset and lightning location dataset from 117.5°E to 119.5°E longitude and 24.5°N to 25.5°N latitude during 2020–2021, utilizing Kriging interpolation to standardize the spatiotemporal precision of different parameters. After that, we conducted preliminary screening of the involved parameters based on the chi-squared test and utilized the Apriori algorithm to identify parameter intervals that were strongly associated with the occurrence of lightning. Subsequently, we extracted strong association rules oriented towards the occurrence of lightning and analyzed those rules with respect to lightning current amplitude, types, and ERA5 parameters. We found that thunderstorm phenomena are more likely to occur under specific ranges of temperature, humidity, and wind speed conditions, and we determined their parameter ranges. After that, we divided the target area into regions with different levels of lightning probability based on the strong association rules. By comparing the actual areas where lightning phenomena occurred with the areas at high risk of lightning based on ERA5 parameters, we validated the credibility of the obtained strong association rules. Full article

An intelligent optimization technology was proposed to mitigate prevalent multi-defects, particularly failure, wrinkling, and springback in sheet metal forming. This method combined deep neural networks (DNNs), genetic algorithms (GAs), and Monte Carlo simulation (MCS), collectively as DNN-GA-MCS. Our primary aim was to determine intricate process parameters while elucidating the intricate relationship between processing methodologies and material properties. To achieve this goal, variable blank holder force (VBHF) trajectories were implemented into five sub-stroke steps, facilitating adjustments to the blank holder force via numerical simulations with an oil pan model. The Forming Limit Diagram (FLD) predicted by machine learning algorithms based on the Generalized Incremental Stress State Dependent Damage (GISSMO) model provided a robust framework for evaluating sheet failure dynamics during the stamping process. Numerical results confirmed significant improvements in formed quality: compared with the average value of training sets, the improvements of 18.89%, 13.59%, and 14.26% are achieved in failure, wrinkling, and springback; in the purposed two-segmented mode VBHF case application, the average value of three defects is improved by 12.62%, and the total summation of VBHF is reduced by 14.07%. Statistical methodologies grounded in material flow analysis were applied, accompanied by the proposal of distinctive optimization strategies for the die structure aimed at enhancing material flow efficiency. In conclusion, our advanced methodology exhibits considerable potential to improve sheet metal forming processes, highlighting its significant effect on defect reduction. Full article

Progressive loss of retinal ganglionic cells (RGC) causes degeneration of optic nerve axons, which leads to blindness in glaucoma. Elevated intraocular pressure (IOP) is the most important, treatable risk factor. Currently, the management of glaucoma is centred on reducing the IOP, and drugs in the form of topical drops are the first line of management. Drugs reduce IOP either by suppressing aqueous humour secretion or improving the aqueous humour outflow. Newer drugs added during the past three decades to the armamentarium of glaucoma treatment have targeted the aqueous outflow. With an evolving understanding of the pathogenesis of glaucoma, the role of 24-h IOP control and other IOP-independent risk factors affecting ocular blood flow and RGC toxicity is also being actively studied in clinical and pre-clinical models of glaucoma. The role of available drugs in controlling IOP over 24 h is being evaluated. Improvement of ocular blood flow and neuroprotection are seen as potential drug targets for preventing the loss of RGC. In this article, we review the pharmacotherapy of glaucoma based on current therapeutic principles. Full article

As the current mainstream high-precision ADC architecture, sigma-delta ADC is extensively employed in a wide range of domains and applications. This paper presents the design of a highly efficient cascaded digital decimation filter for sigma-delta ADCs, emphasizing the suppression of high folding band noise and the achievement of a flat passband. Additionally, this study addresses the critical balance between filter performance and power consumption. An inserting zero (IZ) filter is incorporated into a cascaded integrator comb (CIC) filter to enhance aliasing suppression. The IZ filter and compensation filter are optimized using the particle swarm optimization (PSO) algorithm to achieve greater noise attenuation and smaller passband ripple. The designed filter achieves a noise attenuation of 93.4 dB in the folding band and exhibits an overall passband ripple of 0.0477 dB within a bandwidth of 20 KHz. To decrease the power consumption in the filter design, polyphase decomposition has been applied. The filter structure is implemented on an FPGA, processing a 5-bit stream from a 64-times oversampling rate and third-order sigma-delta modulator. The signal-to-noise ratio (SNR) of the output signal reaches 91.7 dB. For ASIC design, the filter utilizes 180 nm CMOS technology with a power consumption of 0.217 mW and occupies a layout area of 0.72 mm². The post-layout simulation result indicates that the SNR remains at 91.7 dB. Full article