Browse Articles

Energy optimization of PV systems under partial shading conditions using various technique-based MPPT methods

Global profiling of α-glucosidase inhibitors from Citri Reticulatae Pericarpium based on affinity ultrafiltration screening coupled with UPLC-ESI-Orbitrap-MS method

As a medicinal and edible herb, Citri Reticulatae Pericarpium has multiple biological activities. The latest modern pharmacological researches have found that Citri Reticulatae Pericarpium has the effect of lowering blood sugar, and its extract can inhibit the activity of α-glucosidase. However, which component has inhibitory activity on α-glucosidase and the degree of inhibition are not clear. In order to solve this problem, this study used affinity ultrafiltration screening coupled with UPLC-ESI-Orbitrap-MS method to systematically screen α-glucosidase inhibitors from Citri Reticulatae Pericarpium for the first time. Through affinity ultrafiltration technology, the active components were selected, and through UPLC-ESI-Orbitrap-MS technology, their structures were identified. Finally, total 84 active ingredients were selected as α-glucosidase inhibitors, and most of them were multimethoxy flavonoids. Our results indicated that inhibiting α-glucosidase activity was probably one of the most important mechanisms for Citri Reticulatae Pericarpium exerting its hypoglycemic effect. In addition, our results first reported that multimethoxy flavonoids had the effects of hypoglycemic activity and potential anti-diabetes value.

Mealworm frass fed on expanded polystyrene helps retention of chrysanthemum flower

Towards an effective refactoring taxonomy for sustainable software systems

Software refactoring is pivotal in improving software quality and ensuring complex software systems’ long-term viability and sustainability. However, developers still face challenges in understanding how refactoring approaches influence software quality, as existing classifications largely overlook sustainability aspects and provide limited guidance for long-term software evolution. This gap creates difficulties for developers in selecting appropriate refactoring approaches supporting quality improvement and sustainable maintenance. Therefore, this study addresses these challenges by proposing a novel refactoring taxonomy based on estimated external quality attributes (EEQAs). The proposed taxonomy was developed through three key phases: exploratory study, experimental study, and multi-case analysis. The exploratory study identified the most used refactoring approaches in practice, the EEQAs (effectiveness, extendibility, flexibility, functionality, reusability, and understandability), and five case studies. In the experimental study, 41 experiments across the case studies were conducted to assess the influence of refactoring approaches on EEQAs. Then, a multi-case analysis was performed to examine these effects across all case studies. The proposed refactoring taxonomy categorized the refactoring approaches into positive, negative, and ineffective groups by using their aggregate impact on the EEQAs. The proposed taxonomy puts software sustainability practices at the forefront, prioritizing EEQAs: effectiveness, extendibility, flexibility, functionality, reusability, and understandability. It offers developers a systematic approach to improving software quality, aligning with user expectations, supporting future enhancements, and facilitating system maintenance. By prioritizing these attributes in refactoring practices, developers can build sustainable, robust, and maintainable software systems that deliver long-term value to stakeholders, effectively manage the complexity of software systems, and maintain high code quality standards over time.

Voice-controlled autonomous navigation for smart wheelchairs using ROS-based SLAM

Abstract Smart wheelchairs have the potential to significantly improve autonomy for individuals with severe motor impairments, yet existing systems often exhibit limited speech robustness, insufficient handling of dynamic environments, and a lack of rigorously validated safety mechanisms. This work presents a fully integrated, voice-controlled smart wheelchair that advances assistive mobility through three main contributions. First, we introduce an inclusive speech-recognition module built from a fine-tuned deep learning model trained on a custom dataset that incorporates recordings from users with mild speech impairments. This adaptation improves robustness to non-standard pronunciation and maintains reliable command execution under realistic noise conditions (70–75 dB), achieving a Word Error Rate of 6.7% in quiet environments. Second, rather than proposing a new SLAM method, we develop a system-level navigation framework that optimally integrates 2D LiDAR-based SLAM (GMapping), AMCL localization, and a dual-level voice-command interface within a real-time coordination layer. This includes a quantitatively parameterized safety module featuring adaptive speed modulation and experimentally calibrated emergency-stop thresholds, ensuring reliable operation in dynamic indoor environments. Third, we conduct an extensive experimental campaign in both simulation and real-world conditions to provide a reproducible and quantitative evaluation of system performance. Tests involving dynamic obstacles (pedestrians, wheeled carts, small animals), constrained passages, and diverse acoustic settings demonstrate a mean localization error below 10 cm, a 94% goal-completion rate, and an end-to-end voice-to-motion latency of 0.8 s. Together, these contributions provide a low-cost, experimentally validated assistive-mobility platform that emphasizes inclusive voice interaction, robust real-time navigation, and safety-aware behavior. The proposed framework moves beyond component-level studies by offering a coherent, deployable, and reproducible solution for everyday indoor environments.

Effects of wet-dry cycles on the bimodal soil-water characteristic curve and unsaturated permeability of granite residual soil

The unsaturated permeability coefficient of granite residual soil (GRS) increases rapidly with rising moisture content, as the loss of matric suction enhances the continuity of the water phase within the soil pores. This can lead to slope instability and embankment collapse during rainfall. This study investigated the effects of wet-dry cycles on the hydraulic and microstructural evolution of GRS, introducing key innovations over prior research. First, microstructure changes were investigated using mercury intrusion porosimetry (MIP) tests, investigates the evolution of bimodal pore structure under cyclic wetting and drying. Second, the entire range of matric suction was comprehensively measured by integrating the pressure plate method (PPM), filter paper method (FPM), and vapor equilibrium method (VEM), capturing both low and high suction regimes comprehensively. Third, the Li model was applied to fit the bimodal SWCC across different wet-dry cycles, the unsaturated permeability coefficient was calculated using the Zhai model. The results indicate that the microstructure of GRS under different wet-dry cycles presents a clear bimodal pore size distribution (PSD), intra-aggregate pores peaked near 450 nm, while inter-aggregate pores ranged between 20,000–60,000 nm.. After six wet-dry cycles, the volume of the dominant intra-aggregate pores decreased by approximately 25%, while the larger inter-aggregate pores saw a reduction of about 15%, indicating a coarsening of the pore network. Meanwhile, there is a clear decrease in inter-aggregate pore distribution density. The combination of measurement methods can cover the entire matric suction range. The Li model is applied to fit the SWCC under different wet-dry cycles, and the correlation coefficient (R2) are all higher than 0.95. The unsaturated permeability coefficient of GRS exhibits a nonlinearly variation with saturation, in-creasing with the increase in saturation or the increase in wet-dry cycles. The unsaturated permeability coefficient of bimodal GRS was calculated based on the Zhai model and the lgk(s) and saturation can be expressed by a logarithmic function, with the correlation coefficient (R2) higher than 0.99 under different wet-dry cycles. The study contributes useful insights into the evolution of pore structure and hydraulic behavior of GRS under cyclic wetting and drying, which is important for slope stability and hydrological modeling in subtropical regions.

Software-defined self-learning control system for industrial robots by using reinforcement learning

Patient satisfaction in outdoor department of primary health care facilities in Rohingya refugee camps in Bangladesh: A cross-sectional study

Background Perception of patients on healthcare services is important in evaluating the quality of a healthcare structure. Focusing on a major humanitarian emergency in South-East Asia, this research aims to explore patient satisfaction regarding primary health care in Rohingya refugee camps placed in Bangladesh. Methods We conducted this cross-sectional study during November 2023 – March 2024 in five randomly selected primary health care centers in five different Rohingya refugee camps of Bangladesh. Upon selection by systematic random sampling method, 810 outdoor patients were interviewed in-person by trained data collectors. We utilized a structured questionnaire based on the Patient Satisfaction Questionnaire Short Form (PSQ‑18) of Marshall and Hays. We analyzed completed response of 723 patients by IBM SPSS (v. 27) checking normality and internal consistency. Mean, standard deviation and percentage were generated for all dimensions of patient satisfaction including all PSQ-18 items. Finally, we used Kruskal–Wallis test and multivariate linear regression to explore differences and associations between patient characteristics and different dimensions of patient satisfaction. Results With major responses from 18–39 years (68.7%), female (81.1%) and Rohingya ethnicity (96.8%), overall satisfaction was found among nearly 90% patients. Domain of interpersonal manner received highest satisfaction (95.93%) whereas the lowest was observed in accessibility and convenience (84.50%) with minor variability across different satisfaction dimensions. Ethnicity, key source of household income, type of visit and perception of type to illness were found as significant predictors in most satisfaction domains ( p  < 0.05). Conclusions We concluded this study with high satisfaction in outpatient care of Rohingya camps. Therefore, focused interventions should be adopted by policymakers for maintaining the high content in patients with additional attention in domains of less patient satisfaction. Extended and periodic evaluation of patient satisfaction should be conducted for upgrading the health system of Rohingya humanitarian emergency in a patient-centric approach.

Advancing skin cancer detection through deep learning and fusion of patient metadata and skin lesion images

Abstract There has been a significant rise in skin cancer incidence during the last three decades and the waiting time for skin lesion assessment in both the NHS and private sectors in the UK has increased significantly. Therefore, to reduce waiting time and to make a faster decision, there is a need to develop automated methods that can be used to classify whether a skin lesion is suspicious or non-suspicious during teledermatology triage. In this study, we propose an AI framework that uses patient metadata together with image data to classify skin lesions into suspicious or non-suspicious categories. To evaluate our proposed approach, we collected 79,246 skin lesion images along with their 22 meta-features such as lesion size, lesion colour, lesion shape, patient age, and gender from 19,295 patients who attended a network of private skin cancer diagnostic centres across the UK. We developed three separate models for skin lesion classification: (1) an AI model using only metadata that achieved 85.24 ± 2.20% sensitivity and 61.12 ± 0.90% specificity; (2) an AI model using only images that achieved 99.72 ± 1.35% sensitivity and 63.22 ± 3.11% specificity; and (3) a fused model based on both metadata and images that achieved 99.66 ± 0.28% sensitivity and 74.45 ± 0.80% specificity. The decisions of the developed AI models were then fused through a majority voting technique, which achieved a sensitivity of 99.50 ± 1.18% and a specificity of 82.72 ± 1.64%, significantly outperforming the state-of-the-art methods that rely solely on image data. Furthermore, we add a post-processing step to explain AI model decisions by implementing a soft-attention module that provides essential explainability and supports healthcare professionals in informed decision-making. The developed AI framework has great potential for the detection of suspicious skin lesions. With a reduction in patient referrals for possible biopsies, waiting times for skin cancer diagnosis and treatment will be shortened, resulting in improved outcomes.

Computational screening of natural inhibitors against Plasmodium falciparum kinases: Toward novel antimalarial therapies

An important worldwide problem is the resistance of Plasmodium falciparum to practically all antimalarial medications. Therefore, new treatment approaches are urgently needed. The development of antimalarial medications frequently involves two important therapeutic targets: casein kinase 2 (CK2) and cGMP-dependent protein kinase (PKG). To identify naturally occurring chemicals that could be used as antimalarial medications to combat multidrug-resistant P. falciparum , we used a multi-targeted in silico strategy in this study. The top 20 compounds, including the reference drug RY-1–65, were selected after pharmacophore-based virtual screening of naturally produced compounds. These compounds were subsequently docked onto both target proteins using Maestro (Schrödinger 2020−3). The best-scoring compounds against PKG and CK2 were Ligand-9 (−7.490 kcal/mol) and Ligand-13 (−11.468 kcal/mol), respectively. These lead compounds may be useful as therapeutic targets based on an assessment of their pharmacological, toxicological, and bioactivity characteristics. Furthermore, Ligand-13’s strong reactivity and stability were demonstrated by density functional theory analysis, and these findings were confirmed by molecular dynamics simulations and binding free energy MMGBSA calculations. These results imply that Ligand-13 may be a promising antimalarial medication.

Factors associated with chronic kidney disease among patients with hepatitis c infection attending Kigeme district hospital, Rwanda

Prognostic value of tumor deposits and their different response to neoadjuvant therapy in locally advanced rectal cancer

Background Tumor deposits (TDs) may have a worse prognosis in rectal cancer, but their significance in the neoadjuvant era is less certain. Post-treatment TDs might even be a sign of tumor response. The present study aimed to assess the clinical significance of TDs detected before and after neoadjuvant therapy, and to investigate the impact of neoadjuvant therapy-induced TDs changes on oncological outcomes. Methods A retrospective cohort analysis using our hospital records from 2017 to 2019 was carried out. All patients received preoperative long-course chemoradiotherapy and part of them received total neoadjuvant therapy. Results A total of 132 patients with cT 3-4 N + M 0 were included. mrTDs were observed in 40 (30.3%) patients. 40% of the patients had two or more mrTDs. 64.4% of mrTDs located in the mesorectal fat. mrTDs were associated with mrT4 stage, lymph node invasion, threatened mrMRF, and positive mrEMVI. 51.4% of mrTDs positive patients achieved complete response after neoadjuvant therapy. 3‐year disease‐free survival (DFS) and overall survival (OS) were worse in mrTD positive patients (3y-DFS: 42.5% vs 73.9%, P  < 0.001; 3y-OS: 55% vs 82.9%, P  < 0.001). Among the patients with mrTDs, those who became ypTDs- after neoadjuvant therapy had better outcome compared to the ypTDs+ patients (3y-DFS: 52.6% vs 22.2%, P  = 0.022; 3y-DMFS: 63.2% vs 27.8%, P  = 0.025). Distant metastasis occurred earlier and more frequently in ypTDs+ group, and multiple metastasis were more common. ypTDs and TDs’ different response to neoadjuvant therapy were prognostic factors of overall survival in multivariate analysis. Conclusions The presence of mrTDs and the poor regression of mrTDs in cT 3-4 N + M 0 rectal cancer after neoadjuvant treatment are associated with advanced disease and worse outcome. Patients with ypTDs+ after neoadjuvant therapy have dismal outcome, which call for more innovative treatment.

Impacts of climate change and land use dynamics on soil erosion in the Qinghai–Tibet plateau

Genome-wide identification and functional characterization of alpha-amylase genes in Litopenaeus vannamei

Alpha-amylase is a key enzyme involved in carbohydrate hydrolysis and food digestion in animals. However, its molecular characteristics and functions remain poorly understood in the economically important Pacific white shrimp, Litopenaeus vannamei . Through comparative genomic analysis, this study revealed that the α-amylase ( Amy ) gene family has undergone an expansion in arthropods, particularly crustaceans, while retaining highly conserved catalytic domains. Six Amy genes were identified in L. vannamei . Their expression patterns across tissues and developmental stages revealed predominant transcription in the hepatopancreas, with significant upregulation during periods of high energy demand, such as zoeal feeding and pre-molting. Among these genes, Lv-Amy (XP_027225605.1) exhibited the highest expression level. Quantitative real-time PCR (qPCR) and fluorescence in situ hybridization (F IS H) further characterized the tissue distribution and cellular localization of Lv-Amy . Structurally, Lv -Amy displays a typical (β/α)₈ TIM barrel conformation and two conserved calcium-binding sites. The recombinant Lv -Amy protein was produced in an E. coli expression system and its enzymatic properties were characterized. Maximal activity of the recombinant Lv -Amy protein was observed at pH 7.5 and 25°C, while activity remained above 50% of the maximum within pH 7.0–8.0 and 20–45°C, indicating that Lv- Amy can function efficiently under environmental conditions characteristic of the tropical marine habitat of L. vannamei . In summary, this study provides new insights into the molecular characteristics and functions of α-amylase in L. vannamei , suggesting that Lv-Amy plays an important role in digestion and offering a reference of stage-specific nutritional formulation for this species.

Detecting illicit transactions in bitcoin: a wavelet-temporal graph transformer approach for anti-money laundering

Well-being issues: Its influence on RPE and enjoyment in masters water polo training and the player–coach gap

The present study aimed to monitor male master water polo players’ training by means of well-being (Hooper-Index), internal training load (ITL) parameters (rating of perceived exertion, RPE; session-RPE), and rate of enjoyment, for different types of training (i.e., swimming, SW; technical and tactical, TTW; training matches, TM; friendly matches; FM). Seventeen male master water polo players (age: 50 ± 12 years) performed 19 ± 7 sessions and reported Hooper-Index scores in the morning of training day, and RPE (CR-10) and rate of enjoyment after sessions. Linear mixed effects models were applied to quantify whether players’ RPE, session-RPE, and rate of enjoyment were: (i) different for type of training session, (ii) affected by pre-session well-being, and (iii) correlated to corresponding coach’s estimations. FM was the training type with the highest session-RPE (p < 0.001, ES range = 1.4–1.9), whereas SW reported the lowest rate of enjoyment (p < 0.05, ES range = 0.8–1.4). Similar effects emerged for coach’s estimations (the highest session-RPE in FM, p < 0.001, ES range = 1.4–2.1; the lowest rate of enjoyment in SW, p < 0.001, ES range = 3.2–5.3). RPE resulted affected by all well-being factors excepting sleep quality (β range = 0.16–0.28), whereas session-RPE was influenced only by fatigue, and Hooper-Index overall (β = 0.23) and no effect emerged for rate of enjoyment. Finally, players’ and coach’s ITL and rate of enjoyment were not correlated, with exception of TM session-RPE (β = 0.21). Master water polo coaches could benefit from these findings, being aware of how training load could be: different for types of workouts, influenced by pre-session well-being, and differently perceived by players if compared with their coach’s estimations.

Correction: Concordance of HER2-low scoring in breast carcinomas among pathologists

Investigating epigenetic biomarkers of age, sex, and disease in captive South African cheetahs (Acinonyx jubatus jubatus)

Epigenetic modifications, particularly DNA methylation, are strongly associated with chronological age across mammalian species. This study developed cheetah-specific epigenetic clocks from methylation profiles generated from cheetah blood and liver samples tested on the HorvathMammalMethylChip40 Illumina Array. The resulting age clock used 52 CpG sites and predicted age across blood and liver samples ( r  = 0.97 and MAE = 0.86). When applied to a test set of blood collected from live cheetahs, the clock provided accurate predictions for adult individuals (age > 3 years) but was less precise at and around age of sexual maturity. A second clock, incorporating cheetah, lion, and tiger profiles, used 46 CpG sites and predicted age across these feline species ( r  = 0.94 and MAE = 1.16). Additionally, a sex clock using 67 CpG sites accurately predicted sex in all test samples. To explore the potential of methylation as a biomarker beyond age and sex, we conducted a differential methylation analysis to investigate disease-related methylation patterns in cheetahs diagnosed with hepatic sinusoidal obstruction syndrome (SOS). This analysis identified 4,377 CpG sites with significant differences between SOS-positive and SOS-negative cheetahs (adjusted p-value < 0.05). These findings advance the development of epigenetic clocks for precise age and sex prediction in cheetahs and related species and establish a foundation for leveraging methylation biomarkers to investigate diseases in wildlife conservation efforts.

Exosome encapsulated albumin nanoparticles target delivery of DBET6 as a treatment for triple-negative breast cancer

Triple-negative breast cancer (TNBC) is a highly aggressive disease with significant mortality, and there is an urgent need for therapies that can effectively target the disease and enhance patient survival rates. The BET family protein BRD4 plays a key role in the development and progression of TNBC. Its degrader, dBET6—a proteolysis-targeting chimera (PROTAC) molecule—shows promising anti-tumor potential but suffers from low bioavailability and poor tissue selectivity. To improve its targeted delivery efficiency, this study developed a novel nanodrug delivery system, Exo-BSA@dBET6, which encapsulates dBET6 within bovine serum albumin (BSA) nanoparticles and further coats them with milk-derived exosomes, leveraging both the natural targeting ability of exosomes and the high drug-loading capacity of BSA. The results demonstrated that Exo-BSA@dBET6 has a uniform particle size of approximately 85.89 nm, good stability, high encapsulation efficiency, and excellent biocompatibility. In vitro experiments showed that this nanosystem significantly enhanced the cellular uptake of the drug in MDA-MB-231 cells, primarily through clathrin-mediated endocytosis, and exhibited efficient lysosomal escape. Compared to free dBET6 and BSA@dBET6, Exo-BSA@dBET6 displayed stronger cytotoxicity, significantly induced apoptosis, increased reactive oxygen species (ROS) levels, reduced mitochondrial membrane potential, and up-regulated caspase-3 protein expression. Western blot analysis further confirmed that Exo-BSA@dBET6 effectively degraded BRD4 protein, down-regulated c-Myc, and up-regulated Bax expression. Transcriptome sequencing analysis indicated that the nanosystem exerts anti-tumor effects by modulating key signaling pathways such as PI3K-Akt and Rap1. This study successfully constructed an exosome-modified albumin-based nanodrug delivery system that significantly enhances the targeting and anti-TNBC efficacy of dBET6, providing a new strategy for the targeted therapy of TNBC.

Blood-brain barrier integrity and prevalence of intrathecal T helper 17.1 cells in Huntington´s disease

Background Blood-brain barrier (BBB) involvement in the pathogenesis of Huntington´s disease (HD) is not well understood. We previously demonstrated increased prevalence of T Helper 17.1 (Th17.1) cells in the cerebrospinal fluid (CSF) of HD gene-expansion carriers (HDGECs), which might indicate a dysfunction in the BBB or the blood-CSF barrier (BCB) in HD. Objective The aim of this exploratory study is to investigate whether the CSF/plasma albumin quotient (Q-Alb) and CSF platelet-derived growth factor-β (PDGFR-β) can be used as biomarkers for BBB/BCB integrity in HD and if there is an association between Q-Alb and the prevalence of intrathecal Th17.1 cells in HDGECs. Methods A total of 145 HDGECs and controls were included in the Q-Alb analysis. Forty-four of these individuals underwent a second lumbar puncture after five years and were included in the analysis of changes in Q-Alb over time. CSF from 33 HDGECs and controls was analysed for Th17.1 cells and CSF from 100 HDGECs and controls was analysed for PDGFR-β. Results No significant difference for Q-Alb was found between the pre-motor manifest HDGECs, motor manifest HDGECs, and controls (p = 0.49). We found a significant increase in Q-Alb in HDGECs over the 5-year period (p = 0.014), but when compared with controls, no significant difference was found (p = 0.32). No significant association was found between Q-Alb and the prevalence of Th17.1 cells (p = 0.97) nor Q-Alb and PDGFR-β (p = 0.89) in HDGECs. Conclusion We found no evidence of increased BBB/BCB leakage of albumin in HDGECs compared to controls. Neither did we find signs of pericyte involvement as measured by PDGFR-β in HDGECs. These results suggest that overt BBB/BCB disruption may be limited in HDGECs. Future longitudinal studies should employ more sensitive methods like dynamic contrast-enhanced magnetic resonance imaging to evaluate region specific microleaks.