Browse Articles

Scene-aware contrastive learning with multi-scale domain-invariant feature alignment for robust visual recognition under complex scenes

Automatic sentence simplification system for Arabic Script Punjabi

In the domain of language simplification, creating aligned monolingual parallel datasets tailored to specific linguistic dialects is a significant endeavor. This pursuit, introduces the pioneering Punjabi Simplification (PUSIM) corpus, which focuses on the Shahmukhi dialect. Shahmukhi, one of the two prominent dialects of Punjabi, serves as the foundation for this corpus development. This study employs a hybrid approach that ensures the comprehensive assessment of simplification outcomes. The detailed process of simplification underwent thorough examination, aiming to transform complex sentences into simpler ones by enhancing writing clarity and vocabulary. To quantify the quality and readability of simplified texts, automated readability assessments were conducted using well-established text readability metrics, a significant SARI score of 45.3, attested to the high quality of simplification approach. The unique aspect of this work lies in its focus on the Shahmukhi dialect, addressing a linguistic facet that had previously received limited attention in natural language processing. It is anticipated that this dataset will pave the way for further exploration and research, offering novel possibilities for leveraging automated simplification techniques in the realm of Shahmukhi Punjabi language processing.

TM-Loop: Transformer multi-omics hierarchical detection of chromatin loop

Abstract Chromatin loops form the hierarchical 3D genome architecture and act as critical regulatory hubs, bringing distant cis-elements together to precisely control target gene transcription. Disruption of these spatial interactions is closely linked to human diseases including cancer. Hi-C provides genome-wide interaction maps, yet robust identification of chromatin loops remains a major bottleneck in 3D genomics, especially for contact matrices with low signal-to-noise ratio and high sparsity. We propose TM-Loop, a framework for accurate chromatin loop detection that integrates multi-omics data, Transformer deep learning, and hierarchical multi-scale clustering. Using 10 kb Hi-C matrices as core data, it combines ATAC-seq and CTCF ChIP-seq signals to build a weighted feature system and reduce sample imbalance. The Transformer’s multi-head attention captures global and local feature dependencies, while dual-threshold filtering and anchor-guided clustering effectively remove false signals and lower false discovery rate. Source code: https://github.com/yimuhuashui/TM-Loop. Experiments show TM-Loop outperforms existing methods in APA, protein enrichment, and 3D structural consistency, providing a new tool for high-precision genome-wide chromatin loop analysis.

From means to meaningful: undertaking cluster analysis to develop health literacy profiles of people in Australian prisons

Prison populations are diverse, experience substantial vulnerabilities and commonly have poor health outcomes. Cluster analysis of Health Literacy Questionnaire (HLQ) data provides an opportunity to account for the prison population’s diversity and generate fit-for-purpose intervention ideas for the prison context. This mixed-methods study aimed to undertake cluster analysis to explore the diverse health literacy profiles of people in the New South Wales (NSW), Australia, prison setting, and to co-design a series of vignettes that represent people in prison. Cluster analysis using Ward’s method was applied to HLQ data (n = 471) to identify health literacy profiles of people in NSW prisons. Semi-structured interviews with people in prison were conducted to collect in-depth personal experiences of prison health services access and use. Interview data were combined with cluster analysis results to co-design vignettes with various stakeholders. A 14-cluster solution was identified as the optimal solution for the sample as a whole, whereas a 9-cluster solution was identified for the sample of people who self-identified as Aboriginal. Qualitative data from 10 semi-structured interviews were combined with the health literacy profiles identified in the cluster analyses. A total of 23 vignettes were co-designed with stakeholders (n = 34) to represent the voices of a typical person with lived experience across each cluster. Cluster analysis has unmasked previously unforeseen variations and enabled us to move from merely reporting means to gaining meaningful insights into the health literacy profiles of people in prisons. Our findings are important because they show that using the mean or proxies alone does not capture population variation, which may inadvertently exclude or disadvantage population subgroups. The co-designed vignettes are expected to stimulate discussions to generate localised, fit-for-purpose health literacy-informed interventions to address health inequities for prison populations in NSW.

Dynamics of genetic and somatic trade-offs in ageing and mortality

Abstract DNA variants modulate mortality risks across an entire lifespan but their dynamic age-dependent effects have not been resolved in any species for either sex. Here we mapped variants that shape mortality using an actuarial approach, starting with a base population of 6,438 pubescent mice and ending with 559 survivors that lived beyond 1,100 days of age. Twenty-nine Vita loci influence lifespan with strong age- and sex-specific effects. Most act during distinct stages with polarities that often invert with age, but a minority have consistent age-dependent effects in one or both sexes. A separate set of 30 Soma loci influence correlations between body mass and life expectancy. Nineteen Soma loci mediate higher mortality in larger young mice, whereas 11 mediate lower mortality in larger old mice. All effects are stronger in male mice than in female mice. Vita and Soma loci form epistatic networks split strictly by sex. These findings provide a genetic bridge between evolutionary theories of ageing and molecular mechanisms that can guide interventions to extend healthy lifespan.

Design of a high-efficiency gilbert mixer with current source assistance and current bleeding for HEV and wireless sensor network applications

Abstract The effective creation of better, faster, and more efficient electronic circuits particularly in the radio frequency (RF) segment, is more important than ever for the entire world. A prevalent issue in wireless communication systems, such as those used for charging or Vehicle-to-Everything (V2X) communication, interference and signal reception problems are related to the receiver front end of electric vehicles (EV) applications. Modern receiver technologies are one way to address this issue, as they reduce interference and enhance signal reception. To address the above requirements, this paper introduces a down conversion Gilbert mixer with the improvement in conversion gain, power efficiency, linearity and noise performance. Here, the proposed mixer design uses current source helpers and current bleeding technique to enhance the performance of the conventional Gilbert mixer. The proposed mixer is simulated in Cadence Tool with an intermediate frequency (IF) of 100 MHz, which provides a conversion gain of 12 dB with the third order input intercept point (IIP3) of 4.5 dBm and a noise figure (NF) of about 9.86 dB. Also, the design functions at a supply voltage of 1.2 V, with a power consumption of only 0.96 mW. So, this mixer design may be the correct choice as a core component in the receiver front end in applications like HEVs and sensor networks, especially where wireless communication, signal conversion, and sensing are involved.

Gene therapy rescues cone function in an all-cone retina mouse model with the most common cone opsin C203R missense mutation

Blue cone monochromacy (BCM) is an X-linked cone dystrophy characterized by loss of long- (L) and medium-wavelength (M) cone function. A common cause is the C203R missense mutation, which occurs in both OPN1LW and OPN1MW , or in hybrid OPN1LW/OPN1MW opsin genes. Because BCM primarily affects foveal cones, we generated Opn1mw C198R /Opn1sw -/- /Nrl -/- ( C198RAC ) mice carrying the murine equivalent of the human C203R mutation on an all-cone retinal background. C198RAC mice exhibited absent photopic ERG responses and significantly shortened cone outer segments, recapitulating foveal cone deficits in BCM. Metabolomic profiling further revealed altered retinal metabolism, including reduced cGMP and elevated oxidative stress–related metabolites. To evaluate therapy, we delivered AAV8-Y733F expressing human L-opsin (OPN1LW) cDNA under the cone-specific PR2.1 promoter at 1 and 5 months of age. Treatment restored cone function, regenerated outer segment structures, and provided rescue for at least 5 months post-injection in both early- and late-treatment groups. These results demonstrate that densely packed cones expressing only the C198R mutant opsin remain viable targets for gene therapy. Together, this study establishes the C198RAC mouse as a cone-rich model mimicking foveal cone conditions in BCM and provides compelling preclinical evidence that AAV-mediated gene augmentation can rescue cone outer segment structure and function, supporting the feasibility of gene therapy for BCM.

Technology mediation in child sexual exploitation and abuse in Africa and Asia

Abstract As digital access expands rapidly among children worldwide, technology-facilitated child sexual exploitation and abuse (CSEA), including online grooming, sexual solicitation, non-consensual image sharing and sexual extortion, has emerged as urgent yet underexamined category of digital harms 1 . Despite growing policy attention to online safety, evidence remains limited, particularly in low- and middle-income countries, where most of the world’s children live 2 . We analysed nationally representative survey data from 11,912 children aged 12–17 years across 12 countries in eastern and southern Africa and Southeast Asia, collected through the Disrupting Harm project in 2020–2021. We found that one in six internet-using children experienced at least one form of technology-facilitated CSEA, equivalent to over 10 million children. Despite this scale, many experiences went undisclosed, pointing to disclosure as a critical pathway for protection in the digital age. When children did disclose, they relied primarily on informal channels, especially friends, rather than formal reporting mechanisms such as police or helplines. Using Bayesian hierarchical models accounting for cross-country heterogeneity, we find that older children were less likely to disclose, whereas enabling parental mediation of online activities and children’s knowledge of where to seek help after sexual harassment or assault were associated with higher rates of disclosure. These findings provide population-level evidence to inform prevention and response across low- and middle-income countries, where coordinated action by policymakers, law enforcement and technology companies is urgently needed to protect all children.

Concept inconsistency in dermoscopic concept bottleneck models: a rough-set analysis of the Derm7pt dataset

Facilitating early diagnosis of chronic thromboembolic pulmonary hypertension with dynamic chest radiography: Protocol for a multicenter, assessor-blinded, case-wise randomized superiority reader study (FIND-DCR)

Introduction Chronic thromboembolic pulmonary hypertension (CTEPH) is a treatable cause of pulmonary hypertension but remains under-recognized and is often diagnosed with delay. Limited access to lung ventilation-perfusion (V/Q) scintigraphy, especially outside tertiary centers, is one contributor. Dynamic chest radiography (DCR), with a pulmonary circulation analysis program, can provide a rapid, non-invasive, and widely deployable assessment of pulmonary perfusion. We describe the protocol of a multicenter reader study testing whether adding DCR-based analysis to standard initial work-up improves diagnostic accuracy for CTEPH among patients with echocardiographically suspected pulmonary hypertension. Methods and analysis This investigator-initiated, multicenter, assessor-blinded, case-wise randomized superiority reader study compares standard initial work-up (blood tests, chest X-ray, ECG, pulmonary function tests, and transthoracic echocardiography per guidelines) with standard work-up plus DCR-based pulmonary circulation analysis. The primary endpoint is diagnostic accuracy for discrimination between CTEPH and non-CTEPH in the intention-to-treat set. The final diagnosis of CTEPH versus non-CTEPH will be defined as the reference standard according to the Japanese and European guidelines for pulmonary hypertension. Secondary endpoints include sensitivity, specificity, positive and negative predictive values; agreement with V/Q scintigraphy regarding regional perfusion defects using κ statistics; and STARD-conformant academic performance evaluation of DCR-based pulmonary circulation analysis and lung perfusion scintigraphy in relation to the site-level final diagnosis of CTEPH versus non-CTEPH in a full analysis set. Safety endpoints include adverse events during DCR acquisition and device malfunctions. The target sample size is 108 cases with 1:1 allocation. Recruitment started on 30/07/2025 and is expected to continue until 28/02/2027, with overall study completion planned for 31/05/2027. Discussion This multicenter reader study addresses a key limitation of current CTEPH diagnostic pathways—reliance on V/Q scintigraphy, which may be delayed or unavailable outside tertiary centers—by evaluating whether DCR-based pulmonary circulation analysis can improve early discrimination of CTEPH and support timely referral. Trial registration number Japan Registry of Clinical Trials (jRCT), jRCT2072250027.

A pro-carcinogenic bacterial toxin binds claudin-4 to cleave E-cadherin

Quality of life experiences of breast cancer patients undergoing chemotherapy: a descriptive qualitative study from Ayder Comprehensive Specialized Hospital, Ethiopia

Prompt engineering in the age of generative AI: Insights from public discourse on social media

Background Public discourse on “prompt engineering” has grown rapidly, but large-scale evidence on how people discuss it is limited. The nascent coinage describes a user journey of optimizing text-based parameters within large language models and generative AI platforms in a trial-and-error process, adding modifiers or key phrases to yield a satisfactory output. While several studies have systematically and taxonomically mapped these techniques, no big data studies have specifically delved into the public reception to the concept. The study significantly contributes to the literature by documenting emerging new trends. It is prudent to keep abreast of discursive content as these techniques enter into the public lexicon, by capturing public discourse, sentiments and dominant themes. Objectives This paper maps prominent discussion peaks and quarter-by-quarter themes and sentiment in posts mentioning “prompt engine*” on X and Reddit (1 May 2023–30 April 2024). Methods We analyzed a large social media corpus (n = 298,774) of publicly-available English-language posts containing “prompt engine*” (engine/engineer/engineering/engineered). Our first research direction detected discussion spikes using peak-prominence modeling (pre-specified prominence threshold at 95 th -percentile significance), then qualitatively coded the top-engagement posts on peak dates. Our second research direction computed quarterly sentiment, frequent bigrams, and emoji usage. Results Six peaks centered on: (i) skill validity, (ii) future ramifications, (iii) title longevity, (iv) artist-attribution disputes, (v) model bias/guardrails, and (vi) analogies to child-rearing. Negative sentiment increased from 14.1% (Q1) to 37.3% (Q4), while positive sentiment fell from 36.4% to 22.8%. Tutorials dominated early content; later quarters featured humor, satire and legal liability discussions. Conclusions Public narratives around prompt engineering increasingly question legitimacy, longevity, and ethics. Clearer terminology, transparency about guardrails, and guidance on responsible use may help align expectations and practice.

GPRF-HPNet Physics-guided texture-aware fusion for real-world underwater image enhancement

Constructing a profound experience model of Chinese Intangible Cultural Heritage Tourism based on grounded theory

The purpose of this paper is to understand the generative mechanism of the profound experience in Chinese Intangible Cultural Heritage (ICH) tourism and its construction of meaning, to enrich the research on cultural tourism experiences, and to provide theoretical support for the sustainable development of Chinese ICH tourism. The study employs a Grounded Theory approach to summarize the theoretical model of profound experiences in Chinese ICH tourism, based on the network text descriptions of typical profound experiences in Chinese ICH tourism. The results of the study indicate that:(1) The theoretical model of profound experience in Chinese ICH tourism consists of four main categories: basic conditions, perceptual evaluation, personal significance, and social significance, along with 15 corresponding subcategories. (2) Professional service touchpoints, experience content innovation, scene atmosphere creation, application of modern technology, participation in interactive socialization are the basic conditions for the generation of profound experiences in ICH tourism. The dimensions of perceptual evaluation, such as sense of participation, sense of wonder, sense of immersion, sense of resonance, and sense of value, can describe the profound experiences obtained by tourists. Cultural cognition, cultural identity, and cultural memory reflect the personal significance achieved through the profound experience of ICH tourism, while the inheritance and dissemination of ICH reflect its social significance. The findings of this paper highlight the importance of profound experiences in enhancing the quality of cultural tourism and offer insights to Chinese tourist attractions, assisting them in improving tourism design in aspects such as tourism products, service systems, and scenarios, thereby elevating the overall experience quality of ICH tourism.

Integrated GC–MS and ATR–FTIR analysis of airborne microplastics captured by spider webs

Abstract Our study evaluated airborne microplastics (MPs) captured by spider webs (Agelenidae) in an urban environment (Wrocław, Poland). GC–MS was used to characterize extractable organic compounds linked to MPs, while ATR–FTIR spectroscopy enabled detection of polymer-related signals in solid residues after solvent extraction. All samples contained compounds associated with polymeric materials, including rubber- and silicone-related components, with rubber signals detected at all sites. No significant differences were observed between central and suburban locations, indicating a relatively uniform distribution of airborne MPs. ATR–FTIR results further suggested the occurrence of tire-derived materials in all samples, along with polyamides (Nylon 6; 40%), polypropylene-related materials (including Epcar 5875; ~20%), polyvinyl alcohol (20%), and polyethylene (LDPE; 13%), expressed as frequency of occurrence across samples. Overall, the results demonstrate that spider webs can serve as accessible passive samplers, providing a qualitative and integrative representation of airborne microplastic contamination in urban environments.

Virulence determinants and toxin profile of methicillin resistant Staphylococcus aureus from commercial cheese in Bangladesh: A public health risk

Cheese, a widely consumed dairy product, can be contaminated with Staphylococcus aureus (S. aureus) , a pathogen capable of producing toxins harmful to humans. Of particular concern is Methicillin-Resistant S. aureus (MRSA), which harbors antimicrobial resistance genes and secretes super-antigenic toxins. Present investigation aimed at determining the occurrence and characterizing MRSA in commercial cheese, to evaluate its potential public health risks. 120 cheese samples representing twelve commercial brands were collected in ten different batches over a six-month period in Sylhet, Bangladesh. The quality of the cheeses was evaluated and compared against the standards of Bangladesh Food Safety Authority (BFSA), European Union (EU), and Food Safety and Standards Authority of India (FSSAI). The occurrence of MRSA and its virulence factors were determined using standard microbiological and molecular techniques. Results revealed that 65% samples were positive for S. aureus , with staphylococcal load surpassing safety thresholds according to the above-mentioned standards. MRSA was detected in 30% of the samples, exhibiting resistance to multiple antibiotics. All the isolates showed resistance against penicillin, tetracycline, doxycycline, trimethoprim-sulfamethoxazole and azithromycin, whereas ceftaroline, norfloxacin, and levofloxacin exhibited intermediate level of sensitivity. Enterotoxin genes SEa and SEc were prevalent in 16.67% and 8.97% of isolates, respectively, while TSST-1 gene was identified in 25.64% among the exfoliative toxin genes. Notably, 85.90% and 80.77% of the isolates exhibited biofilm formation based on the Congo Red and microtiter plate techniques, respectively, with significant percentages of biofilm associated regulatory genes icaA (73.08%), icaD (53.85%), clfA (78.21%) , clfB (61.54%) , and fnbA (69.23%). The substantial prevalence of bla CTX-M-2a (88.46%) and bla TEM (25.64%) highlights the significant public health risks associated with MRSA contamination in cheese. The high occurrence of S. aureus and the detection of multiple toxin-encoding genes further emphasize the need for strengthened monitoring and stricter control measures across the production and distribution chain to reduce contamination and ensure product safety.

Fault diagnosis method for gearbox systems using OVMD and KLIRVM

Translation, cultural adaptation, and psychometric evaluation of the Patient Assessment Chronic Illness Care tool in Ethiopia (PACIC-5As-ET) for patients with type 2 diabetes

Introduction Chronic conditions are a significant global health challenge that adversely affects the quality of care for patients with type 2 diabetes (T2D). To evaluate and improve the quality of care, the Patient Assessment Chronic Illness Care (PACIC-5As) tool has been developed. It is the most widely used tool designed to assess the perceived quality of care among individuals with chronic conditions, including diabetes. Nevertheless, it has not yet been culturally adapted and validated in the Ethiopian context. Therefore, this study aimed to translate, culturally adapt, and evaluate the psychometric properties of the PACIC-5As tool in Ethiopia. Methods A multicenter cross-sectional study was conducted among individuals with type 2 diabetes from March 24, 2025, to May 5, 2025, in the Amhara region’s comprehensive specialized referral hospitals. A systematic random sampling technique was used to select the study participants. Data were collected through face-to-face interviews. The tool consists of 26 items and 5 domains. Content validity was assessed at both the individual and scale levels. Internal consistency was evaluated using Cronbach’s alpha (α) and composite reliability (CR), with a value ≥ 0.70 considered acceptable. Confirmatory factor analysis (CFA) was conducted to evaluate model fit and factor structure. Model fit was assessed using the absolute and incremental fit indices and interpreted based on the recommended thresholds. Convergent validity was computed using average variance extracted (AVE), with a value ≥ 0.4 considered adequate, while discriminant validity was evaluated using AVE and inter-construct correlations. Results A total of 520 study participants were enrolled, and 517 (99.4%) were included in the study. The overall mean summary score of PACIC-5As-ET was 2.68 (±0.62). The content validity index at the item and scale levels ranged from 80% to 100%, with an inter-rater agreement of 95%. The Cronbach’s alpha and composite reliability (CR) of the PACIC-5As-ET were 0.93. The Cronbach’s alpha values for the subscales ranged from 0.71 (Assist) to 0.82 (Arrange). The test-retest reliability of PACIC-5As-ET was 0.94. The model fit indices were χ²/df (2.79), RMSEA (0.06), SRMR (0.08), GFI (0.89), and CFI (0.40). The AVE value of the overall PACIC-5As-ET was 0.93, and the subscales ranged from 0.47 (Advise) to 0.59 (Arrange). Conclusions The Amharic version of the PACIC-5As-ET tool demonstrated excellent internal consistency and acceptable validity for assessing the perceptions of patients with T2D. The absolute fit indices were generally within the recommended range, whereas the incremental fit indices were low. Therefore, support for the hypothesized five-factor structure is limited and should be interpreted with caution.

Individual differences in affect: explaining work environment perceptions and later wellbeing

Abstract Individual differences in employees’ affective dispositions influence how they perceive the work environment and report their well-being. A recurring challenge in this literature is that self-reported measures of working conditions and well-being cannot easily distinguish objective environmental features from the perceptual lens through which employees report them. Using a large, stratified sample of Danish employees (T1 N  = 3970; T2 N  = 2375) and the Danish Psychosocial Questionnaire, we quantified the extent to which positive and negative affect account for associations between work environment perceptions and employee well-being. Partial correlations, both cross-sectional and longitudinal over six months, showed that two brief affect measures accounted for an average of 73–75% of the observed associations. These findings suggest that a substantial portion of commonly reported work environment-well-being associations reflects stable individual differences in affective dispositions rather than objective environmental conditions—with direct implications for how self-report surveys are designed and interpreted in research and practice.