Search Results (44)

Hyperspectral imaging has emerged as a promising modality for forensic document analysis due to its ability to capture spectral and material information beyond conventional RGB representations. However, existing hyperspectral forensic studies typically focus on individual tasks and provide limited insight into the transferability of learned representations across different forensic applications. This study investigates episodic hyperspectral representation learning for forensic document analysis using a shared spectral–spatial embedding space learned through prototypical optimization. The proposed framework is evaluated on the complete UWA WIHSI and iVision HHID hyperspectral datasets across multiple forensic applications, namely writer identification, writer verification, ink mismatch detection, forgery detection, gender prediction, and age prediction.The proposed method achieved high performance on the controlled UWA WIHSI dataset across multiple forensic tasks. On the more challenging iVision HHID dataset, it attained a writer identification accuracy of 90.74%, together with writer verification and ink mismatch detection ROC–AUC scores of 0.9936 and 0.9915, respectively. Cross-dataset experiments further highlighted both the potential and the challenges of transferring learned hyperspectral representations across different acquisition conditions and writer populations, while extensive ablation studies confirmed the importance of spectral information, embedding design, and optimization strategy in learning effective hyperspectral representations. Overall, the results show that shared hyperspectral representations can support diverse forensic document analysis applications within a common embedding space while providing insight into the opportunities and challenges of developing transferable hyperspectral representations for forensic settings. Full article

Methylation of histone H3 at lysine 4 (H3K4me) is a key epigenetic mark in plants, governing transcriptional regulation, development, and stress adaptation. While the enzymes that deposit and remove this mark are well studied, how H3K4me signals are interpreted by reader proteins remains less understood. This review synthesizes recent advances in the molecular recognition of H3K4me states by plant reader domains, including PHD, BAH, CW, Tudor, and chromodomain modules. Unlike prior reviews that focused on writers and erasers or on stress-specific responses, we systematically examine the reader-side mechanisms, with particular emphasis on how distinct methylation states, including trimethylated (H3K4me3), dimethylated (H3K4me2), monomethylated (H3K4me1), and unmethylated H3K4, are discriminated and translated into chromatin-based outputs. These readers function as signaling hubs, integrating environmental and hormonal cues to regulate flowering, DNA repair, and stress memory, with implications for crop performance. However, fundamental gaps remain, including the identification of H3K4me1-specific readers, the structural basis for combinatorial histone mark recognition, and the evolutionary divergence of reader pathways between monocots and dicots. Our review provides a framework for understanding H3K4me reader biology and explores its potential for application in plant breeding. Full article

N6-methyladenosine (m⁶A) is a dynamic and reversible RNA modification governed by the tripartite machinery of writers, erasers, and readers, which plays crucial roles in plant adaptation to environmental stresses. However, the repertoire and function of m⁶A machinery in pepper (Capsicum chinense) remain uncharacterized. Here, we performed a genome-wide identification of m⁶A regulators in pepper (Ccm⁶As), revealing 20 high-confidence genes, comprising 6 writers, 7 erasers, and 7 readers. Comprehensive analysis of their phylogeny, conserved domains, and promoter cis-elements revealed structural conservation and a transcriptional architecture highly enriched in stress-responsive elements. Notably, in silico analysis revealed that the core catalytic writer CcMTA, the essential adaptor CcFIP37A, and the paralog CcMTB1 exhibited strong interactions, suggesting the formation of a functional methyltransferase complex. Using a comparative approach with cadmium-tolerant (CdRes-1) and cadmium-sensitive (CdSen-1) genotypes, we found that Cd stress induced a genotype-specific transcriptional reprogramming of the m⁶A machinery. In the tolerant genotype CdRes-1, eight regulators were significantly upregulated, whereas only CcMTA showed a modest induction in the sensitive CdSen-1. Subcellular localization experiments confirmed dual nuclear and cytoplasmic localization of CcMTA. Our findings provide a foundational epitranscriptomic resource for future functional investigations into the molecular mechanisms underlying cadmium stress responses in pepper. Full article

In offline signature verification, extracting effective features and enhancing identification accuracy remain critical challenges. Traditional feature extraction modules struggle to capture comprehensive, detailed characteristics from signatures alone and often suffer from overfitting issues. This paper introduces ResT, a novel approach that integrates the Residual Network (ResNet) and Transformer architectures for multi-scale feature extraction. The proposed method comprises two components: ResNet blocks and Transformer blocks, designed to extract local and global signature characteristics, respectively. Within the ResNet blocks, we integrate two modules—Spatial-to-Depth Convolution (SPD-Conv) and Spatial and Channel Reconstruction Convolution (SCConv)—to emphasize stroke-level features, thereby improving local feature extraction. For the Transformer blocks, Vision Transformer (ViT) is employed to analyze the signature’s overall shape and stroke trends, capturing global features. To evaluate performance, we implement a writer-independent (WI) verification system and conduct extensive experiments on four public datasets: GPDS, CEDAR, BHSig-Bengali, and BHSig-Hindi. Results demonstrate that the proposed ResT model effectively distinguishes genuine from forged signatures and achieves competitive performance compared to existing methods. Full article

This study investigates the traditional life within Al-Gh’deer Market Square, which constitutes a fundamental component of the vernacular urban fabric of Sidi Okba’s old city from a sensorial perspective. This oasis, located in the southeast of Algeria, is currently severely degraded and requires urban and architectural preservation. However, the sensory experiences that once characterised traditional urban life have not yet been systematically explored. The aim of this study is to fill this gap by analysing the historical atmospheres depicted in various literary and iconographic sources created by French and European explorers who visited Algeria during the colonial period. This research highlights each component of the “Al-Gh’deer” market square, which had a sensory impact on writers and photographers during their visit to Sidi Okba. This impact is revealed through the different tangible and intangible signals generated by these components, which were then felt and described textually and/or visually by the travellers. To this end, the thematic content analysis is used as a research technique in order to analyse this textual corpus, whilst the image formatting and staging constitute the method used for the iconographic corpus study. The first method makes it possible to detect the most relayed ambiences by travellers. This is revealed by the identification and computation of the associated words and/or expressions within the considered textual corpus. The second technique consists of the extraction of the elements generating the physical signals that should create a sensory relationship with the people within the scene or looking at it. The identified ambiences among the two corpora are crossed in order to determine the most felt ones in the marketplace as well as the various components generating them. The outcomes of this research work would serve as a basis for revitalisation initiatives within the frame of socio-economic and cultural development projects. Full article

This essay analyzes Chinese theater director Li Jianjun’s play The Metamorphosis (Bianxingji) under Pierre Bourdieu’s idea of cultural capital. Reimagining Kafka’s Gregor Samsa as a package delivery rider in contemporary China, the play stages a failed narrative of storytelling through live-feed video and informs the impossibility of representing the riders’ labor resulting from the fragmented realities of postsocialist China. It thus challenges the middle-class writers’ efforts to transform delivery riders’ labor into a form of cultural capital and confronts the audience with the exploitative potential of their spectating position. Ultimately, the impossibility of representation staged by the play articulates the inequality and stratification that structures China at the postsocialist moment. The play interweaves three layers of narratives: Geligaoer’s family’s various forms of labor, documentary clips of real-life delivery riders in contemporary China, and an interplay between an external voice and the performers’ bodily movements. This layered narrative foregrounds the artificiality of storytelling and can be situated within the ongoing discussions in the recent decade in China, in which scholars and journalists attempt to secure their middle-class identities by transforming the riders’ laboring condition into a form of cultural capital. In contrast, the play stages the failure of the narrative of storytelling through a projection screen and live-feed cameras to inform the impossibility of a transparent representation of the delivery riders. By excluding the audience from the riders’ subjectivity, the play blocks the audience’s identification with the latter. Through the heavy beauty filter projected on the screen as a metaphor, the play confronts the audience with their own middle-class identity and warns them of the violence inherent in their spectating position. Full article

English argumentative writing is a cornerstone of academic and professional communication, yet it remains a significant challenge for second-language (L2) learners. While Large Language Models (LLMs) show promise as components in automated feedback systems, their responses are often generic and lack the structural insight necessary for meaningful improvement. Existing Automated Essay Scoring (AES) systems, conversely, typically provide holistic scores without the kind of actionable, fine-grained advice that can guide concrete revisions. To bridge this systemic gap, we introduce ARGUS (Argument Understanding and Structured-feedback), a novel neuro-symbolic system that synergizes the semantic understanding of LLMs with the structured reasoning of Graph Neural Networks (GNNs). The ARGUS system architecture comprises three integrated modules: (1) an LLM-based parser transforms an essay into a structured argument graph; (2) a Relational Graph Convolutional Network (R-GCN) analyzes this symbolic structure to identify specific logical and structural flaws; and (3) this flaw analysis directly guides a conditional LLM to generate feedback that is not only contextually relevant but also pinpoints precise weaknesses in the student’s reasoning. We evaluate ARGUS on the Argument Annotated Essays corpus and on an additional set of 150 L2 persuasive essays collected from the same population to augment training of both the parser and the structural flaw detector. Our argument parsing module achieves a component identification F1-score of 90.4% and a relation identification F1-score of 86.1%. The R-GCN-based structural flaw detector attains a macro-averaged F1-score of 0.83 across the seven flaw categories, indicating that the enriched training data substantially improves its generalization. Most importantly, in a human evaluation study, feedback generated by the ARGUS system was rated as consistently and significantly more specific, accurate, actionable, and helpful than that from strong baselines, including a fine-tuned LLM and a zero-shot GPT-4. Our work demonstrates a robust systems engineering approach, grounding LLM-based feedback in GNN-driven structural analysis to create an intelligent teaching system that provides targeted, pedagogically valuable guidance for L2 student writers engaging with persuasive essays. Full article

This article provides a comprehensive review and explores the gaps in current knowledge of lysine metabolism in humans and its potential nutritional and therapeutic indications. The first part of this study examines lysine sources, requirements, transport through the plasma membrane, lysine catabolism, and its disorders. The central part is focused on post-translational modifications of lysine in proteins, primarily desmosine formation in elastin, hydroxylation in collagen, covalent bonds with glutamine, methylation, ubiquitination, sumoylation, neddylation, acylation, lactylation, carbamylation, and glycation. Special sections are devoted to using lysine as a substrate for homoarginine and carnitine synthesis and in nutrition and medicine. It is concluded that the identification and detailed knowledge of writers, readers, and erasers of specific post-translational modifications of lysine residues in proteins is needed for a better understanding of the role of lysine in epigenetic regulation. Further research is required to explore the influence of lysine availability on homoarginine formation and how the phenomenon of lysine–arginine antagonism can be used to influence immune and cardiovascular functions and cancer development. Of unique importance is the investigation of the use of lysine in osteoporosis therapy and in reducing the resorption of harmful substances in the kidneys, as well as the therapeutic potential of polylysine and lysine analogs. Full article

Identifying the scriptwriter in historical manuscripts is crucial for historians, providing valuable insights into historical contexts and aiding in solving historical mysteries. This research presents a robust deep learning system designed for classifying historical manuscripts by writer, employing intelligent feature selection and vision transformers. Our methodology meticulously investigates the efficacy of both handcrafted techniques for feature identification and deep learning architectures for classification tasks in writer identification. The initial preprocessing phase involves thorough document refinement using bilateral filtering for denoising and Otsu thresholding for binarization, ensuring document clarity and consistency for subsequent feature detection. We utilize the FAST detector for feature detection, extracting keypoints representing handwriting styles, followed by clustering with the k-means algorithm to obtain meaningful patches of uniform size. This strategic clustering minimizes redundancy and creates a comprehensive dataset ideal for deep learning classification tasks. Leveraging vision transformer models, our methodology effectively learns complex patterns and features from extracted patches, enabling precise identification of writers across historical manuscripts. This study pioneers the application of vision transformers in historical document analysis, showcasing superior performance on the “ICDAR 2017” dataset compared to state-of-the-art methods and affirming our approach as a robust tool for historical manuscript analysis. Full article

Research exploring involvement of RNA N⁶-methyladenosine (m⁶A) in tomato (Solanum lycopersicum) seed germination remains limited. There is also a lack of direct evidence supporting the interaction among tomato seed germination, microgravity, and m⁶A modification. In this study, Micro-Tom tomatoes are used as the experimental material to conduct tomato genetic transformation, seed germination assay, and m⁶A modification levels identification experiments. During tomato seed germination processes, the m⁶A modification level significantly increases under the mutual influence of various m⁶A methyltransferase subunits and multiple eraser proteins. As a m⁶A reader gene, SlYTP9 expression significantly affects the germination of tomato seeds, with promotion and inhibition in OE (overexpression) and RNAi (RNA interference) transgenic tomato plants, respectively. Microgravity promotes seed germination in the early germination period (0–3 days past germination; 0–3 DPG), but this promoting effect gradually disappears as the seedling grows (8–15 DPG). Further exploration revealed that this promoting effect is correlated with m⁶A modification, manifested as enhanced expression of most m⁶A writer genes; increased expression levels of overall reader genes; altered expression trends of some m⁶A eraser genes, particularly SlALKBH2; and enhanced m⁶A modification levels. The experimental results obtained in this study can provide a theoretical basis and evidence support for elucidating the role of m⁶A in tomato seed germination, as well as for exploring the interactions between seed germination, microgravity, and m⁶A modification. Full article

The origins of multiple sclerosis (MS) have been a subject intriguing researchers and scholars for generations. The multifactorial etiological nature of the disease continues to be studied as a complex combination of genetic aspects and environmental or external risk elements contributing to the development of the disease. Descriptions of symptoms or clinical disorders suggestive of MS affecting historical figures or prominent individuals (i.e., Lidwina of Schiedam, Heinrich Heine, Augustus d’Este) did not provide clues on the origin of the disease, except for the observation that all these early possible cases were white European individuals. MS was initially framed as a neurological entity and named in the 19th century by the historical participation of the French masters Cruveilhier, Vulpian, and Charcot, among others, but the question of how the disease originated was not addressed until Charles Poser raised his conjecture on the origins of MS in two historical essays (1994 and 1995), raising the question if the Viking voyages and invasions from the 8th to the 11th century carried the Scandinavian MS genetic risk factor to Europe and the rest of the known world at that time. Poser did not have the benefit of access to ancient molecular DNA data and based his theoretical postulation on interesting historical and archeological observations. A series of studies and opinions published in 2024, utilizing sophisticated genetic analyses and genome identification, archeological DNA analysis, and other advanced techniques and biological computation, distinctly demonstrate the installation of HLA-DRB1*15:01 (class II allele) in Europe (with a higher prevalence in Scandinavia) following the massive Yamnaya pastoralists migration from the Pontic Steppe in Eurasia to western Europe (~5000 to 2500 BCE). The data suggest HLA-DRB1*15:01, the strongest genetic association with MS, underwent an evolutive switch (“thrifty drift”) from immune protector against novel zoonotic diseases appearing among the early pastoralists of the Yamnaya civilization to an autoimmune deleterious reactor to molecular mimicry and self-antigens, enabled by lifestyle changes and reduction of pastoralism once communities settled in Europe after the migration from the Pontic Steppe. This writer offers a new perspective on the origins of MS through a phase 1, the ancient east to west migration in the late Bronze Age, consolidating the HLA-DRB1*15:01 haplotype in Europe, and phase 2, the additional dissemination of the genetic MS risk through the Viking invasions, reinforcing inheritability by enabling a homozygous dominant inheritance. Full article

In the People’s Republic of China (PRC), the Cultural Revolution (1966–1976) left many writers severed from their cultural roots. Starting in the 1980s, literary authors sought to address this disconnection by turning their attention to rural communities. This tendency is exemplified by the emergence of two significant trends: root-seeking literature and new fiction from Tibet. Root-seeking authors focused on local customs, marginalized cultures, and minority groups to reinvigorate Chinese literature and fill the perceived cultural void. Around the same time, new fiction from Tibet featured diverse responses to post-Mao changes, with some idealizing Tibet as a repository of “authentic” traditions, while others criticized its perceived backwardness. Both trends have been interpreted in scholarship as responses, often critical, to state policies. The short story “Mountain Pass” (1985) by Hui writer Bai Lian intersects with these movements temporally and thematically. However, unlike them, Bai Lian’s portrayal of rural communities emphasizes the Hui’s historical role in resisting the Qing empire, pivotal to the emergence of the PRC, while also highlighting the group’s Arab and Persian origins. This three-layered identification with the local, national, and transnational enriches our understanding of the 1980s literary landscape, challenging the notion that this era was solely characterized by resistance to the central state. Full article

Mechanoluminescent (ML) materials can exhibit visible-to-near-infrared mechanoluminescence when responding to the fracture or deformation of a solid under mechanical stimulation. Transforming mechanical energy into light demonstrates promising applications in terms of visual mechanical sensing. In this work, we synthesized the phosphor CaZnOS:Tb³⁺, Sm³⁺, which exhibited intense and tunable multicolor mechanoluminescence without pre-irradiation. Intense green ML materials were obtained by doping Tb³⁺ with different concentrations. Tunable multicolor mechanoluminescence (such as green, yellow-green, and orange-red) could be realized by combining green emission (about 542 nm), attributed to Tb³⁺, and red emission (about 600 nm) generated from the Sm³⁺ in the CaZnOS substrate. The tunable multicolor ML materials CaZnOS:Tb³⁺, Sm³⁺ exhibited intense luminance and recoverable mechanoluminescence when responding to mechanical stimulation. Benefiting from the excellent ML performance and multicolor tunability in CaZnOS:Tb³⁺, Sm³⁺, we mixed the phosphor with PDMS and a curing agent to explore its practical application. An application for visual mechanical sensing was designed for handwriting identification. By taking a time-lapsed shot while writing, we easily obtained images of the writer’s handwriting. The images of the ML intensity were acquired by using specific software to transform the shooting data. We could easily distinguish people’s handwriting through analyzing the different ML performances. Full article

Background: Sex work remains a contentious and marginalized aspect of society, with sex workers facing a myriad of challenges that impact their mental health and well-being. Objective: This review explores, reviews, and examines the psychiatric challenges encountered by sex workers daily and seeks to identify key gaps in the current research and highlight areas of future intervention and support. Methodology: This study followed five stages of the integrative review suggested by Whittmore and Knafl. The identification of the problem, literature search, data evaluation, data extraction, analysis, and presentation of results were the five stages of the integrative review that were carried out. This review examined English-language publications from 2010 to 2023 that discussed the mental health issues that sex workers experienced. Furthermore, this study excluded publications that were published before 2010, articles written in languages other than English, publications whose complete texts could not be retrieved, and works that did not address the mental health problems that sex workers encounter. For their initial search, the writers employed electronic databases like PubMed, Scopus, Psych-Info, Google Scholar, Science Direct, and Medline. The search terms were as follows: ‘sex work’, ‘sex workers’, ‘prostitution’, ‘mental health’, ‘psychiatric challenges’, ‘stigma’, Risk factors’, and ‘barriers’. Results: Following the critical appraisal, out of 150 studies, only 34 studies were chosen for analysis. Using Cresswell’s Tesch method, two themes emerged from this study: (1) mental health challenges faced by sex workers and (2) primary risk factors contributing to their mental health challenges. Conclusions: Moreover, addressing the psychiatric challenges faced by sex workers requires a multifaceted approach that acknowledges the intersectionality of factors influencing sex workers’ mental health outcomes, thus also highlighting the imperative for tailored interventions and support systems to promote their well-being. Full article

N⁶-methyladenosine (m⁶A) RNA modification is the most prevalent form of RNA methylation and plays a crucial role in plant development. However, our understanding of m⁶A modification in Masson pine (Pinus massoniana Lamb.) remains limited. In this study, a complete analysis of m⁶A writers, erasers, and readers in Masson pine was performed, and 22 m⁶A regulatory genes were identified in total, including 7 m⁶A writers, 7 m⁶A erases, and 8 readers. Phylogenetic analysis revealed that all m⁶A regulators involved in Masson pine could be classified into three distinct groups based on their domains and motifs. The tissue expression analysis revealed that the m⁶A regulatory gene may exert a significant influence on the development of reproductive organs and leaves in Masson pine. Moreover, the results from stress and hormone expression analysis indicated that the m⁶A regulatory gene in Masson pine might be involved in drought stress response, ABA-signaling-pathway activation, as well as resistance to Monochamus alternatus. This study provided valuable and anticipated insights into the regulatory genes of m⁶A modification and their potential epigenetic regulatory mechanisms in Masson pine. Full article