Identification Of Regions Research Articles

Analisis Intellectual Capital dan Relationship Satisfaction Terhadap Business Performance: Studi UMKM Rumah Makan Nasi Padang di Kota Sukabumi

Micro, Small and Medium Enterprises or what are often called UMKM support 60% of the Indonesian economy. Sukabumi is an area that has 57,319 UMKM, one of which is Padang rice restaurant UMKM. Nasi Padang restaurant UMKM is Padang or Minangkabau cuisine, a cultural heritage from generation to generation, maintaining the authenticity of the tastes of the past as a regional identity that has problems with business performance as well as intellectual capital and relationship satisfaction. The aim of this research is to find out how intellectual capital and relationship satisfaction influence the business performance of UMKM at Nasi Padang restaurants in the city of Sukabumi. The population in this study were UMKM Padang rice restaurants in the city of Sukabumi. The method used is a quantitative method with an associative descriptive approach. With a total sample of 51 with saturated sampling. The statistical results of the f test (simultaneous) show a simultaneous and significant influence of the intellectual capital and relationship satisfaction variables on business performance. Based on the statistical results of the t test (partial test), intellectual capital has a negative and insignificant effect on business performance. Meanwhile, relationship satisfaction has a positive and significant effect on business performance.

Deep-learning surrogate models for the stability of a wide rectangular tunnel

The stability of a wide rectangular tunnel in spatially variable soils is investigated using deep-learning surrogate models combined with a mixed formulation of limit analysis. The mixed formulation is employed to perform stochastic simulations of tunnels in spatially random soils, generating the data to train the surrogate models. Two types of deep-learning models are tested: Fully Connected Neural Networks (FCNs) and Convolutional Neural Networks (CNNs). To enhance model performance, the study introduces two novel encoding techniques to enhance the identification of tunnel regions in the input data. The first, Mask-FCN, directly incorporates spatial information into the model by adding a binary mask layer to distinguish tunnel regions from the surrounding soil. The second, Grad-FCN, modifies training gradients to indirectly highlight these differences. Additionally, a Mask-CNN model is developed, leveraging spatial filtering to better capture local patterns and correlations. Our results show that the surrogate models, trained on data from stochastic reliability analyses, demonstrate robustness and accuracy across various evaluation metrics. The encoding neural networks outperform the baseline model in accuracy and overall regression performance on training datasets. Importantly, both encoding networks achieve acceptable accuracy on unseen datasets with new tunnel geometric features, a task the baseline model fails to accomplish. The FCN-based encoding neural network achieves prediction capabilities comparable to ordinary CNNs, while the CNN-based encoding neural network delivers high prediction accuracy for unknown datasets with new tunnel geometric characteristics. The study concludes that the generated surrogate models offer a computationally efficient alternative for predicting tunnel stability in spatially variable soils.

Husaini M. Hasan on The Concept of Political Activism in The Social And Political Context of Aceh

This article analyzes Aceh's political activism from a political and historical perspective. This research uses a qualitative methodology, which focuses on the role of Husaini M. Hasan in the Free Aceh Movement and his struggle for the implementation of Islamic law in Aceh. This article explains how Aceh has struggled to maintain its Islamic identity within the framework of the Unitary State of the Republic of Indonesia from colonial times to contemporary times. This research analyzes various documents and interviews to show how Aceh's desire to implement Islamic law is related to the desire for regional autonomy and national identity. Aceh's social and political identity was shaped by political activism and Islamic ideology, which also interacted with Indonesian national politics. This study found that the political initiative in Aceh was not an independent state, but special autonomy. This shows that understanding and dealing with problems related to social identity, politics, and Islamic law in Aceh requires a more holistic and contextual approach.

Genome‐Wide Diversity in Lowland and Highland Maize Landraces From Southern South America: Population Genetics Insights to Assist Conservation

ABSTRACTMaize (Zea mays ssp. mays L.) landraces are traditional American crops with high genetic variability that conform a source of original alleles for conventional maize breeding. Northern Argentina, one the southernmost regions of traditional maize cultivation in the Americas, harbours around 57 races traditionally grown in two regions with contrasting environmental conditions, namely, the Andean mountains in the Northwest and the tropical grasslands and Atlantic Forest in the Northeast. These races encounter diverse threats to their genetic diversity and persistence in their regions of origin, with climate change standing out as one of the major challenges. In this work, we use genome‐wide SNPs derived from ddRADseq to study the genetic diversity of individuals representing the five groups previously described for this area. This allowed us to distinguish two clearly differentiated gene pools, the highland northwestern maize (HNWA) and the floury northeastern maize (FNEA). Subsequently, we employed essential biodiversity variables at the genetic level, as proposed by the Group on Earth Observations Biodiversity Observation Network (GEO BON), to evaluate the conservation status of these two groups. This assessment encompassed genetic diversity (Pi), inbreeding coefficient (F) and effective population size (Ne). FNEA showed low Ne values and high F values, while HNWA showed low Ne values and low Pi values, indicating that further genetic erosion is imminent for these landraces. Outlier detection methods allowed identification of putative adaptive genomic regions, consistent with previously reported flowering‐time loci and chromosomal regions displaying introgression from the teosinte Zea mays ssp. mexicana. Finally, species distribution models were obtained for two future climate scenarios, showing a notable reduction in the potential planting area of HNWA and a shift in the cultivation areas of FNEA. These results suggest that maize landraces from Northern Argentina may be unable to cope with climate change. Therefore, active conservation policies are advisable.

Safe Reinforcement Learning With Dual Robustness.

Reinforcement learning (RL) agents are vulnerable to adversarial disturbances, which can deteriorate task performance or break down safety specifications. Existing methods either address safety requirements under the assumption of no adversary (e.g., safe RL) or only focus on robustness against performance adversaries (e.g., robust RL). Learning one policy that is both safe and robust under any adversaries remains a challenging open problem. The difficulty is how to tackle two intertwined aspects in the worst cases: feasibility and optimality. The optimality is only valid inside a feasible region (i.e., robust invariant set), while the identification of maximal feasible region must rely on how to learn the optimal policy. To address this issue, we propose a systematic framework to unify safe RL and robust RL, including the problem formulation, iteration scheme, convergence analysis and practical algorithm design. The unification is built upon constrained two-player zero-sum Markov games, in which the objective for protagonist is twofold. For states inside the maximal robust invariant set, the goal is to pursue rewards under the condition of guaranteed safety; for states outside the maximal robust invariant set, the goal is to reduce the extent of constraint violation. A dual policy iteration scheme is proposed, which simultaneously optimizes a task policy and a safety policy. We prove that the iteration scheme converges to the optimal task policy which maximizes the twofold objective in the worst cases, and the optimal safety policy which stays as far away from the safety boundary. The convergence of safety policy is established by exploiting the monotone contraction property of safety self-consistency operators, and that of task policy depends on the transformation of safety constraints into state-dependent action spaces. By adding two adversarial networks (one is for safety guarantee and the other is for task performance), we propose a practical deep RL algorithm for constrained zero-sum Markov games, called dually robust actor-critic (DRAC). The evaluations with safety-critical benchmarks demonstrate that DRAC achieves high performance and persistent safety under all scenarios (no adversary, safety adversary, performance adversary), outperforming all baselines by a large margin.

The inheritance of Tang Sancai pottery figurines in Luoyang: The integration of traditional handicrafts and the regional cultural background of social transformation

Creative Documentary Research Data Methodology for mixing the Qualitative Research Methods and collecting research data through surveys, interviews, observations, group discussions and seminars, literature analysis, and field research.to let the educational audience understand and learn the historical background and aesthetic knowledge of Tang Sancai Pottery Figurines. Sancai is a versatile decoration on Chinese pottery and other painted pieces using glazes or slip, predominantly in the three colors of brown (or amber), green, and creamy off-white. Tang Sancai Pottery Figurines is three-colored pottery in Kilns near Xi'an and Luoyang. During the Tang Dynasty, porcelain pottery appeared. Porcelain is ceramic pottery characterized by its white, translucent appearance. It is known for its durability and is often used for making delicate and intricate objects such as vases, bowls, and figurines. This research focused on the inheritance strategy of traditional handicrafts combined with education in the regional cultural regeneration system under the background of China's social transformation. In social transformation, combining traditional handicrafts with modern education and cultivating the educational audience's awareness of protecting traditional culture can not only allow handicraft skills to continue in the classroom. It is also conducive to the survival and development of traditional handicrafts in their place of origin can reshape the regional cultural identity of traditional handicrafts, promote the diversity and innovation of different cultures, traditions, and perspectives, and how to promote cultural diversity, equity, and harmony education and enhance cultural confidence and national identity.

Model decomposition method for minimizing the consumption of support structure for FFF

Fused filament fabrication (FFF) often requires additional support structures for manufacturing parts with overhanging areas, leading to substantial material and time wastage. Although several model decomposition techniques have been developed to tackle this issue, most focus solely on the constraint of overhang surface area. As a result, these techniques often struggle with parts that have intricate overhang characteristics, causing reduced printing surface accuracy and quality. This study introduces a precise method for detecting overhang regions and support-relevant overhang regions to improve the accuracy of overhang region identification and printing precision. Additionally, a model decomposition strategy leveraging genetic algorithm optimization is proposed to minimize the need for support structures, aiming for nearly support-free printing. Moreover, for intricate structures with a high topology where support structures are unavoidable, a novel projection support based on the distribution of periodic points in triangular form is developed to address this printing challenge. Experimental results demonstrate that the implementation of the algorithm outlined in this work on an FFF printer has achieved nearly support-free printing. Moreover, the proposed method for generating support structures has the potential to reduce material usage by 27 %.

The Geolinguistic Diffusion of Lexically Enregistered Variants in Michigan’s Upper Peninsula

This geolinguistic study investigates perceptions of usage frequency and local identity connection for seven distinctive words in Michigan’s Upper Peninsula (U.P.): camp, chook, choppers, cudighi, pank, sisu, and swampers. Data were collected from 860 participants through an on-line survey, incorporating demographic details and hometown zip codes. Participants’ attitudes were evaluated using two 5-point Likert scales, assessing perceived frequency of use and importance to identity. The study reveals a tight correlation between these variables for each word, alongside unique geographic distribution patterns across the U.P. of Michigan. The findings highlight the enregisterment of these terms within various U.P. speech communities, influenced by processes of koineization, reallocation, and commodification. The words exhibit cultural significance and usage that are geolinguistically distinct, often delineated by a west-east divide in the region. This research illustrates how these unique U.P. words not only embody regional linguistic identity but are also shaped by the convergence of diverse sociolinguistic processes, adding to the rich and dynamic linguistic environment of Michigan’s Upper Peninsula.

Accurate Spatial Heterogeneity Dissection and Gene Regulation Interpretation for Spatial Transcriptomics using Dual Graph Contrastive Learning.

Recent advances in spatial transcriptomics have enabled simultaneous preservation of high-throughput gene expression profiles and the spatial context, enabling high-resolution exploration of distinct regional characterization in tissue. To effectively understand the underlying biological mechanisms within tissue microenvironments, there is a requisite for methods that can accurately capture external spatial heterogeneity and interpret internal gene regulation from spatial transcriptomics data. However, current methods for region identification often lack the simultaneous characterizing of spatial structure and gene regulation, thereby limiting the ability of spatial dissection and gene interpretation. Here, stDCL is developed, a dual graph contrastive learning method to identify spatial domains and interpret gene regulation in spatial transcriptomics data. stDCL adaptively incorporates gene expression data and spatial information via a graph embedding autoencoder, thereby preserving critical information within the latent embedding representations. In addition, dual graph contrastive learning is proposed to train the model, ensuring that the latent embedding representation closely resembles the actual spatial distribution and exhibits cluster similarity. Benchmarking stDCL against other state-of-the-art clustering methods using complex cortex datasets demonstrates its superior accuracy and effectiveness in identifying spatial domains. Ouranalysis of the imputation matrices generated by stDCL reveals its capability to reconstruct spatial hierarchical structures and refine differential expression assessment. Furthermore, it is demonstrated that the versatility of stDCL in interpretability of gene regulation, spatial heterogeneity at high resolution, and embryonic developmental patterns. In addition, it is also showed that stDCL can successfully annotate disease-associated astrocyte subtypes in Alzheimer's disease and unravel multiple relevant pathways and regulatorymechanisms.

Identification of resistance sources and genomic regions regulating Septoria tritici blotch resistance in South Asian bread wheat germplasm.

The Septoria tritici blotch (STB) [Zymoseptoria tritici (Desm.)] of wheat (Triticum aestivum L.) is characterized by its polycyclic and hemibiotrophic nature. It is one of the most dangerous diseases affecting wheat production worldwide. Durable resistance is largely decided by the combined effect of several quantitative trait loci (QTLs) having a minor effect. Currently, STB is not important in South Asia. However, STB expanding and wider adaptability, changing climatic conditions, and agronomic practices can create a situation of concern. Therefore, dissection of the genetic architecture of adult-plant resistance with genome-wide association mapping and selection of resistant sources for adult plant STB resistance were carried out on a panel of South Asian germplasm. We discovered the 91 quantitative trait nucleotides (QTNs) associated with STB resistance; 23 QTNs were repetitive across the different years and models. Many of these QTNs could differentiate the mapping panel into resistant versus susceptible groups and were linked to candidate genes related to disease resistance functions within linkage disequilibrium blocks. The repetitive QTNs, namely, Q.CIM.stb.2DL.2, Q.CIM.stb_dh.2DL.3, Q.CIM.stb.2AL.5, and Q.CIM.stb.7BL.1, may be novel due to the absence of co-localization of previously reported QTLs, meta-quantitative trait loci, and STB genes. There was a perfect negative correlation between the stacking of favorable alleles and STB susceptibility, and STB resistance response was improved by ∼50% with the stacking of ≥60% favorable alleles. The genotypes, namely, CIM20, CIM56, CIM57, CIM18, CIM44, WK2395, and K1317, could be used as resistant sources in wheat breeding programs. Therefore, this study could aid in designing the breeding programs for STB resistance before the onset of the alarming situation of STB in South Asia.

Exploration and Enrichment Analysis of the QTLome for Important Traits in Livestock Species

Background: Quantitative trait loci (QTL) are genomic regions that influence essential traits in livestock. Understanding QTL distribution and density across species’ genomes is crucial for animal genetics research. Objectives: This study explored the QTLome of cattle, pigs, sheep, and chickens by analyzing QTL distribution and evaluating the correlation between QTL, gene density, and chromosome size with the aim to identify QTL-enriched genomic regions. Methods: Data from 211,715 QTL (1994–2021) were retrieved from the AnimalQTLdb and analyzed using R software v4.2.1. Unique QTL annotations were identified, and redundant or inconsistent data were removed. Statistical analyses included Pearson correlations and binomial, hypergeometric, and bootstrap-based enrichment tests. Results: QTL densities per Mbp were 10 for bovine, 4 for pig, 1 for sheep, and 3 for chicken genomes. Analysis of QTL distribution across chromosomes revealed uneven patterns, with certain regions enriched for QTL. Correlation analysis revealed a strong positive relationship between QTL and gene density/chromosome size across all species (p < 0.05). Enrichment analysis identified pleiotropic regions, where QTL affect multiple traits, often aligning with known candidate and major genes. Significant QTL-enriched windows (p < 0.05) were detected, with 699 (187), 355 (68), 50 (15), and 38 (17) genomic windows for cattle, pigs, sheep, and chickens, respectively, associated with overall traits (and specific phenotypic categories). Conclusions: This study provides critical insights into QTL distribution and its correlation with gene density, offering valuable data for advancing genetic research in livestock species. The identification of QTL-enriched regions also highlights key areas for future exploration in trait improvement programs.

Classification of motor imagery EEG with ensemble RNCA model

Motor Imagery (MI) based brain-computer interface (BCI) systems are used for regaining the motor functions of neurophysiologically affected persons. But the performance of MI tasks is degraded due to the presence of redundant EEG channels. Hence, a novel ensemble regulated neighborhood component analysis (ERNCA) method provides a perfect identification of neural region that stimulate motor movements. Domains of statistical, frequency, spatial and transform-based features narrowed down the misclassification rate. The gradient boosting method selects the relevant features thereby reduces the computational complexity. Finally, Bayesian optimized ensemble classifier finetuned the classification accuracies of 97.22 % and 91.62 % for Datasets IIIa and IVa respectively. This approach is further strengthened by analyzing real-time data with the accuracy of 93.75 %. This method qualifies out of four benchmark methods with significant percent of improvement in accuracy for these three datasets. As per the spatial distribution of refined EEG channels, majority of the brain's motor functions concentrates on frontal and central cortex regions of brain.

Regional identity of schoolchildren in foreign language communication

Regional identity of schoolchildren in foreign language communication

Reexamination of the Sida Micrantha Mosaic Virus and Sida Mottle Virus Complexes: Classification Status, Diversity, Cognate DNA-B Components, and Host Spectrum.

Sida mottle virus (SiMoV) and Sida micrantha mosaic virus (SiMMV) are major Brazilian begomoviruses (Geminiviridae). However, the range of DNA-A identity of isolates of these viruses (81-100%) is not in agreement with the current criteria for Begomovirus species demarcation (<91%). To clarify this putative classification problem, we performed a comprehensive set of molecular analyses with all 53 publicly available isolates (with complete DNA-A genomes) designated as either SiMoV or SiMMV (including novel isolates obtained herein from nationwide metagenomics-based studies). Two well-defined phylogenetic clusters were identified. The SiMMV complex (n = 47) comprises a wide range of strains (with a continuum variation of 88.8-100% identity) infecting members of five botanical families (Malvaceae, Solanaceae, Fabaceae, Oxalidaceae, and Passifloraceae). The SiMoV group now comprises eight isolates (90-100% identity) restricted to Malvaceae hosts, including one former reference SiMMV isolate (gb|NC_077711) and SP77 (gb|FN557522; erroneously named as "true SiMMV"). Iteron analyses of metagenomics-derived information allowed for the discovery of the missing DNA-B cognate of SiMoV (93.5% intergenic region identity), confirming its bipartite nature. Henceforth, the correct identification of SiMoV and SiMMV isolates will be a crucial element for effective classical and biotech resistance breeding of the viral host species.

How does contact valence and group salience affect outgroup attitudes in asynchronous computer mediated contact? Experiments on intergroup contact via social media posts

ABSTRACT The prejudice reduction potential of face-to-face intergroup contact is widely established, but we know much less about computer-mediated intergroup contact (online contact) specifically via social media where interactions are less controlled and mostly asynchronous. Additionally, much of the work on online contact has focused on positive, controlled contact, neglecting the effect of negative contact. We examined the effects of mediated contact via online posts with differing valence (positive, negative, and neutral) in three experimental studies, in an imaginary scenario (Study 1: N = 120) and a real intergroup scenario with South and North Indians (Study 2: N = 296, Study 3: N = 336). Main effects of One way and factorial ANOVA showed that contact valence significantly affected outgroup attitudes in Study 1 & 2 but was not replicated in Study 3, where quality and quantity of past contact and status differences emerged as significant predictors of attitudes. Multiple mediation analysis revealed that intergroup anxiety and quality of contact explained changes in attitudes, which was less affected by valence and more by regional identity and history of contact. Findings are discussed in light of the possibilities and limitations of asynchronous mediated contact on social media.

Abstract B063: DiMMER: A robust computational pipeline for differential methylation marker evaluation in R of cell-free DNA fragments

Abstract Background: Decoding the origins of cell-free DNA (cfDNA) released from dying cells in a liquid biopsy sample offers the potential to provide insight into the dynamic, organism-wide changes reflective of health and disease, making cfDNA an ideal target for serial, minimally invasive monitoring of disease-related changes. To this end, cell-type specific DNA methylation patterns offer a promising target to facilitate tissue of origin analysis, yet limited methods exist to identify differentially methylated regions that distinguish cell-types. Methods: We develop a robust differentially methylated marker region identification pipeline, DiMMER, that leverages cfDNA fragment level information of neighboring, co-regulated CpG sites on methylome-wide sequencing reads. Compared to prior methods that utilize simple heuristics in one-vs-all average methylation rate comparisons, we implement an individual pairwise statistical test procedure across all cell-types or groups under consideration. We assess the cell-specific nature of identified differentially methylated marker regions by generating in-silico mixtures from known cell-type of origin at each region, and calculating the area under the receiver operating characteristic curve (AUROC). We utilize our differentially methylated marker finding pipeline to identify melanocyte specific methylation marker regions and assess their functional role through annotations. We show these cell-specific regions are conserved in melanoma cell-lines and are distinct from the aberrant changes in a cancer context. Results: We identified the most cell-type specific differentially methylated marker regions across 24 distinct cell-type groups using our pipeline. Compared to a simpler one-vs-all heuristic, we demonstrate improved cell-type specificity evidenced by a higher AUROC on average. Using our pipeline we identified melanocyte-specific marker regions, which were commonly found in intronic and promoter regions of genes related to melanocyte development and differentiation. When comparing methylation patterns between melanocytes and melanoma cell-lines, we demonstrate melanocyte specific methylation marks are conserved through the transformation to malignant melanoma. Conclusion: As methylome-wide sequencing methods continue to rapidly develop and more cell-specific methylation data is generated, there is unmet need for more statistically robust differentially methylated marker finding tools. Here we present one such tool, DiMMER, and demonstrate the potential utility of identifying such regions to be used to assess organ-specific load as a measure of residual disease, as opposed to traditional circulating tumor DNA quanitification. Citation Format: Arthur P McDeed, Sidharth S Jain, Megan E McNamara, Amber Alley, Anton Wellstein, Jaeil Ahn. DiMMER: A robust computational pipeline for differential methylation marker evaluation in R of cell-free DNA fragments [abstract]. In: Proceedings of the AACR Special Conference: Liquid Biopsy: From Discovery to Clinical Implementation; 2024 Nov 13-16; San Diego, CA. Philadelphia (PA): AACR; Clin Cancer Res 2024;30(21_Suppl):Abstract nr B063.

From words to wealth: Decoding the language markers and compositions of shop names in Banda Aceh

This qualitative study examines the names of 100 local and independent businesses to study the linguistic diversity and features of the linguistic landscape in Banda Aceh, Indonesia. The names here refer to those written in specific languages used in Aceh (Indonesian, Acehnese, English, Arabic, and other indigenous languages spoken in the province). The data was collected from five main roads, capturing the shop names for analysis. The results show that English is the dominant language choice, composing a majority of 45% of signage, showing the influence of globalization and the desire for international appeal. While English appears to convey prestige, some businesses blend it with Indonesian or Acehnese, connecting with local culture and engaging diverse audiences. This deliberate language choice reflects a commitment to cultural preservation and authentic customer experiences. Meanwhile, diverse linguistic combinations, emphasizing global influences, cultural preservation, and strategic branding, were also revealed. The most prevalent linguistic structure of signs is product+X (57%), which highlights product types, followed by place+X (14%) which emphasizes regional or cultural identity. In addition, a name/person’s name+X establishes a personalized connection (6%). Finally, in language markers, shop names reveal globalization’s prevalence and demonstrate efforts to convey a global image. The revitalization marker reflects the commitment to the Acehnese language and cultural pride. Identity markers, which include place, name, abbreviation, product, plant name, and brand, establish trust, familiarity, and resonance, creating a dynamic linguistic and cultural landscape where businesses steer global influences and local heritage to connect authentically with customers. To conclude, shop names in Banda Aceh illustrate a vibrant linguistic and cultural environment where businesses use global influences and local heritage to create meaningful bonds with customers.

Specific binding between Arabidopsis thaliana phytochrome-interacting factor 3 (AtPIF3) bHLH and G-box originated prior to embryophyte emergence

The basic helix-loop-helix (bHLH) domain via critical amino acid residues on basic region binding to E-box (5′-CANNTG-3′) is known in embryophyte. However, the dictated E-box types selection by bHLH dimers and the significant impact of these critical amino acid residues along embryophyte evolution remain unclear. The Arabidopsis thaliana PIF3-bHLH (AtPIF3-bHLH) recombinant protein and a series of AtPIF3-bHLH mutants were synthesized and analyzed. The reduced DNA binding ability and affinity of AtPIF3-bHLH point-mutation proteins, observed via fluorescence-based electrophoretic mobility shift assay (fEMSA) and isothermal titration calorimetry (ITC), suggest the critical role of these DNA-recognition sites in maintaining the AtPIF3-bHLH–DNA interaction. The purifying selection signals and the DNA-recognition-site conservation at the species level suggest the invariant roles of these sites throughout embryophyte evolution. The G-box outcompeted other types of E-box for binding in our competitive fEMSAs. The dynamic hydrogen bond formed between AtPIF3-bHLH and the G-box core indicates flexible identification of the core region. These features highlight a fast fixation of the bHLH-G-box recognition mechanism through embryophyte evolution and serve as a blueprint for studying DNA recognition determinants of other TF families.

Deep-Learning-Based Approach in Cancer-Region Assessment from HER2-SISH Breast Histopathology Whole Slide Images.

Fluorescence in situ hybridization (FISH) is widely regarded as the gold standard for evaluating human epidermal growth factor receptor 2 (HER2) status in breast cancer; however, it poses challenges such as the need for specialized training and issues related to signal degradation from dye quenching. Silver-enhanced in situ hybridization (SISH) serves as an automated alternative, employing permanent staining suitable for bright-field microscopy. Determining HER2 status involves distinguishing between "Amplified" and "Non-Amplified" regions by assessing HER2 and centromere 17 (CEN17) signals in SISH-stained slides. This study is the first to leverage deep learning for classifying Normal, Amplified, and Non-Amplified regions within HER2-SISH whole slide images (WSIs), which are notably more complex to analyze compared to hematoxylin and eosin (H&E)-stained slides. Our proposed approach consists of a two-stage process: first, we evaluate deep-learning models on annotated image regions, and then we apply the most effective model to WSIs for regional identification and localization. Subsequently, pseudo-color maps representing each class are overlaid, and the WSIs are reconstructed with these mapped regions. Using a private dataset of HER2-SISH breast cancer slides digitized at 40× magnification, we achieved a patch-level classification accuracy of 99.9% and a generalization accuracy of 78.8% by applying transfer learning with a Vision Transformer (ViT) model. The robustness of the model was further evaluated through k-fold cross-validation, yielding an average performance accuracy of 98%, with metrics reported alongside 95% confidence intervals to ensure statistical reliability. This method shows significant promise for clinical applications, particularly in assessing HER2 expression status in HER2-SISH histopathology images. It provides an automated solution that can aid pathologists in efficiently identifying HER2-amplified regions, thus enhancing diagnostic outcomes for breast cancer treatment.

Decoding the Strands of Women Oppression in Fiction of North Eastern Women Writers: A Study of Temsula Ao’s The Night (2005), Easterine Kire’s A Terrible Matriarchy (2007) and Jahnavi Barua’s Rebirth (2010)

India had long come out of the shadows of otherisation by the West, but ironically, it had constructed its own facets of misinterpretation and otherisation of its diverse indigenous groups within the subcontinent. Northeast India is one such geographical region that have always been viewed as exotic, backward owing to the distinct cultural and traditional patterns of its numerous tribes, castes and groups, of which very little is explored by the mainstream society and hence deemed as rooted in backwardness. The region has always been entangled in the web of national, ethnic, regional identities as it seems to exist in isolation from mainland India and grapples with insurgency and the inability to accommodate long term cultural and indigenous diversity. Additionally, the cultural, ethnic ethos and norms of each indigenous group acts as an influential factor in shaping the identities of the North East Indian people. In such contexts, the women question becomes a case of double marginalisation owing to unbalanced power relations as well as patriarchal customs and rules of various indigenous groups and the perpetual militarisation and regional identity crisis in the area. The research aims to investigate the factors moulding the identity of north eastern woman from the lens of gendered subalternity, through some strong, vivid narratives with passive-strong female characters. It is an attempt to understand how the multiple social ideologies of region, ethnicity, race, gender, nation, identity overlap to delineate to hierarchal disparities in the society contributing to victimisation of women.