Miracle-dz/UniFAR-FTUs huggingface dataset:
An Angle-Insensitive 138-dB Dynamic Range Light Sensor With 4 Time-Interleaved Channels 32-ppm/°C Temperature-Independent Flicker Detection

This brief presents an angle-insensitive, high dynamic range light sensor with 4-channels (CHs) temperature-independent flicker detection. Angle insensitivity is achieved by two pairs of Dual-Photodiodes (PDs) for X-axis and Y-axis respectively. 4-CHs temperature-independent flicker detection is realized by a time-interleaved architecture sharing two Trans-Impedance-Amplifiers (TIAs) and one 16-bit third-order incremental $\Delta \Sigma $ ADC, whose clock provided by a newly proposed relaxation oscillator with real-time comparator offset and current-mirror mismatch temperature variation calibration. 7-Levels Auto-Gain-Control (AGC) is implemented to extend dynamic range. The chip was fabricated using 180nm CMOS technology. Experiment results show that the proposed light sensor can achieve −30°~30° flat angular response with +/−67° field-of-view (FOV). 4-CHs flicker detection with 32ppm/°C temperature coefficient is achieved in the range of −30~85°C. 7-Levels AGC extends input light dynamic range to 138dB (0.012~103klux). The chip power consumption is 0.39mW under 1.8V supply and chip area is 2mm x 0.65mm.
Innovation Adoption Process Using the Online Anywhere Service Application at the Population and Civil Registration Office of Tanah Datar Regency

Innovation renewal is present as an effort to use technology to optimize service to the community. One form is in the form of online services for various community affairs by government institutions. This research was conducted to find out how the process of adopting online service innovations via the Online Anywhere Service (OASE) application at the Population and Civil Registration Office of Tanah Datar Regency was carried out by the Population and Civil Registration Office (Disdukcapil) of Tanah Datar Regency using Rogers' Theory. This study uses a descriptive qualitative approach. Data were collected using field research techniques, including observation and in-depth interviews with purposive sampling techniques to determine informants. The results of this study are that online services via the OASE application for the Population and Civil Registration Office of Tanah Datar Regency were successfully adopted from the knowledge stage to the confirmation stage, because the informants considered them to be according to needs and more flexible. Pamphlets and banners are communication channels that act as initial information dissemination tools. It is also known that interpersonal communication between the community and government representatives acts as a process of exchanging information for adopters to obtain additional information. Informants' ability to use technology influences their perceptions in seeing the degree of relative advantage, suitability, and complexity of the innovation.
A Novel All Members Group Search Optimization Based Data Acquisition in Cloud Assisted Wireless Sensor Network for Smart Farming

– Recent times, the Wireless Sensor Networks (WSN) has played an important role in smart farming systems. However, WSN-enabled smart farming (SF) systems need reliable communication to minimize overhead, end-to-end delay, latency etc., Hence, this work introduces a 3-tiered framework based on the integration of WSN with the edge and cloud computing platforms to acquire, process and store useful soil data from agricultural lands. Initially, the sensors are deployed randomly throughout the network region to collect information regarding different types of soil components. The sensors are clustered based on distance using the Levy flight based K-means clustering algorithm to promote efficient communication. The Tasmanian devil optimization (TDO) algorithm is used to choose the cluster heads (CHs) based on the distance among the node and edge server, residual energy, and the number of neighbors. Then, the optimal paths to transmit the data are identified using the all members group search optimization (AMGSO) algorithm based on different parameters. Each edge server assesses the quality of the data (QoD) with respect to some data quality criteria after receiving the data from the edge server. Also, the load across the servers are balanced in order to overcome the overloading and under loading issues. The legitimate data that received higher scores in the QoD evaluation alone is sent to the cloud servers for archival. Using the ICRISAT dataset, the efficiency of the proposed work is evaluated using a number of indicators. The average improvement rate attained by the proposed model in terms of energy consumption is 40%, in terms of packet delivery ratio is 7%, in terms of network lifetime is 38%, and in terms of latency is 24% for a total of 250 nodes.
Survival Prediction of Patients with Bladder Cancer after Cystectomy Based on Clinical, Radiomics, and Deep-Learning Descriptors

Simple Summary Survival prediction of bladder cancer patients following cystectomy is essential for treatment planning. We propose a hybrid method that integrates clinical, radiomics, and deep-learning descriptors to improve survival prediction models. This approach demonstrates potential for more accurately predicting survival and prognosis in radical cystectomy treatment and in determining whether imaging adds additional predictive value over patients’ clinical information. Abstract Accurate survival prediction for bladder cancer patients who have undergone radical cystectomy can improve their treatment management. However, the existing predictive models do not take advantage of both clinical and radiological imaging data. This study aimed to fill this gap by developing an approach that leverages the strengths of clinical (C), radiomics (R), and deep-learning (D) descriptors to improve survival prediction. The dataset comprised 163 patients, including clinical, histopathological information, and CT urography scans. The data were divided by patient into training, validation, and test sets. We analyzed the clinical data by a nomogram and the image data by radiomics and deep-learning models. The descriptors were input into a BPNN model for survival prediction. The AUCs on the test set were (C): 0.82 ± 0.06, (R): 0.73 ± 0.07, (D): 0.71 ± 0.07, (CR): 0.86 ± 0.05, (CD): 0.86 ± 0.05, and (CRD): 0.87 ± 0.05. The predictions based on D and CRD descriptors showed a significant difference (p = 0.007). For Kaplan–Meier survival analysis, the deceased and alive groups were stratified successfully by C (p < 0.001) and CRD (p < 0.001), with CRD predicting the alive group more accurately. The results highlight the potential of combining C, R, and D descriptors to accurately predict the survival of bladder cancer patients after cystectomy.
A DNA Plasmid-Based Approach for Efficient Synthesis of Sacbrood Virus Infectious Clones within Host Cells

RNA viruses are often cited as a significant factor affecting the populations of both domestic honey bees and wild pollinators. To expedite the development of effective countermeasures against these viruses, a more comprehensive understanding of virus biology necessitates extensive collaboration among scientists from diverse research fields. While the infectious virus clone is a robust tool for studying virus diseases, the current methods for synthesizing infectious clones of bee-infecting RNA viruses entail the in vitro transcription of the viral genome RNA in 8–10 kb, presenting challenges in reproducibility and distribution. This article reports on the synthesis of an infectious clone of the Chinese variant sacbrood virus (SBV) using a DNA plasmid containing an Autographa californica multiple nucleopolyhedrovirus (AcMNPV) immediate-early protein (IE1) promoter to trigger transcription of the downstream viral genome within hosts. The results demonstrate that the IE1-SBV plasmid can synthesize SBV clones in a widely used lepidopteran immortal cell line (Sf9) and honey bee pupae. Furthermore, the negative strand of the clone was detected in both Sf9 cells and honey bee pupae, indicating active infection and replication. However, the transfection of Sf9 cells was observed in only a limited proportion (less than 10%) of the cells, and the infection did not appear to spread to adjacent cells or form infective virions. The injection of honey bee pupae with 2500 ng of the IE1-SBV plasmid resulted in high infection rates in Apis cerana pupae but low rates in A. mellifera pupae, although the dosage was comparatively high compared with other studies using in vitro transcribed viral RNA. Our findings suggest that the synthesis of bee-infecting RNA viruses using DNA plasmids is feasible, albeit requiring additional optimization. However, this method holds substantial potential for facilitating the production of clones with various sequence modifications, enabling the exploration of viral gene functions and biology. The ease of distributing infectious clones in DNA plasmid form may foster collaboration among scientists in applying the clone to bee biology, ecology, and behavior, ultimately offering a comprehensive approach to managing virus diseases in the future.
Risk Stratification in Primary Biliary Cholangitis

Primary Biliary Cholangitis (PBC) is a chronic cholestatic liver disease with a heterogeneous presentation, symptomatology, disease progression, and response to therapy. The current risk stratification assessment, aimed at identifying patients with a higher risk of disease progression, encompasses an in-depth analysis of demographic data, clinical and laboratory findings, antibody profiles, and the evaluation of liver fibrosis using both invasive and noninvasive techniques. Treatment response scores after one year of therapy remain to date a major factor influencing the prognosis of PBC patients. While the initial therapeutic approach with ursodeoxycholic acid (UDCA) is universally applied, new second-line treatment options have recently emerged, with many others under investigation. Consequently, the prevailing one-size-fits-all approach is poised to be supplanted by tailored strategies, ensuring high-risk patients receive the most appropriate treatment regimen from diagnosis. This will require the development of a risk prediction model to assess, at the time of diagnosis, the course, outcome, and response to first and additional treatments of PBC patients. This manuscript provides a comprehensive overview of the current and emerging tools used for risk stratification in PBC and speculates on how these developments might shape the disease landscape in the near future.
The acceptance of tablet for note-taking in consecutive interpreting in a classroom context: The students’ perspectives

This study aims to examine interpreting students’ perceptions of using tablets for interpreting note-taking (INT). A mixed-method approach was adopted, including quantitative methods based on Gile’s two-phase effort model of consecutive interpreting (CI) to investigate respondents’ experiences and perceptions, as well as qualitative methods to explore differences between professionals and beginners regarding their preferences and user experiences with note-taking tools. Additionally, factors within the Technology Acceptance Model (TAM) framework that significantly impacted the acceptance of tablet-based interpreting were analyzed. Our research findings reveal valuable insights into students’ attitudes towards integrating technology into interpreter training programs while highlighting key factors influencing tablet-based note-taking adoption or rejection among participants. Moreover, this study emphasizes the importance of developing an application specifically designed for INT to meet the unique needs of interpreters and stresses that training plays an essential role in facilitating the adoption of tablet-based INT. Teachers are suggested to take the initiative to try tablet-based INT themselves before they make their decisions on whether to introduce the technology to their students.
TOWARDS THE INTEGRATED ADOPTION OF BLM AND DT IN AECO-FM SECTOR: A SCIENTOMETRIC APPROACH

The Architecture, Engineering, Construction, Operation and Facility Management (AECO-FM) industry presents a well-known discrepancy in terms of productivity and digitalization compared with other sectors. The introduction of building lifecycle management (BLM) could lead to several benefits covering all the phases of the building lifecycle (BLC) and enabling the implementation of a model-based integrated management system. Nevertheless, its adoption is far from being spread across the construction field and the case studies in the existing literature present several criticalities related to the adopted technologies and policies which hinder the complete development of a BLM system. To overcome these obstacles, digital twins (DTs) could be exploited to enhance the collaboration among actors, preserving the integrity of data, and offering a multidisciplinary environment to carry out realistic simulations. The purpose of this research is to conduct a scientometric analysis to evaluate the relationships between the topics of BLM and DT in the AECO-FM sector. The most common key studies and patterns are identified by processing bibliometric metadata. The most investigated topics related to BLM and DT are system design, system management, and Building Information Modeling (BIM) applications. The analysis reveals a gap regarding the connection between BLM and DT, identifying a potential research area that is currently unexplored in the academic field. The integrated adoption of these topics could contribute to promoting a holistic approach in the built environment by preserving data consistency, reducing information loss between design and construction phases, and strengthening connectivity among the actors involved in the process.
Adaptation of the temporal bisection task for remote collection: development, analysis, and validation

The COVID-19 pandemic posed a significant impediment to experimental research, leading several researchers to adapt psychophysical data acquisition. With the development and proliferation of information technology, paper-based organizational processes have gradually begun to be replaced by computer-based equivalents. This study describes how we developed, analyzed data, and validated the temporal bisection task in a remote data acquisition scenario. We implemented the data acquisition using the open science software OpenSesame, in conjunction with the JATOS platform. We described in detail all the steps to use our codes, which we made available for reuse. We acquired data from 28 participants using the remote acquisition system and compared them with data obtained in person (from Penney et al., 2000). Our remote data showed compatible results with live experiments, suggesting that the modality of data acquisition (remote or live) does not influence the results.
The antecedence of green supply chain management and its impact on business performance in the traditional fashion industry

This study aims to identify and analyze the antecedence of GSCM and their impact on business performance in the traditional fashion industry. This study uses a quantitative method by collecting data through a survey conducted using a questionnaire. For this analysis, the object of this research is a total of 60 traditional fashion industries in Yogyakarta. The sampling method used is a census, namely surveying the population as a whole. The analysis technique used in this research is Structural Equation Modeling (SEM) using Partial Least Squares (PLS) 4.0. Based on the results of this study: supply chain connectivity has a significant positive effect on GSCM; owner commitment has a significant positive effect on GSCM; GSCM has a significant positive effect on business performance; supply chain connectivity has a significant positive effect on business performance; owner commitment has a significant positive effect on business performance; supply chain connectivity has a significant positive effect on business performance through GSCM as a mediating variable; and owner commitment has a significant positive effect on business performance through GSCM as a mediating variable. The recommendation from this study is that hopefully, in the future, more SMEs will increase owner commitment in several aspects such as developing cooperation, working together to create competitive advantage, developing vision and mission, and developing metrics to monitor business success together.
Persistent Flows in Deterministic Chains

This paper studies, the role of persistent flows in the convergence of infinite backward products of stochastic matrices of deterministic chains over networks with nonreciprocal interactions between agents. An arc describing the interaction strength between two agents is said to be persistent if its weight function has an infinite $l_1$ norm; convergence of the infinite backward products to a rank-one matrix of a deterministic chain of stochastic matrices is equivalent to achieving consensus at the node states. We discuss two balance conditions on the interactions between agents, which generalize the arc-balance and cut-balance conditions in the literature, respectively. The proposed conditions require that such a balance should be satisfied over each time window of a fixed length instead of at each time instant. We prove that in both cases global consensus is reached if and only if the persistent graph, which consists of all the persistent arcs, contains a directed spanning tree. The convergence rates of the system to consensus are also provided in terms of the interactions between agents having taken place. The results are obtained under a weak condition without assuming the existence of a positive lower bound of all the nonzero weights of arcs and are compared with the existing results. Illustrative examples are provided to validate the results and show the critical importance of the nontrivial lower boundedness of the self-confidence of the agents.
Compressible mixing layer in shock-induced separation

Unsteadiness in separated shock–boundary layer interactions have been previously analysed in order to propose a scenario of entrainment–discharge as the origin of unsteadiness. It was assumed that the fluid in the separated zone is entrained by the free shear layer formed at its edge, and that this layer follows the properties of the canonical mixing layer. This last point is addressed by reanalysing the velocity measurements in an oblique shock reflection at a nominal Mach number of 2.3 and for two cases of flow deviation ( $8^{\circ }$ and $9.5^{\circ }$ ). The rate of spatial growth of this layer is evaluated from the spatial growth of the turbulent stress profiles. Moreover, the entrainment velocity at the edge of the layer is determined from the mean velocity profiles. It is shown that the values of turbulent shear stress, spreading rate and entrainment velocity are consistent, and that they follow the classical laws for turbulent transport in compressible shear layers. Moreover, the measurements suggest that the vertical normal stress is sensitive to compressibility, so that the anisotropy of turbulence is affected by high Mach numbers. Dimensional considerations proposed by Brown & Roshko (J. Fluid Mech., vol. 64, 1974, 775–781) are reformulated to explain this observed trend.
RBP7 Regulated by EBF1 Affects Th2 Cells and the Oocyte Meiosis Pathway in Bone Metastases of Bladder Urothelial Carcinoma.

BACKGROUND Bladder urothelial carcinoma (BLCA) is a malignancy with a high incidence worldwide. One-third of patients may experience aggressive progression later on, and 70% of patients who have undergone surgical intervention will still suffer from metastasis. MATERIALS AND METHODS RNA sequencing profiles of BLCA samples were obtained from The Cancer Genome Atlas (TCGA) database. Differential expression and univariate Cox regression analyses were performed to identify prognosis-related differentially expressed immune genes (DEIGs). Subsequently, a proportional hazards model of DEIGs was then constructed by univariate regression analysis. Differential expression and correlation analyses, CIBERSORT, Single Sample Gene Set Enrichment Analysis (ssGSEA), GSVA were conducted on transcription factors (TFs), immune cells/pathways and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. The regulation network was then constructed. Eventually, ATAC-seq, ChIP-seq, scRNA-seq, and multiple online databases were employed for further validation. RESULTS A proportional hazards model of 31 DEIGs was constructed and risk score was calculated and proven to be a independent prognostic factor. Then 5 immune genes were characterized to be significantly correlated with bone metastasis, stage and TF expression simultaneously. 4 TFs were identified to be significantly correlated with prognosis and RBP7 expression. 5 immune cells/pathways were revealed to be significantly correlated with RBP7 expression. Only 1 KEGG pathway was identified to be significant in Gene Set Enrichment Analysis (GSEA) and Gene Set Variation Analysis (GSVA) analyses. The regulatory relationship was then constructed, in which the correlation between EBF1 and RBP7 (R = 0.677, p < 0.001), Th2 cells and RBP7 (R = 0.23, p < 0.001), the oocyte meiosis pathway and RBP7 (R = 0.14, p = 0.042) were the most statistically significant. The results were further confirmed by Assay for Transposase Accessible Chromatin with high-throughput sequencing (ATAC-seq), Chromatin Immunoprecipitation sequencing (ChIP-seq), single-cell RNA sequencing (scRNA-seq), and multiple online databases validation. CONCLUSIONS This study revealed that the EBF1-RBP7 regulatory relationship had potential importance in the bone metastasis in BLCA through Th2 cells and the oocyte meiosis pathway.
Marine Bacterioplankton Community Dynamics and Potentially Pathogenic Bacteria in Seawater around Jeju Island, South Korea, via Metabarcoding

Understanding marine bacterioplankton composition and distribution is necessary for improving predictions of ecosystem responses to environmental change. Here, we used 16S rRNA metabarcoding to investigate marine bacterioplankton diversity and identify potential pathogenic bacteria in seawater samples collected in March, May, September, and December 2013 from two sites near Jeju Island, South Korea. We identified 1343 operational taxonomic units (OTUs) and observed that community diversity varied between months. Alpha- and Gamma-proteobacteria were the most abundant classes, and in all months, the predominant genera were Candidatus Pelagibacter, Leisingera, and Citromicrobium. The highest number of OTUs was observed in September, and Vibrio (7.80%), Pseudoalteromonas (6.53%), and Citromicrobium (6.16%) showed higher relative abundances or were detected only in this month. Water temperature and salinity significantly affected bacterial distribution, and these conditions, characteristic of September, were adverse for Aestuariibacter but favored Citromicrobium. Potentially pathogenic bacteria, among which Vibrio (28 OTUs) and Pseudoalteromonas (six OTUs) were the most abundant in September, were detected in 49 OTUs, and their abundances were significantly correlated with water temperature, increasing rapidly in September, the warmest month. These findings suggest that monthly temperature and salinity variations affect marine bacterioplankton diversity and potential pathogen abundance.