Search Results (347)

The global coffee supply chain is a complex multi-stakeholder ecosystem plagued by fragmented records, unverifiable origin claims, and limited real-time visibility. These limitations pose risks to ethical sourcing, product quality, and consumer trust. To address these issues, this paper proposes a blockchain and IoT-enabled framework for secure and transparent coffee supply chain management. The system integrates simulated IoT sensor data such as Radio-Frequency Identification (RFID) identity tags, Global Positioning System (GPS) logs, weight measurements, environmental readings, and mobile validations with Ethereum smart contracts to establish traceability and automate supply chain logic. A Solidity-based Ethereum smart contract is developed and deployed on the Sepolia testnet to register users and log batches and to handle ownership transfers. The Internet of Things (IoT) data stream is simulated using structured datasets to mimic real-world device behavior, ensuring that the system is tested under realistic conditions. Our performance evaluation on 1000 transactions shows that the model incurs low transaction costs and demonstrates predictable efficiency behavior of the smart contract in decentralized conditions. Over 95% of the 1000 simulated transactions incurred a gas fee of less than ETH 0.001. The proposed architecture is also scalable and modular, providing a foundation for future deployment with live IoT integrations and off-chain data storage. Overall, the results highlight the system’s ability to improve transparency and auditability, automate enforcement, and enhance consumer confidence in the origin and handling of coffee products. Full article

Background: Chryseobacterium indologenes, an environmental bacterium, is increasingly recognized as an emerging nosocomial pathogen, particularly in Asia, and is often characterized by multidrug resistance. Objectives: This study aimed to investigate the genomic features of clinical C. indologenes isolates from Maharaj Nakorn Chiang Mai Hospital, Thailand, to understand their mechanisms of multidrug resistance, virulence factors, and mobile genetic elements (MGEs). Methods: Twelve C. indologenes isolates were identified, and their antibiotic susceptibility profiles were determined. Whole genome sequencing (WGS) was performed using a hybrid approach combining Illumina short-reads and Oxford Nanopore long-reads to generate complete bacterial genomes. The hybrid assembled genomes were subsequently analyzed to detect antimicrobial resistance (AMR) genes, virulence factors, and MGEs. Results: C. indologenes isolates were primarily recovered from urine samples of hospitalized elderly male patients with underlying conditions. These isolates generally exhibited extensive drug resistance, which was subsequently explored and correlated with genomic determinants. With one exception, CMCI13 showed a lower resistance profile (Multidrug resistance, MDR). Genomic analysis revealed isolates with genome sizes of 4.83–5.00 Mb and GC content of 37.15–37.35%. Genomic characterization identified conserved resistance genes (bla_IND-2, bla_CIA-4, adeF, vanT, and qacG) and various virulence factors. Phylogenetic and pangenome analysis showed 11 isolates clustering closely with Chinese strain 3125, while one isolate (CMCI13) formed a distinct branch. Importantly, each isolate, except CMCI13, harbored a large genomic island (approximately 94–100 kb) carrying significant resistance genes (bla_OXA-347, tetX, aadS, and ermF). The absence of this genomic island in CMCI13 correlated with its less resistant phenotype. No plasmids, integrons, or CRISPR-Cas systems were detected in any isolate. Conclusions: This study highlights the alarming emergence of multidrug-resistant C. indologenes in a hospital setting in Thailand. The genomic insights into specific resistance mechanisms, virulence factors, and potential horizontal gene transfer (HGT) events, particularly the association of a large genomic island with the XDR phenotype, underscore the critical need for continuous genomic surveillance to monitor transmission patterns and develop effective treatment strategies for this emerging pathogen. Full article

This paper presents a multi-sensor fusion framework for the accurate indoor localization and trajectory tracking of a differential-drive mobile robot. The proposed system integrates Ultra-Wideband (UWB) trilateration, wheel odometry, and Attitude and Heading Reference System (AHRS) data using a Kalman filter. This fusion approach reduces the impact of noisy and inaccurate UWB measurements while correcting odometry drift. The system combines raw UWB distance measurements with wheel encoder readings and heading information from an AHRS to improve robustness and positioning accuracy. Experimental validation was conducted through repeated closed-loop trajectory trials. The results demonstrate that the proposed method significantly outperforms UWB-only localization, yielding reduced noise, enhanced consistency, and lower Dynamic Time Warping (DTW) distances across repetitions. The findings confirm the system’s effectiveness and suitability for real-time mobile robot navigation in indoor environments. Full article

With the widespread adoption of mobile reading across diverse scenarios, understanding environmental impacts on attention has become crucial for reading performance optimization. Building upon this premise, the study examined the impacts of different reading environments on attention during mobile reading, utilizing a mixed-methods approach that combined eye-tracking experiments with semi-structured interviews. Thirty-two college students participated in the study. Quantitative attention metrics, including total fixation duration and fixation count, were collected through eye-tracking, while qualitative data regarding perceived environmental influences were obtained through interviews. The results indicated that the impact of different environments on mobile reading attention varies significantly, as this variation is primarily attributable to environmental complexity and individual interest. Environments characterized by multisensory inputs or dynamic disturbances, such as fluctuating noise and visual motion, were found to induce greater attentional dispersion compared to monotonous, low-variation environments. Notably, more complex potential task-like disturbances (e.g., answering calls, conversations) were found to cause the greatest distraction. Moreover, stimuli aligned with an individual’s interests were more likely to divert attention compared to those that did not. These findings contribute methodological insights for optimizing mobile reading experiences across diverse environmental contexts. Full article

Daoist robes in the Ming Dynasty literature underwent a marked transformation from exclusive religious vestments to widespread secular attire. Originally confined to Daoist priests and sacred rites, these garments began to appear in everyday work, entertainment, and ceremonies across social strata. Drawing on a hand-coded corpus of novels that yields robe related passages, and by analyzing textual references from Ming novels, Daoist canonical works, and visual artifacts, and applying clothing psychology and semiotic theory, this study elucidates how Daoist robes were re-coded as secular fashion symbols. For example, scholar-officials donned Daoist robes to convey moral prestige, laborers adopted them to signal upward mobility, and merchants donned them to impersonate the educated elite for commercial gain. By integrating close textual reading with cultural theory, the article advances a three-stage model, sacred uniform, ritual costume, and secular fashion, that clarifies the semantic flow of Daoist robes. In weddings and funerals, many commoners flaunted Daoist robes despite sumptuary laws, using them to assert honor and status. These adaptations reflect both the erosion of Daoist institutional authority and the dynamic process of identity construction through dress in late Ming society. Our interdisciplinary analysis highlights an East Asian perspective on the interaction of religion and fashion, offering historical insight into the interplay between religious symbolism and sociocultural identity formation. Full article

Acinetobacter baumannii is listed by the World Health Organization as an emerging bacterial priority pathogen, the prevalence and multidrug resistance of which have been increasing. This functional genomics study aimed to understand the drug-resistance mechanisms of an extensively drug-resistant (XDR) A. baumannii strain (IRMCBCU95U) isolated from a transtracheal aspirate sample from a female patient with end-stage renal disease in Saudi Arabia. The whole genome of IRMCBCU95U (4.3 Mbp) was sequenced using Oxford Nanopore long-read sequencing to identify and compare the antibiotic-resistance profile and genomic features of A. baumannii IRMCBCU95U. The antibiogram of A. baumannii IRMCBCU95U revealed resistance to multiple antibiotics, including cefepime, ceftazidime, ciprofloxacin, imipenem, meropenem and piperacillin/tazobactam. A comparative genomic analysis between IRMCBCU95U and A. baumannii K09-14 and ATCC 19606 identified significant genetic heterogeneity and mosaicism among the strains. This analysis also demonstrated the hybrid nature of the genome of IRMCBCU95U and indicates that horizontal gene transfer may have occurred between these strains. The IRMCBCU95U genome has a diverse range of genes associated with antimicrobial resistance and mobile genetic elements (ISAba1 and IS26) associated with the spread of multidrug resistance. The presence of virulence-associated genes that are linked to iron acquisition, motility and transcriptional regulation confirmed that IRMCBCU95U is a priority human pathogen. The plasmid fragment IncFIB(pNDM-Mar) observed in the strain is homologous to the plasmid in Klebsiella pneumoniae (439 bp; similarity: 99.09%), which supports its antimicrobial resistance. From these observations, it can be concluded that the clinical A. baumannii IRMCBCU95U isolate is an emerging extensively drug-resistant human pathogen with a novel combination of resistance genes and a plasmid fragment. The complex resistome of IRMCBCU95U highlights the urgent need for genomic surveillance in hospital settings in Saudi Arabia to fight against the spread of extensively drug-resistant A. baumannii. Full article

Navigational aids play a vital role in enhancing the mobility and independence of blind and visually impaired (VI) individuals. However, existing solutions often present challenges related to discomfort, complexity, and limited ability to provide detailed environmental awareness. To address these limitations, we introduce SnapStick, an innovative assistive technology designed to improve spatial perception and navigation. SnapStick integrates a Bluetooth-enabled smart cane, bone-conduction headphones, and a smartphone application powered by the Florence-2 Vision Language Model (VLM) to deliver real-time object recognition, text reading, bus route detection, and detailed scene descriptions. To assess the system’s effectiveness and user experience, eleven blind participants evaluated SnapStick, and usability was measured using the System Usability Scale (SUS). In addition to the 94% accuracy, the device received an SUS score of 84.7%, indicating high user satisfaction, ease of use, and comfort. Participants reported that SnapStick significantly improved their ability to navigate, recognize objects, identify text, and detect landmarks with greater confidence. The system’s ability to provide accurate and accessible auditory feedback proved essential for real-world applications, making it a practical and user-friendly solution. These findings highlight SnapStick’s potential to serve as an effective assistive device for blind individuals, enhancing autonomy, safety, and navigation capabilities in daily life. Future work will explore further refinements to optimize user experience and adaptability across different environments. Full article

The motion control of a tracked mobile robot remains an important capability for autonomous navigation. Kinematic path-tracking algorithms are commonly used in mobile robotics due to their ease of implementation and real-time computational cost advantage. This paper integrates an extended Kalman filter (EKF) into a common kinematic controller for path-tracking performance improvement. The extended Kalman filter estimates the instantaneous center of rotation (ICR) of tracks using the sensor readings of GPS and IMU. These ICR estimations are then given as input to the motion control algorithm to generate the track velocity demands. The platform to be controlled is a heavyweight off-road tracked vehicle, which necessitates the investigation of slip values. A high-fidelity simulation model, which is verified with field tests, is used as the plant in the path-tracking simulations. The performance of the filter and the algorithm is also demonstrated in field tests on a stabilized road. The field results show that the proposed estimation increases the path-tracking accuracy significantly (about 44%) compared to the classical pure pursuit. Full article

This paper introduces a configuration and integration model for mobile robots deployed in emergency and special operations scenarios. The proposed method is designed for implementation within the operational technology (OT) domain, enforcing security protocols that ensure both data encryption and network isolation. The primary objective is to establish a dedicated operational environment encompassing a command and control center where the robotic network server resides, alongside real-time data storage from network clients and remote control of field-deployed mobile robots. Building on this infrastructure, operational strategies are developed to enable an efficient robotic response in critical situations. By leveraging remote robotic networks, significant benefits are achieved in terms of personnel safety and mission efficiency, minimizing response time and reducing the risk of injury to human operators during hazardous interventions. Unlike generic IoT or IoRT systems, this work focuses on secure robotic integration within segmented OT infrastructures. The technologies employed create a synergistic system that ensures data integrity, encryption, and safe user interaction through a web-based interface. Additionally, the system includes mobile robots and a read-only application positioned within a demilitarized zone (DMZ), allowing for secure data monitoring without granting control access to the robotic network, thus enabling cyber-physical isolation and auditability. Full article

Blood pressure is a vital indicator of cardiovascular health and plays a crucial role in the early detection and management of heart-related diseases. However, current practices for recording blood pressure readings are still largely manual, leading to inefficiencies and data inconsistencies. To address this challenge, we propose a deep learning-based method for automated digit recognition and measurement-type classification (systolic, diastolic, and pulse) from images of blood pressure monitors. A total of 2147 images were collected and expanded to 3649 images using data augmentation techniques. We developed and trained three YOLOv8 variants (small, medium, and large). Post-training quantization (PTQ) was employed to optimize the models for edge deployment in a mobile health (mHealth) application. The quantized INT8 YOLOv8-small (YOLOv8s) model emerged as the optimal model based on the trade-off between accuracy, inference time, and model size. The proposed model outperformed existing approaches, including the RT-DETR (Real-Time DEtection TRansformer) model, achieving 99.28% accuracy, 96.48% F1-score, 641.40 ms inference time, and a compact model size of 11 MB. The model was successfully integrated into the mHealth application, enabling accurate, fast, and automated blood pressure tracking. This end-to-end solution provides a scalable and practical approach for enhancing blood pressure monitoring via an accessible digital platform. Full article

Inheriting a tradition of religious tolerance from the Inner Asian Steppe, the Mongol Yuan Empire elevated Buddhism to a pivotal role in unifying its multiethnic and culturally diverse domain, with Tengriist ideology serving as the political foundation for these Buddhist veneration policies. The ruling class of the Yuan dynasty practiced a complex interaction between religion and political unity through the institutionalization of the cult of writing, printing, and reading the Buddhist Canon. Specifically, the Yuan dynasty established specialized government offices to mobilize elites from Mongolian, Han Chinese, Goryeo, and other ethnic groups for the construction of a multilingual Buddhist Canon. They copied the scriptures with gold and silver ink in Chinese, Tibetan, Uyghur, and other languages. Participants in scripture copying were rewarded or granted official positions. In this way, they achieved the goal of enlisting local elites, the cohesion of the community’s beliefs, and enhanced the unity of the local elites. By subsidizing the writing and reading of Buddhist classics, the Yuan rulers succeeded in constructing a space of identity at the level of material culture and facilitated cultural interaction and political integration among various social groups such as the Mongols, ethnic groups, and Han Chinese. Through state-sponsored scripture carving and recitation activities, the Yuan rulers cultivated a shared identity in the material culture sphere, facilitating cultural exchange and political integration across the Mongolians, the Han Chinese, and other ethnic communities. However, the effectiveness of state unification was significantly constrained by the Mongolian rulers’ policy of ethnic segregation, central–local conflict, and the high concentration of social wealth in the Buddhist communities. Full article

Background/Objectives: Chronic low back pain (CLBP) is a prevalent condition that significantly impacts the aging population. Among non-invasive assessment tools, infrared thermography (IRT) has been highlighted as a radiation-free method to evaluate thermal variations in the lumbar region. However, its applicability in clinical practice and correlation with functional and pain-related parameters remain unclear. This study aimed to analyze the thermal profile of the lumbar region in elderly individuals with CLBP and explore potential correlations between lumbar temperature patterns and clinical factors such as pain intensity and functional capacity. Methods: A cross-sectional observational study was performed in an outpatient setting. The population included thirty-one elderly individuals diagnosed with CLBP. IRT was used to assess the lumbar temperature distribution, including participants who reported pain radiating to the lower limbs. Pain intensity was measured using a numerical rating scale (0–10). The functional assessments included spine mobility tests and validated questionnaires evaluating clinical characteristics. Results: No significant differences in lumbar temperature patterns were observed among the participants. Additionally, no correlation was found between pain intensity and functional capacity based on a thermographic analysis. Nonetheless, individuals reporting lower fatigue levels and those with a higher body mass index (BMI) were generally associated with cooler thermal readings on the lumbar region’s thermographic maps. Conclusions: These findings suggest that IRT may require methodological refinements, including optimized technical specifications and image acquisition protocols, to enhance its applicability in assessing CLBP. Indeed, IRT might not be the most effective tool for evaluating pain-related thermal changes in elderly populations. Further research is needed to clarify its role in clinical assessments. Full article

In the N$\nu$DEx collaboration, a high-pressure gas TPC is being developed to search for the neutrinoless double beta decay. The use of electronegative ⁸²SeF₆ gas mandates an ion-TPC. The reconstruction of the z coordinate is to be realized by exploiting the feature of multiple species of charge carriers. As the initial stage of the development, we studied the properties of the ${\mathrm{SF}}_6$ gas, which is non-toxic and has a similar molecular structure to ${\mathrm{SeF}}_6$. In the paper, we present the measurement of drift velocities and mobilities of the majority and minority negative charge carriers found in ${\mathrm{SF}}_6$ at a pressure of 750 Torr, slightly higher than the local atmospheric pressure. The reduced fields range between 3.0 and 5.5 Td. This was performed using a laser beam to ionize the gas inside a small TPC, with a drift length of 3.7 cm. A customized charge-sensitive amplifier was developed to read out the anode signals induced by the slowly drifting ions. The closure test of the reconstruction of the z coordinate using the difference in the velocities of the two carriers was also demonstrated. Full article

As a critical component of computer systems, static random access memory (SRAM) plays a significant role in the fields of high-performance computing, artificial intelligence, and the Internet of Things. However, the conventional silicon-based SRAM is facing problems such as high power consumption, integration limitations, and the need for performance improvement. For the power consumption challenge of SRAM, a novel read/write-decoupled SRAM cell is proposed in this paper. When SRAM is in a standby state, utilization of this cell can effectively reduce the leakage current, thereby reducing the static power consumption. In addition, a novel carbon–silicon heterogeneous-integrated SRAM technology is proposed in this paper. The carbon–silicon heterogeneous-integrated SRAM technology combines the high mobility, low power consumption, and low temperature process compatibility of carbon nanotubes (CNTs) with mature silicon-based fabrication processes, enabling significant optimization of access time and power consumption. The SRAM was implemented by a silicon-based 55 nm process and a carbon-based 500 nm process. The simulation results showed that when the power supply was 1.2 V, the access time of SRAM with the silicon 55 nm process was 886 ps. The static and dynamic power consumption was 91.51 nW and 1.48 mW, respectively. The SRAM with carbon–silicon heterogeneous-integrated technology achieved an access time of 872 ps, a static power consumption of 62.54 nW, and a dynamic power consumption of 1.07 mW, representing reductions of 1.58%, 31.66%, and 27.70%, respectively. Full article

The performance of urban transport is a critical aspect of a city’s functionality, which needs to be supported by innovative data sources to analyze travel patterns. This study explores the use of Google Location History (GLH) as a participatory geographic information system for mobility surveys, offering a cost-effective and more detailed alternative to traditional approaches. GLH is a novel data source with high potential, but still underutilized and underresearched, especially in developing countries. This study uses a new approach in GLH data collection and data processing. Data were collected from 420 respondents in Medan, Binjai, and Deli Serdang (Mebidang) in Indonesia, to examine urban travel patterns, including trip distances, modes, and purposes, while addressing issues of data accuracy, privacy, and representation. GLH provides granular insights into mobility, reducing biases associated with self-reported surveys and identifying discrepancies between stated and actual transport usage. The findings highlight GLH’s potential for understanding spatial mobility patterns linked to demographic characteristics and travel purpose in more detail. However, technical challenges, such as data anomalies and the reliance on two devices for data collection, underscore the need to improve location readings and develop add-on tools capable of direct data export for large-scale mobility surveys. This study advances the application of GLH in mobility research, demonstrating its potential use and challenges for large-scale mobility surveys. Future research should address privacy concerns and optimize data collection to enable more inclusive and sustainable urban mobility strategies. Full article