Miracle-dz/UniFAR-FTUs huggingface dataset:
Chronic Morphine Treatment and Antiretroviral Therapy Exacerbate HIV-Distal Sensory Peripheral Neuropathy and Induce Distinct Microbial Alterations in the HIV Tg26 Mouse Model

Distal Sensory Peripheral Neuropathy (DSP) is a common complication in HIV-infected individuals, leading to chronic pain and reduced quality of life. Even with antiretroviral therapy (ART), DSP persists, often prompting the use of opioid analgesics, which can paradoxically worsen symptoms through opioid-induced microbial dysbiosis. This study employs the HIV Tg26 mouse model to investigate HIV-DSP development and assess gut microbiome changes in response to chronic morphine treatment and ART using 16S rRNA sequencing. Our results reveal that chronic morphine and ART exacerbate HIV-DSP in Tg26 mice, primarily through mechanical pain pathways. As the gut microbiome may be involved in chronic pain persistence, microbiome analysis indicated distinct bacterial community changes between WT and Tg26 mice as well as morphine- and ART-induced microbial changes in the Tg26 mice. This study reveals the Tg26 mouse model to be a relevant system that can help elucidate the pathogenic mechanisms of the opioid- and ART-induced exacerbation of HIV-associated pain. Our results shed light on the intricate interplay between HIV infection, ART, opioid use, and the gut microbiome in chronic pain development. They hold implications for understanding the mechanisms underlying HIV-associated pain and microbial dysbiosis, with potential for future research focused on prevention and treatment strategies.
A 187-dB FoMS Power-Efficient Second-Order Highpass ΔΣ Capacitance-to-Digital Converter

The escalating demand for high-resolution sensor interface systems, driven by the proliferation of the Internet of Things (IoT) and wearable smart devices, has led to the widespread use of capacitive sensing transducers. These transducers are valued for their low-noise and low-power characteristics, making them suitable for various applications, including environmental and biomedical sensing. However, designing a high-resolution capacitive sensor interface system while maintaining power efficiency remains challenging. This article proposes a high-resolution energy-efficient highpass (HP) <inline-formula> <tex-math notation="LaTeX">$\Delta \Sigma $ </tex-math></inline-formula> capacitance-to-digital converter (CDC) architecture. The architecture incorporates a 2nd-order HP <inline-formula> <tex-math notation="LaTeX">$\Delta \Sigma $ </tex-math></inline-formula> modulator (<inline-formula> <tex-math notation="LaTeX">$\Delta \Sigma \text{M}$ </tex-math></inline-formula>) and a continuous-time capacitance-to-voltage converter (CT CVC). The proposed CDC achieves an excellent capacitance resolution of 5.85 aFrms, with a power efficiency of 46 fJ/conversion-step and an FoMS of 187.4 dB. The HP <inline-formula> <tex-math notation="LaTeX">$\Delta \Sigma \text{M}$ </tex-math></inline-formula>, designed with superior power efficiency, offers a promising solution for high-resolution capacitive sensor applications. Compared to state-of-the-art, the proposed CDC achieves more than 2<inline-formula> <tex-math notation="LaTeX">$\times $ </tex-math></inline-formula> FoMS improvement while maintaining competitive FoMW.
Implementing Many-Lights Rendering with IES-Based Lights

In recent years, many research projects on real-time rendering have focused on the introduction of global illumination effects in order to improve the realism of a virtual scene. The main goal of these works is to find a compromise between the achievable quality of the resulting rendering and the intrinsic high computational cost of global illumination. An established approach is based on the use of Virtual Point Lights, i.e., “fictitious” light sources that are placed on surfaces in the scene. These lights simulate the contribution of light rays emitted by the light sources and bouncing on different objects. Techniques using Virtual Point Lights are often called Many-Lights techniques. In this paper, we propose an extension of a real-time Many-Lights rendering technique characterized by the integration of photometric data in the process of Virtual Point Lights distribution. We base the definition of light sources and the creation of Virtual Point Lights on the description provided in the IES standard format, created by the Illuminating Engineering Society (IES).
Separable Spatial–Temporal Patch-Tensor Pair Completion for Infrared Small Target Detection

The infrared small target detection (IRSTD) task presents significant challenges due to low signal-to-clutter ratio (SCR), complicated background, and strong interferences. While tensor theory has shown promise in detection performance, three issues regarding damaged tensor construction, inaccurate tensor models, and high-computation complexity remain. This study addresses these issues by introducing an independent spatial–temporal perspective, and proposes a fast and separable spatial–temporal tensor completion model. A new tensor structure named separable spatial–temporal patch-tensor pair (SSPP) is conceived to alleviate the dilemma of maintaining neighborhood structure and temporal consistency when constructing image tensors. By treating spatial and temporal dimensions as independent, SSPP enables flexible distribution hypotheses and representations in each dimension. Two tensor models are devised: the spatial model focuses on target enhancement in the spatial dimension, while the temporal one concentrates on suppressing strong interference in the temporal dimension. A long-term memory regularization is further introduced to the temporal model for target movement perception, enhancing its robustness to interferences. By combining these tensor models and employing a coarse-to-fine detection strategy, our method offers an effective solution for IRSTD. Extensive experiments on practical datasets have demonstrated the superiority of the proposed method in terms of target enhancement, background suppression (BS), and detection efficiency.
Effective driver distraction warning system incorporating fast image recognition methods

Modern cars are equipped with advanced automatic technology featuring various safety measures for car occupants. However, the growing density of vehicles, especially in areas where infrastructure development lags, poses potential dangers, particularly accidents caused by driver subjectivity. These incidents may occur due to driver distraction or the presence of high-risk obstacles on the road. This article presents a comprehensive solution to assist drivers in mitigating these risks. Firstly, the study introduces a novel method to enhance the recognition of a driver's facial features by analyzing benchmarks and the whites of the eyes to assess the distraction level. Secondly, a domain division method is proposed to identify obstacles and lanes in front of the vehicle, enabling the assessment of the danger level. This information is promptly relayed to the driver and relevant individuals, such as the driver's manager or supervisor. An experimental device has also been developed to evaluate the effectiveness of the algorithms, solutions, and processing capabilities of the system.
Dynamic Characteristics and Energy Consumption of Electromechanical Converter of High-Speed On/Off Valve Under Multiple Motion Cycles Considering Eddy Current and Hysteresis

The current, electromagnetic force, and dynamic displacement of the high-speed on/off valve’s (HSV) electromechanical converter under stable working cycle are significantly different from those under the initial movement cycle. This phenomenon determines whether the electromechanical converter can continue to operate stably, and it also leads to temperature rise and high energy consumption over long periods of time. Therefore, in this study, a high-precision model is proposed that can fully analyze the characteristics of the electromechanical converter under multiple motion cycles with the consideration of the effects of eddy current and hysteresis. First, the hysteresis loop of the material is tested, and the Jiles–Atherton hysteresis model is identified based on the test data and verified through experiments. Second, the fundamental reasons for the differences in current and electromagnetic forces between initial motion and stable motion are analyzed. On this basis, a new law of dynamic evolution of electromechanical converters under multiple motion cycles is discovered. Finally, the important influence of hysteresis characteristics and eddy current on the dynamic performance and energy loss of the electromechanical converter under multiple motion cycles is analyzed. The effects of frequency, voltage, and external resistance on the dynamic characteristics and energy loss of electromechanical converters have also been analyzed. The results indicate that as the voltage increases, the response time decreases, but the eddy current loss increases. An increase in external resistance will increase response time but reduce eddy current losses. This study can provide a theoretical basis for further improving the performance of electromechanical converters.
Comparison Metaphor and Reasoning Comprehension Between Children with Borderline Intelligence and Typical Developing School-Aged children

Purpose: Metalinguistic skills play a critical role in school-aged children’s language development and academic achievement. This study investigates whether metaphorical reasoning in children with borderline intellectual functioning (BIF) (or slow learners) differs from that of typically developing children.Methods: A total of 52 children (29 boys and 23 girls), who voluntarily agreed to participate in the study, were included. Children were categorized into three groups (15 slow learner group, 18 chronological age-matched group, and 19 language age-matched group) based on their K-WISC and receptive vocabulary scores in the Receptive and Expressive Vocabulary Test (REVT). All children completed the Metaphorical and Reasoning Comprehension test (MARC) to estimate their metaphor and reasoning comprehension ability.Results: As a result of a one-way analysis of variance, there was a significant difference among the groups, and a significant difference was found between the slow learners and the chronological age-matched group (p=0.000), but no significant difference was presented between the slow learner group and the language age-matched group. Similarly, regarding the expressive vocabulary score, a one-way ANOVA revealed a significant difference only between the slow learner and the chronological age-matched group (p=0.000). When comparing the scores for metaphorical reasoning comprehension among the three groups, the metaphorical reasoning comprehension scores were significantly different among the groups, with the slow learners having the lowest scores: the slow learner group was substantially different from the language age-matched group (p=0.025), while there was also a significant difference between the slow learner group and the chronological age-matched group (p=0.000). Conclusions: This study suggests that the semantic component of language is not affected in BIF children, but rather, the meaning of words is affected by tasks that require higher-order metalinguistic skills, such as understanding metaphorical inferences embedded in the context of a sentence. Accordingly, the ability to understand metaphorical reasoning can identify slow learners.
Machine learning-based optimization of storage ring injection efficiency

Since the DELTA accelerator facility does not use a White circuit-driven fast topping-up mode, each software-driven injection ramp cycle takes about 7 seconds. Depending on the injection efficiency, 150 to 200 ramp cycles are required to reach the maximum beam current of 130 mA in the storage ring. Thus, for fast post-injection, a high electron transfer rate is crucial. During the injection process, a large number of parameters (e. g., magnet settings, timings of pulsed elements) have to be adjusted manually. The injection efficiency depends mainly on the settings of the booster extraction elements, the T2 transfer line magnets, and the storage ring injection components. In order to automate the injection procedure and to improve the electron transfer efficiency, the application of innovative machine learning concepts was studied.
Assimilation of Satellite Soil Moisture for Improved Atmospheric Reanalyses

A newly developed, weakly coupled land and atmosphere data assimilation system for NASA’s Global Earth Observing System model is presented, and used to demonstrate the benefit of assimilating satellite soil moisture into an atmospheric reanalysis. Specifically, Advanced Scatterometer and Soil Moisture Ocean Salinity soil moisture retrievals are assimilated into a system that uses the same model, atmospheric assimilation system, and atmospheric observations as the Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2). The atmosphere is sensitive to soil moisture only under certain conditions. Hence, while the globally averaged model improvements were small, regionally, the soil moisture assimilation induced some substantial improvements. For example, in a large region spanning from western Europe across southern Russia, the soil moisture assimilation decreased the RMSE against independent station observations of daily maximum 2-m temperature () by up to 0.4 K, and of 2-m specific humidity (q2m) by up to 0.5 g kg−1. Over all available stations, the mean RMSE was reduced from 2.82 to 2.79 K, while the mean q2m RMSE was reduced from 1.25 to 1.20 g kg−1. The soil moisture assimilation also reduced the mean RMSE across 29 flux tower sites from 34.2 to 32.6 W m−2 for latent heating, and from 37.7 to 36.5 W m−2 for sensible heating. For all variables evaluated, the soil moisture assimilation improved the model at monthly to seasonal, rather than daily, time scales. Based on the above experiments, it is recommended that satellite soil moisture be assimilated into future reanalyses, including the follow-on to MERRA-2.
Improved Efficacy of Delayed Treatment with Human Bone Marrow-Derived Stromal Cells Evaluated in Rats with Spinal Cord Injury

The treatment of spinal cord injury (SCI) with uncultivated human bone marrow-derived stromal cells (bmSCs) prepared by negative selection has been proposed to be therapeutically superior to treatment with stem cells that were expanded in vitro. To explore their use in clinical trials, we studied the functional effects of delayed application at 7 days after SCI by testing different doses of bmSCs. Spinal cord contusion injury was induced in adult male Wistar rats at the thoracic level T9. Human bmSCs were prepared by negative selection without expansion in vitro (NeuroCellsTM). Treatment consisted of one 150 µL injection into the cisterna magna containing 0.5 or 2.5 million fresh bmSCs or 2.5 million bmSCs. The recovery of motor functions was evaluated during a surveillance period of six weeks (6 W), during which spinal cords were assessed histologically. Treatment resulted in a significant, dose-dependent therapeutic effect on the recovery of motor performance. The histological analysis revealed a lower degree of axonal degeneration and better survival of neurons and oligodendrocytes in bmSCs treated rats. Our results support delayed intrathecal application of bmSCs prepared by negative selection without expansion in vitro as a treatment of SCI.
A Meta-Analytical Study Appraising the Effectiveness and Safety of Diclofenac Sodium for Senescent Knee Arthritis Treatment

The analysis yielded significant revelations regarding the effectiveness and safety of utilizing diclofenac sodium as a treatment choice for knee osteoarthritis in the elderly population. The keywords "diclofenac sodium" and "knee osteoarthritis" were used to search the Chinese National Knowledge Infrastructure and Wanfang databases, while the terms "diclofenac" and "knee osteoarthritis" were employed to search Web of Science, Embase, Cochrane Library and PubMed. Two assessors independently evaluated the quality of the included articles using the Cochrane scoring system. Extraction of data from the selected studies was performed, and the effect of diclofenac sodium was quantified through meta-analysis with RevMan 5.3. Following the process of literature search, selection, and quality assessment, a total of 8 studies were identified as suitable for incorporation in the meta-analysis. The meta-analysis results indicated that participants in the diclofenac sodium experimental group experienced significant enhancements in Western Ontario and McMaster universities osteoarthritis index pain, physical function, and stiffness scores, surpassing those of the control group. Furthermore, the experimental group displayed a superior treatment efficacy. According to the meta-analysis results, the diclofenac sodium experimental group demonstrated a higher occurrence of gastrointestinal adverse events than the control group. In opposition, no significant discrepancy was detected in the occurrence of skin and other adverse events between the two groups. This meta-analysis conclusively established that diclofenac sodium exerts statistically significant effects on pain, physical function, and stiffness improvement in elderly patients suffering from knee osteoarthritis. Taking into account the results of this meta-analysis and systematic review, diclofenac sodium can be recommended as a primary non-surgical treatment option for knee osteoarthritis in elderly individuals. Nonetheless, healthcare professionals should closely monitor and manage the occurrence of
Evaluation of the cyber security models implemented across common attack vectors: A review of literature

Cybersecurity is an organizational issue that should be looked at through the lens of various stakeholders. However, it is often treated as a siloed issue in which more is always seen as better. The CISOs, CIOs, and the key decision-makers struggle to understand how much security is enough. Cybersecurity solutions, referred to as controls, more often than not result in a residual risk. To assess this risk better, the security controls should be studied in further detail. The objective of this paper is to educate the audience with the various cyber security controls being used in the academia and in the industry. In order to circumvent the security issues faced by large organization, the tradeoffs of each controls should be studied further. The paper is meant to provide a balanced view providing the positive and the critical aspect of implementing some of the known security solutions. There is no one perfect formula when it comes to selecting security controls. However, picking a security control that are in line with the users’ needs will help reduce some of the risks associated with implementing the controls. An optimal solution requires a balanced approach towards the risk, cost, and benefit of the solution. The aim of the paper is to help the reader assess some of risks and the tradeoff associated with the security controls being practiced in the industry today.
Assessing the Drought Vulnerability of Alberta: A Deep Learning Approach for Hydro-Climatological Analysis

: This study investigates the vulnerability of Alberta province in Canada to extreme weather events, particularly drought, which has historically caused significant financial losses. Accurate simulating techniques are crucial for obtaining reliable results to identify trends and patterns in Alberta climatology. In this study, 4-monthly synoptic station data spanning 35 years (1979 to 2014) are used alongside Long Short-Term Memory (LSTM) to analyze patterns of precipitation. Additionally, the Standardized Precipitation Index (SPI) is used to identify drought severity at different time scales (3, 6, and 12 months). The results demonstrate that drought occurrences have been observed in the Southern part of Alberta, with rising tendencies in larger areas, such as Calgary agricultural areas, being prone to severe drought.
JOB SATISFACTION AND TURNOVER INTENTION OF BLUD WORKERS AT TROSOBO PUBLIC PRIMARY HEALTH CARE

Job satisfaction is defined as a person's attitude or emotional response toward their job duties. Poor job satisfaction leads to turnover. Trosobo public primary health care staffing data showed a high turnover intention of BLUD workers. This study aims to determine the job satisfaction and turnover intention of BLUD worker at the Trosobo public primary health care. This study was quantitative study with a cross-sectional design. The research was conducted in November 2023 at Trosobo public primary care. Eleven BLUD workers were obtained using total sampling calculations. Data analyzed descriptively. The instruments used in this study were MSQ and TIS-6. The lowest average satisfaction score was recognition (43.64) and the highest were authority and achievement (80,00). Job satisfaction of BLUD workers was in the moderate category (score 26-74) and the turnover intention was in the high category (score >15). Trosobo public primary health care BLUD workers had a moderate category of job satisfaction and high turnover intention. Providing services based on workload and length of service, as well as opportunities for career development to BLUD workers, can be carried out by the Trosobo public primary health care as an effort to reduce the turnover problem
A single bout of discontinuous exercise as a pragmatic approach to augment glycaemic control in pregnancy: a pilot study

x ACKNOWLEGEMENTS . xii PUBLICATIONS . xiii 1. CHAPTER ONE: INTRODUCTION 14 THE ROLE OF ACUTE EXERCISE IN ENHANCING GLYCAEMIC CONTROL IN PREGNANCY . 15 1.1 AIMS AND HYPOTHESES . 18 2. CHAPTER TWO: REVIEW OF THE RELATED LITERATURE 20 2.1 METABOLIC CHANGES IN HUMAN PREGNANCY . 21 2.1.1 IMPORTANCE OF GLYCAEMIC CONTROL . 22 2.2 EXERCISE RECOMMENDATIONS, BELIEFS AND BARRIERS IN PREGNANCY . 23 2.2.1 EXERCISE ROLE IN ADDRESSING MATERNAL METABOLIC DYSFUNCTION . 24 2.3 EXERCISE –A POTENT STIMULUS FOR GLYCAEMIC CONTROL . 26 2.3. 1WHAT DOSE OF EXERCISE IS NEEDED? 27 2.3. 2 CONTINUOUS OR INTERVAL TRAINING FOR GLYCAEMIC CONTROL? 28
Ground Simultaneous Measurements and Analysis of Radiometric Characterization of Dunhuang Test Site for Calibrating CBERS-1 Sensors

The Dunhuang test site is situated in the northwest corner of the Gobi desert near the city of Dunhuang. The calibration area is (400×400)m 2 and situated in the centre of a relative homogeneous and flat zone of (30×40)km 2. During August to September, 2000, China Center for Resources Satellite Data and Application (CRESDA) conducted a field measurement campaign for determining the characteristics of the ground reflectance and of the atmosphere. The results show that the test site has a very good homogeneity with a variation coefficient of the reflectance in any channel lower than 3%. The ground reflectance increases progressively from 0.18 at 485 nm to 0.26 at 830 nm. Atmospheric measurements show that at 0.55 μm the total atmospheric optical depth (about 0.34) and the aerosol optical depth (about 0.26) are relatively low and the effect of atmospheric water vapour content is also relatively small. These preliminary results show that the selected test site is well adapted to the absolute radiometric calibiration of in-flight satellite sensors such as CBERS-1 CCD.