Miracle-dz/UniFAR-FTUs huggingface dataset:
The Prodigious Need for Fueling South Asian Economies through Sustainable Energies

South Asia is one of the fastest growing regions in the world during the last two decades. This growth momentum has been fuelled by carbon-intensive fossil fuels as reflected through the expansion in fossil fuel utilization in the total energy mix of 60.5 per cent on average for the period 1996-2000 to 70.3 per cent by 2011-2015. Against this backdrop, the study intended to identify the relationship between energy consumption and economic growth in South Asia to recognize the feasibility of promoting low-carbon economic progress in the future. The study employed annual data for the period from 1971-2014 for five selected South Asian countries. The unit root test results indicate that all the variables are stationary at their first difference and the four statistics of the Pedroni cointegration test indicate the existence of a long-run relationship between the variables. The FMOLS estimator implies the significance of the energy consumption in economic growth in the region where one per cent increase in energy consumption leads to a 0.78 per cent increase in economic growth. The study finds a strong bi-directional relationship between the core variables which illustrates the necessity to shift towards sustainable energy sources to achieve an undisrupted economic expansion with a minimum carbon footprint. Thus, the study lays the foundations to identify the aforementioned relationships and encourage the derive of sustainable energy solutions to fuel the growth in the region.
The Impact of Different Forcing Agents on the Residual Circulation in a Tropical Estuary (Baía de Todos os Santos, Brazil)

ABSTRACT Santana, R. ; Teixeira, C. , and Lessa, G. , 2018. The impact of different forcing agents on the residual circulation in a tropical estuary (Baía de Todos os Santos, Brazil). This study investigated the forcing of the residual circulation in a tropical estuary, Baía de Todos os Santos, Brazil (BTS). A numerical model (Regional Ocean Modeling System), forced with climatological means, was used to investigate the seasonal roles of the tide, wind, net heat, surface water fluxes, and river discharge on the residual circulation. The tide is the main driver of the circulation and its residual flow is structured at the bay mouth with a net-landward flow in the channel center and a net-seaward flow on the shoulders. The addition of wind drag affected the surface circulation, forcing W-bound (N-bound) currents in the spring–summer (fall–winter) months and generating a positive sea-level slope toward the continent. The addition of heat and surface water fluxes to the simulation established an incipient gravitational circulation, mainly because of the large (approximately 0.2°C/km) temperature gradients in the summer. The river discharge, added last, was second to the tide in driving the residual circulation in the BTS and established the gravitational circulation through most of the bay, including the bay mouth. The residual velocities attained magnitudes smaller than 0.13 ms−1 in the main channel and were seasonally controlled, with stronger currents during the summer when the river discharge peaked. The onset of the baroclinic forcing (heat and surface water fluxes plus river discharge) reduced the e-folding flushing time by a factor of five relative to the experiment with barotropic forcing (wind and tides) only.
Platelet-Activating Factor Receptor (PAFR) Regulates Retinal Progenitor/Stem Cells Profile in Ciliary Epithelium Cells

The retina is a central nervous tissue essential to visual perception and highly susceptible to environmental damage. Lower vertebrate retinas activate intrinsic regeneration mechanisms in response to retinal injury regulated by a specialized population of progenitor cells. The mammalian retina does not have populations of progenitor/stem cells available to activate regeneration, but contains a subpopulation of differentiated cells that can be reprogrammed into retinal stem cells, the ciliary epithelium (CE) cells. Despite the regenerative potential, stem cells derived from CE exhibit limited reprogramming capacity probably associated with the expression of intrinsic regulatory mechanisms. Platelet-activating factor (PAF) is a lipid mediator widely expressed in many cells and plays an important role in stem cell proliferation and differentiation. During mammalian development, PAF receptor signaling showed important effects on retinal progenitors’ cell cycle regulation and neuronal differentiation that need to be further investigated. In this study, our findings suggested a dynamic role for PAF receptor signaling in CE cells, impacting stem cell characteristics and neurosphere formation. We showed that PAF receptors and PAF-related enzymes are downregulated in retinal progenitor/stem cells derived from PE cells. Blocking PAFR activity using antagonists increased the expression of specific progenitor markers, revealing potential implications for retinal tissue development and maintenance.
Low-Light Mine Image Enhancement Algorithm Based on Improved Retinex

Aiming at solving the problems of local halo blurring, insufficient edge detail preservation, and serious noise in traditional image enhancement algorithms, an improved Retinex algorithm for low-light mine image enhancement is proposed. Firstly, in HSV color space, the hue component remains unmodified, and the improved multi-scale guided filtering and Retinex algorithm are combined to estimate the illumination and reflection components from the brightness component. Secondly, the illumination component is equalized using the Weber–Fechner law, and the contrast limited adaptive histogram equalization (CLAHE) is fused with the improved guided filtering for the brightness enhancement and denoising of reflection component. Then, the saturation component is adaptively stretched. Finally, it is converted back to RGB space to obtain the enhanced image. By comparing with single-scale Retinex (SSR) algorithm and multi-scale Retinex (MSR) algorithm, the mean, standard deviation, information entropy, average gradient, peak signal-to-noise ratio (PSNR), and structural similarity (SSIM) are improved by an average of 50.55%, 19.32%, 3.08%, 28.34%, 29.10%, and 22.97%. The experimental dates demonstrate that the algorithm improves image brightness, prevents halo artifacts while retaining edge details, reduces the effect of noise, and provides some theoretical references for low-light image enhancement.
Quantitative susceptibility mapping for iron monitoring of multiple subcortical nuclei in type 2 diabetes mellitus: a systematic review and meta-analysis

Introduction Iron accumulation in the brain has been linked to diabetes, but its role in subcortical structures involved in motor and cognitive functions remains unclear. Quantitative susceptibility mapping (QSM) allows the non-invasive quantification of iron deposition in the brain. This systematic review and meta-analysis examined magnetic susceptibility measured by QSM in the subcortical nuclei of patients with type 2 diabetes mellitus (T2DM) compared with controls. Methods PubMed, Scopus, and Web of Science databases were systematically searched [following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines] for studies reporting QSM values in the deep gray matter (DGM) regions of patients with T2DM and controls. Pooled standardized mean differences (SMDs) for susceptibility were calculated using fixed-effects meta-analysis models, and heterogeneity was assessed using I2. Sensitivity analyses were conducted, and publication bias was evaluated using Begg’s and Egger’s tests. Results Six studies including 192 patients with T2DM and 245 controls were included. This study found a significant increase in iron deposition in the subcortical nuclei of patients with T2DM compared to the control group. The study found moderate increases in the putamen (SMD = 0.53, 95% CI 0.33 to 0.72, p = 0.00) and dentate nucleus (SMD = 0.56, 95% CI 0.27 to 0.85, p = 0.00) but weak associations between increased iron levels in the caudate nucleus (SMD = 0.32, 95% CI 0.13 to 0.52, p = 0.00) and red nucleus (SMD = 0.22, 95% CI 0.00 0.44, p = 0.05). No statistical significance was found for iron deposition alterations in the globus pallidus (SMD = 0.19; 95% CI −0.01 to 0.38; p = 0.06) and substantia nigra (SMD = 0.12, 95% CI −0.10, 0.34, p = 0.29). Sensitivity analysis showed that the findings remained unaffected by individual studies, and consistent increases were observed in multiple subcortical areas. Discussion QSM revealed an increase in iron in the DGM/subcortical nuclei in T2DM patients versus controls, particularly in the motor and cognitive nuclei, including the putamen, dentate nucleus, caudate nucleus, and red nucleus. Thus, QSM may serve as a potential biomarker for iron accumulation in T2DM patients. However, further research is needed to validate these findings.
Titanium nitride-based hyperbolic metamaterial for near-infrared ultrasensitive sensing of microbes.

We demonstrate an ultrasensitive microbe sensor for the first time using a titanium nitride (TiN) nanowire-based hyperbolic metamaterial (HMM) structure. We detected the change in the resonance wavelength shift due to the inclusion of microbes in a freshwater environment employing the finite-difference time-domain (FDTD) method. Our proposed HMM sensor exhibits strong bulk plasmon polariton (BPP) modes in the anisotropic hyperbolic regime (λ ≥ 590 nm) and operates in the near-infrared (NIR) wavelength region. We studied the impact of structural parameters on the resonance wavelength shift, where our proposed HMM sensor structure exhibited an outstanding sensing capability of 11 nm per bacteria. A limit of detection of 0.00008 RIU was achieved for our proposed HMM sensor structure. Additionally, we verified our results theoretically to calculate mode frequency shift by solving the effective medium theory (EMT). Our study revealed that HMM is the origin of highly sensitive BPP modes. We obtained two BPP modes, where the BPP mode at a longer wavelength (q = 1) exhibited the highest resonance wavelength shift compared to the BPP mode at a shorter wavelength (q = 2). More importantly, we demonstrated numerically the point-detection capability of our proposed HMM microbe sensor structure, which was unattainable in previously reported sensor work. Moreover, this sensor can be adapted to detect different viruses and bacteria. Our proposed TiN-based HMM structure can potentially be an ultrasensitive and straightforward microbe sensor for label-free detection.
The Effect of Coordination Capability on Knowledge Transfer: The Moderating Role of Learning Orientation

Previous article has considered antecedents in the knowledge transfer process; however, these articles assume that knowledge does not update all the time in firms. Therefore, based on transactive memory systems (TMSs) theory, this article tests the effect of different dimensions of coordination capability on knowledge transfer, and the important role of learning orientation. Through 232 surveys, this article explores the direct effect of coordination capability on knowledge transfer and learning orientation as a moderator of these relationships. The empirical results show that job rotation, cross-functional interfaces, and decision participation have positive effects on knowledge transfer. And learning orientation moderates the relationship between job rotation, cross-functional interfaces, decision participation, and knowledge transfer, respectively. The results will give some helpful suggestions for Chinese firms. To transfer internal knowledge effectively, firms should stress the role of job rotation, cross-functional interfaces, and decision participation, and cultivate organization culture which makes firms have a good learning environment.
Evaluating Opt-In Vaginal Human Papillomavirus Self-Sampling: Participation Rates and Detection of High-Grade Lesions (CIN2+) among Unscreened Japanese Women Aged 30–39

Cervical cancer incidence is increasing among Japanese women, which is partly attributed to low screening rates. This study examined the implementation of opt-in human papillomavirus (HPV) self-sampling among Japanese women aged 30–39 years who had not undergone cervical cancer screening, focusing on those requiring preconception care. The responses to the opt-in approach and effectiveness in detecting cervical squamous intraepithelial neoplasia 2 or worse (CIN2+) were evaluated. Participants used the Evalyn® Brush for self-sampling, with HPV testing conducted using the Cobas 4800 system (version 2.2.0). Out of 3489 eligible, unscreened women from four municipalities in Fukui Prefecture, only 10.6% (370/3489) requested the self-sampling kit. Of these, 77.3% (286/370) returned the kit (HPV testing rate: 8.2% (286/3489)). The HPV positivity rate was 13.7% (39/285), yet only 61.5% (24/39) of those with positive HPV results proceeded to cytology testing. Subsequently, three cases of CIN2+ were detected (10.5/1000). While this study demonstrated a reasonable kit return rate and indicated the capability of opt-in HPV self-sampling to detect CIN2+ cases in unscreened women, the low ordering rate of kits and suboptimal compliance for follow-up cytology testing highlight significant challenges. The findings suggest the need for more effective strategies to enhance participation in cervical cancer screening programs.
Seasonal and interannual variability of land–atmosphere coupling across the Southern Great Plains of North America using the North American regional reanalysis

The purpose of this study was to investigate the seasonal to interannual variability of the temporal and spatial distributions of land–atmosphere coupling (LAC) at the mesoscale within the Southern Great Plains (SGP) of the United States. The North American Regional Reanalysis data set from 1979 to 2014 was used to complete this study. To further expand the relationship between soil moisture and precipitation, LAC was examined for the effects of soil moisture variability on latent heat flux (SM‐E) and the impact of latent heat flux variability on precipitation (E‐P). Results revealed that within the SGP there is a temporal and spatial seasonal evolution of the SM‐E relationship and dry boreal summer month (June, July and August, JJA) periods exhibit a stronger E‐P relationship relative to pluvial boreal summer month periods. Further, the variability of coupling was large both within‐season (i.e. JJA) as well as at the interannual scale while the interannual spatial and temporal coherence was such that no specific locations showed consistent coupling within the domain. Thus, the results indicate that while the SGP domain is sensitive to coupling, the location of preferred coupling is likely due to non‐local factors at the mesoscale embedded within synoptic conditions as well as the regional climate.
Leveraging Artificial Intelligence to Predict Health Belief Model and COVID-19 Vaccine Uptake Using Survey Text from US Nurses

We investigated how artificial intelligence (AI) reveals factors shaping COVID-19 vaccine hesitancy among healthcare providers by examining their open-text comments. We conducted a longitudinal survey starting in Spring of 2020 with 38,788 current and former female nurses in three national cohorts to assess how the pandemic has affected their livelihood. In January and March–April 2021 surveys, participants were invited to contribute open-text comments and answer specific questions about COVID-19 vaccine uptake. A closed-ended question in the survey identified vaccine-hesitant (VH) participants who either had no intention or were unsure of receiving a COVID-19 vaccine. We collected 1970 comments from VH participants and trained two machine learning (ML) algorithms to identify behavioral factors related to VH. The first predictive model classified each comment into one of three health belief model (HBM) constructs (barriers, severity, and susceptibility) related to adopting disease prevention activities. The second predictive model used the words in January comments to predict the vaccine status of VH in March–April 2021; vaccine status was correctly predicted 89% of the time. Our results showed that 35% of VH participants cited barriers, 17% severity, and 7% susceptibility to receiving a COVID-19 vaccine. Out of the HBM constructs, the VH participants citing a barrier, such as allergic reactions and side effects, had the most associated change in vaccine status from VH to later receiving a vaccine.
A Proposal for a Tokenized Intelligent System: A Prediction for an AI-Based Scheduling, Secured Using Blockchain

Intelligent systems are being proposed every day as advances in cloud systems are increasing. Mostly, the services offered by these cloud systems are dependent only on their providers, without the inclusion of services from other providers, specialized third parties, or individuals. This ‘vendor lock-in’ issue and the limitations related to offering tailored services could be resolved by allowing multiple providers or individuals to collaborate through intelligent task scheduling. To address such real-world systems’ limitations in provisioning and executing heterogeneous services, we employed Blockchain and Deep Reinforcement Learning here; the first is used for the token-based secured communication between parties, and the latter is to predict the appropriate task scheduling; hence, we guarantee the quality of not only the immediate decision but also the long-term. The empirical results show a high reward achieved, meaning that it accurately selected the candidates and adaptably assigned the tasks based on job nature and executors’ individual computing capabilities, with 95 s less than the baseline in job completion time to maintain the Quality of Service. The successful collaboration between parties in this tokenized system while securing transactions through Blockchain and predicting the right scheduling of tasks makes it a promising intelligent system for advanced use cases.
Development and application of the overseas exchange willingness and demand survey questionnaire for medical students

There has been a significant increase in international student exchange in recent years, with medical students comprising a large proportion of international students. This study aimed to develop and validate a questionnaire, the Medical Student Overseas Exchange Willingness and Demand Survey Questionnaire (MS-OEWDSQ), to assess medical students’ intentions to study abroad and explore the potential influencing factors.This study was conducted in three stages: item generation and scale development; pilot study; and examination of scale reliability and validity. The item pool for the questionnaire was compiled from a literature review, an assessment of other relevant questionnaires, and interviews with medical students. Descriptive statistics were generated, and correlation analysis was performed to analyze the questionnaire data. The reliability of the measure was examined according to its internal consistency and split-half reliability. Exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) were used to determine the factor structure and test the construct validity.The final version of the MS-OEWDSQ comprised three factors with a total of 14 items. The total Cronbach’s α coefficient of the questionnaire was 0.844, and the total split-half reliability coefficient was 0.639. This study also identified several factors that may affect medical students’ willingness to go abroad for exchange. Specifically, education (p < 0.05) and foreign language level (p < 0.05) were associated with the MS-OEWDSQ score, providing directions for future related research.This study developed and validated a questionnaire to measure medical students’ willingness and demand for overseas exchange. This measure provides a powerful tool for evaluating whether medical students are willing to participate in overseas exchange. The questionnaire can be employed to help medical students self-test their intention to study abroad and to help medical colleges provide more accurate support and assistance to students who intend to study abroad.
Nitrogen and Microelements Co-Drive the Decomposition of Typical Grass Litter in the Loess Plateau, China

In grassland ecosystems, the decomposition of litter serves as a vital conduit for nutrient transfer between plants and soil. The aim of this study was to depict the dynamic process of grass litter decomposition and explore its major driver. Three typical grasses [Stipa bungeana Trin (St. B), Artemisia sacrorun Ledeb (Ar. S), and Thymus mongolicus Ronniger (Th. M)] were selected for long-term litter decomposition. Experiments were conducted using three single litters, namely, St. B, Ar. S, and Th. M, and four different compositions of mixed litter: ML1 (55% St. B and 45% Th. M), ML2 (55% St. B and 45% Ar. S), ML3 (75% St. B and 25% Th. M), and ML4 (75% St. B and 25% Ar. S). The dynamic patterns of mass and microelements (Ca, Mg, Fe, Mn, Cu, and Zn) within different litter groups were analyzed. Our findings indicated that, after 1035 days of decomposition, the proportion of residual mass for the single litters was as follows: Th. M (60.6%) > St. B (47.3%) > Ar. S (44.3%), and for the mixed groups it was ML1 (48.0%) > ML3 (41.6%) > ML2 (40.9) > ML4 (38.4%). Mixed cultivation of the different litter groups accelerated the decomposition process, indicating that the mixture of litters had a synergistic effect on litter decomposition. The microelements of the litter exhibited an initial short-term increase followed by long-term decay. After 1035 days of decomposition, the microelements released from the litter were, in descending order, Mg > Ca > Fe > Cu > Mn > Zn. Compared to the separately decomposed St. B litter, mixing led to an inhibition of the release of Ca (antagonistic effect), while it promoted the release of Mg, Cu, and Zn (synergistic effect). For the single litter, the stepwise regression analysis showed that Ca was the dominant factor determining early litter decomposition. Mg, Mn, and Cu were the dominant factors regulating later litter decomposition. For the mixed litter groups, Ca, Mn, and Mg were the dominant factors closely related to early decomposition, and TN emerged as a key factor regulating the mass loss of mixtures during later decomposition. In summary, nitrogen and microelements co-drive the decomposition of typical grass litter. Our study underscores that, in the succession process of grassland, the presence of multiple co-existing species led to a faster loss of plant-derived materials (litter mass and internal elements), which was primarily modulated by species identity and uniformity.