Miracle-dz/UniFAR-FTUs huggingface dataset:
Validating the Arabic version of the Connor-Davidson resilience scale among university students

Background The Connor-Davidson Resilience Scale (CD-RISC) stands out as a widely used measure of psychological resilience. The original CD-RISC consists of 25 items, commonly referred to as CD-RISC-25. Aim This study aims to validate the Arabic version of the CD-RISC-25 involving a sample size of 1220 participants from three universities in Jordan. Methods The researcher conducted a methodological investigation to examine the validation process. This included an examination of the translation process and an evaluation of content validity, which was assessed using the content validity index (CVI). Construct validity was assessed through exploratory factor analysis and confirmatory factor analysis, while convergent and discriminant validity were both evaluated using composite reliability (CR) and the square root of the average variance extracted. Results Results showed a prominent level of psychological resilience 76.74±15.2 among the participating university students. Regarding the validity of the Arabic version of CD-RISC-25, the CVI yielded a value of 0.88, signifying a robust level of content validity. The analysis identified four constructs that accounted for 56.26% of the total variance. The goodness-of-fit indices, including goodness of fit index of 0.91, comparative fit index of 0.91, incremental fit index of 0.93, Tucker-Lewis index of 0.94, and root mean square error of approximation of 0.048, provided strong evidence supporting the alignment between the observed data and the hypothesized constructs. Discriminant and convergent validity were found to support the validity of the Arabic version of CD-RISC-25. Regarding the reliability, it demonstrated excellent reliability, with a total Cronbach’s alpha of 0.934 and all CR values surpassing the threshold of 0.70, thereby further establishing its overall robustness. Conclusion The results provide substantial evidence for the validity and reliability of the translated Arabic CD-RISC-25.
Rhythmic temporal prediction enhances neural representations of movement intention for brain–computer interface

Objective. Detecting movement intention is a typical use of brain–computer interfaces (BCI). However, as an endogenous electroencephalography (EEG) feature, the neural representation of movement is insufficient for improving motor-based BCI. This study aimed to develop a new movement augmentation BCI encoding paradigm by incorporating the cognitive function of rhythmic temporal prediction, and test the feasibility of this new paradigm in optimizing detections of movement intention. Methods. A visual-motion synchronization task was designed with two movement intentions (left vs. right) and three rhythmic temporal prediction conditions (1000 ms vs. 1500 ms vs. no temporal prediction). Behavioural and EEG data of 24 healthy participants were recorded. Event-related potentials (ERPs), event-related spectral perturbation induced by left- and right-finger movements, the common spatial pattern (CSP) and support vector machine, Riemann tangent space algorithm and logistic regression were used and compared across the three temporal prediction conditions, aiming to test the impact of temporal prediction on movement detection. Results. Behavioural results showed significantly smaller deviation time for 1000 ms and 1500 ms conditions. ERP analyses revealed 1000 ms and 1500 ms conditions led to rhythmic oscillations with a time lag in contralateral and ipsilateral areas of movement. Compared with no temporal prediction, 1000 ms condition exhibited greater beta event-related desynchronization (ERD) lateralization in motor area (P< 0.001) and larger beta ERD in frontal area (P< 0.001). 1000 ms condition achieved an averaged left–right decoding accuracy of 89.71% using CSP and 97.30% using Riemann tangent space, both significantly higher than no temporal prediction. Moreover, movement and temporal information can be decoded simultaneously, achieving 88.51% four-classification accuracy. Significance. The results not only confirm the effectiveness of rhythmic temporal prediction in enhancing detection ability of motor-based BCI, but also highlight the dual encodings of movement and temporal information within a single BCI paradigm, which is promising to expand the range of intentions that can be decoded by the BCI.
Single-cell profiling coupled with lineage analysis reveals vagal and sacral neural crest contributions to the developing enteric nervous system

During development, much of the enteric nervous system (ENS) arises from the vagal neural crest that emerges from the caudal hindbrain and colonizes the entire gastrointestinal tract. However, a second ENS contribution comes from the sacral neural crest that arises in the caudal neural tube and populates the post-umbilical gut. By coupling single-cell transcriptomics with axial-level-specific lineage tracing in avian embryos, we compared the contributions of embryonic vagal and sacral neural crest cells to the chick ENS and the associated peripheral ganglia (Nerve of Remak and pelvic plexuses). At embryonic day (E) 10, the two neural crest populations form overlapping subsets of neuronal and glia cell types. Surprisingly, the post-umbilical vagal neural crest much more closely resembles the sacral neural crest than the pre-umbilical vagal neural crest. However, some differences in cluster types were noted between vagal and sacral derived cells. Notably, RNA trajectory analysis suggests that the vagal neural crest maintains a neuronal/glial progenitor pool, whereas this cluster is depleted in the E10 sacral neural crest which instead has numerous enteric glia. The present findings reveal sacral neural crest contributions to the hindgut and associated peripheral ganglia and highlight the potential influence of the local environment and/or developmental timing in differentiation of neural crest-derived cells in the developing ENS.
Wasserstein HOG: Local Directionality Extraction via Optimal Transport

Directionally sensitive radiomic features including the histogram of oriented gradient (HOG) have been shown to provide objective and quantitative measures for predicting disease outcomes in multiple cancers. However, radiomic features are sensitive to imaging variabilities including acquisition differences, imaging artifacts and noise, making them impractical for using in the clinic to inform patient care. We treat the problem of extracting robust local directionality features by mapping via optimal transport a given local image patch to an iso-intense patch of its mean. We decompose the transport map into sub-work costs each transporting in different directions. To test our approach, we evaluated the ability of the proposed approach to quantify tumor heterogeneity from magnetic resonance imaging (MRI) scans of brain glioblastoma multiforme, computed tomography (CT) scans of head and neck squamous cell carcinoma as well as longitudinal CT scans in lung cancer patients treated with immunotherapy. By considering the entropy difference of the extracted local directionality within tumor regions, we found that patients with higher entropy in their images, had significantly worse overall survival for all three datasets, which indicates that tumors that have images exhibiting flows in many directions may be more malignant. This may seem to reflect high tumor histologic grade or disorganization. Furthermore, by comparing the changes in entropy longitudinally using two imaging time points, we found patients with reduction in entropy from baseline CT are associated with longer overall survival (hazard ratio = 1.95, 95% confidence interval of 1.4-2.8, ${p}$ = 1.65e-5). The proposed method provides a robust, training free approach to quantify the local directionality contained in images.
Predicting enzymatic function of protein sequences with attention

Abstract Motivation There is a growing number of available protein sequences, but only a limited amount has been manually annotated. For example, only 0.25% of all entries of UniProtKB are reviewed by human annotators. Further developing automatic tools to infer protein function from sequence alone can alleviate part of this gap. In this article, we investigate the potential of Transformer deep neural networks on a specific case of functional sequence annotation: the prediction of enzymatic classes. Results We show that our EnzBert transformer models, trained to predict Enzyme Commission (EC) numbers by specialization of a protein language model, outperforms state-of-the-art tools for monofunctional enzyme class prediction based on sequences only. Accuracy is improved from 84% to 95% on the prediction of EC numbers at level two on the EC40 benchmark. To evaluate the prediction quality at level four, the most detailed level of EC numbers, we built two new time-based benchmarks for comparison with state-of-the-art methods ECPred and DeepEC: the macro-F1 score is respectively improved from 41% to 54% and from 20% to 26%. Finally, we also show that using a simple combination of attention maps is on par with, or better than, other classical interpretability methods on the EC prediction task. More specifically, important residues identified by attention maps tend to correspond to known catalytic sites. Quantitatively, we report a max F-Gain score of 96.05%, while classical interpretability methods reach 91.44% at best. Availability and implementation Source code and datasets are respectively available at https://gitlab.inria. fr/nbuton/tfpc and https://doi.org/10.5281/zenodo.7253910
Indication for total knee arthroplasty based on preoperative functional score: Are we operating earlier?

Background: The number of total knee arthroplasty (TKA) procedures performed annually is increasing for reasons not fully explained by population growth and increasing rates of obesity. The purpose of this study was to determine the role of patient functional status as an indication for surgery and to determine if patients are undergoing surgery with a higher level of preoperative function than in the past. Methods: A systematic review and meta-analysis of the MEDLINE, Embase and Cochrane databases was performed in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Functional status was assessed using the 36-Item Short Form Health Survey’s physical component summary (PCS) score. Only primary procedures were included. Articles were screened by 2 independent reviewers, with conflicts resolved with a third reviewer. Meta-regression analysis was performed to determine the effect of time, age and sex on preoperative PCS score. Subgroup analysis was performed to compare results for the United States with those for the rest of the world. Results: A total of 1502 articles were identified, of which 149 were included in the study. Data from 257 independent groups including 57 844 patients recruited from 1991 to 2015 were analyzed. The mean preoperative PCS score was 31.1 (95% confidence interval 30.6–31.7) with a 95% prediction interval of 22.8–39.5. The variance across studies was found to be significant (p < 0.001) with 99.01% true variance. Year of enrolment, age, the percentage of female patients and geographic region did not have any significant effect on preoperative PCS score. Conclusion: Patients are undergoing TKA with a level of preoperative function similar to their level of function in the past. Patient age, sex and location did not influence the functional status at which patients were considered to be candidates for surgery.
Improving interfacial shear strength of fique fibres using an acrylic coating

Natural fibres have proven to be a potential alternative to replace synthetic fibres in some composite materials applications. However, drawbacks such as impregnation difficulties and the poor fibre–matrix interface limit the use of natural fibres in high-performance applications. This work proposes using an acrylic resin to coat the fibre surface to enhance the interfacial compatibility among fique fibres and polyester resin. Pull-out tests revealed an improvement in the interfacial shear strength of about 110% for coated fibres. Furthermore, nanoindentation test, Micro Raman spectroscopy and scanning electronic microscopy indicated that the acrylic resin eliminates the gap at the fibre/matrix interface seen in the uncoated fibres. Observed behaviour could be attributed to a better chemical bonding between the fibre and matrix and is also hypothesised that the elastic characteristic of the coating helps to transfer loads effectively from the matrix to the fibre.
Method for landmark extraction for autonomous vision based navigation of UAVs

Autonomous navigation of Unmanned Aerial System (UAS) has been achieved with active sensor systems and the Global Positioning System (GPS). These systems are vulnerable to jamming. Passive methods such as vision are considered to be a promising alternative. Vision based systems have operational limitations at night and other invisible periods such as foggy/ cloudy conditions. Even in the presence of sunlight it has to deal with various atmospheric/ environmental conditions. We present an algorithm to address vision based navigation during varying atmospheric/environmental conditions. Our algorithm is tested in synthetic as well as real world environments demonstrating good performance.
Framing an Indigenous Food Sovereignty Research Agenda

Access to healthy and appealing food is essential for individuals to be able to live a healthy and quality life. For decades, food security has been a priority issue for public health professionals. Food sovereignty expands upon the concept of food insecurity (i.e., having access to nutritious and culturally relevant food) by incorporating people’s rights to define their own food system. The expanded focus of food sovereignty on food systems prioritizes public health professionals’ role in supporting environmental- and systems-level initiatives and evaluating their implications for health, economics, and the natural environment. Food sovereignty is of particular importance for Indigenous peoples (i.e., American Indian, Alaska Native, Native Hawaiian, and Pacific Islander communities). Colonization had demonstrable consequences, with many Indigenous communities being forcibly relocated from traditional lands, alongside the destruction of traditional food sources. Indigenous food sovereignty aligns with the sovereign nation status that American Indian tribes and Alaska Native communities have with the United States. Furthermore, the worldviews that incorporate Indigenous communities’ relational responsibilities to care for their food systems, according to their traditional practices and beliefs (Coté, 2016; Morrison, 2011), uniquely positions Indigenous peoples to lead food sovereignty initiatives. In this article, we explore what is currently known regarding food sovereignty and health. We then discuss opportunities to expand the evidence on Indigenous food sovereignty’s relationships with (1) health and well being, (2) economics, (3) the natural environment, and (4) programming facilitators and barriers.
Functional knockout of the TRPV1 channel has no effect on the exercise pressor reflex in rats

The role played by the transient receptor potential vanilloid 1 (TRPV1) channel on the thin fibre afferents evoking the exercise pressor reflex is controversial. To shed light on this controversy, we compared the exercise pressor reflex between newly developed TRPV1+/+, TRPV1+/− and TRPV1−/− rats. Carotid arterial injection of capsaicin (0.5 μg), evoked significant pressor responses in TRPV1+/+ and TRPV1+/− rats, but not in TRPV1−/− rats. In acutely isolated dorsal root ganglion neurons innervating the gastrocnemius muscles, capsaicin evoked inward currents in neurons isolated from TRPV1+/+ and TRPV1+/− rats but not in neurons isolated from TRPV1−/− rats. The reflex was evoked by stimulating the tibial nerve in decerebrated rats whose femoral artery was either freely perfused or occluded. We found no difference between the reflex in the three groups of rats regardless of the patency of the femoral artery. For example, the peak pressor responses to contraction in TRPV1+/+, TRPV1+/− and TRPV1−/− rats with patent femoral arteries averaged 17.1 ± 7.2, 18.9 ± 12.4 and 18.4 ± 8.6 mmHg, respectively. Stimulation of the tibial nerve after paralysis with pancuronium had no effect on arterial pressure, findings which indicated that the pressor responses to contraction were not caused by electrical stimulation of afferent tibial nerve axons. We also found that expression levels of acid‐sensing ion channel 1 and endoperoxide 4 receptor in the L4 and 5 dorsal root ganglia were not upregulated in the TRPV1−/− rats. We conclude that TRPV1 is not needed to evoke the exercise pressor reflex in rats whose contracting muscles have either a patent or an occluded arterial blood supply.
A survival prediction model based on PCA-HSIDA-LSSVM for patients with esophageal squamous cell carcinoma

Esophageal squamous cell carcinoma (ESCC) is a type of cancer and has some of the highest rates of both incidence and mortality globally. Developing accurate models for survival prediction provides a basis clinical judgment and decision making, improving the survival status of ESCC patients. Although many predictive models have been developed, there is still lack of highly accurate survival prediction models for ESCC patients. This study proposes a novel survival prediction model for ESCC patients based on principal component analysis (PCA) and least-squares support vector machine (LSSVM) optimized by an improved dragonfly algorithm with hybrid strategy (HSIDA). The original 17 blood indicators are condensed into five new variables by PCA, reducing data dimensionality and redundancy. An improved dragonfly algorithm based on hybrid strategy is proposed, which addresses the limitations of dragonfly algorithm, such as slow convergence, low search accuracy and insufficient vitality of late search. The proposed HSIDA is used to optimize the regularization parameter and kernel parameter of LSSVM, improving the prediction accuracy of the model. The proposed model is validated on the dataset of 400 patients with ESCC in the clinical database of First Affiliated Hospital of Zhengzhou University and the State Key Laboratory of Esophageal Cancer Prevention and Control of Henan Province. The experiment results demonstrate that the proposed HSIDA-LSSVM has the best prediction performance than LSSVM, HSIDA-BP, IPSO-LSSVM, COA-LSSVM and IBA-LSSVM. The proposed model achieves the accuracy of 96.25%, sensitivity of 95.12%, specificity of 97.44%, precision of 97.50%, and F1 score of 96.30%. Graphical abstract
Local communities’ perceptions of climate variability in the Mt. Elgon region, eastern Uganda

Abstract In order to develop climate adaptation strategies that address location and context-specific vulnerabilities, there is need to understand how communities perceive the variability in their climate as perception of climate variability is a critical component within which climate adaptation should operate. This paper examines communities’ perceptions about climate variability in relation to available meteorological data in the Mt. Elgon region. The study demonstrates that community perceptions of temperature and precipitation trends as indicators of climate variability are in agreement with meteorologically observed trends. It also reveals that local communities’ perceptions of climate variability may also provide more localized contexts of climate variability which be insufficiently captured by meteorological data in communities where capture of meteorological data is not fully developed.
Unraveling Spatiotemporal Transient Dynamics at the Nanoscale via Wavelet Transform-Based Kelvin Probe Force Microscopy

Mechanistic probing of surface potential changes arising from dynamic charge transport is the key to understanding and engineering increasingly complex nanoscale materials and devices. Spatiotemporal averaging in conventional heterodyne detection-based Kelvin probe force microscopy (KPFM) inherently limits its time resolution, causing an irretrievable loss of transient response and higher-order harmonics. Addressing this, we report a wavelet transform (WT)-based methodology capable of quantifying the sub-ms charge dynamics and probing the elusive transient response. The feedback-free, open-loop wavelet transform KPFM (OL-WT-KPFM) technique harnesses the WT’s ability to simultaneously extract spatial and temporal information from the photodetector signal to provide a dynamic mapping of surface potential, capacitance gradient, and dielectric constant at a temporal resolution 3 orders of magnitude higher than the lock-in time constant. We further demonstrate the method’s applicability to explore the surface-photovoltage-induced sub-ms hole-diffusion transient in bismuth oxyiodide semiconductor. The OL-WT-KPFM concept is readily applicable to commercial systems and can provide the underlying basis for the real-time analysis of transient electronic and electrochemical properties.
Impact of PmrB mutations on clinical Klebsiella pneumoniae with variable colistin‐susceptibilities: Structural insights and potent therapeutic solutions

Carbapenem‐resistant Klebsiella pneumoniae (CRKP) infections continue to impose high morbidity threats to hospitalized patients worldwide, limiting therapeutic options to last‐resort antibiotics like colistin. However, the dynamic genomic landscape of colistin‐resistant K. pneumoniae (COLR‐Kp) invoked ardent exploration of underlying molecular signatures for therapeutic propositions/designs. We unveiled the structural impact of the widespread and emerging PmrB mutations involved in colistin resistance (COLR) in K. pneumoniae. In the present study, clinical isolates of K. pneumoniae expressed variable susceptibilities to colistin (>0.5 μg/mL for resistant and ≤0.25 μg/mL for susceptible) despite mutations such as T157P, G207D and T246A. The protein sequences extracted from in‐house sequenced genomes were used to model mutant PmrB proteins and analyze the underlying structural alterations. The mutations were contrasted based on molecular dynamics simulation trajectories, free‐energy landscapes and structural flexibility profiles. The altered backbone flexibilities can be an essential factor for mutant selection by COLR K. pneumoniae and can provide clues to deal with emerging mutants. Furthermore, PmrB having high druggability confidence (>0.99), was explored as a potential target for 1396 virtually screened FDA‐approved drug candidates. Among the top‐10 compounds (scores >70), amphotericin B was found to be potential candidate with high affinity (Binding energy <−8 kcal/mol) and stable interactions (RMSF <0.7 Å) against PmrB druggable pockets, despite the mutations, which encourages future adjunct therapeutic research against COLR‐Kp.