Miracle-dz/UniFAR-FTUs huggingface dataset:
Eccentric training effects for patients with post-stroke hemiparesis on strength and speed gait: A randomized controlled trial.

BACKGROUND In hemiparetic patients, the skeletal muscle is mainly affected with a combination of abnormalities (denervation, remodeling, spasticity, and eventually muscular atrophy). OBJECTIVE This study examined the role of eccentric exercise in strengthening muscles of the lower extremity and ultimately improving autonomy in patients with post-stroke hemiparesis during gait. METHODS Thirty-seven patients hemiparetic adults were recruited, randomized into a control group (n = 19) and an intervention group receiving eccentric muscle strengthening (n = 18). The protocol consisted of three sets of five repetitions of eccentric contraction of the paretic limb after determining the maximum repetition (1 MRI). Evaluation of the 1RM, 10 meters and 6WMT was performed before and after the exercise for each group. Manova test was used to compare the differences between the control and intervention groups. RESULTS The paretic limb showed significant increase in one-repetition maximum (1RM) between before and after rehabilitation (p≤0.00003). The two groups of Patients increased their walking speed (p≤0.0005), but we observed a significant difference between groups only for the 6MWT and not on the 10 meters Test. CONCLUSIONS Eccentric training can be useful in strengthening the muscles of the lower limbs, and promoting gait performance. Eccentric training could complement other methods of managing patients with post-stroke hemiparesis.
Considerations on the flow configuration of membrane chromatography devices for the purification of human basic fibroblast growth factor from crude lysates

Membrane chromatography possesses numerous advantages such as operation at high flow rates, low back pressure, ease of handling and scale up, which make the membrane adsorber process a viable alternative to conventional packed column chromatography. A purification process for the isolation of human recombinant basic fibroblast growth factor (FGF‐2) based on membrane chromatography was investigated using devices with different flow configurations. In the first process, the FGF‐2 capture step was performed with an axial flow device, while the alternative method achieved direct capture of FGF‐2 from unclarified cell lysate with a tangential flow device. In both processes, FGF‐2 purities exceeded 82% and the purified cytokine displayed high biological activity. Binding capacity (BC) from fermentation broth of the axial flow device was 28 mg/mL. This was 50% higher than the BC obtained with the tangential flow device under particle‐free supernatant conditions (18 mg/mL) and 150% higher compared to the BC achieved with unclarified cell lysate (11 mg/mL). While membrane chromatography in tangential flow mode omits clarification and thus reduces the number of stages in the downstream process, it displays lower peak resolution and leads to a lower overall process yield.
Concrete crack detection and 3D mapping by integrated convolutional neural networks architecture

This paper presents an image-based crack detection system, in which its architecture is modified to use deep convolutional neural networks in a feature extraction step and other classifiers in the classification step. In the classification step, classifiers including Support Vector machines (SVMs), Random Forest (RF) and Evolutionary Artificial Neural Network (EANN) are used as an alternative to a Softmax classifier and the performance of these classifiers are studied. The data set was created from various types of concrete structures using a standard digital camera and an unmanned aerial vehicle (UAV). The collected images are used in the crack detection system and in creating a 3D model of a sample concrete building using an image- based 3D photogrammetry technique. Then, the 3D model is used to create a mosaic image, in which the crack detection system was applied to create a global view of a crack density map. The map is then projected onto the 3D model to allow cracks to be located in the 3D world. A comparative study was conducted on the proposed crack detection system and the results prove that the combined architecture of CNN as a feature extractor and SVM as a classifier shows the best performance with the accuracy of 92.80. The results also show that the modified architecture by integrating CNN and other types of classifiers can improve a system performance, which is better than using the Softmax classifier.
A double-edged sword: The effects of social network ties on job satisfaction in primary care organizations

Background Social ties between health care workers may be an important driver of job satisfaction; however, research on this topic is limited. Purpose We used social network methods to collect data describing two types of social ties, (a) instrumental ties (i.e., exchange of advice that enables work) and (b) expressive ties (i.e., exchange of social support), and related those ties to workers’ job satisfaction. Methodology We surveyed 456 clinicians and staff at 23 primary care practices about their social networks and workplace attitudes. We used multivariable linear regression to estimate the relationship between an individual’s job satisfaction and two network properties: (a) eigenvector centrality (a measure of the importance of an individual in a network) and (b) ego network density (a measure of the cohesiveness of an individual’s network). We examined this relationship for both instrumental and expressive ties. Results Individuals who were more central in the expressive network were less satisfied in their job, b = −0.40 (0.19), p < . 05, whereas individuals who had denser instrumental networks were more satisfied in their job, b = 0.49 (0.21), p < . 05. Conclusion Workplace relationships affect worker well-being. Centrality in an expressive network may require greater emotional labor, increasing workers’ risk for job dissatisfaction. On the other hand, a dense instrumental network may promote job satisfaction by strengthening workers’ access to full information, supporting competence and confidence. Practice Implications Efforts to increase job satisfaction should consider both the positive and negative effects of social networks on workers’ sense of well-being.
Self-supported NiMoP2 nanowires on carbon cloth as an efficient and durable electrocatalyst for overall water splitting

Designing and exploring efficient and stable non-noble bifunctional catalysts by nanostructure modification and chemical composition tuning for water splitting is of critical importance for sustainable resources. Herein, pure phase nickel molybdenum phosphide (NiMoP2) nanowires on carbon cloth are successfully synthesized through a simple and highly reproducible in situ P/O exchange process. Such a NiMoP2 nanowire catalyst requires low overpotentials of 199 and 330 mV to obtain a high current density of 100 mA cm−2 towards the hydrogen evolution reaction (HER) and oxygen evolution reaction (OER), respectively, and is among the most active HER and OER electrocatalysts yet reported. The bifunctional NiMoP2 is used as both anode and cathode catalysts in a two-electrode water electrolysis configuration, which delivers a current density of 10 mA cm−2 under a potential of 1.67 V. Furthermore, the overall water-splitting of the bifunctional NiMoP2 nanowire catalyst is further driven by a dry battery with a nominal voltage of 1.5 V which exhibits excellent performance and durability in a strong alkaline electrolyte.
Converting Sentiment Annotated Data to Emotion Annotated Data

Existing supervised solutions for emotion classification demand large amount of emotion annotated data. Such resources may not be available for many languages. However, it is common to have sentiment annotated data available in these languages. The sentiment information (+1 or -1) is useful to segregate between positive emotions or negative emotions. In this paper, we propose an unsupervised approach for emotion recognition by taking advantage of the sentiment information. Given a sentence and its sentiment information, recognize the best possible emotion for it. For every sentence, the semantic relatedness between the words from sentence and a set of emotion-specific words is calculated using cosine similarity. An emotion vector representing the emotion score for each emotion category of Ekman’s model, is created. It is further improved with the dependency relations and the best possible emotion is predicted. The results show the significant improvement in f-score values for text with sentiment information as input over our baseline as text without sentiment information. We report the weighted f-score on three different datasets with the Ekman’s emotion model. This supports that by leveraging the sentiment value, better emotion annotated data can be created.
Acetovanillone prevents cyclophosphamide‐induced acute lung injury by modulating PI3K/Akt/mTOR and Nrf2 signaling in rats

Cyclophosphamide (CP) is a medication used as an anticancer drug and to suppress the immune system. However, its clinical applications are restricted because of the toxic and adverse side effects. The present study investigated the protective effect of acetovanillone (AV), a natural NADPH oxidase inhibitor, against acute lung injury (ALI) induced by CP. Rats were administered AV (100 mg/kg) for 10 days and a single injection of CP (200 mg/kg) at day 7. At the end of the experiment, the animals were sacrificed, and lung samples were collected for analyses. CP caused ALI manifested by the histopathological alterations. Lipid peroxidation and NADPH oxidase activity were increased, whereas GSH and antioxidant enzymes were decreased in the lung of CP‐intoxicated rats. Oral administration of AV prevented CP‐induced lung injury and oxidative stress and enhanced antioxidant defenses. AV downregulated Keap1 and upregulated Nrf2, GCLC, HO‐1, and SOD3 mRNA. In addition, AV boosted the expression of PI3K, Akt, mTOR, and cytoglobin. In vitro, AV showed a synergistic anticancer effect when combined with CP. In conclusion, AV protected against CP‐induced ALI by attenuating oxidative stress and boosting Nrf2/HO‐1 and PI3K/Akt/mTOR signaling. Therefore, AV might represent a promising adjuvant to prevent lung injury in patients receiving CP.
Cytotoxic alkaloids from the root of Zanthoxylum paracanthum (mildbr) Kokwaro

Abstract Chemical investigation of the root of Zanthoxylum paracanthum afforded 1 new alkamide derivative, (2E,4E)-6-oxo-N-isobutyldeca-2,4-dienamide (1) together with 10 known congeners including one phenolic amide (2), four benzophenanthridines (3 − 6), three indolonaphthyridines (7 − 9) and two lignans (10 and 11). Their structures were elucidated by a combination of spectroscopic and spectrometric data. Using resazurin reduction assay, the crude extract (10 µg/mL) and isolates (10 µM) were screened for their cytotoxic activities against the drug-sensitive (CCRF-CEM) leukemia cell line and its multidrug-resistant counterpart (CEM/ADR5000). Compounds 3, 4 and 6 showed cytotoxicity against CCRF-CEM with IC50 values of 2.00 ± 0.33, 2.31 ± 0.20 and 0.11 ± 0.04 µM, respectively. Only compound 6 exhibited strong cytotoxic activity against CEM/ADR5000 with an IC50 value of 2.34 ± 0.34 µM in comparison with the standard drug doxorubicin which showed IC50 values of 0.01 ± 0.14 (CCRF-CEM) and 26.78 ± 3.30 µM (CEM/ADR5000). Graphical Abstract
Does Long-Term Playing Violin Cause Unilateral Hearing Loss?

Objective: This study compared the differences between two ears, the one which is close to the violin and the far one from the violin, in individuals who have been playing violin, and evaluated by using Distortion Product Otoacoustic Emission. Methods: 30 individuals between the ages of 18-30, playing violin for at least 2 hours a day for 5 years and having no history of hearing loss or ear diseases were included in the study. Pure tone audiometry test and Distortion Product Otoacoustic Emission test were apLONplied on all subjects included in the study. The differences in these measurements for between two ears were subjected to statistical analyses. Results: In all frequencies (996 – 7998 Hz) SNRs of the ear close to the violin and the ear far from the violin were obtained normal, above 6 dB SNR in the results of Distortion Product Otoacoustic Emission. However, there were not statistically significant differences between two ears (p>0.05), only at 1416 Hz a statistically significant difference was observed between the two ears (p = 0.03). Conclusion: The violinists had better hearing function than expected. But noiseinduced hearing loss happens slowly over time and may be hard to detect at first. Violinists are at risk for occupational exposure to high noise. Therefore, the violinists with normal hearing should be monitored by DPOAE which shows noise-induced damage in outer hear cells.
Three Ribosomal Operons of Escherichia coli Contain Genes Encoding Small RNAs That Interact With Hfq and CsrA in vitro

Three out of the seven ribosomal RNA operons in Escherichia coli end in dual terminator structures. Between the two terminators of each operon is a short sequence that we report here to be an sRNA gene, transcribed as part of the ribosomal RNA primary transcript by read-through of the first terminator. The sRNA genes (rrA, rrB and rrF) from the three operons (rrnA, rrnB and rrnD) are more than 98% identical, and pull-down experiments show that their transcripts interact with Hfq and CsrA. Deletion of rrA, B, F, as well as overexpression of rrB, only modestly affect known CsrA-regulated phenotypes like biofilm formation, pgaA translation and glgC translation, and the role of the sRNAs in vivo may not yet be fully understood. Since RrA, B, F are short-lived and transcribed along with the ribosomal RNA components, their concentration reflect growth-rate regulation at the ribosomal RNA promoters and they could function to fine-tune other growth-phase-dependent processes in the cell. The primary and secondary structure of these small RNAs are conserved among species belonging to different genera of Enterobacteriales.
Gene-Based Tests of a Genome-Wide Association Study Dataset Highlight Novel Multiple Sclerosis Risk Genes

Multiple sclerosis (MS) is an autoimmune disorder influenced by genetic and environmental factors. Many studies have provided insights into genetic factors’ contribution to MS via large-scale genome-wide association study (GWAS) datasets. However, genetic variants identified to date do not adequately explain genetic risks for MS. This study hypothesized that novel MS risk genes could be identified by analyzing the MS-GWAS dataset using gene-based tests. We analyzed a GWAS dataset consisting of 9,772 MS cases and 17,376 healthy controls of European descent. We performed gene-based tests of 464,357 autosomal single nucleotide polymorphisms (SNPs) using two methods (PLINK and VEGAS2) and identified 28 shared genes satisfied p-value < 4.56 × 10–6. In further gene expression analysis, ten of the 28 genes were significantly differentially expressed in the MS case-control gene expression omnibus (GEO) database. GALC and HLA-DOB showed the most prominent differences in gene expression (two- and three-fold, respectively) between MS patients and healthy controls. In conclusion, our results reveal more information about MS hereditary characteristics and provide a basis for further studies.
Chemo Proling and Simultaneous Analysis of Different Combinations of Sinomenii Caulis and Ramulus Cinnamomi Using UHPLC-Q-TOF-MS, GC-MS and HPLC Methods.

OBJECTIVE Sinomenii Caulis (QingFengTeng) and Ramulus Cinnamomi (GuiZhi) are traditional Chinese drugs that have been used for anti-inflammation. In this study, the team plans to find out the material basis of a Chinese herb combination composed of the two herbs with different ratios. METHODS The extracts of the herbal compound with various ratios obtained from ethanol extraction were analyzed by ultra-high-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (UHPLC-Q-TOF-MS) and gas chromatography coupled mass spectrometry to identify the basic chemical compounds. Simultaneously, the contents of the eight main components (sinomenine, magnoflorine, laurifoline, dauricine, coumarin, cinnamyl alcohol, cinnamic acid and cinnamaldehyde) from herb formula were determined by gradient elution by high-performance liquid chromatography. Furthermore, the content of sinomenine and cinnamaldehyde were determined by isocratic elution, respectively. RESULTS Eighteen compounds in the herb formula were identified by UHPLC-Q-TOF-MS. The components in the GuiZhi are mostly volatile oils and the kinds of compounds isolated from the formula in the ratio of 4:1 were the most. Wherein eight compounds were identified as the main detection targets in the content determination. CONCLUSION The extraction rate of sinomenine in QingFengTeng was related to the proportion of GuiZhi in the drug pairs. Synchronously, the addition of sinomenine in different proportions also had some influence on the extraction of cinnamaldehyde in GuiZhi. Furthermore, the series of methods was successfully applied to the simultaneous determination of chemical compounds in different samples of QingFengTeng-GuiZhi decoction.
Questioning the Impact of the Impact Factor. A Brief Review and Future Directions

ABSTRACT Purpose To provide a brief review of literature on the journal impact factors (JIF) and the newer research metrics being proposed or implemented. Methods The authors performed a PubMed search of articles published in the English language on the journal impact factors. Data captured include historical perspectives, evolution, calculation, criticisms of JIF and their rebuttals, and organized efforts to address JIF issues, alternate research metrics, and future directions. Specific emphasis was laid on evaluating the criticisms, current lacunae, and the changing practice patterns. Results One of the measures to assess the research impact of an article is the number of citations it receives. Hence, citation-based metrics are commonly used for such purposes. While editors and well-known scholars refrain from attributing article success to the journal’s prominence, the same is not true for most authors. JIF is still one of the top factors when deciding on an article submission. JIF is today an acceptable objective and quantifiable measure of knowledge dissemination. However, JIF should not be used as a surrogate measure to assess an individual researcher or an individual article. The reverence to JIF in this regard needs to be questioned. While alternate metrics or altmetrics have their advantages and limitations, they nevertheless augur well an era where scientometrics are complementary to one another without undue reliance on a sole parameter. Conclusion While there is no need to demonize the JIF, its role in the scholarly assessment should be scaled down. The over-reliance and undue hype surrounding it should be discouraged at multiple scientific levels.
Forest structure and degradation drive canopy gap sizes across the Brazilian Amazon

Canopy gaps are openings in the forest canopy resulting from branch fall and tree mortality events. Light reaches the lower layers of the canopy through these gaps, enabling understory trees to grow and maintaining the high heterogeneity and biodiversity of tropical forests. The size-frequency distribution of canopy gaps follows a power-law distribution, and the slope of this power-law (α) is a key indicator of forest structure and dynamics. We detected canopy gaps using a unique LiDAR data set consisting of 650 transects randomly distributed across the Brazilian Amazon Forest providing an unprecedented perspective on forest structural variation over 2500 km2 of forest. We then investigated how α varied with forest structure, elevation, soil fertility, water deficit, wind gust speed and lightning intensity. We found that human modified forests had more large gaps than intact forests. Within the intact forests we observed a large-scale Northwest to Southeast pattern in α (more large gaps in the Southeast), which aligns with recent work on tree mortality rates. The two most important variables in predicting α were median canopy height and maximum modeled height, which had opposite effects on the number of large gaps. Forests with higher median canopy height contain fewer large gaps but the presence of very tall trees was associated with more large gaps. Environmental variables were of secondary importance in our model, with larger gaps occurring in drier forests with high soil fertility, wind speed, and lightning intensity. The distribution of large gaps in the forest canopy varies substantially over the Brazilian Amazon as a result of canopy structure and mortality rates. We mapped this variation and found more large gaps in human modified forests, forests on fertile soils and those exposed to higher wind, lightning and drought stress. Increasing extreme weather events due to climate change may therefore increase the number of large gaps in currently intact forests, causing them to resemble human modified forests.
The Stability and Elasticity in Ta-Ti-V Medium-Entropy Alloys Using First-Principles Calculations

Due to the low neutron activity, the high thermal stability, and the good compression strength at elevated temperatures, medium-entropy Ta-Ti-V alloys have the application potential to be used in future nuclear engineering. According to experimental results, a special quasi-random structure (SQS) model and first-principles calculations are used to calculate the structural stability and the elasticity of the ternary single-phase body-centered cubic (BCC) Ta-Ti-V alloys with the compositions Ta24Ti14V16, Ta19Ti17V18, Ta16Ti21V17, Ta22Ti23V9, and Ta18Ti18V18. The mixing energy of five compositions is positive, which indicates that they are unstable at low temperature but stable at high temperature. Meanwhile, we predict the ability of elasticity in those five compositions, and the sequence of bulk modulus is Ta24Ti14V16 > Ta19Ti17V18 > Ta18Ti18V18 > Ta16Ti21V17 > Ta22Ti23V9 and ductility is Ta19Ti17V18 > Ta18Ti18V18 > Ta22Ti23V9 > Ta24Ti14V16 > Ta16Ti21V17. Additionally, the influence of the element content on elastic properties shows that the Ta content will increase the bulk modulus of the alloys, while Ti content decreases the bulk modulus. Higher V and Ti contents are beneficial to ductility, especially the V content. The higher Ta content will sharply reduce the ductility of the alloys. Our calculation has provided further theoretical mechanism for the Ta-Ti-V medium-entropy alloys (MEAs) preparation and development.