Miracle-dz/UniFAR-FTUs huggingface dataset:
Inclusive Leadership for Employee Workplace Well-Being in Public Organizations

Various public organizations realize that promoting workplace well-being is crucial for the effectiveness of their employees. It is believed that when creating an environment where employees feel welcomed, are treated fairly, and their contributions are appreciated, they will be happy and work better. Therefore, diversity management has gained increased attention. However, since diversity does not necessarily mean inclusion in decision-making and the appreciation of employee differences and input, a growing body of research has advocated the adoption of positive relational leadership styles, such as inclusive leadership. Inclusive leadership embraces employee differences, manages diversity, and recognizes employee input. Hence this paper investigates how inclusive leadership correlates to employee workplace well-being in public organizations. Relying on quantitative analysis, a questionnaire was distributed to N= 234 Egyptian local government officials who demonstrated diversity in gender and educational levels. The data collected were analyzed using SPSS version 20. The study's conclusions reveal that inclusive leadership has an uneven influence on employee workplace well-being based on educational levels. The correlation was strongest among the least educated and weakest among the highly educated. Gender, on the other hand, did not show any significant difference in the correlation between inclusive leadership and workplace well-being and hence, was not considered for further analysis. Moreover, the traits of inclusive leadership have different effects on employee workplace well-being based on their educational levels. For the least educated, leadership accessibility had the greatest influence on employee workplace well-being, while for the highly educated, leadership openness had the strongest influence. In conclusion, this paper highlights the importance of inclusive leadership in promoting employee workplace well-being in public organizations, especially for marginalized groups who may feel excluded in the workplace. Additionally, public organizations should recognize that inclusive leadership practices should be tailored to meet the diverse needs of employees based on their educational levels.
Planets Across Space and Time (PAST). IV. The Occurrence and Architecture of Kepler Planetary Systems as a Function of Kinematic Age Revealed by the LAMOST–Gaia–Kepler Sample

One of the fundamental questions in astronomy is how planetary systems form and evolve. Measuring the planetary occurrence and architecture as a function of time directly addresses this question. In the fourth paper of the Planets Across Space and Time series, we investigate the occurrence and architecture of Kepler planetary systems as a function of kinematic age by using the LAMOST–Gaia–Kepler sample. To isolate the age effect, other stellar properties (e.g., metallicity) have been controlled. We find the following results. (1) The fraction of stars with Kepler-like planets (F Kep) is about 50% for all stars; no significant trend is found between F Kep and age. (2) The average planet multiplicity ( N¯p ) exhibits a decreasing trend (∼2σ significance) with age. It decreases from N¯p ∼ 3 for stars younger than 1 Gyr to N¯p ∼ 1.8 for stars of about 8 Gyr. (3) The number of planets per star (η = F Kep× N¯p ) also shows a decreasing trend (∼2σ–3σ significance). It decreases from η ∼ 1.6–1.7 for young stars to η ∼ 1.0 for old stars. (4) The mutual orbital inclination of the planets (σ i,k ) increases from 1. °2−0.5+1.4 to 3. °5−2.3+8.1 as the stars age from 0.5 to 8 Gyr with a best fit of logσi,k=0.2+0.4×logAge1Gyr . Interestingly, the solar system also fits such a trend. The fact that F Kep remains relatively constant at approximately ∼ 50% across different ages suggests the robustness of planet formation throughout the history of the Galaxy. The age dependence of N¯p and σ i,k demonstrates that the planetary architecture is evolving, and planetary systems generally become dynamically hotter with fewer planets as they age.
IL1A regulates the inflammation in gout through the Toll-like receptors pathway

Objective: Gout is a dangerous metabolic condition related to monosodium urate (MSU). Our aim is to study the molecular mechanisms underlying gout and to identify potential clinical biomarkers by bioinformatics analysis and experimental validation. Methods: In this study, we retrieved the overlapping genes between GSE199950-Differential Expressed Genes (DEGs) dataset and key module in Weighted Gene Co-Expression Network Analysis (WGCNA) on GSE199950. These genes were then analyzed by protein-protein interaction (PPI) network, expression and Gene Set Enrichment Analysis to identify the hub gene related to gout. Then, the gene was investigated by peripheral blood mononuclear cells (PBMCs), immunoassay and cell experiments like western blotting to uncover its underlying mechanism in gout cells. Results: From the turquoise module and 83 DEGs, we identified 62 overlapping genes, only 11 genes had mutual interactions in PPI network and these genes were highly expressed in MSU-treated samples. Then, it was found that the IL1A (interleukin 1 alpha) was the only one gene related to Toll-like receptor signaling pathway that was associated with the occurrence of gout. Thus, IL1A was determined as the hub gene in this study. In immunoassay, IL1A was significantly positively correlated with B cells and negatively correlated with macrophages. Moreover, IL1A is highly expressed in gout patients,it has a good clinical diagnostic value. Finally, the results of in vitro experiments showed that after knocking down IL1A, the expressions of pro-inflammatory cytokines and Toll-like receptor signaling pathway-related proteins (TLR2, TLR4, MyD88) were all reduced. Conclusion: It is confirmed that IL1A is a promoting gene in gout with a good diagnostic value, and specifically it affects the inflammation in gout through Toll-like receptor pathway. Our research offers fresh perspectives on the pathophysiology of gout and valuable directions for future diagnosis and treatment.
A Novel Near-Field Resonant Parasitic Electrically Small Antenna With a Wide Tuning Range

An electrically small antenna (ESA), designed on the near-field resonant parasitic (NFRP) technology and with a wide tuning range, is proposed. It utilizes a capacitively loaded loop (CLL) as its NFRP element, and tunes its resonant frequency by adjusting CLL's capacitance. Quite different from normal NFRP antennas using one ESA such as a semiloop antenna (SLA) as the driven element, the proposed antenna employs a composite driven element (CDE), which combines a monopole and a SLA. Analyses reveal the CDE is able to realize good tuning impedance matching and effectively excite the CLL over a wide frequency range. A prototype is designed, fabricated, and measured. Results show it achieves a 10 dB tuning bandwidth up to 107.9% (36–117 MHz) with a dimension of only 0.036<inline-formula><tex-math notation="LaTeX">$\lambda \times {\text {0.030}}\lambda \times {\text {0.018}}\lambda$</tex-math></inline-formula> (<italic>ka</italic> = 0.18), where <inline-formula><tex-math notation="LaTeX">$\lambda$</tex-math></inline-formula> is the wavelength corresponding to the start tuning frequency of 36 MHz.
Low-Complexity BFGS-Based Soft-Output MMSE Detector for Massive MIMO Uplink

For the massive multiple-input multiple-output (MIMO) uplink, the linear minimum mean square error (MMSE) detector is near-optimal but involves undesirable matrix inversion. In this paper, we propose a low-complexity soft-output detector based on the simplified Broyden–Fletcher–Goldfarb–Shanno method to realize the matrix-inversion-free MMSE detection iteratively. To accelerate convergence with minimal computational overhead, an appropriate initial solution is presented leveraging the channel-hardening property of massive MIMO. Moreover, we employ a low-complexity approximated approach to calculating the log-likelihood ratios with negligible performance losses. Simulation results finally verify that the proposed detector can achieve the near-MMSE performance with a few iterations and outperforms the recently reported linear detectors in terms of lower complexity and faster convergence for the realistic massive MIMO systems.
Ischemic stroke outcome prediction based on the whole-brain features extracted from minimum intensity projection of DSC-PWI images by pre-trained Med3D network

Accurate stroke outcome prediction is of great significance to making treatment plans and evaluating the rehabilitation state of patients. Previous works paid more attention to the basic information and volume of ischemic tissue for predicting outcomes, ignoring the role of the whole-brain. The purpose of this paper was to prove the value of wholebrain features in outcome prediction. In detail, the pre-trained Med3D model was used to extract whole-brain features from minimum intensity projection (MinIP) of PWI-DSC images, the Least absolute shrinkage and selection operator was used to select outstanding whole-brain features, and ten machine learning models were applied to validate the role of the selected outstanding whole-brain features on predicting outcomes. As the results, when taking ResNet10, ResNet18, ResNet34, and ResNet50 as encoders in the Med3D model, the best AUC of outstanding whole-brain features were 0.88, 0.939, 0.781, and 0.883, and the mean ± std on the ten machine models were 0.756 ± 0.097, 0.766 ± 0.123, 0.714 ± 0.044, and 0.761 ± 0.105, respectively. It can be concluded that the outstanding whole-brain features extracted from the MinIP image can predict good outcomes and poor outcomes for ischemic stroke patients, and the whole-brain features from ResNet18 performed best. The method provided in this study may provide new insight for ischemic stroke research.
Quality by Design (Qbd) Based Development and Evaluation of Carvedilol Loaded Polymeric Nanoparticles for Enhanced Solubility

By preparing a polymeric nanoparticle by nanoprecipitation using specific polymers like Chitosan and HPMC K15M and Poloxamer 407 as a surfactant, the drug solubility of Carvedilol, a BCS class-II drug with poor water solubility, can be improved through the release of drug over time. Critical quality parameters, such as drug release (%), entrapment efficiency (%), particle size (nm), and zeta potential (mV), are used to eliminate unnecessary process and formulation variables. The model drug has a sharp melting point, and the FT-IR and DSC investigations show that it does not interact with the polymers or show any additional peaks. Particle size, zeta potential, entrapment efficiency and in-vitro drug release were among the characteristics studied for the generated drug-loaded polymeric nanoparticles. According to the results of the drug release and stability investigations, the F6 formulation was the most reliable, boasting increased drug solubility and efficient drug trapping as it formed a nano-sized polymeric particle. Non-Fickian diffusion-controlled drug release with Higuchi kinetics was demonstrated by the correlation coefficient data and the release exponent numbers from Koresmeyer Peppa’s. Drug entrapment efficiency and in vitro dissolution rate remained constant during the 6-month stability trial, indicating that the optimised formulation (F6) is more stable.
LCP1 knockdown in monocyte-derived macrophages: mitigating ischemic brain injury and shaping immune cell signaling and metabolism

Rationale: Ischemic stroke poses a significant health burden with limited treatment options. Lymphocyte Cytosolic Protein 1 (LCP1) facilitates cell migration and immune responses by aiding in actin polymerization, cytoskeletal rearrangements, and phagocytosis. We have demonstrated that the long non-coding RNA (lncRNA) Maclpil silencing in monocyte-derived macrophages (MoDMs) led to LCP1 inhibition, reducing ischemic brain damage. However, the role of LCP1 of MoDMs in ischemic stroke remains unknown. Methods and Results: We investigated the impact of LCP1 on ischemic brain injury and immune cell signaling and metabolism. We found that knockdown of LCP1 in MoDMs demonstrated robust protection against ischemic infarction and improved neurological behaviors in mice. Utilizing the high-dimensional CyTOF technique, we demonstrated that knocking down LCP1 in MoDMs led to a reduction in neuroinflammation and attenuation of lymphopenia, which is linked to immunodepression. It also showed altered immune cell signaling by modulating the phosphorylation levels of key kinases and transcription factors, including p-PLCg2, p-ERK1/2, p-EGFR, p-AKT, and p4E-BP1 as well as transcription factors like p-STAT1, p-STAT3, and p-STAT4. Further bioinformatic analysis indicated that Akt and EGFR are particularly involved in fatty acid metabolism and glycolysis. Indeed, single-cell sequencing analysis confirmed that enrichment of fatty acid and glycolysis metabolism in Lcp1high monocytes/macrophages. Furthermore, Lcp1high cells exhibited enhanced oxidative phosphorylation, chemotaxis, migration, and ATP biosynthesis pathways. In vitro experiments confirmed the role of LCP1 in regulating mitochondrial function and fatty acid uptake. Conclusions: These findings contribute to a deeper understanding of LCP1 in the context of ischemic stroke and provide valuable insights into potential therapeutic strategies targeting LCP1 and metabolic pathways, aiming to attenuating neuroinflammation and lymphopenia.
Exploratory Searching As Conceptual Exploration

The aim of this paper is to analyze the characteristics of exploratory searching for inferring ideas on how to evaluate exploratory search systems. Exploratory searching is defined as conceptual exploration. Information search process is divided into major stages. Goals, criteria and measures of attaining goals in explicating information need and formulating search are proposed. They can be applied for evaluating search systems aiming at supporting these two stages in searching.
The loss mechanisms of plane-wave reflection from the seafloor with elastic characteristics

As an integral part of the waveguide, the seafloor plays an important role in underwater acoustic propagation, particularly in shallow water environment where the acoustic waves strongly interact with the seafloor. It is therefore critical to understand the fundamental loss mechanisms from the interaction between acoustic waves and the seafloor for both forward and inverse underwater acoustics problems in shallow water. This paper reviews the classic theory of plane-wave reflection from layered solid media, and its application on revealing the mechanisms of the reflection loss from the seafloor with a specific geoacoustic structure consisting of a sediment layer of weak elasticity overlaying a solid substrate. The significant reflection loss mechanisms include the compressional-shear wave conversion, the possible sediment-substrate surface wave excitation, and the resonances in the sediment layer.
Characterisation of South African field Ehrlichia ruminantium using multilocus sequence typing

Heartwater, one of the major tick-borne diseases of some domestic and wild ruminants in Africa, is caused by Ehrlichia ruminantium. The genetic diversity of E. ruminantium isolates renders the available vaccine ineffective against certain virulent isolates. To better understand the E. ruminantium genotypes in South Africa, a total of 1004 Amblyomma hebraeum tick deoxyribonucleic acid (DNA) samples from cattle in three South African provinces were tested by pCS20 Sol1 real-time polymerase chain reaction (qPCR) and characterised by multilocus sequence typing (MLST) using five housekeeping genes. Out of 1004 samples tested, 222 (22%) were positive for E. ruminantium. The occurrence of E. ruminantium in Mpumalanga, KwaZulu-Natal and Limpopo provinces was 19%, 22% and 27%, respectively. The E. ruminantium positive samples were screened for housekeeping genes and sequenced. Phylogenetic analysis revealed three main lineages: clade 1 made up of worldwide isolates (eastern, southern Africa, and Caribbean isolates), clade 2 comprised only West African isolates and clade 3 consisted of Omatjenne, Kümm2 and Riverside. Some study sample sequences were not identical to any of the reference isolates. However, they could all be grouped into the worldwide clade. Genetic variation in the sequenced regions was observed in the form of single nucleotide polymorphisms (SNPs). Using MLST to characterise E. ruminantium field isolates allowed the South African genotypes to be clearly distinguished from the distinct West African isolates. Contribution Characterisation of E. ruminantium field isolates is important for the control of heartwater and contributes to preliminary knowledge required for the development of a more practical vaccine against heartwater.
Mutual Compensation Range Detection Method Using Multimodulation Radar for Precision Range Detection

A mutual compensation range detection method using a multimodulation radar is proposed to detect the absolute distance of a target with high accuracy while using a narrow bandwidth. The waveform of the multimodulation radar consists of a combination of both a chirp of the frequency-modulated continuous wave (FMCW) radar and two-tone signals of the frequency-shift keying (FSK) radar for the precise mixing of the measured distances. The proposed mutual compensation range detection method can simultaneously solve the uncertainty by the phase offset and unambiguous range of the FSK radar and the limitation of the range resolution of the FMCW radar. Using the proposed method, the 5.8-GHz multimodulation radar with a bandwidth of 150 MHz detected the absolute distance of the target in the range of 2.1–5.1 m with a distance error of 2.1%. The distances between two persons located at 5 and 20 m were detected individually and distinguished when they crossed each other. The experimental results show that the proposed method using the multimodulation radar can solve the problem of unknown initial position caused by clutters and multipath interference in the surroundings, and the limited range resolution by the frequency bandwidth of the chirp.
A CLOUD MASK ANALYSIS WITH SUNSHINE AND CLEARNESS INDEX: A CASE STUDY FOR MARMARA AND SOUTHEASTERN ANATOLIA REGIONS OF TURKEY

The aim of this paper is to evaluate the satellite derived cloud mask product to determine whether it can be used in radiation modeling studies or not. For this purpose, the cloud mask data set for 2011, obtained from EUMETSAT, was processed and used. On the other hand, the sunshine and clearness index time series have been arranged for the same year, which are computed by taking into account the ground based observations of 9 meteorological stations of Turkey. The simple correlations between the aforementioned time series were investigated. A pronounced relation between the satellite based cloud mask product and the determined indices was observed. However, this relation was not found to be enough for using the cloud mask product in solar radiation modelling studies.
The development of a novel terrestrial/aerial robot: autonomous quadrotor tilting hybrid robot

Abstract Unmanned aerial vehicles (UAVs) possess fast-moving abilities and have been used in various tasks in the past decades. However, their performances are still restricted by insufficient endurance and confined environments. Intuitively, combining other locomotion modes with UAVs, such as diving and driving, would be an appropriate idea to improve the robot’s adaptability and solve the endurance problem. Recently, the terrestrial/aerial hybrid robots have drawn the researchers’ eyes for their outstanding performances, which can deploy flight mode to traverse insurmountable terrains and ground mode to increase endurance and realize detailed searches. Therefore, this paper developed the autonomous quadrotor tilting hybrid robot (AQT-HR) to achieve terrestrial/aerial dual-modal mobility and verified that the robot delivers high energy efficiency. The AQT-HR can achieve flying and driving through a quadrotor tilting mechanism, which can alter one single driving force into different directions. Furthermore, the dynamic models of the hybrid robot’s aerial and ground locomotion are derived and introduced into the model-feedforward PID control algorithm for improving the robot’s flying stability. Finally, we conducted some mobility tests and experiments about traversing obstacles to demonstrate that the proposed hybrid robot can realize autonomous mode switching and perform a low energy consumption in ground movement mode.
Dysautonomia, but Not Cardiac Dysfunction, Is Common in a Cohort of Individuals with Long COVID

Despite the prevalence of dysautonomia in people with Long COVID, it is currently unknown whether Long COVID dysautonomia is routinely accompanied by structural or functional cardiac alterations. In this retrospective observational study, the presence of echocardiographic abnormalities was assessed. Left ventricular (LV) chamber sizes were correlated to diagnostic categories and symptoms via standardized patient-reported outcome (PRO) questionnaires. A total of 203 individuals with Long COVID without pre-existing cardiac disease and with available echocardiograms were included (mean age, 45 years; 67% female). Overall, symptoms and PRO scores for fatigue, breathlessness, quality of life, disability, anxiety and depression were not different between those classified with post-COVID dysautonomia (PCD, 22%) and those unclassified (78%). An LV internal diameter at an end-diastole z score < −2 was observed in 33 (16.5%) individuals, and stroke volume (SV) was lower in the PCD vs. unclassified subgroup (51.6 vs. 59.2 mL, 95% C.I. 47.1–56.1 vs. 56.2–62.3). LV end-diastolic volume (mean diff. (95% CI) −13 [−1–−26] mL, p = 0.04) and SV (−10 [−1–−20] mL, p = 0.03) were smaller in those individuals reporting a reduction in physical activity post-COVID-19 infection, and smaller LVMI was weakly correlated with worse fatigue (r = 0.23, p = 0.02). The majority of individuals with Long COVID report shared symptoms and did not demonstrate cardiac dysfunction on echocardiography.