Miracle-dz/UniFAR-FTUs huggingface dataset:
Omnidirectional Solid Angle Beam-Switching Flexible Array Antenna in Millimeter Wave for 5G Micro Base Station Applications

This study proposes a cylindrical conformal array antenna (CCAA) for fifth-generation (5G) micro base station applications. The CCAA is composed of five Chebyshev flexible linear array antennas (LAAs) with a circumferentially uniform arrangement on the cylindrical surface. The LAA with a logarithmic periodic arrangement is constructed by synthesizing the current amplitude distribution coefficients in elements with the Chebyshev method. The LAA with a half-power bandwidth (HPBW) wider than 76° (−8.41° to 38.58°) and a peak gain greater than 10 dBi is fabricated via the micro-electromechanical system process. Cost–performance analysis shows that five is the best number of linear arrays. To achieve omnidirectional switching scanning of the circumferential section, five LAAs wrapped on the cylindrical surface are individually excited by connecting a radio frequency semiconductor switch to the exciting ports of an eight-way power divider. Moreover, beam-switch scanning of the CCAA is measured with the aid of a standard anechoic chamber. The irradiated performance with low mutual coupling and high realized gain is verified to be irrelevant to the structural variation of various flexible experiments of LAAs wrapped around a cylindrical surface. The CCAA with beam-switch scanning operates at 26 GHz and belongs to the 5G millimeter-wave band. Results show the proposed antenna achieves omnidirectional scanning property in the H plane and has a HPBW of only 9.08° in the E plane. The performances of the CCAA present potential advantage in flexible terminal equipment wireless communication.
Calreticulin and Galectin-3 Opsonise Bacteria for Phagocytosis by Microglia

Opsonins are soluble, extracellular proteins, released by activated immune cells, and when bound to a target cell, can induce phagocytes to phagocytose the target cell. There are three known classes of opsonin: antibodies, complement factors and secreted pattern recognition receptors, but these have limited access to the brain. We identify here two novel opsonins of bacteria, calreticulin, and galectin-3 (both lectins that can bind lipopolysaccharide), which were released by microglia (brain-resident macrophages) when activated by bacterial lipopolysaccharide. Calreticulin and galectin-3 both bound to Escherichia coli, and when bound increased phagocytosis of these bacteria by microglia. Furthermore, lipopolysaccharide-induced microglial phagocytosis of E. coli bacteria was partially inhibited by: sugars, an anti-calreticulin antibody, a blocker of the calreticulin phagocytic receptor LRP1, a blocker of the galectin-3 phagocytic receptor MerTK, or simply removing factors released from the microglia, indicating this phagocytosis is dependent on extracellular calreticulin and galectin-3. Thus, calreticulin and galectin-3 are opsonins, released by activated microglia to promote clearance of bacteria. This innate immune response of microglia may help clear bacterial infections of the brain.
Micro-Ribonucleic Acid-216a Regulates Bovine Primary Muscle Cells Proliferation and Differentiation via Targeting SMAD Nuclear Interacting Protein-1 and Smad7

MicroRNAs (miRNAs), belonging to a class of evolutionarily conserved small noncoding RNA of ∼22 nucleotides, are widely involved in skeletal muscle growth and development by regulating gene expression at the post-transcriptional level. While the expression feature and underlying function of miR-216a in mammal skeletal muscle development, especially in cattle, remains to be further elucidated. The aim of this study was to investigate the function and mechanism of miR-216a during bovine primary muscle cells proliferation and differentiation. Herein, we found that the expression level of miR-216a both presented a downward trend during the proliferation and differentiation phases, which suggested that it might have a potential role in the development of bovine skeletal muscle. Functionally, during the cells proliferation phase, overexpression of miR-216a inhibited the expression of proliferation-related genes, reduced the cell proliferation status, and resulted in cells G1 phase arrest. In cells differentiation stages, overexpression of miR-216a suppressed myogenic maker genes mRNA, protein, and myotube formation. Mechanistically, we found that SNIP1 and smad7 were the directly targets of miR-216a in regulating bovine primary muscle cells proliferation and differentiation, respectively. Altogether, these findings suggested that miR-216a functions as a suppressive miRNA in development of bovine primary muscle cells via targeting SNIP1 and smad7.
How Ethical Leadership Shapes Employees’ Readiness to Change: The Mediating Role of an Organizational Culture of Effectiveness

Today’s organizations are operating in a highly competitive and changing environment that pushes them to continuously adapt their organizational structures to such environment. However, the success of change initiatives may face a barrier in the response of employees, especially when they lack readiness to change. While leadership can shape the culture of an organization and a culture of effectiveness can help increase employees’ readiness to change, ethical leaders, who serve as a guide and offer support, can also make a difference by reducing uncertainty. Yet existing research on the role of ethical leadership in the enhancement of the employees’ readiness to change is practically non-existent. Far less is the research that analyses the mechanisms that ethical leadership can use to foster employees’ readiness to change. This study aims to investigate whether the ethical leadership of middle–lower echelons influences on employees’ readiness to change positively (H1) and if this relationship is mediated through shaping an organizational culture of effectiveness (H2). Using data from 270 direct reports of middle–lower managers in public foreign trade Egyptian companies, the findings reveal that ethical leadership enhances employees’ readiness to change and that this impact is partially mediated by an organizational culture of effectiveness. Thus, with these findings, new light is shed on the positive role of ethical leadership and the mechanisms it uses to enhance employees’ readiness to change.
A Framework for Long-Term Data Collection to Support Automatic Human Activity Recognition

Human activity recognition (HAR) is a very active field of research and many techniques have been developed in recent years. Deep learning techniques applied to 3D and 4D signals such as images and videos have proven to be effective, achieving significant classification accuracy. Recently, these techniques are also being used for 1D signals and are exploited to recognize human Activities of Daily Living (ADLs). They process inertial signals such as those obtained from accelerometers and gyroscopes. However, to compute accurate and reliable deep learning models, a lot of sample data is required. Moreover, the creation of a dataset to be used with deep learning techniques is an onerous process that requires the involvement of a significant number of possibly heterogeneous subjects. The publicly available datasets are few and, with rare exceptions, contain few subjects. Furthermore, datasets are heterogeneous and therefore not directly usable all together. The goal of our work is the definition of a platform to support long-term data collection to be used in training HAR algorithms. The platform, termed Continuous Learning Platform (CLP), aims to integrate datasets of inertial signals in order to make available to the scientific community a large dataset of homogeneous signals and, when possible, enrich it with context information (e.g., characteristics of the subject, device position, and so on). Moreover, the platform has been designed to provide additional services such as the deployment of activity recognition models and online signal labelling services. The architecture has been defined and some of the main components have been developed in order to verify the soundness of the approach.
Different Amyloid-β Self-Assemblies Have Distinct Effects on Intracellular Tau Aggregation

Alzheimer’s disease (AD) pathology is characterized by the aggregation of beta-amyloid (Aβ) and tau in the form of amyloid plaques and neurofibrillary tangles in the brain. It has been found that a synergistic relationship between these two proteins may contribute to their roles in disease progression. However, how Aβ and tau interact has not been fully characterized. Here, we analyze how tau seeding or aggregation is influenced by different Aβ self-assemblies (fibrils and oligomers). Our cellular assays utilizing tau biosensor cells show that transduction of Aβ oligomers into the cells greatly enhances seeded tau aggregation in a concentration-dependent manner. In contrast, transduced Aβ fibrils slightly reduce tau seeding while untransduced Aβ fibrils promote it. We also observe that the transduction of α-synuclein fibrils, another amyloid protein, has no effect on tau seeding. The enhancement of tau seeding by Aβ oligomers was confirmed using tau fibril seeds derived from both recombinant tau and PS19 mouse brain extracts containing human tau. Our findings highlight the importance of considering the specific form and cellular location of Aβ self-assembly when studying the relationship between Aβ and tau in future AD therapeutic development.
StressMon

Stress and depression are a common affliction in all walks of life. When left unmanaged, stress can inhibit productivity or cause depression. Depression can occur independently of stress. There has been a sharp rise in mobile health initiatives to monitor stress and depression. However, these initiatives usually require users to install dedicated apps or multiple sensors, making such solutions hard to scale. Moreover, they emphasise sensing individual factors and overlook social interactions, which plays a significant role in influencing stress and depression while being a part of a social system. We present StressMon, a stress and depression detection system that leverages single-attribute location data, passively sensed from the WiFi infrastructure. Using the location data, it extracts a detailed set of movement, and physical group interaction pattern features without requiring explicit user actions or software installation on client devices. These features are used in two different machine learning models to detect stress and depression. To validate StressMon, we conducted three different longitudinal studies at a university with different groups of students, totalling up to 108 participants. Our evaluation demonstrated StressMon detecting severely stressed students with a 96.01% True Positive Rate (TPR), an 80.76% True Negative Rate (TNR), and a 0.97 area under the ROC curve (AUC) score (a score of 1 indicates a perfect binary classifier) using a 6-day prediction window. In addition, StressMon was able to detect depression at 91.21% TPR, 66.71% TNR, and 0.88 AUC using a 15-day window. We end by discussing how StressMon can expand CSCW research, especially in areas involving collaborative practices for mental health management.
Are Nearby Neighbors Relatives? Testing Deep Music Embeddings

Deep neural networks have frequently been used to directly learn representations useful for a given task from raw input data. In terms of overall performance metrics, machine learning solutions employing deep representations frequently have been reported to greatly outperform those using hand-crafted feature representations. At the same time, they may pick up on aspects that are predominant in the data, yet not actually meaningful or interpretable. In this paper, we therefore propose a systematic way to test the trustworthiness of deep music representations, considering musical semantics. The underlying assumption is that in case a deep representation is to be trusted, distance consistency between known related points should be maintained both in the input audio space and corresponding latent deep space. We generate known related points through semantically meaningful transformations, both considering imperceptible and graver transformations. Then, we examine within- and between-space distance consistencies, both considering audio space and latent embedded space, the latter either being a result of a conventional feature extractor or a deep encoder. We illustrate how our method, as a complement to task-specific performance, provides interpretable insight into what a network may have captured from training data signals.
The Use of Q-ICPMS to Apply Enriched Zinc Stable Isotope Source Tracing for Organic Fertilizers

Organic fertilizer applications can contribute to Zinc (Zn) biofortification of crops. An enriched stable isotope source tracing approach is a central tool to further determine the potential of this biofortification measure. Here, we assessed the use of the widely available quadrupole single-collector ICPMS (Q-ICPMS, analytical error = 1% relative standard deviation) and the less accessible but more precise multicollector ICPMS as reference instrument (MC-ICPMS, analytical error = 0.01% relative standard deviation) to measure enriched Zn stable isotope ratios in soil–fertilizer–plant systems. The isotope label was either applied to the fertilizer (direct method) or to the soil available Zn pool that was determined by isotope ratios measurements of the shoots that grew on labeled soils without fertilizer addition (indirect method). The latter approach is used to trace Zn that was added to soils with complex insoluble organic fertilizers that are difficult to label homogeneously. To reduce isobaric interferences during Zn isotope measurements, ion exchange chromatography was used to separate the Zn from the sample matrix. The 67Zn:66Zn isotope ratios altered from 0.148 at natural abundance to 1.561 in the fertilizer of the direct method and 0.218 to 0.305 in soil available Zn of the indirect method. Analysis of the difference (Bland–Altman) between the two analytical instruments revealed that the variation between 67Zn:66Zn isotope ratios measured with Q-ICPMS and MC-ICPMS were on average 0.08% [95% confidence interval (CI) = 0.68%]. The fractions of Zn derived from the fertilizer in the plant were on average 0.16% higher (CI = 0.49%) when analyzed with Q- compared to MC-ICPMS. The sample matrix had a larger impact on isotope measurements than the choice of analytical instrument, as non-purified samples resulted on average 5.79% (CI = 9.47%) higher isotope ratios than purified samples. Furthermore, the gain in analytical precision using MC-ICPMS instead of Q-ICPMS was small compared to the experimental precision. Thus, Zn isotope measurements of purified samples measured with Q-ICPMS is a valid method to trace Zn sources in soil–fertilizer–plant systems. For the indirect source tracing approach, we outlined strategies to sufficiently enrich the soil with Zn isotopes without significantly altering the soil available Zn pool.
Tau Phosphorylation in a Mouse Model of Temporal Lobe Epilepsy

Hyperphosphorylation of the microtubule-associated protein tau and its resultant aggregation into neurofibrillary tangles (NFT) is a pathological characteristic of neurodegenerative disorders known as tauopathies. Tau is a neuronal protein involved in the stabilization of microtubule structures of the axon and the aberrant phosphorylation of tau is associated with several neurotoxic effects. The discovery of tau pathology and aggregates in the cortex of Temporal lobe epilepsy (TLE) patients has focused interest on hyperphosphorylation of tau as a potential mechanism contributing to increased states of hyperexcitability and cognitive decline. Previous studies using animal models of status epilepticus and tissue from patients with TLE have shown increased tau phosphorylation in the brain following acute seizures and during epilepsy, with tau phosphorylation correlating with cognitive deficits in patients. Suggesting a functional role of tau during epilepsy, studies in tau-deficient and tau-overexpressing mice have demonstrated a causal role of tau during seizure generation. Previous studies, analyzing the impact of seizures on tau hyperphosphorylation, have mainly used animal models of acute seizures. These models, however, do not replicate all aspects of chronic epilepsy. In this study, we investigated the effects of acute seizures (status epilepticus) and chronic epilepsy upon the expression and phosphorylation of tau using the intra-amygdala kainic acid (KA)-induced status epilepticus mouse model. Status epilepticus resulted in an immediate increase in total tau levels in the hippocampus, in particular, the dentate gyrus, and phosphorylation of the AT8 epitope (Ser202, Thr205), with phosphorylated tau mainly localizing to the mossy fibers of the dentate gyrus. During epilepsy, abnormal phosphorylation of tau was detected again at the AT8 epitope with lower total tau levels in the CA3 and CA1 subfields of the hippocampus. Chronic epilepsy in mice also resulted in a strong localization of AT8 phospho-tau to microglia, indicating a distinct pattern of tau hyperphosphorylation during chronic epilepsy compared to status epilepticus. Our results reaffirm previous observations of tau phosphorylation post-status epilepticus, but also elaborate on tau alterations in epileptic mice which more faithfully mimic TLE. Our results confirm seizures affect tau hyperphosphorylation, however, suggest epitope-specific phosphorylation of tau and differences in cell-specific localization according to disease progression.
The Homeodomain Transcription Factor NKX3.1 Modulates Bladder Outlet Obstruction Induced Fibrosis in Mice

Fibrosis is an irreversible remodeling process characterized by the deposition of collagen in the extracellular matrix of various organs through a variety of pathologies in children, leading to the stiffening of healthy tissues and organ dysfunction. Despite the prevalence of fibrotic disease in children, large gaps exist in our understanding of the mechanisms that lead to fibrosis, and there are currently no therapies to treat or reverse it. We previously observed that castration significantly reduces fibrosis in the bladders of male mice that have been partially obstructed. Here, we investigated if the expression of androgen response genes were altered in mouse bladders after partial bladder outlet obstruction (PO). Using a QPCR microarray and QRTPCR we found that PO was sufficient to increase expression of the androgen response gene Nkx3.1. Consistent with this was an increase in the expression of NKX3.1 protein. Immunofluorescent antibody localization demonstrated nuclear NKX3.1 in most bladder cells after PO. We tested if genetic deletion of Nkx3.1 alters remodeling of the bladder wall after PO. After PO, Nkx3.1KO/KO bladders underwent remodeling, demonstrating smaller bladder area, thickness, and bladder: body weight ratios than obstructed, wild type controls. Remarkably, Nkx3.1KO/KO specifically affected histological parameters of fibrosis, including reduced collagen to muscle ratio. Loss of Nkx3.1 altered collagen and smooth muscle cytoskeletal gene expression following PO which supported our histologic findings. Together these findings indicated that after PO, Nkx3.1 expression is induced in the bladder and that it mediates important pathways that lead to tissue fibrosis. As Nkx3.1 is an androgen response gene, our data suggest a possible mechanism by which fibrosis is mediated in male mice and opens the possibility of a molecular pathway mediated by NKX3.1 that could explain sexual dimorphism in bladder fibrosis.
Modeling the Ongoing Dynamics of Short and Long-Range Temporal Correlations in Broadband EEG During Movement

Electroencephalogram (EEG) undergoes complex temporal and spectral changes during voluntary movement intention. Characterization of such changes has focused mostly on narrowband spectral processes such as Event-Related Desynchronization (ERD) in the sensorimotor rhythms because EEG is mostly considered as emerging from oscillations of the neuronal populations. However, the changes in the temporal dynamics, especially in the broadband arrhythmic EEG have not been investigated for movement intention detection. The Long-Range Temporal Correlations (LRTC) are ubiquitously present in several neuronal processes, typically requiring longer timescales to detect. In this paper, we study the ongoing changes in the dynamics of long- as well as short-range temporal dependencies in the single trial broadband EEG during movement intention. We obtained LRTC in 2 s windows of broadband EEG and modeled it using the Autoregressive Fractionally Integrated Moving Average (ARFIMA) model which allowed simultaneous modeling of short- and long-range temporal correlations. There were significant (p < 0.05) changes in both broadband long- and short-range temporal correlations during movement intention and execution. We discovered that the broadband LRTC and narrowband ERD are complementary processes providing distinct information about movement because eliminating LRTC from the signal did not affect the ERD and conversely, eliminating ERD from the signal did not affect LRTC. Exploring the possibility of applications in Brain Computer Interfaces (BCI), we used hybrid features with combinations of LRTC, ARFIMA, and ERD to detect movement intention. A significantly higher (p < 0.05) classification accuracy of 88.3 ± 4.2% was obtained using the combination of ARFIMA and ERD features together, which also predicted the earliest movement at 1 s before its onset. The ongoing changes in the long- and short-range temporal correlations in broadband EEG contribute to effectively capturing the motor command generation and can be used to detect movement successfully. These temporal dependencies provide different and additional information about the movement.
Diversity, Ecology, and Prevalence of Antimicrobials in Nature

Microorganisms possess a variety of survival mechanisms, including the production of antimicrobials that function to kill and/or inhibit the growth of competing microorganisms. Studies of antimicrobial production have largely been driven by the medical community in response to the rise in antibiotic-resistant microorganisms and have involved isolated pure cultures under artificial laboratory conditions neglecting the important ecological roles of these compounds. The search for new natural products has extended to biofilms, soil, oceans, coral reefs, and shallow coastal sediments; however, the marine deep subsurface biosphere may be an untapped repository for novel antimicrobial discovery. Uniquely, prokaryotic survival in energy-limited extreme environments force microbial populations to either adapt their metabolism to outcompete or produce novel antimicrobials that inhibit competition. For example, subsurface sediments could yield novel antimicrobial genes, while at the same time answering important ecological questions about the microbial community.