Miracle-dz/UniFAR-FTUs huggingface dataset:
Scoping review of disease-modifying effect of drugs in experimental epilepsy

Objective Epilepsy affects ~50 million people worldwide causing significant medical, financial, and sociologic concerns for affected patients and their families. To date, treatment of epilepsy is primarily symptomatic management because few effective preventative or disease-modifying interventions exist. However, recent research has identified neurobiological mechanisms of epileptogenesis, providing new pharmacologic targets to investigate. The current scientific evidence remains scattered across multiple studies using different model and experimental designs. The review compiles different models of anti-epileptogenic investigation and highlights specific compounds with potential epileptogenesis-modifying experimental drugs. It provides a platform for standardization of future epilepsy research to allow a more robust compound analysis of compounds with potential for epilepsy prevention. Methods PubMed, Ovid MEDLINE, and Web of Science were searched from 2007 to 2021. Studies with murine models of epileptogenesis and explicitly detailed experimental procedures were included in the scoping review. In total, 51 articles were selected from 14,983 and then grouped by five core variables: (1) seizure frequency, (2) seizure severity, (3) spontaneous recurrent seizures (SRS), (4) seizure duration, and (5) mossy fiber sprouting (MFS). The variables were differentiated based on experimental models including methods of seizure induction, treatment schedule and timeline of data collection. Data was categorized by the five core variables and analyzed by converting original treatment values to units of percent of its respective control. Results Discrepancies in current epileptogenesis models significantly complicate inter-study comparison of potential anti-epileptogenic interventions. With our analysis, many compounds showed a potential to reduce epileptogenic characteristics defined by the five core variables. WIN55,212-2, aspirin, rapamycin, 1400W, and LEV + BQ788 were identified compounds with the potential of effective anti-epileptic properties. Significance Our review highlights the need for consistent methodology in epilepsy research and provides a novel approach for future research. Inconsistent experimental designs hinder study comparison, slowing the progression of treatments for epilepsy. If the research community can optimize and standardize parameters such as methods of seizure induction, administration schedule, sampling time, and aniMal models, more robust meta-analysis and collaborative research would follow. Additionally, some compounds such as rapamycin, WIN 55,212-2, aspirin, 1400W, and LEV + BQ788 showed anti-epileptogenic modulation across multiple variables. We believe they warrant further study both individually and synergistically.
Characteristics of antimicrobial peptide OaBac5mini and its bactericidal mechanism against Escherichia coli

Introduction Antimicrobial peptides (AMPs) play an important role in defending against the attack of pathogenic microorganisms. Among them, the proline-rich antibacterial peptides (PrAMPs) have been attracting close attention due to their simple structure, strong antibacterial activity, and low cell toxicity. OaBac5mini is an active fragment of the sheep-derived OaBac5 belonging to the PrAMPs family. Methods In this study, the antibacterial activity of OaBac5mini was investigated by testing the MICs against different stains of E. coli and S. aureus as well as the time-kill curve. The bactericidal mechanism was explored by determining the effect of OaBac5mini on the cell membrane. The stability and biosafety were also evaluated. Results The susceptibility test demonstrated that OaBac5mini showed potent antibacterial activity against the multidrug-resistant (MDR) E. coli isolates. It is noticeable that the absence of inner membrane protein SbmA in E. coli ATCC 25922 caused the MIC of OaBac5mini to increase 4-fold, implying OaBac5mini can enter into the cytoplasm via SbmA and plays its antibacterial activity. Moreover, the antibacterial activity of OaBac5mini against E. coli ATCC 25922 was not remarkably affected by the serum salts except for CaCl2 at a physiological concentration, pH, temperature, repeated freeze-thawing and proteases (trypsin < 20 μg/mL, pepsin or proteinase K). Time-kill curve analysis showed OaBac5mini at the concentration of 200 μg/mL (8 × MICs) could effectively kill E. coli ATCC 25922 after co-incubation for 12 h. In addition, OaBac5mini was not hemolytic against rabbit red blood cells and also was not cytotoxic to porcine small intestinal epithelial cells (IPEC-J2). Bioinformatic analysis indicated that OaBac5mini is a linear peptide with 8 net positive charges. Furthermore, OaBac5mini significantly increased the outer membrane permeability and impaired the inner membrane integrity and ultrastructure of E. coli ATCC25922. Conclusion OaBac5mini is a stable and potent PrAMP that kills E. coli by two different modes of action - inhibiting intracellular target(s) and damaging cell membrane.
A generalized neuronal activation function derived from ion-channel characteristics

An abstract model neuron, simple enough to be used in analytical studies of neural networks, is defined. It incorporates neuronal adaptation, i.e. the coupling between neuronal activity and excitability, which can control the complexity of neural network dynamics. A generalized neuronal activation function is defined as the output activity, i.e. The firing rate of action potentials, as a function of an input and an excitability variable. For a biological neuron, the intracellular concentration of Ca ions is shown to be a useful excitability variable. The principal features of the generalized activation function are derived by means of a multicompartment model neuron with ionic currents described by Hodgkin-Huxley-type equations. As a relevant neuron type for investigations of cortical associative memory, a neocortical pyramidal cell of the regularly-spiking type is selected. An approximate analytical consideration suggests a simple form of independent variable of the generalized activation function. The c.
Simultaneous and Sensitive Detection of Three Pesticides Using a Functional Poly(Sulfobetaine Methacrylate)-Coated Paper-Based Colorimetric Sensor

Chlorpyrifos (CHL), profenofos (PRO) and cypermethrin (CYP) are widely used in combination to increase crop yields. However, these three pesticides can cause serious harm to human health and do not easily degrade. In this study, a novel visible paper sensor has been prepared successfully and different colorimetric reactions were utilized to detect the three pesticides simultaneously. The sensor was constructed by grafting a zwitterionic polymer onto a cellulose filter (CF) and placing it on a glass surface modified with PDMS. The branch shape was designed to form multiple detection areas, which were modified with specific pesticides and corresponding chromogenic reagents. The as-prepared colorimetric platform exhibited high sensitivity, a short detection time, a good linear response and a low detection limit (LOD) for the three pesticides (chlorpyrifos: y = 46.801 − 1.939x, R2 = 0.983, LOD = 0.235 mg/L; profenofos: y = 40.068 + 42.5x, R2 = 0.988, LOD = 4.891 mg/L; cypermethrin: y = 51.993 + 1.474x, R2 = 0.993, LOD = 4.053 mg/L). The comparison of the results obtained by the proposed paper sensor and those obtained by spectrophotometry further revealed the stability and reliability of the paper sensor. In particular, the color intensity of the interaction between the pesticides and coloring agents could be directly observed by the human eye. The consistency of the colorimetric/optical assay was proven in real target pesticide samples. Thus, this sensing strategy provides a portable, cost-effective, accurate and visualized paper platform, which could be suitable for application in the fruit and vegetable industry for monitoring CHL, PRO and CYP in parallel.
X-ray-standing-wave-modulated electron emission near absorption edges in centrosymmetric and noncentrosymmetric crystals

Energy-dispersive electron-emission yields were measured for (111) Bragg reflections of x rays from Ge and GaAs crystals. The reflection angle was changed continuously over the Bragg reflection range, thus causing the internal x-ray-standing-wave pattern to move across the atomic planes. With the use of synchrotron radiation, these measurements were performed at photon energies below and above the Ga and As E absorption edges. This introduces an energy-dependent position shift of the noncentrosymmetric diffraction planes relative to the atomic planes. It is shown how to determine, from such measurements, (i) the dispersion parameters f' and f"; (ii) lattice deviations, including amorphous and crystalline surface layers; (iii) a mean electron escape depth; and (iv) crystal polarity.
Plasma sheet Pi2 pulsations associated with bursty bulk flows

There is a debate as to whether magnetic Pi2 pulsations (0.006–0.025 Hz) observed in the plasma sheet and on the ground are triggered by the earthward moving bursty bulk flows (BBFs) from midtail or distant tail or are caused by the substorm plasma instabilities initiated in the near‐Earth plasma sheet. To resolve this debate, we conducted case and statistical studies of enhanced plasma sheet Pi2 pulsations using Time History of Events and Macroscale Interactions during Substorms (THEMIS) observations from X~−30 RE to X~−8 RE. The case studies show that for both substorm‐related and quiet time BBFs, enhanced Pi2 oscillations are observed in front of BBFs from midtail to the near‐Earth plasma sheet. The oscillations intensify 1–4 min prior to the substantial flow enhancement, and usually initiate within several narrow discrete frequency bands, with lower frequencies intensifying earlier. We further examined the wave properties using low‐frequency MHD fitting method and found that one or more discrete waves for each event are magnetosonic waves. Our statistical study of 364 BBFs shows that Pi2 pulsations are commonly associated with BBFs throughout the plasma sheet. The lowest‐frequency oscillations usually appear below 0.01 Hz, and the strongest power oscillations appear at ~0.01 Hz or higher frequencies. We found that over 75% of the discrete oscillations are magnetosonic waves, and that 70%–75% of them are slow mode. These suggest that plasma sheet Pi2 pulsations are likely triggered by BBFs in the entire plasma sheet regardless of substorm onsets.
Joining a migrant caravan: herd behaviour and structural factors

Abstract The largest migrant caravan headed from the Northern Triangle of Central America to the southern border of the United States left Honduras on 13 October 2018. When it crossed the border into Mexico, many people wondered why more than 7000 Central Americans were moving to a country with such adverse immigration policies. This research answers the question by interviewing migrants from the Caravan during their travel through Mexico, and combining previously documented factors, such as the search for jobs, better wages, preserving their lives from threats from criminal groups, migration policies and economic interests, with novel explanations derived from herd behaviour in the Caravan. This theoretical addition of herd behaviour allows us to better understand the aggregation of individual preferences that have economic incentives and contributes to the academic debate on the factors that drive collective migrations.
Accuracy and Precision of a Novel Photogate System to Measure Toe Clearance on Stairs

Background: Toe clearance on stairs is typically measured using optoelectronic systems, though these are often constrained to the laboratory, due to their complex setups. Here we measured stair toe clearance through a novel prototype photogate setup and compared this to optoelectronic measurements. Methods: Twelve participants (age 22 ± 3 years) completed 25 stair ascent trials, each on a seven-step staircase. Toe clearance over the fifth step edge was measured using Vicon and the photogates. Twenty-two photogates were created in rows through laser diodes and phototransistors. The height of the lowest photogate broken at step-edge crossing was used to determine photogate toe clearance. A limits of agreement analysis and Pearson’s correlation coefficient compared the accuracy, precision and relationship between systems. Results: We found a mean difference of −1.5 mm (accuracy) between the two measurement systems, with upper and lower limits (precision) of 10.7 mm and −13.8 mm, respectively. A strong positive correlation was also found (r = 70, n = 12, p = 0.009) between the systems. Discussion: The results suggest that photogates could be an option for measuring real-world stair toe clearances, where optoelectronic systems are not routinely used. Improvements to the design and measurement factors may help to improve the precision of the photogates.
Efficient visualization of 3D city scenes by integrating the GIS and Unreal Engine

Achieving a smooth and high-fidelity visualization of 3D city scenes in virtual geographic environment is a key technology for digital twins. Geographical information system (GIS) researchers have proposed many methods for loading and visualizing such city-scale scenes. However, if the scale of the scene is too large, the current methods cannot achieve a smooth and high-fidelity visualization of 3D city scenes. In this study, we propose an efficient visualization method for 3D city scenes through calculating potential visible sets (PVS) and hierarchical levels of detail (HLOD). We use adaptive quadtree partition to divide the 3D city scenes. Then, we calculate the potential visible set of each leaf node using an improved ray-casting algorithm, and visual perception parameters model were evaluated by employing the screen error, which was used to constrain the dynamic scheduling of HLOD. We implemented our method on Unreal Engine (UE4) and designed multiple sets of controlled experiments to illustrate the advantages of our method in terms of visualization efficiency and rendering effect. The results show that our method can significantly improve the visualization fluency, maintain good global and local detail.
Matrix polynomials and their inversion: the algebric framework of unit-root econometrics representation theorems

In this paper the issue of the inversion of a matrix polynomial about a unit root is tackled by resorting to Laurent expansion: The principal-part matrix coefficients associated with a simple and a second order pole are properly characterized and closed-form expressions are derived by virtue of a recent result on partitioned inversion (Faliva and Zoia, 2002). This eventually sheds more light on the analytical foundations of unit-root econometrics which in turn paves the way to an elegant unified representation theorem for (co)integrated processes up to the second order.
The Effect of Business Intelligence on Bank Operational Efficiency and Perceptions of Profitability

The purpose of the study is to examine the effects of business intelligence on the bank’s operational efficiency and perceptions of profitability. The study is based on 259 responses from 27 branches of a commercial bank, employing a simple random sampling technique. This research uses the partial least square- structural equation method (PLS-SEM) method to test the hypotheses. The study verifies construct’s reliability and construct’s validity of the measurement model, and tests the fitness of the structural model. The study finds that business intelligence is positively associated with operational efficiency and profitability. Further, the study reveals that operational efficiency through business intelligence positively affects bank’s profitability. Based on competitive theory, this research states that business intelligence allows the productive entity to generate superior margins compared to its market rivals. Thus, banks can offer better options more cheaply than their rivals and thereby ensure competitive advantage. Further, based on resource-based view theory, the study argues that business intelligence as a strategic resource can provide the foundation to develop bank capabilities that can lead to superior performance over time. Therefore, the study implies business intelligence application in the banking companies and helps decision-making effectiveness for the management body of banks, academics, and policymakers.
Metabolomics-based response of Salmonella to desiccation stress and skimmed milk powder storage

The strong survival ability of Salmonella in low-moisture foods (LMFs) has been of public concern, and is considered a threat to people’s health. Recently, the development of omics technology has promoted research on the molecular mechanisms of the desiccation stress response of pathogenic bacteria. However, multiple analytical aspects related to their physiological characteristics remain unclear. We explored the physiological metabolism changes of S. enterica Enteritidis exposed to a 24 h-desiccation treatment and a subsequent 3-month desiccation storage in skimmed milk powder (SMP) with an approach of gas chromatography–mass spectrometry (GC–MS) and ultra-performance liquid chromatography-Q Exactive-mass spectrometry (UPLC-QE-MS). A total of 8,292 peaks were extracted, of which 381 were detected by GC–MS and 7,911 peaks were identified by LC–MS/MS, respectively. Through analyses of differentially expressed metabolites (DEMs) and key pathways, a total of 58 DEMs emerged from the 24 h-desiccation treatment, which exhibited the highest relevance for five metabolic pathways, involving glycine, serine, and threonine metabolism, pyrimidine metabolism, purine metabolism, vitamin B6 metabolism, and pentose phosphate pathway. After 3-month SMP storage, 120 DEMs were identified, which were related to several regulatory pathways including arginine and proline metabolism, serine and threonine metabolism, β-alanine metabolism, glycerolipid metabolism, and glycolysis. The analyses of key enzyme activities of XOD, PK, and G6PDH and ATP content provided further evidence that supported the metabolic responses such as nucleic acid degradation, glycolysis, and ATP production played an important role in Salmonella’s adaptation to desiccation stress. This study enables a better understanding of metabolomics-based responses of Salmonella at the initial stage of desiccation stress and the following long-term adaptive stage. Meanwhile, the identified discriminative metabolic pathways may serve as potentially useful targets in developing strategies for the control and prevention of desiccation-adapted Salmonella in LMFs.
Bilateral Lateral Rectus Recession in Duane Retraction Syndrome Type II: A Case Report

A two year presented to the clinic with abnormal head posture and right-sided face turn since birth. On examination, he showed a large right face turn of 40° while concentrating on a near target. His ocular motility assessment showed a -4 limitation of adduction in the left eye with 40 prism diopters (PD) exotropia and grade 1 globe retraction of the left eye. He was diagnosed with type II Duane retraction syndrome (DRS) in the left eye and planned for lateral rectus recession of both eyes. Postoperatively, the patient was orthotropic at distance and near in primary gaze with resolved face turn and improvement of limitation of adduction to -2, but some limitation of abduction -1 in the left eye was observed. Herein, we discuss the clinical features, etiologies, tailored evaluation, and management for type II DRS patient.
The Reliability of Subjective Probabilities: Obtained Through Decomposition

The use of decomposition as a procedure for improving the consistency of subjective probability encoding is discussed. Using a psychometric measurement model, an expression is developed that describes the random error associated with decomposition estimates as a function of characteristics of the component assessments. Decomposition is compared to direct assessment in terms of the percent change in measurement error that can be attributed to the use of decomposition. Potential benefits of decomposition are specified and recommendations made on how to utilize decomposition as an approach for error control.
ORC-UNet: optimal residual semantic segmentation network based on U-Net architecture for high-resolution remote sensing imagery

Nowadays, semantic segmentation is commonly used to solve various remote sensing image problems. Furthermore, it has emerged as a critical technology for remote sensing image applications. In recent years, with the widespread application of deep learning in computer vision, deep learning semantic segmentation has been appreciated by more remote sensing researchers. Its performance depends on the learning of remote sensing data by the model. However, the complexity and multiplicity of remote sensing data lead to the increased difficulty of learning remote sensing data, and also reduce the ability of the model to segment high-resolution remote sensing images. To improve the model performance for deep learning semantic segmentation, many improvement methods have been proposed, such as batch regularization (BN), data augmentation, and residual networks. However, most of the methods are optimization strategies for deep learning with natural domain images. Further exploration of the effectiveness of related methods in specific application areas is necessary. In high-resolution remote sensing images, the correlation between segmentation model hyperparameter settings and residual networks has rarely been investigated, which makes the residual methods inadequately applied to the semantic segmentation of high-resolution remote sensing images. In this paper, an optimal residual semantic segmentation network based on the U-Net architecture is proposed. The ORC-UNet not only considers the loss function configuration of the model, but also the initial filter number setting of the model. With these two hyperparameter configurations, the residual method can effectively improve the segmentation performance of the model. In order to confirm the effectiveness of ORC-UNet, comprehensive experiments are conducted on the Potsdam dataset in this paper. The experimental results show that ORC-UNet achieves the best overall segmentation performance with an F1-score value of 74.44%, and it also achieves the best performance in three categories of the dataset (Background, Building, and Roads) with F1-score values of 30.78%, 89.58%, and 86.05%, respectively. Meanwhile, ORC-UNet is also close to the best results for the remaining categories. In addition, the relevant comparison results also indicate that the cross-entropy loss function and initialization value 64 of ORC-UNet are the best configurations. Meanwhile, ORC-UNet is the best segmentation model among all residual models.
Hollow cathode theory and experiment. II. A two-dimensional theoretical model of the emitter region

Despite their long history and wide range of applicability that includes electric propulsion, detailed understanding of the driving physics inside orificed hollow cathodes remains elusive. The theoretical complexity associated with the multicomponent fluid inside the cathode, and the difficulty of accessing empirically this region, have limited our ability to design cathodes that perform better and last longer. A two-dimensional axisymmetric theoretical model of the multispecies fluid inside an orificed hollow cathode is presented. The level of detail attained by the model is allowed by its extended system of governing equations not solved for in the past within the hollow cathode. Such detail is motivated in part by the need to quantify the effect(s) of the plasma on the emitter life, and by the need to build the foundation for future modeling that will assess erosion of the keeper plate. Results from numerical simulations of a 1.2-cm-diam cathode operating at a discharge current of 25A and a gas flow ra.