Miracle-dz/UniFAR-FTUs huggingface dataset:
The attachment length in orificed hollow cathodes

A first-principles approach to obtain the attachment length within a hollow cathode with a constrictive orifice, and its scaling with internal cathode pressure, is developed. This parameter, defined herein as the plasma density decay length scale upstream of (away from) the cathode orifice, is critical because it controls the utilization of the hollow cathode insert and influences cathode life. A two-dimensional framework is developed from the ambipolar diffusion equation for the insert-region plasma. A closed-form solution for the plasma density is obtained using standard partial differential equation techniques by applying an approximate boundary condition at the cathode orifice plane. This approach also yields the attachment length and electron temperature without reliance on measured plasma property data or complex computational models. The predicted plasma density profile is validated against measurements from the NSTAR discharge cathode, and calculated electron temperatures and attachment lengths agree with published values. Nondimensionalization of the governing equations reveals that the solution depends almost exclusively on the neutral pressure-diameter product in the insert plasma region. Evaluation of analytical results over a wide range of input parameters yields scaling relations for the variation of the attachment length and electron temperature with the pressure-diameter product. For the range of orifice-to-insert diameter ratio studied, the influence of orifice size is shown to be small except through its effect on insert pressure, and the attachment length is shown to be proportional to the insert inner radius, suggesting high-pressure cathodes should be constructed with larger-diameter inserts.
Analysis of Factors Influencing Longitudinal Force of Welded Turnout on Simply Supported Beam Bridge

Based on the characteristic of longitudinal interaction of welded turnout on a bridge,a finite element model for welded turnout-bridge-platform was established.By taking No.18 welded turnout on a simply supported beam bridge as an example,factors influencing its longitudinal force and displacement were analyzed.These factors are the temperature of rail,the temperature of bridge,the length of beam,the layout of support,the stiffness of pier,the structure of frog heel,and the resistance of fastening and ballast.Calculational results show that the influence range of welded turnout on a simply supported beam bridge was within two spans.The arrangement of welded turnout on simply supported beam bridges should make the expansion displacement directions of the turnout lead rail and the beam be opposite.The longitudinal stiffness of piers under welded turnout should be increased,and spacer block should not be adopted as the frog heel of welded turnout on a simply supported beam bridge.The No.18 welded turnout is suitable for laying on a simply supported beam bridge with a span of 32 or 48 m.
Stratified and Un-stratified Sampling in Bagging: Data Mining

: Stratified sampling is often used in opinion polls to reduce standard errors, and it is known as variance reduction technique in sampling theory. The most common approach of resampling method is based on bootstrapping the dataset with replacement. A main purpose of this work is to investigate extensions of the resampling methods in classification problems, specifically we use decision trees, from a family of stratification models to improve prediction accuracy by aggregating classifiers built on a perturbed dataset. We use bagging, as a method of estimating a good decision boundary according to a family of stratification models. The overall conclusion is that for decision trees, un-stratified bootstrapping with bagging can yield lower error rates than other sampling strategies for simulated datasets. Based on the results in these experiments, a possible explanation as to why un-stratified sampling is a best is because bagging is itself a method of stratification.
THE EFFECT OF ORGANISATIONAL CYNICISM ON EMPLOYEE PERFORMANCE: TESTING THE AFFECTIVE, COGNITIVE AND BEHAVIOURAL DIMENSIONS

Organisational cynicism is one of the understudied topics, which is being overlooked in organisations for a long period of time. This has three dimensions: cognitive-lack of sincerity, honesty in organisation; Affective: emotional and sentimental responses towards the workplace; and Behavioural: showing negative attitude within workplace. Moreover, it results in decreased motivation, interpersonal conflicts, absenteeism, low organisational commitment, and low efficiency, dissatisfaction in work, unethical behaviour and reluctance in organisational citizenship behaviour. The Antecedents and consequences of organisational cynicism can be taken into account while calculating the turnover of the employees, efficiency and overall productivity of the organisation. Organisational cynicism can also be considered as one of the important factors to study whether an employee is happy with their organisation, their team mates, managers and the organisational climate. This study compares this variable with the performance of the employees. In the previous studies, job satisfaction was studied as one of the consequences of the study. There are only a few literatures which study the impact of organisational cynicism on performance. And most of these researches were conducted in either teaching or banking industries across the world. In the last three decades, IT industry has been the most outsourced industry from India. This Industry also contributes about 7.7% towards the GDP in India. From the studies of the performance of the employees in the IT industry, it has showed that lack of proper leadership, over-timing, Journal of Contemporary Issues in Business and Government Vol. 27, No. 2,2021 https://cibg.org. au/ P-ISSN: 2204-1990; E-ISSN: 1323-6903 DOI: 10.47750/cibg.2021. 27.02. 493 4694 inefficiency of the manager were some of the major sources of stress to the employees. This links the external factors of performance with consequences of organisational cynicism, which is employee burnout. So it is about time that a study analyses whether there is existence of organisational cynicism in the Industry, and relate it to the performance of the employees and the demographic factors which might also contribute to it. A conceptual model of organizational cynicism was developed as a result. This study focuses on the IT employees from one of the major software Hubs in India, which is Bangalore.
Potential pharmacokinetic and pharmacodynamic herb-drug interactions of Andrographis paniculata (Burm. f.) and andrographolide: A systematic review

Introduction: Herb–drug interactions (HDIs) in pharmacokinetics and pharmacodynamics can occur when natural compounds are used in combination with drugs. This study aimed to review the potential interaction of Andrographis paniculata (Burm. f.) extract (APE) and its primary compound andrographolide (AND) with several drugs exhibiting various pharmacological activities.Methods: In this systematic review, articles were collected from international databases such as PubMed, Science Direct, Springer Link, and Scopus until August 2021. The following keywords were used: Andrographis paniculata, andrographolide, HDI, drug interaction, pharmacokinetics, and pharmacology. This review was written in accordance with the guidelines of the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA), SYRCLE’s risk of bias (RoB) tool for animal intervention studies, and Cochrane RoB 2 tool to analyze the RoB for qualitative assessment.Results: Twelve articles were included in accordance with the inclusion and exclusion criteria of this study. Five studies explored the potential of HDIs for combining APE with drugs and AND with theophylline, etoricoxib, nabumetone, naproxen, and tolbutamide. Five studies focused on AND in combination with aminophylline and doxofylline, meloxicam, glyburide, glimepiride, metformin, and warfarin. Two studies tested the combination of APE with gliclazide and midazolam. The HDI mechanism involving the inhibition or induction of cytochrome P450 enzyme expression was dominant in influencing the drug’s pharmacokinetic profile. Pharmacological studies on the combination of several drugs, particularly anti-inflammatory and antidiabetic drugs, showed a synergistic activity.Conclusion: APE and AND have potential pharmacokinetic and pharmacodynamic HDIs with various drugs. This study can be used as a therapeutic consideration in clinical aspects related to the possibility of HDIs of A. paniculata (Burm. f.).
Neurons in the Network Learning in Governance Networks in the Context of Environmental Management

In the face of apparent failures to govern complex environmental problems by the central state, new modes of governance have been proposed in recent years. Network governance is an emerging concept that has not yet been consolidated. In network governance, processes of (collective) learning become an essential feature. Collective learning refers to cognitive changes in individuals within a network and is moreover understood as a process in which individual changes in cognition lead to modifications in collective institutions. The key issue this paper seeks to approach is the mutual relation between network structures and collective learning with the aim to improve environmental management. As of now, there have been few attempts to apply techniques of Social Network Analysis (SNA) to collective learning and governance issues. Given the ambiguities of the concepts at stake, we begin by explicating our understanding of both networks and collective learning. We consider learning-related functions that networks can perform to different degrees: information transmission, deliberation, and resilience. We address two main research questions: (1) What are the characteristics of networks that foster collective learning in each of the three dimensions? To this end, we consider SNA-based network measures such as network size, density, cohesion, centralisation, or the occurrence of weak vs. strong ties. (2) How does collective learning alter network structures? We conclude by outlining a number of open issues for further research.
Microsoft Word-31088317-file00

Cytochrome P450scc (CYP11A1) can hydroxylate vitamin D3 producing 20S-hydroxyvitamin D3 [20(OH)D3] and 20S,23-dihydroxyvitamin D3 [20,23(OH)2D3] as the major metabolites. These are biologically active acting as partial vitamin D receptor [VDR] agonists. Minor products include 17-hydroxyvitamin D3, 17,20-dihydroxyvitamin D3 and 17,20,23trihydroxyvitamin D3. In the current study we have further analyzed the reaction products from P450scc action on vitamin D3 and have identified two 22-hydroxy-derivatives as products, 22hydroxyvitamin D3 [22(OH)D3] and 20S,22-dihydroxyvitamin D3 [20,22(OH)2D3]. The structures of both of these derivatives were determined by NMR. P450scc could convert purified 22(OH)D3 to 20,22(OH)2D3. The 20,22(OH)2D3 could also be produced from 20(OH)D3 and was metabolized to a trihydroxyvitamin D3 product. We compared the biological activities of these new derivatives to those of 20(OH)D3, 20,23(OH)2D3 and 1α,25-dihydroxyvitamin D3 [1,25(OH)2D3]. 1,25(OH)2D3, 20(OH)D3, 22(OH)D3, 20,23(OH)2D3 and 20,22(OH)2D3 significantly inhibited keratinocyte proliferation in a dose dependent manner. The strongest inducers of involucrin expression (a marker of keratinocyte differentiation) were 20,23(OH)2D3, 20,22(OH)2D3, 20(OH)D3 and 1,25(OH)2D3, with 22(OH)D3 having a heterogeneous effect. Little or no stimulation of CYP24 mRNA expression was observed for all the analogues tested except for 1,25(OH)2D3. All the compounds stimulated VDR translocation from the cytoplasm to the nucleus with 22(OH)D3 and 20,22(OH)2D3 having less effect than 1,25(OH)2D3 and 20(OH)D3. Thus we have identified 22(OH)D3 and 20,22(OH)2D3 as products of CYP11A1 action on vitamin D3 and shown that like 20(OH)D3 and 20,23(OH)2D3, they are active on keratinocytes via the VDR, however, showing a degree of phenotypic heterogeneity in comparison to other P450scc-derived hydroxy-metabolites of vitamin D3. DMD #40071 This article has not been copyedited and formatted. The final version may differ from this version. DMD Fast Forward. Published on June 15, 2011 as DOI: 10.1124/dmd.111. 040071 at A PE T Jornals on M arch 6, 2022 dm d.aspurnals. org D ow nladed from
The Influence of the Probiotic "Rescue Kit" On the Growth and Development of Accelerated Rabit Youngsters under the Conditions of Northern Kazakhstan

The article presents the results of application of probiotic preparation "Rescue Kit" (Germany) for rearing of early developed rabbits of "White Giant”, «Soviet Chinchilla» breeds and their hybrids. Probiotic "Rescue Kit" is a homogeneous fine powder white to cream color with a slight milky odor. Feed additive contains a freeze-dehydrated culture of Bacillus subtilis and Bacillus licheniformis. The use of probiotic preparation "Rescue Kit" in the diets of young animals normalizes gastrointestinal tract, improves accessibility of feeding stuff, increases average daily gains, and ensures better preservation of young animals up to their slaughter. It is revealed that the application of probiotic "Rescue Kit" in various doses provided the improving effect on the accessibility of dietary nutrients in young early developed rabbits of different groups.
An Adaptive CMT-SCTP Scheme: A Reinforcement Learning Approach

With the continuous increase of end users and types of services, the scale of the network has shown explosive growth, which has brought tremendous pressure and challenges to network data transmission. How to achieve high-quality data transmission has become a core issue. Single-path transmission has been difficult to meet the above requirements. The concurrent multipath transfer extension for stream control transmission protocol (CMT-SCTP), which supports multipath and independent data streams, can solve this problem. However, the current transmission path assessment scheme has too large granularity to make full use of the resources of the transition zone. Most studies ignore the different requirements of different services, a single transmission strategy, and the lack of an intelligent dynamic adjustment mechanism. Therefore, we designed a QCMT(Q-learning based CMT-SCTP) scheduling method. This method considers the multi-dimensional characteristics of the path and the characteristic preferences of different services, periodically evaluates and trains the reinforcement learning model for service adaptation, and makes scheduling decisions dynamically. Experimental results show that dynamic scheduling based on path parameters and service preferences can reduce message delay and improve network throughput.
South African commoning, cooperatives and eco-socialist potentials in the context of Covid-19

Covid-19 began to spread across South Africa starting on March 1, 2020, initiated by a group of friends (white, upper-middle-class) who returned that day, via Dubai on Emirates, from a skiing trip in northern Italy. Most of them tested positive, spreading the disease quickly in a society whose neo-apartheid-style health system threatened to buckle. Other travellers with similar race and class privileges transmitted new strains. By March 26, the government imposed one of the world’s most rigorous public health interventions: a lockdown knocking out at least three quarters of economic activity. On May 4 there was a slight relaxation, and at that stage, the ‘essential services’ workers were joined by another quarter of the formalsector workforce who were allowed to return to their jobs. (Together that still accounted for only a fifth of the active labour force receiving permission to be back at work, with most of the informal sector still disallowed from activity deemed by the state to be non-essential).
Component Learning Community for Informal Education to Support Culinary Community at Era New Normal Covid-19: A Systematic Literature Review

Informal education will be successful as an alternative for the community because not all people are able to receive formal education. This study uses a qualitative method with a systematic literature review (SLR) technique to look for learning community components in informal education to support learning in the culinary community in the new normal era of Covid-19. The author collects, studies, and analyzes reference sources according to the specified keywords. Found 53 papers from 2002 to 2021 with background authors from academia, industry, and the public sector with reference sources from journals, conferences, white papers, and research reports. Systematic literature review results obtained 6 components of learning community in informal education, namely content, forum, method, technology, figure/layout, and human/social resources. The six components as a reference and the author's first step in the next research through searching for the characteristics of the learning community in the culinary field, then making a learning model of the culinary community. Because of the importance of the learning community component in informal education to help community members share knowledge, solve problems, share common goals and interests among community members.
Micro air vehicle flight simulation system based on DirectX

A flight simulation system of micro air vehicle is introduced.This system running on PC/Windows is developed by VC++6.0 and DirectX API.In the modeling of flight simulation,a six-degree-of-freedom whole non-linear equation and wind-tunnel tests data of MAV are used,the propeller twist and induced air flow on MAV are took into account.Except for MAV flight dynamics analysis,this software has practical value for design,flight test and reconnaissance evaluation of MAV.
Natural Language Models to Identify Internet Hate Speech

In this paper, we have reimplemented an LSTM based model to detect online hate speech from a 2018 paper (Gao, L. and Huang, R.) which evaluated performance of various neural network and logistic regression based models on the task of identifying hate speech with context. To evaluate the robustness of this model to determine whether it has potential to be expanded, we have prepared a new data set of comments from recent news articles. The model is fairly robust against time, with a reduction in accuracy by only 6.17 percent after 5 years, which can be potentially even lower if the model is trained for less epochs to reduce overﬁtting.
“Good tool but too soon”? Effects and processes of a mHealth intervention for management of chronic diseases – a prospective observational study

Background: MHealth interventions for self-management and self-management support are a promising way to meet the needs of patients with multimorbidity and primary care practices. Therefore, an mHealth intervention TelePraCMan in German primary care setting was developed and evaluated. Objective: We examined the effects of TelePraCMan on patient activation and quality of life and explored underlying contextual factors, impacts, and degree of implementation. Methods: In a prospective observational study design, we collected data using interviews and written questionnaires in participating patients (intervention and control group) and primary care workers (physicians and practice assistants). Primary outcomes of interest were patient reported quality of life (SF-12) and patient activation (PAM). Quantitative analysis focused on differences between patients of the intervention and control group. Interviews were analysed using qualitative content analysis
Lipid profile of the ethanol-methanol (1:1) extracts of Anacadium occidentale and Jatropha tanjorensis administration in Wistar rats

Hyperlipidaemia is characterized by an increase in one or more of the plasma lipids. This study evaluated the lipid profile of albino Wistar rats administered ethanol-methanol extracts of Anacadium occidentale and Jatropha tanjorensis leaves. Twenty-five (25) male Wistar rats weighing between 180 220 g were divided into five (5) groups of five (5) rats each and treated thus: Group 1 (normal control received normal saline), group 2 and 3 administered low dose (400 mg/kg-1 b.wt.) and high dose (800 mg/kg-1 b.wt.) of Anacadium occidentale extract respectively, group 4 and 5 administered low dose (400 mg/kg-1 b.wt.) and high dose (800 mg/kg-1 b.wt.) of Jatropha tanjorensis extract respectively. At the end of the experiment, the rats were sacrificed to obtain the sera for the evaluation of serum lipid profile. The result revealed a significant (P<0.05) decrease in TC in all the groups except group IV compared with control. There was a significant (P<0.05) increase in TG and VLDL-c levels in all groups compared with control. HDL-c level significantly (P<0.05) increased in group III only compared with control. LDL-c level significantly (P<0.05) decreased in group III and V only compared with control. The LDL-c/HDL-c ratio showed no significant (P≥0.05) difference between groups II, V and control, however group III significantly (P<0.05) decreased and group IV significantly (P<0.05) increased compared with the rest groups. The study suggests that the plant extracts possess lipid lowering potentials and may be employed in the treatment of metabolic disorders such as obesity and cardiovascular diseases.
Ultra-low Latency Spiking Neural Networks with Spatio-Temporal Compression and Synaptic Convolutional Block

Spiking neural networks (SNNs), as one of the brain-inspired models, has spatio-temporal information processing capability, low power feature, and high biological plausibility. The effective spatio-temporal feature makes it suitable for event streams classification. However, neuromorphic datasets, such as N-MNIST, CIFAR10-DVS, DVS128-gesture, need to aggregate individual events into frames with a new higher temporal resolution for event stream classification, which causes high training and inference latency. In this work, we proposed a spatio-temporal compression method to aggregate individual events into a few time steps of synaptic current to reduce the training and inference latency. To keep the accuracy of SNNs under high compression ratios, we also proposed a synaptic convolutional block to balance the dramatic change between adjacent time steps. And multi-threshold Leaky Integrate-and-Fire (LIF) with learnable membrane time constant is introduced to increase its information processing capability. We evaluate the proposed method for event streams classification tasks on neuromorphic N-MNIST, CIFAR10-DVS, DVS128 gesture datasets. The experiment results show that our proposed method outperforms the state-of-the-art accuracy on nearly all datasets, using fewer time steps.
Modeling soft sensor based on support vector machine and particle swarm optimization algorithms

The estimation of 4-CBA (carboxybenzaldchydc) concentration in industrial PTA (purified terephthalic acid) oxidation process is of fundamental importance in process monitoring,advanced control and optimization.The support vector machine (SVM) and particle swarm optimization (PSO) algorithms are used to estimate the parameters of the first principle model.The training set for estimating the parameters is the feature subset selected by SVM regression algorithm, which overcomes the drawback of the trail-and-error method.Parameter estimation method based on the PSO algorithm is also used to avoid dependence on initial parameters and training samples.By use of real industrial data,the simulation results show that the presented method is effective for modeling the soft sensor of 4-CBA concentration in industrial PTA oxidation process.