Miracle-dz/UniFAR-FTUs huggingface dataset:
Intelligent fault diagnosis of rolling bearing using one-dimensional multi-scale deep convolutional neural network based health state classification

Fault diagnosis of rolling element bearings based on vibration signal is the most popular way to avoid underlying damage for any unexpected fault. In recent years, intelligent fault diagnosis algorithms using machine learning technique have achieved much success, and many deep learning techniques have also found their way into fault diagnosis of rotating machines. Considering that convolution is the most important method to analyze signals in digital signal processing, a novel deep convolutional neural networks is developed to operate directly on the raw vibration signal. The proposed MS-DCNN model could broaden and deepen the neural networks to learn better and more robust feature representations owing to multi-scale convolution layer, meanwhile, reduce the network parameters and the training time. Fault classification experiments of rolling element bearings have been undertaken to indicate the effectiveness of the MS-DCNN model. Compared with 1d-DCNN and 2d-DCNN, MS-DCNN can not only achieve higher accuracy rate in the testing set, but also run more smoothly in the training process.
semantic analysis : The case of word level semantics in Danish

The present research is motivated by the need for accessible and efficient tools for automated semantic analysis in Danish. We are interested in tools that are completely open, so they can be used by a critical public, in public administration, non-governmental organizations and businesses. We describe data-driven models for Danish semantic relatedness, word intrusion and sentiment prediction. Open Danish corpora were assembled and unsupervised learning implemented for explicit semantic analysis and with Gensim’s Word2vec model. We evaluate the performance of the two models on three different annotated word datasets. We test the semantic representations’ alignment with single word sentiment using supervised learning. We find that logistic regression and large random forests perform well with
Retaining Mathematics and Science Teachers in Rural and Remote Schools

Why teachers in remote and rural schools do not remain longer in their posts is a central concern in Australian education. In particular, the lack of mathematics and science teachers in regional areas has reached critical levels endangering the adequate delivery of the curriculum to thousands of school students. While many teachers‘ personal grievances revolved about geographical isolation, other factors point at a number of instructional, curricular and organisational factors influencing teacher attrition. This study characterises and examines those factors using data from 191 teachers in 27 remote and rural schools in the State of New South Wales (NSW). The findings suggest a professional environment where, as mostly beginning practitioners, teachers are put into work situations with related pressing demands and expectations, puts them at risk.
Assessment of Phycoremediation Efficiency of Spirogyra Sp. Using Sugar Mill Effluent

Phycoremediation is the use of algae for the removal of pollutants from wastewater since algal species are relatively easy to grow, adapt and manipulate within a laboratory setting and appear to be ideal organisms for use in remediation studies. The present investigation was carried out to determine the phycoremediation potential of Spirogyra sp. using sugar mill effluent. The results of the present study revealed that sugar mill effluent is considerable loaded with TDS, EC, BOD, COD, TKN, PO43- , Ni, Cr, Fe and Mn. The phycoremediation studies showed that the maximum removal of TDS (24.92%), EC (14.47%), pH (11.47%), BOD (47.82%), DO (21.46%), COD (15.73%), TKN (40%), PO43- (44.44%), Ni (42.79%), Cr (40.74%), Fe (24.78%) and Mn (34.92%) was recorded after 60 days of phycoremediation experiments using Spirogyra sp. moreover, the removal of TDS, EC, BOD, COD, TKN, PO43- , Ni, Cr, Fe and Mn of the sugar mill effluent was progressively increased at 15, 30, 45 and 60 days of phycoremediation experiments using Spirogyra sp. Therefore, the phycoremediation study clearly indicated the effectiveness of microalgae Spirogyra sp. for the removal of nutrients and heavy metals present in the sugar mill effluent.
Starting size and tadpole performance in the frog Rana latastei

Egg provisioning is a major maternal effect in amphibians. We evaluated the relationship between starting body size (a proxy of egg provisioning) and multiple measures of larval performance in the Italian agile frog Rana latastei; we analysed within-clutch variation, to remove co-variation between provisioning and genetic maternal effect. We reared tadpoles from multiple clutches in a common environment under two food treatments (high- and low-protein content), and measured the mortality, tadpole size during development and development rate. We used a Bayesian framework (Markov chain Monte Carlo generalized linear mixed models) for the multivariate analysis of performance measures. Tadpoles with a large starting size remained the largest ones through the entire larval development, and attained metamorphosis earlier. Food with a high-protein content reduced mortality and increased the growth and development rate; the choice of food may be important in captive-breeding/headstarting programmes. We did not detect effects of the interaction between provisioning and type of food on tadpole performance. Our study confirms the importance of egg provisioning in amphibians, showing that it can affect multiple traits, and that their effects can last through the entire larval development.
Influence of Chromolaena odorata compost on growth and yield of finger millet

Chromolaena odorata is an invasive weed posing problems in plantation crops and replacing existing fauna in high rain fall areas of Karnataka. Chromolaena produce 3 to 4 kg biomass/m 2 in non-cropped areas in high rain fall areas and contains nutrient equivalent to that of traditional green manure crops. It’s utility for composting or green manure can serve as alternative strategy to contain the weed. Field study was planned under this content at Main Research Station, Hebbal, University of Agricultural Sciences, Bengaluru, during Kharif 2013 in irrigated finger millet. The treatments comprised of various combinations of Chromolaena’s compost with recommended dose of fertilizer (RDF), RDF+ farm yard manure (FYM), RDF alone and unfertilized control. Finger millet receiving recommended fertilizer alone resulted in significantly lower total dry matter production per plant, yield and yield components than various combination of Chromolaena’s compost with RDF and RDF+ FYM. Higher grain yield (5367 kg ha -1 ) obtained in application of Chromolaena odorata (90%) + cow dung slurry (10%) + microbial slurry + rock phosphate @ 7.5 t.ha -1 +RDF (5367 kg ha -1 ) and Chromolaena odorata (90%) + cow dung slurry (10%) + microbial culture @ 7.5 t.ha -1 +RDF over RDF alone (5142 kg/ha).
Palmitoylation and Plasma Membrane Targeting of RGS7 Are Promoted by αo

Regulator of G protein signaling (RGS) proteins modulate G protein signaling by acting as GTPase-activating proteins for G protein α-subunits. RGS7 belongs to a subfamily of RGS proteins that exist as dimers with the G protein β5-subunit. In this report, we addressed the mechanisms of plasma membrane localization of β5RGS7. When expressed in human embryonic kidney 293 cells, β5RGS7 was found to be cytoplasmic and soluble. Expression of αo promoted a strong redistribution of β5RGS7 to the plasma membrane. Expression of αq, however, failed to affect the subcellular localization of β5RGS7. The constitutively active mutant αoR179C, like wild-type αo, strongly recruited β5RGS7 to plasma membranes; however, inactive αoG204A, RGS-insensitive αoG184S, and lipidation-deficient αoG2A were all defective in the ability to promote plasma membrane localization of β5RGS7. In addition, palmitoylation of RGS7 was demonstrated, and palmitoylation required expression of αo or αoR179C. To examine potential palmitoylation sites of RGS7, several cysteines were substituted with serines. β5RGS7C133S failed to localize to plasma membranes when coexpressed with αo, suggesting cysteine 133 of RGS7 as a putative palmitoylation site. Finally, deletion of amino acids 76 to 128 of RGS7, which includes part of the disheveled, EGL-10, pleckstrin (DEP) domain, prevented αo-mediated plasma membrane recruitment of β5RGS7. These findings are the first to demonstrate Gα-regulated plasma membrane localization and palmitoylation of β5RGS7 and suggest that membrane targeting of β5RGS7 is a complex process requiring at least RGS domain-mediated interaction with αo and RGS7 palmitoylation.
A machine learning approach to TCP state monitoring from passive measurements

Many applications in the Internet use the reliable end-to-end Transmission Control Protocol (TCP) as a transport protocol due to practical considerations. There are many different TCP variants in use, and each variant uses a specific end-to-end congestion control algorithm to avoid congestion, while also attempting to share the underlying network capacity equally among the competing users. This paper shows how an intermediate node (e.g., a network operator) can identify the transmission state of the TCP client associated with a TCP flow by passively monitoring the TCP traffic. We demonstrate how the intermediate node can predict the Congestion Window (cwnd) size of the TCP client. The method can also be extended to predict other TCP transmission states of the client. We use a generic machine learning-based prediction approach for inferring cwnd within a flow from a passive traffic collected at an intermediate node. Our experimental results indicate the effectiveness of our prediction model with reasonably good accuracy across different scenarios and multiple TCP variants.
Açımlayıcı Faktör Analiz Sürecini Etkileyen Unsurların Değerlendirilmesi

Egitim arastirmalarinda oldukca sik kullanilan faktor analizi teknigi, aralarinda iliski bulundugu dusunulen cok sayidaki degiskenin daha az sayidaki dogrudan gozlenemeyen degisken veya degiskenler ile yorumlanabilmesine imkân saglamaktadir. Bu teknik Spearman tarafindan 1904 yilinda ortaya atilmis ve bilgisayar teknolojisindeki gelisime bagli olarak istatistik paket programlari yardimiyla bircok arastirmaci tarafindan veri toplama araclarinin yapisal olarak gecerliligini sinamak amaciyla kullanilmaya baslanmistir. Faktor analizi surecini bir butun olarak ele aldigimizda, 6 tane unsurun bu surecin saglikli olarak islemesinde rol aldigi gorulmektedir. Bu unsurlar; R-matris, orneklem genisligi, R-matrisin yapisal uygunlugu, faktor cikarim metodunun belirlenmesi, rotasyon, faktor sayisinin belirlenmesi ve bulgularin raporlandirilmasi asamalarindan olusmaktadir. Faktor analiz surecinde bahsedilen unsurlar analiz sonuclarinin kesinliginin belirlenmesi acisindan onemlidir. Bu bakimdan, her bir unsur kendi icinde belirli kurallar veya olcutler ile saglanmali ve surec ile olan iliskisi goz ardi edilmemelidir.
The Role of TonB Gene in Edwardsiella ictaluri Virulence

Edwardsiella ictaluri is a Gram-negative facultative intracellular pathogen that causes enteric septicemia in catfish (ESC). Stress factors including poor water quality, poor diet, rough handling, overcrowding, and water temperature fluctuations increase fish susceptibility to ESC. The TonB energy transducing system (TonB-ExbB-ExbD) and TonB-dependent transporters of Gram-negative bacteria support active transport of scarce resources including iron, an essential micronutrient for bacterial virulence. Deletion of the tonB gene attenuates virulence in several pathogenic bacteria. In the current study, the role of TonB (NT01EI_RS07425) in iron acquisition and E. ictaluri virulence were investigated. To accomplish this, the E. ictaluri tonB gene was in-frame deleted. Growth kinetics, iron utilization, and virulence of the EiΔtonB mutant were determined. Loss of TonB caused a significant reduction in bacterial growth in iron-depleted medium (p > 0.05). The EiΔtonB mutant grew similarly to wild-type E. ictaluri when ferric iron was added to the iron-depleted medium. The EiΔtonB mutant was significantly attenuated in catfish compared with the parent strain (21.69 vs. 46.91% mortality). Catfish surviving infection with EiΔtonB had significant protection against ESC compared with naïve fish (100 vs. 40.47% survival). These findings indicate that TonB participates in pathogenesis of ESC and is an important E. ictaluri virulence factor.
CHAPTER 23 ELECTROMAGNETICALLY INDUCED TRANSPARENCY

EIT electromagnetically induced transparency CPT coherent population trapping STIRAP stimulated Raman adiabatic passage RAP rapid adiabatic passage SCRAP Stark chirped rapid adiabatic passage CPR coherent population return LWI lasing without inversion lambda (Λ) scheme three coupled atomic levels with the initial and final states at lower energy than the intermediate state ladder scheme three coupled atomic levels with the energy of the initial state below the intermediate state, and the energy of the intermediate state below the final state vee (V) scheme three coupled atomic levels with the initial and final states at higher energy than the intermediate state cw continuous wave
Numerical simulation of turbulent gas-particle flow in a riser using a quadrature-based moment method

Gas-particle flows are used in many industrial applications in the energy, oil and gas fields, such as coal gasification, production of light hydrocarbons by fluid catalytic cracking, catalytic combustion and different treatments aiming to reduce or eliminate pollutants. The particle phase of a gas-particle flow is described by analogy to a granular gas, by finding an approximate solution of the kinetic equation in the velocity-based number density function. In the recent past, many studies have been published on the mathematical modeling of gas-particle flows using hydrodynamic models (e.g. Enwald et al. 1996), where Navier-Stokes-type equations are solved to describe the particle phase as a continuum, computing its stress tensor using moment closures from kinetic theory (Gidaspow 1994). These closures, however, are obtained assuming that the flow is dominated by collisions and near equilibrium, which corresponds to considering a very small particle-phase Knudsen number. This assumption leads to inconsistencies and erroneous predictions of physical phenomena when these models are applied to dilute fluid-particle flows, where rarefaction effects are not negligible. In these flows, the wall Knudsen layers extend inside the bulk of the fluid, and cannot be accounted for with the simple addition of partial-slip boundary conditions. Recently Desjardin et al. (2008) showed that two-fluid models are unable to correctly capture particle trajectory crossing, seriously compromising their ability to correctly describe any velocity moment for finite Stokes numbers. These authors clarified that the particle segregation captured by two-fluid models for finite Knudsen numbers is artificially high due to their mathematical formulation, which leads to the formation of delta-shocks. In order to overcome these shortcomings, Fox (2008) developed a third-order quadrature-based moment method for dilute gas-particle flows, which has been successfully coupled to a fluid solver to compute dilute and moderately dilute gas-particle flows by Passalacqua et al. (2010) in two dimensions. These authors validated their model against Euler-Lagrange and two-fluid simulations. In this work, the fully coupled quadrature-based fluid-particle code described in Passalacqua et al. (2010) is applied to simulate turbulent gas-particle flow in the riser described by He et al. (2009), using a three-dimensional configuration. This application shows the predictive capabilities and the robustness of the quadrature-based moment method to predict the behavior of gas-particle flows in accordance with experiments (He et al. 2009).
Hartree-Fock and Density Functional Theory Studies on the Molecular Recognition of the Cyclodextrin

This study involves initial Hartree-Fock and Density Functional theory calculations on the molecular recognition of the cyclodextrins. The α -cyclodextrin-acetophenone complexation system was investigated with PM3, HF/3-21G* and B3LYP/3-21G* methods. The results indicated that the inclusion orientation in which the acetyl group of the acetophenone points towards the secondary hydroxyls of the α -cyclodextrin was preferable in energy. The steric effect was supposed as the physical reason of such a behavior. Hence, the simple rule the anti-parallel arrangement of the dipoles of the host and guest molecules in the cyclodextrin complexation is not generally applicable.
Human Memory Reconsolidation: A Guiding Framework and Critical Review of the Evidence

Research in nonhuman animals suggests that reactivation can induce a transient, unstable state in a previously consolidated memory, during which the memory can be disrupted or modified, necessitating a process of restabilization in order to persist. Such findings have sparked a wave of interest into whether this phenomenon, known as reconsolidation, occurs in humans. Translating research from animal models to human experiments and even to clinical interventions is an exciting prospect, but amid this excitement, relatively little work has critically evaluated and synthesized existing research regarding human memory reconsolidation. In this review, we formalize a framework for evaluating and designing studies aiming to demonstrate human memory reconsolidation. We use this framework to shed light on reconsolidation-based research in human procedural memory, aversive and appetitive memory, and declarative memory, covering a diverse selection of the most prominent examples of this research, including studies of memory updating, retrieval-extinction procedures, and pharmacological interventions such as propranolol. Across different types of memory and procedure, there is a wealth of observations consistent with reconsolidation. Moreover, some experimental findings are already being translated into clinically relevant interventions. However, there are a number of inconsistent findings, and the presence of alternative explanations means that we cannot conclusively infer the presence of reconsolidation at the neurobiological level from current evidence. Reconsolidation remains a viable but hotly contested explanation for some observed changes in memory expression in both humans and animals. Developing effective and efficient new reconsolidation-based treatments can be a goal that unites researchers and guides future experiments.
The Language of Religious Affiliation

Religious affiliation is an important identifying characteristic for many individuals and relates to numerous life outcomes including health, well-being, policy positions, and cognitive style. Using methods from computational linguistics, we examined language from 12,815 Facebook users in the United States and United Kingdom who indicated their religious affiliation. Religious individuals used more positive emotion words (β = .278, p < .0001) and social themes such as family (β = .242, p < .0001), while nonreligious people expressed more negative emotions like anger (β = −.427, p < .0001) and categories related to cognitive processes, like tentativeness (β = −.153, p < .0001). Nonreligious individuals also used more themes related to the body (β = −.265, p < .0001) and death (β = −.247, p < .0001). The findings offer directions for future research on religious affiliation, specifically in terms of social, emotional, and cognitive differences.
Metabolic risk in depression and treatment with selective serotonin reuptake inhibitors: are the metabolic syndrome and an increase in cardiovascular risk unavoidable?

Depression is one of the most common psychiatric disorders, and has become an epidemic in modern medical practice; notorious for frequently co-occurring with multiple comorbidities, especially cardiovascular disease (CVD), type 2 diabetes mellitus (DM2), and its various risk factors comprised in the metabolic syndrome (MS). Selective serotonin reuptake inhibitors (SSRIs) are the most widely used class of psychotropic drugs in this and many other clinical scenarios; yet their impact on cardiometabolic health has not been elucidated. The objective of this review was to summarize current views on the pharmacology of SSRIs and cardiometabolic risk, as well as available epidemiological evidence regarding its clinical significance. SSRIs appear to intervene in cardiometabolic physiology fundamentally by modulating chronic inflammation, a key pathophysiologic phenomenon in MS, DM2 and CVD. However, the dosing necessary to achieve a beneficial impact in this regard, as well as their clinical correlations, remain controversial. Each SSRI displays a particular profile regarding each of the components of the MS: weight gain seems to be the most common effect of SSRIs, more frequent with paroxetine, followed by citalopram and escitalopram. As a drug class, SSRIs also appear to promote hypercholesterolemia rather uniformly, while fluoxetine and citalopram appear to particularly increase triacylglyceride levels. In contrast, fluvoxamine and paroxetine seem to have the greatest impact on dysglycemia. Lastly, most SSRIs appear to be innocuous or even beneficial regarding blood pressure and high-density lipoprotein cholesterol. Nevertheless, many of these effects may vary significantly upon specific clinical circumstances, especially timing. This topic remains rather unexplored in clinical psychopharmacology, and further, larger-scale epidemiological studies are needed in order to offer improved care in this field.
Common SDN control channel for seamless handover in 802.11

This article is focused on the area of client mobility in Software-Defined Networking (SDN) for 802.11 standards. Recently, there are a few SDN solutions how to perform smooth and fast handover. Usually these solutions are using separated control channel for control 802.11 functionality. In our work, we demonstrate efficiency of common control channels for 802.11 and SDN under Odin framework improvement. Our solution for common control channels is extending OpenFlow protocol. The proposed approach is significantly improving network architecture in following points: network scalability, security and in parallel it supports seamless handover for delay critical scenarios.