Miracle-dz/UniFAR-FTUs huggingface dataset:
Eye movement desensitization and reprocessing as a treatment for PTSD: current neurobiological theories and a new hypothesis

Eye movement desensitization and reprocessing (EMDR), a form of psychotherapy for individuals with post‐traumatic stress disorder (PTSD), has long been a controversial topic, hampered in part by a lack of understanding of the neural mechanisms that contribute to its remedial effect. Here, we review current theories describing EMDR's potential neurobiological mechanisms of action involving working memory, interhemispheric communication, de‐arousal, and memory reconsolidation. We then discuss recent studies describing the temporal and spatial aspects of smooth pursuit and predictive saccades, which resemble those made during EMDR, and their neural correlates within the default mode network (DMN) and cerebellum. We hypothesize that if the production of bilateral predictive eye movements is supportive of DMN and cerebellum activation, then therapies that shift the brain towards this state correspondingly would benefit the processes regulated by these structures (i.e., memory retrieval, relaxation, and associative learning), all of which are essential components for PTSD recovery. We propose that the timing of sensory stimulation may be relevant to treatment effect and could be adapted across different patients depending on their baseline saccade metrics. Empirical data in support of this model are reviewed and experimental predictions are discussed.
Robust adaptive output feedback tracking control for flexible-joint robot manipulators based on singularly perturbed decoupling

SUMMARY This paper presents a robust adaptive output feedback tracking controller for the flexible-joint robot manipulators to deal with the unknown upper bounds of parameter uncertainties and external disturbances. With applying the singular perturbation theory and integral manifold concept, the complex nonlinear coupled system of the flexible-joint robot manipulators is divided into a slow subsystem and a fast subsystem. A robust adaptive control scheme based on an improved linear parameterization expression is designed for the slow subsystem, and a saturation function is applied in the robust control term to make the torque output smooth. In the meantime, different from the previous approaches, the second-order derivative term of elastic torque is avoided by using the proposed computed torque method, which simplifies the implementation of the fast control law. Moreover, to carry out the whole control system with only position measurements, an approximate differential filter is involved to generate pseudo velocity signals for links and joint motors. In addition, an explicit but strict stability proof of the control system based on the theory of singularly perturbed systems is presented. Finally, simulation results verify the superior dynamic performance of the proposed controller.
Developmental Changes in Isometric Strength: Longitudinal Study in Adolescent Soccer Players

Abstract This study aimed to examine longitudinal changes in isometric strength of the knee extensors (ImKE) and knee flexors (ImKF) at 30° and 60°. The sample was composed of 67 players aged 11.0–13.9 years at baseline over five years. Stature, body mass, skinfolds, and isometric strength (ImKE30°, ImKF30°, ImKE60° and ImKF60°) were measured. Fat mass and fat-free mass (FFM) were derived from skinfolds. Skeletal age was obtained using TW2 RUS. Multilevel random effects regression analyses extracted developmental polynomial models. An annual increment on chronological age (CA) corresponded to 5.6 N (ImKE30°), 2.7 N (ImKF30°), 4.6 N (ImKE60°) and 1.5 N (ImKF60°). An increment of 1 kg in FFM predicted isometric strength as follows: 1.2 N (ImKE30°), 2.1 N (ImKF30°), 3.1 N (ImKE60°) and 2.0 N (ImKF60°). The following equations were obtained: ImKE30°=5.759×CA+1.163×FFM; ImKF30°=−19.369+2.691×CA+0.693×CA2+2.108×FFM; ImKE60°=4.553×CA+3.134×FFM; and, ImKF60°=-19.669+1.544×CA+2.033×FFM. Although skeletal maturity had a negligible effect on dependent variables, age and body size, based on FFM, were relevant longitudinal predictors. During adolescence, systematic assessment of knee extensors and knee flexors are strongly recommended to prevent impairment of knee muscle groups.
In vitro differentiation of spermatogonial stem cells using testicular cells from Guangxi Bama mini-pig

In this study, we attempted to establish a culture system for in vitro spermatogenesis from spermatogonial stem cells (SSCs) of Bama mini-pig. Dissociated testicular cells from 1-month-old pigs were co-cultured to mimic in vivo spermatogenesis. The testicular cells were seeded in minimum essential medium alpha (α-MEM) supplemented with Knockout serum replacement (KSR). Three-dimensional colonies formed after 10 days of culture. The colonies showed positive staining for SSC-associated markers such as UCHL1, PLZF, THY1, OCT4, Dolichos biflorus agglutinin, and alkaline phosphatase. Induction of SSCs was performed in α-MEM + KSR supplemented with retinoic acid, bone morphogenetic protein 4, activin A, follicle-stimulating hormone, or testosterone. The results showed that STRA8, DMC1, PRM1, and TNP1 were upregulated significantly in the colonies after induction compared to that in testis from 1-month-old pigs, while expression levels of those genes were significantly low compared to those in 2-month-old testis. However, upregulation of ACROSIN was not significant. Replacement of α-MEM and KSR with Iscove's modified Dulbecco's medium and fetal bovine serum did not upregulate expression of these genes significantly. These results indicate that SSCs of Bama mini-pig could undergo differentiation and develop to a post-meiotic stage in α-MEM supplemented with KSR and induction factors.
Astragaloside IV protects RGC-5 cells against oxidative stress

Astragaloside IV is the main active compound of Astragalus membranaceus. Astragaloside IV has strong anti-oxidative activities and protective effects against progression of peripheral neuropathy. In this study, we determined whether astragaloside IV protects retinal ganglion cells (RGC) from oxidative stress injury using the rat RGC-5 cell line. Hydrogen peroxide (H2O2) was used to induce oxidative stress injury, with the protective effect of astragaloside IV examined. Cell Counting Kit-8 and 4′,6-diamidino-2-phenylindole staining showed that astragaloside IV increased cell survival rate and decreased apoptotic cell number. Flow cytometry showed that astragaloside IV decreased H2O2-induced reactive oxygen species levels. While laser confocal microscopy showed that astragaloside IV inhibited the H2O2-induced decrease of mitochondrial membrane potential. Western blot assay showed that astragaloside IV reduced cytochrome c release induced by H2O2, inhibited Bax and caspase-3 expression, and increased Bcl-2 expression. Altogether, these results indicate that astragaloside IV has potential protective effects against H2O2-induced oxidative stress in retinal ganglion cells.
Predicting software aging related bugs from imbalanced datasets by using data mining techniques

Software aging bugs are related with the life-span of the software. Rebooting is one of the solutions of this problem, however, it is time consuming and causes resources loss. It is difficult to detect these bugs during the time-limited software testing process. Data mining techniques can be useful to predict whether a piece of software has aging related bugs or not. The available datasets of software aging bugs present a challenge as they are imbalanced datasets. In these datasets, the number of data points with bugs is very small as compared to the number of data points with no bugs. It is important to predict the rare class (Bugs). In this paper we carried out experiment with a dataset containing data points related to aging-related bugs found in an open-source project MySQL DBMS. Data mining techniques developed for imbalanced datasets were compared with general data mining techniques. Various performance measures were used for the comparative study. The results suggest that data mining techniques developed for imbalanced datasets are more useful for correct prediction of data points related to aging related bugs. Data mining techniques developed for imbalanced datasets performed better than general data mining techniques on G-mean measure which is an important performance measure for imbalanced datasets.
A Method for Fast Leaderboard Calculations in Massive Online Game-Based Environments

Leaderboards and other game elements are present in many online environments, not just in videogames. When such environments have relatively few users, the implementation of those leaderboards is not usually a problem; however, that is no longer the case when they have dozens of thousands or more. For those situations we propose a method that is easy and cheap to implement. It is based on two particular data structures, a Self-Balanced Ordering Statistic Tree and a hash table, to perform proper leaderboard calculations in a fast and cheap way. More specifically, our proposal has time complexity, whereas other approaches also based on in-memory data structures like linked lists have , and others based on Hard Disk Drive operations like a relational database have . Such improvement with regard to the other approaches is corroborated with experimental results for several scenarios, also presented in this paper.
Fluorescence imaging for specific analysis of cancer cells

2. Fluorescence imaging of cells Optical methods are relatively cheap non-ionizing techniques based on the specific optical properties and are due to their variability, flexibility, specificity and sensitivity an important tool for non-invasive and objective diagnosis with still improving resolution [11-14]. Fluorescence imaging is the optical method based on the usage of fluorophores, the compounds, that can emit light after absorption of the appropriate wavelength light [15]. Fluorescence detection of cancer cells has the potential to be used in early cancer diagnosis [16]. The fluorescence of the dyes for imaging should be in the „tissue optical window“ spectral ranges between 650 and 900 nm [17] or in the infrared spectrum [18]. The long wavelength (far-red to NIR) fluorescent probes are advantageous for in vivo bioimaging because of minimum photo-damage to biological samples, deep tissue penetration, and minimum interference from background autofluorescence by biomolecules in the living systems. Therefore great attention is paid in the development of new long wavelength fluorescent probes [19]. Fluorescence imaging for specific analysis of cancer cells
Advance e-governance system

This Electronic government system is a web application for the public to provide all type of services online. Where online means using internet and services means applications submission for pan card, passport, driving license etc. The services may be provided by NGO, public sector or private sector organization but till date service providers are only government and mobile companies like Airtel and Vodafone etc. for paying bill only. The main concept of the proposed system is to maximize the services of the present tools by adding new modules for services like education, banking, insurance, health, notice board, inbox and Grievances. And also improve existing modules of personal, utilities and agriculture by adding new features like home for poor, expert suggestion for farming etc.
Parasitic interactions between nosema spp. and varroa destructor in apis mellifera colonies

The European honey bee Apis mellifera is affected by many parasites and pathogens that modify its immune system being the most destructive ectoparasitc mite Varroa destructor. The parasitic disease caused by this mite results in high mortality levels in honeybee colonies without acaricide treatment. In addition, the microsporidium Nosema apis and Nosema ceranae produce serious damages to the colonies. Taking into account that the sporulation dynamics of the microsporidium can be affected by several factors the objective of this investigation was to analyze if there are parasitic interactions between V. destructor and Nosema spp. when both parasites co-infect A. mellifera colonies. Studies were carried out in an apiary in the Entre Rios province, Argentina. The apiary was sampled for a 10 month period. Parameters recorded per hive in fi eld examination were: (a) adult bee population (estimated as number of combs covered with adult bees); (b) brood area (estimated as number of combs covered by at least a 50 % of brood cells); (c) number of honey combs; (d) the V. destructor presence (a colony was considered parasitized by V. destructor when phoretic mite infestation was higher than 1 %) and (e) number of Nosema spp. spores (parasite abundance). Abundance of Nosema (ANij) per colony was analyzed using the mixed general additive model (GAM) with variable intercept. The fi nal data modeling confi rmed that Nosema abundance is explained by the time and by the interaction between the month and the V. destructor infestation. Possible causes explaining this ecological relationship between V. destructor and Nosema spp. populations were discussed. Key Words: Parasite interactions; Varroa destructor; Nosema; Apis mellifera
Robust Data Center Network Design Based on Space Division Multiplexing

Data center networks, using a reliable, high speed communication network, is a core component of cloud computing. Recently, optical networks using Space Division Multiplexing has been proposed as a solution to the speed bottleneck anticipated in data center networks. To our knowledge the new challenges of designing such communication systems have not been addressed yet. In this paper we have proposed an optimal approach to the problem of developing a path-protection scheme to handle communication requests in data center (DC) networks using elastic optical networking and space division multiplexing. We have formulated our problem as an Integer Linear Program (ILP). We have also proposed a heuristic that can handle problems of practical size. Our simulations explore important features of our approach.
Implementing GloVe for context based k-means++ clustering

In this paper, we have implemented a unique form of clustering that takes a non-numeric data set and clusters it with the help of the word embedding provided by the GloVe dataset. The related word embedding are generated for each of the items in the dataset we want to cluster using the GloVe vector representation of those words. We then perform dimensionality reduction on the data set to obtain the accurate number of dimensions to be taken for appropriate cluster formation. The data is then clustered using k-means++. This paper provides one of the ways to overcome the limitation of k-means clustering in terms of initialising the cluster centres and hence gives better quality clusters. With the synthetic examples, the k-means method does not perform well, because the random seeding inevitably merges clusters together, and the algorithm is unable to then split them apart. Careful seeding method used by k-means++ prevents this problem and hence usually gives optimal results even when datasets are synthetic.
Quick response codes decodability improvements using error correction levels

In today's era usage of QR Codes (Quick Responsive codes) has become very common. The problem arise with the poor quality of QR Code. Due to this its decodability must need to be focused. As the reproduction (i.e. printing process) of QR Code for different image formats may include compressions and transformations, there are the major cause of distortion and noise which majorly affects the quality of the QR Codes and so apparently the decodability of QR Codes will get affected. In this approach we have discussed about the vital point of QR Codes called Error Correction levels L, M, Q, and H. For the different image formats (such as bmp, jpg, png etc.) the MSE (Mean Squared Error) and PSNR (Peak Signal Noise Ratio) values will be calculated to carry out better quality for the QR Codes by reducing the distortion and noise. The improvement will help to give better results to make QR Codes more useful in every way such as, for commercial purpose, for the education purpose, to store the information, to store the URL.
Downlink Cooperative Broadcast Transmission Based on Superposition Coding in a Relaying System for Future Wireless Sensor Networks

This study investigates the superiority of cooperative broadcast transmission over traditional orthogonal schemes when applied in a downlink relaying broadcast channel (RBC). Two proposed cooperative broadcast transmission protocols, one with an amplify-and-forward (AF) relay, and the other with a repetition-based decode-and-forward (DF) relay, are investigated. By utilizing superposition coding (SupC), the source and the relay transmit the private user messages simultaneously instead of sequentially as in traditional orthogonal schemes, which means the channel resources are reused and an increased channel degree of freedom is available to each user, hence the half-duplex penalty of relaying is alleviated. To facilitate a performance evaluation, theoretical outage probability expressions of the two broadcast transmission schemes are developed, based on which, we investigate the minimum total power consumption of each scheme for a given traffic requirement by numerical simulation. The results provide details on the overall system performance and fruitful insights on the essential characteristics of cooperative broadcast transmission in RBCs. It is observed that better overall outage performances and considerable power gains can be obtained by utilizing cooperative broadcast transmissions compared to traditional orthogonal schemes.
Wind Turbine Blade Breakage Monitoring With Deep Autoencoders

Monitoring wind turbine blade breakages based on supervisory control and data acquisition (SCADA) data is investigated in this research. A preliminary data analysis is performed to demonstrate that existing SCADA features are unable to present irregular patterns prior to occurrences of blade breakages. A deep autoencoder (DA) model is introduced to derive an indicator of impending blade breakages, the reconstruction error (RE), from SCADA data. The DA model is a neural network of multiple hidden layers organized symmetrically. In training DA models, the restricted Boltzmann machine is applied to initialize weights and biases. The back-propagation method is subsequently employed to further optimize the network structure. Through examining SCADA data, we observe that the trend of RE will shift by the blade breakage. To effectively detect RE shifts through online monitoring, the exponentially weighted moving average control chart is deployed. The effectiveness of the proposed monitoring approach is validated by blade breakage cases collected from wind farms located in China. The computational results prove the capability of the proposed monitoring approach in identifying impending blade breakages.
Speech emotion recognition on mobile devices based on modulation spectral feature pooling and deep neural networks

In this study, the problem of speech emotion recognition (SER) in-the-wild is addressed. A new modulation spectral feature pooling scheme is proposed to mitigate the detrimental effects of background noise. On top of these features, two DNN-based architectures are tested for the prediction of arousal and valence emotional primitives: a multi-layer perceptron (MLP) and a recurrent neural network based on Long-Short Term Memory (LSTM). Experiments are conducted using the RECOLA dataset of spontaneous interactions. In order to simulate data collected in-the-wild, the clean speech files were corrupted with different levels of background noise and room impulse responses collected using a mobile device. Both stationary and non-stationary noise types (fan and babble) were considered in our experiments. Three distinct scenarios were explored: noise only, reverberation only and noise-plus-reverberation. Experimental results have shown that, in most of the scenarios, the proposed SER system achieved better performance in terms of concordance correlation coefficients (CCC) compared to the benchmark algorithm described in the 2016 Audio/Visual Emotion Challenge. The proposed feature system also showed to be more robust when noise-plus-reverberation is considered.
MAC layer intrusion detection system by cooperation of cross layer in MANET

Cross layer convention configuration is one of the predominant approaches that have been recently presented in network administration research and lead to significant performance benefits. This paper presents the performance of cross layer interaction and investigates its effects with respect to security and information assurance of mobile ad hoc networks. In this paper cross layer based anomaly Intrusion Detection System (IDS) is utilized to recognize malicious nodes (attacks), IDS is utilized with conventional AODV Power and Delay optimized (PDOAODV) for finding fair load balancing path while selecting nodes. The simulated results like throughput, power consumption and packet drop proportion are contrasted among AODV, PDO AODV and IDS with respect to node mobility and simulation time. The outcomes demonstrate that the proposed IDS out performs for enhancing network performance.
The role of matrix metalloproteinase-3 functional 5 A / 6 A promoter polymorphism in tumor cell progression and metastasis of breast cancer

In the human genome, chromosome 11 contains a cluster of matrix metalloproteinase (MMP) genes. Single nucleotide polymorphisms in the promoter region of MMP genes are important for MMP expression. A common adenine deletion polymorphism (5A) at position -1171 of the MMP-3 gene promoter (5 ́AAAAAACCAT-3 ́ change to 5 ́-AAAAACCAT-3 ́) facilitates transcriptional factor binding and MMP-3 promoter activity. A case-control study was performed including 120 breast cancer patients (60 patients with metastatic activity and 60 patients without metastatic activity); and 60 healthy controls. Whole blood samples were obtained from patients and healthy controls. Genomic DNA was extracted from samples and the MMP-3 5A/6A genotypes were determined using PCRRFLP. MMP-3 genotype distributions between patients and controls were similar (OR= 0.89, 95%CI, 0.431.84, P= 0.047). It was observed that the 5A allele was more frequent among patients with metastatic activity than controls (OR= 2.9, 95%CI, 0.94-8.9, P= 0.074). Therefore, the 5A polymorphism in the MMP-3 promoter showed correlation with the metastasis group than patients without metastasis; both at the time of diagnosis. However our results do not show evidence for correlation between 5A/6A polymorphism and breast cancer susceptibility.
Naïve Bayesian Classifier and Classification Trees for the Predictive Accuracy of Probability of Default Credit Card Clients

Decision Trees use a decision support tool that utilizes tree like graph model and make decisions. Naive Bayesian classifier is a binary classifier to get yes/no from the data and it is a very primitive method of finding true or false classification from a dataset. Both algorithms can be used as a predictive model in machine learning and data-mining. Here, a comparative analysis between these two machine learning algorithms is done. The data we have is used to classify if the client is the default credit card holder or not. In the perspective of risk management, the result can be used to accurately get the result of classifying credible or non-credible clients.