Miracle-dz/UniFAR-FTUs huggingface dataset:
Investigating the Minimum Required Number of Genes for the Classification of Neuromuscular Disease Microarray Data

The discovery of potential microarray markers, which will expedite molecular diagnosis/prognosis and provide reliable results to clinical decision-making and treatment selection for patients, is of paramount importance. Feature selection techniques, which aim at minimizing the dimensionality of the microarray data by keeping the most statistically significant genes, are a powerful approach toward this goal. In this paper, we investigate the minimum required subsets of genes, which best classify neuromuscular disease data. For this purpose, we implemented a methodology pipeline that facilitated the use of multiple feature selection methods and subsequent performance of data classification. Five feature selection methods on datasets from ten different neuromuscular diseases were utilized. Our findings reveal subsets of very small number of genes, which can successfully classify normal/disease samples. Interestingly, we observe that similar classification results may be obtained from different subsets of genes. The proposed methodology can expedite the identification of small gene subsets with high-classification accuracy that could ultimately be used in the genetics clinics for diagnostic, prognostic, and pharmacogenomic purposes.
Chinese Character Recognition Method Based on Image Processing and Hidden Markov Model

On the basis of image processing, the Chinese character recognition model of non specific people is researched based on hidden Markov model (HMM), and an improved isolated Chinese character recognition model is proposed based on HMM and scale invariant feature transform (SIFT) algorithm. The SIFT algorithm is used to extract the feature points of Chinese character, the SIFT feature point extraction algorithm for Chinese character is realized. The adaptive median filtering method and the gray histogram equalization method are used for the image preprocessing. The affine model is used to solve the strokes of a Chinese character moving parameters, and the Kalman filter is taken for the scanning filtering of the isolated Chinese character, the corresponding angular points of Chinese character image and the strokes feature are calculated. The frame window and pre-emphasis methods are used to extract the feature parameters. Finally, the HMM training is taken for the parameters. The template matching is implemented. The Chinese character recognition of uncertain people is achieved. Simulation result shows that the method can recognize the rare Chinese character image accurately, the recognition precision is improved greatly, and the image enhancement and noise reduction effect is obvious, the recognition model is stable with robustness. It has good application value in practice.
LITHIUM ABUNDANCES OF EXTREMELY METAL-POOR TURNOFF STARS

We have determined Li abundances for eleven metal-poor turnoff stars, among which eight have [Fe/H] <−3, based on LTE analyses of high-resolution spectra obtained with the High Dispersion Spectrograph on the Subaru Telescope. The Li abundances for four of these eight stars are determined for the first time by this study. Effective temperatures are determined by a profile analysis of Hα and Hβ. While seven stars have Li abundances as high as the Spite Plateau value, the remaining four objects with [Fe/H] <−3 have A(Li) =log (Li/H)+ 12 ≲ 2.0, confirming the existence of extremely metal-poor (EMP) turnoff stars having low Li abundances, as reported by previous work. The average of the Li abundances for stars with [Fe/H]<−3 is lower by 0.2 dex than that of the stars with higher metallicity. No clear constraint on the metallicity dependence or scatter of the Li abundances is derived from our measurements for the stars with [Fe/H]<−3. Correlations of the Li abundance with effective temperatures, with abundances of Na, Mg, and Sr, and with the kinematical properties are investigated, but no clear correlation is seen in the EMP star sample.
AN OVERVIEW OF ON DEMAND WIRELESS ADHOC NETWORKS PROTOCOLS : DSR AND TORA RAHUL MALHOTRA AND GURPREET SINGH

Wireless network are becoming popular now a days due their features like easy setup without the need of cabling. Wireless ad-hoc networks are a collection of mobile/semi-mobile nodes with no pre-established infrastructure, forming a temporary network. Each node in the network has a wireless Interface and communicates with each other over either radio frequency or infrared, that is, point to point communication. An ad-hoc network is a local area network (LAN) that is built spontaneously as the devices connect. Dynamic Source Routing protocol is a self-organizing and self-configuring routing protocol which allows the easy access to the network without the need for any existing network infrastructure or administration and uses Route Discovery and Route Maintenance techniques for routing packets from source to random destinations. Temporally Ordered Routing Algorithm (TORA) is a distributed routing algorithm based on the concept of link reversal. TORA is implemented where nodes are continuously moving from one place to another. This paper is aimed to study the on-demand routing protocols DSR and TORA for wireless adhoc networks. Further, the implementation of a network using network simulator OPNET will be done to analyze the performance of these two network protocols for traffic sent and received, end to end delay during data communication and download and upload response time.
Time to wake up: reactive countermeasures to sleep inertia

Sleep inertia is the period of impaired performance and grogginess experienced after waking. This period of impairment is of concern to workers who are on-call, or nap during work hours, and need to perform safety-critical tasks soon after waking. While several studies have investigated the best sleep timing and length to minimise sleep inertia effects, few have focused on countermeasures -especially those that can be implemented after waking (i.e. reactive countermeasures). This structured review summarises current literature on reactive countermeasures to sleep inertia such as caffeine, light, and temperature and discusses evidence for the effectiveness and operational viability of each approach. Current literature does not provide a convincing evidence-base for a reactive countermeasure. Caffeine is perhaps the best option, although it is most effective when administered prior to sleep and is therefore not strictly reactive. Investigations into light and temperature have found promising results for improving subjective alertness; further research is needed to determine whether these countermeasures can also attenuate performance impairment. Future research in this area would benefit from study design features highlighted in this review. In the meantime, it is recommended that proactive sleep inertia countermeasures are used, and that safety-critical tasks are avoided immediately after waking.
Model Checking the SET Purchasing Process Protocol with SPIN

Electronic Commerce is a considerable wide spread business engineering model in the Internet. The analysis of the EC's security is a hot research topic in the present. The article studies the Secure Electronics Transactions (SET) protocol and uses the model checking tool SPIN to model and to verify the key part of the protocol-purchasing process protocol. We describe the abstract model of the protocol with promela language of SPIN. During the modeling process, we plant some exploits which the intruders can take advantage of. Then we use LTL to describe the attributes that the protocol should satisfy and carry out the model checking. In our experiment, the intruder is detected with the tool SPIN.
A Variational Approach for Bias Correction and Boundary Delineation of SAR Image with Intensity Inhomogeneity

This paper presents a variational approach for bias correction and boundary delineation of Synthetic Aperture Radar (SAR) images with intensity inhomogeneity. The bias fields in SAR images might have a negative impact on boundary delineation. Our approach is implemented by two steps within a unified framework of energy minimization. First we propose a deviation correction method in which no physical parameter is needed. Then we conduct an improved geodesic active contour model using the tensor voting method to delineate boundaries. The advantage of combining the geodesic active contour model and the tensor voting method is that the active contour is more sensitive to weak boundaries.
Shrink - Prescribing Resiliency Solutions for Streaming

Streaming query deployments make up a vital part of cloud oriented applications. They vary widely in their data, logic, and statefulness, and are typically executed in multi-tenant distributed environments with varying uptime SLAs. In order to achieve these SLAs, one of a number of proposed resiliency strategies is employed to protect against failure. This paper has introduced the first, comprehensive, cloud friendly comparison between different resiliency techniques for streaming queries. In this paper, we introduce models which capture the costs associated with different resiliency strategies, and through a series of experiments which implement and validate these models, show that (1) there is no single resiliency strategy which efficiently handles most streaming scenarios; (2) the optimization space is too complex for a person to employ a "rules of thumb" approach; and (3) there exists a clear generalization of periodic checkpointing that is worth considering in many cases. Finally, the models presented in this paper can be adapted to fit a wide variety of resiliency strategies, and likely have important consequences for cloud services beyond those that are obviously streaming.
Density depletions and current singularities observed by Freja

High time resolution data collected by the Freja spacecraft in the topside ionosphere (h ∼ 1500 km) reveal that the low-frequency turbulence observed commonly below the ion gyrofrequency consists of a large number of coherent plasma structures which represent intense field-aligned currents (j∥ ∼ 30 - 300 μAm -2 ) accompanied by plasma density depletions (cavities). The electromagnetic fluctuations are identified with inertial electron Alfven waves (IEAW) at perpendicular wavelengths ≤ 6 km. The coherent structures with singularly strong j∥ are consistent with being the resonance cones of IEAW generated by localized sources at h ≥ 1 R E . The density cavities are observed to be directly related to the magnetic field gradient, i.e., intensity of field-aligned current. Using multiresolution wavelet analysis we have investigated also the wave impedance and the polarization of the electromagnetic structures at different scales. The polarization records show phase discontinuities at small-scale electromagnetic structures which is consistent with the hypothesis that they represent resonance cones or interference patterns of IEAW.
PSO optimization of synergetic neural classifier for multichannel emotion recognition

In the world of technology, human-machine interaction is becoming more common and will perhaps be a part of our life in the future. Human-machine interaction is more natural if machines are able to perceive and respond to human non-verbal communication such as emotions instead of relying only on audio-visual emotion channels. A particle swarm optimization (PSO) of synergetic neural classifier for multimodal emotion recognition is proposed in this paper. In the experiments, a music induction method which elicits natural emotional reactions from the subject is used and four-channel biosensors are used to obtain electromyogram (EMG), electrocardiogram (ECG), skin conductivity (SC) and respiration changes (RSP) of the subject. The most significant features are extracted via testing several feature selection/reduction methods. Four classes of emotions, that is, joy, anger, sadness, and pleasure are considered and the synergetic neural classifier is used for multimodal emotion recognition. Weights are assigned to the different channels of the classifier and PSO is applied to optimize the weights for enhancing performance. Fast classification speed has been achieved and the experimental results look promising.
An admission control strategy for differentiated services in IEEE 802.11

With the provisioning of high-speed wireless LAN (WLAN) environments, traffic classes (e.g., VoIP or video-conference) with different QoS requirements will be introduced in future WLANs. The IEEE 802.11e draft is currently standardizing a distributed access approach, called the enhanced distributed coordination function (EDCF), to support service differentiation in the MAC layer. However, since each mobile station transmits data packets egotistically in a distributed environment, the QoS requirement of each traffic class may not be guaranteed. In this paper, we develop an admission control strategy to guarantee the QoS requirement of each traffic class. In order to provide a criterion for admission decision, we introduce an analytical model for EDCF to evaluate the expected bandwidth and the expected packet delay of each traffic class. The admission control strategy uses the performance measures derived from the analytical model to decide if a new traffic stream is permitted into the system. We validate the accuracy of the analytical model by using the ns-2 simulator. Some performance evaluations are also demonstrated to illustrate the effect of the proposed admission control strategy.
Domain-Specific Self-Reported and Objectively Measured Physical Activity in Children

Little is known about the extent that different domains contribute to total sedentary (SED), light (LPA) and moderate-to-vigorous physical activity (MVPA). We aimed to identify domain-specific physical activity (PA) patterns in school-aged children who were assessed by questionnaire and accelerometry. For the study, 298 German school children and adolescents aged 6–17 years wore an accelerometer for one week and completed a PA recall-questionnaire for the same period. Spearman coefficients (r) were used to evaluate the agreement between self-reported and objectively measured PA in five domains (transport, school hours, physical education, leisure-time, organized sports activities). School hours mainly contributed to the total objectively measured SED, LPA and MVPA (55%, 53% and 46%, respectively), whilst sports activities contributed only 24% to total MVPA. Compared to accelerometry, the proportion of self-reported LPA and MVPA during school hours was substantially underestimated but overestimated during leisure-time. The agreement of self-reported and objectively measured PA was low for total LPA (r = 0.09, 95% CI (confidence interval): −0.03–0.20) and total MVPA (r = 0.21, 95% CI: 0.10–0.32), while moderate agreement was only found for total SED (r = 0.44, 95% CI: 0.34–0.53), LPA during transport (r = 0.59; 95% CI: 0.49–0.67) and MVPA during organized sports activities (r = 0.54; 95% CI: 0.38–0.67). Since school hours mainly contribute to total SED, LPA and MVPA and self-reported LPA and MVPA during school were importantly underestimated compared to objectively measured LPA and MVPA, the application of objective measurements is compulsory to characterize the entire activity pattern of school-aged children.
A Vision Based Approach for Assessing Equine Locomotion and Whole-Body Vibration Induced on a Horse Rider

systems such as horse locomotion are investigated by using inertial sensor systems composed of accelerometers, gyroscopes and magnetometers, or by optical motion tracking systems. The major difficulty in the inertial sensor systems is the integration process. Furthermore, the signals possess noise that has to be filtered. On the other hand, the motion tracking systems are expensive and mostly adapted to indoor laboratory conditions. Hence, in some studies, horses are trained to walk on treadmills with various speeds. This training process is time consuming and may lead to unnatural gaits. In this study, an inexpensive, portable vision system for tracking the motion in a large calibration volume is designed; and an algorithm for obtaining kinematics of a rigid body is developed and implemented in MATLAB. Using the overall system, it is possible to determine the position, velocity and acceleration of any point in the calibration volume which may contain multiple rigid bodies. The point of interest may correspond to points which do not allow an accelerometer to be mounted, or points which are invisible to the cameras. This is the major advantage of our method. A singularity analysis of the algorithm, which yields useful information on the positioning of the markers that are to be tracked by the vision system, is also performed. The method is used to study the whole-body vibrations (WBV) imposed on a horse rider. To the authors' knowledge, there exists no studies on this topic in the literature. Regarding the imposed WBV, the differences between the gaits of the same horse and the differences between the gaits of different horses (executing the same gait) are investigated. The results are experimentally shown to be consistent with the comfort assessment of four experienced riders.
A characterization of strong wave tails in curved spacetimes

A characterization of when wave tails are strong is proposed. The existence of curvature-induced tails is commonly understood to cause backscattering of the field governed by the relevant wave equation. Strong tails are characterized as those for which the purely radiative part of the field is backscattered. With this definition, it is shown that electromagnetic fields in asymptotically flat spacetimes and fields governed by tail-free propagation have weak tails, but minimally coupled scalar fields in a cosmological scenario have strong tails.
Toward more rigor in ontological analyses

Ontological analyses have been used in numerous publications to compare existing modelling grammars with an ontology. However, a sound theoretical research framework is still missing. Consequently, working with the results of such ontological analyses is theoretically questionable. The aim of the paper is threefold. Firstly, we want to contribute to such a theoretical research framework by formalising the ontological analyses approach. Secondly, we derive four formal requirements each ontological analyses must comply with. Lastly, we analyse whether current state of the art ontological analyses comply with our findings. While the formalisation demonstrates the strengths of the approach we conclude that current ontological analyses have theoretical deficiencies, which lead to serious limitations in their application.
Sequential Elimination Graphs ⋆

A graph is chordal if it does not contain any induced cycle of size greater than three. An alternative characterization of chordal graphs is via a perfect elimination ordering, which is an ordering of the vertices such that, for each vertex v, the neighbors of v that occur later than v in the ordering form a clique. Akcoglu et al [2] define an extension of chordal graphs whereby the neighbors of v that occur later than v in the elimination order have at most k independent vertices. We refer to such graphs as sequentially k-independent graphs. Clearly this extension of chordal graphs also extends the class of (k+1)-claw-free graphs. We study properties of such families of graphs, and we show that several natural classes of graphs are sequentially kindependent for small k. In particular, any intersection graph of translates of a convex object in a two dimensional plane is a sequentially 3-independent graph; furthermore, any planar graph is a sequentially 3-independent graph. For any fixed constant k, we develop simple, polynomial time approximation algorithms for sequentially k-independent graphs with respect to several well-studied NPcomplete problems based on this k-sequentially independent ordering. Our generalized formulation unifies and extends several previously known results. We also consider other classes of sequential elimination graphs.
Synthesis and Characterizations of Novel Ca-Mg-Ti-Fe-Oxides Based Ceramic Nanocrystals and Flexible Film of Polydimethylsiloxane Composite with Improved Mechanical and Dielectric Properties for Sensors

Armalcolite, a rare ceramic mineral and normally found in the lunar earth, was synthesized by solid-state step-sintering. The in situ phase-changed novel ceramic nanocrystals of Ca-Mg-Ti-Fe based oxide (CMTFOx), their chemical reactions and bonding with polydimethylsiloxane (PDMS) were determined by X-ray diffraction, infrared spectroscopy, and microscopy. Water absorption of all the CMTFOx was high. The lower dielectric loss tangent value (0.155 at 1 MHz) was obtained for the ceramic sintered at 1050 °C (S1050) and it became lowest for the S1050/PDMS nanocomposite (0.002 at 1 MHz) film, which was made by spin coating at 3000 rpm. The excellent flexibility (static modulus ≈ 0.27 MPa and elongation > 90%), viscoelastic property (tanδ = E″/E′: 0.225) and glass transition temperature (Tg: −58.5 °C) were obtained for S1050/PDMS film. Parallel-plate capacitive and flexible resistive humidity sensors have been developed successfully. The best sensing performance of the present S1050 (3000%) and its flexible S1050/PDMS composite film (306%) based humidity sensors was found to be at 100 Hz, better than conventional materials.
Mycoplasmas and cancer: focus on nucleoside metabolism

The standard of care for patients suffering cancer often includes treatment with nucleoside analogues (NAs). NAs are internalized by cell-specific nucleobase/nucleoside transporters and, after enzymatic activation (often one or more phosphorylation steps), interfere with cellular nucleo(s)(t)ide metabolism and DNA/RNA synthesis. Therefore, their efficacy is highly dependent on the expression and activity of nucleo(s)(t)ide-metabolizing enzymes, and alterations thereof (e.g. by down/upregulated expression or mutations) may change the susceptibility to NA-based therapy and/or confer drug resistance. Apart from host cell factors, several other variables including microbial presence may determine the metabolome (i.e. metabolite concentrations) of human tissues. Studying the diversity of microorganisms that are associated with the human body has already provided new insights in several diseases (e.g. diabetes and inflammatory bowel disease) and the metabolic exchange between tissues and their specific microbiota was found to affect the bioavailability and toxicity of certain anticancer drugs, including NAs. Several studies report a preferential colonization of tumor tissues with some mycoplasma species (mostly Mycoplasma hyorhinis). These prokaryotes are also a common source of cell culture contamination and alter the cytostatic activity of some NAs in vitro due to the expression of nucleoside-catabolizing enzymes. Mycoplasma infection may therefore bias experimental work with NAs, and their presence in the tumor microenvironment could be of significance when optimizing nucleoside-based cancer treatment.