Miracle-dz/UniFAR-FTUs huggingface dataset:
Drug target interaction predictions using PU- Leaming under different experimental setting for four formulations namely known drug target pair prediction, drug prediction, target prediction and unknown drug target pair prediction

Predicting new drug target interactions experimentally through wet lab experiments is time as well as resource intensive. In general, drug-target interaction prediction problem leads to drug discovery, drug repositioning and uncovers interesting patterns in chemogenomics research. Drug and target represent heterogeneous nodes within a network of interactions. Presence of an edge between the nodes indicates a positive interaction whereas an absence suggests an unknown interaction. Classification based machine learning algorithms are heavily applied in this area of research. Classification algorithms need positive as well as negative data to yield optimized results. The major problem in this field is lack of negative data because the data that are found in the public databases are positive interaction samples. Considering unknown drug target pairs as negative data may cause severe consequences for the prediction performance. Thereby, we propose a positive un-labelled (PU) learning- based approach that uses one class support vector machine technique as the learning algorithm. The algorithm learns the positive distribution from the unified feature vector space of drugs and targets and regards unknown pairs as unlabeled instead of labelling them as negative pairs. Additionally, we use 4860 Klekota Roth fingerprint + 881 PubChem fingerprint as a high dimensional and highly discriminative feature vector representation for drugs. To represent protein features, we create a protein-motif matrix based on the sliding window score that records the probability of a motif pattern occurring within a given protein sequence. Also, we separately evaluate the prediction performance using 5-fold nested cross- validation under different experimental setting for each of the four formulations: 1) Known drug-target pair,2) Drug prediction, 3) Target prediction and 4) Unknown drug target pair. We show that our approach yields the best AUC score over previous benchmark techniques and outperforms most of the recent works based on one class classifiers and PU-based learning.
Soft wearable non-vibratory tactile displays

This paper presents a new type of wearable finger-tip tactile displays aimed at providing electrically tuneable tactile stimuli interactions with soft bodies. This is achieved by a new actuation technology based on soft electroactive polymers, capable of generating large and quasi-static displacements at moderate forces. This is intentionally different from the high-frequency small vibrations at high forces that are used in several state-of-the-art tactile displays. We describe the ongoing development of devices having a volume of 20×12×23 mm and weigh of only 6 g on finger, which can render electrically tuneable displacements of up to 3.5 mm and forces of up to 0.8 N.
Adaptive fuzzy control for a class of uncertain chaotic systems based on proportional-integral sliding mode control approach

In this paper, the chaos control problem of a class of uncertain chaotic systems with unknown external disturbances is studied by using adaptive fuzzy sliding mode control. A proportional-integral (PI) sliding mode surface is designed to implement a sliding mode controller. Fuzzy logic systems are used to approximate the unknown nonlinear functions. The underlying parameter adaptation design as well as stability analysis are discussed by using Lyapunov stability criterion. Finally, numerical examples are given to show the effectiveness of our method.
Chebyshev neural network observer based RBF neural network terminal sliding mode controller for a class of nonlinear system

This paper focuses on an observer-based controller for a class of nonlinear systems. In order to solve the problem of unknown dynamic in practical systems, two different Neural Networks (NNs) for observer and controller parts are adopted. In the observer part, a Multi-Layer Perceptron (MLP) neural network based on error back propagation algorithm is applied to update the weights of neural network that will be used to estimate the system states. In the controller part, Radial Basis Function Neural Network (RBFNN) with terminal sliding mode controller, based on a new sliding surface, is combined to achieve a finite time stability and fast convergence speed. The update law in the controller part is related to the proposed sliding surface. The stability of the closed loop system is analyzed by Lyapunov stability theory. In simulation, the proposed technique is applied to a chaotic system to obtain the effectiveness of the proposed approach.
Method of decrease of discrete Fourier transform sidelobes without window functions

The paper suggests the technique for the spectral analysis of polyharmonic signals in Fourier basis that can be used in hydroacoustic monitoring tasks, radiolocation, radiocommunication and measurement capabilities. The technique decreases sidelobes levels without deterioration in the spectral analysis resolution, and increases signal-to-noise ratio. The technique was compared with other window functions. Main advantages of the suggested technique were defined.
The Effect of Stance Width and Anthropometrics on Joint Range of Motion in the Lower Extremities during a Back Squat

The purpose of this study was to assess whether changing the stance width has an effect on the range of motion of hip flexion, knee flexion, and ankle dorsiflexion during an unloaded back squat, and whether these joint movements are affected by anthropometric differences. Thirty-two healthy, young adults performed unloaded back squats at three different stance widths, normalized to pelvic width. Joint angles were assessed using electromagnetic motion capture sensors on the sacrum, and thigh, shank and foot of the dominant leg. ANOVA comparison of joint angles for the three stance widths, at 10° intervals of thigh orientation during the squat, indicated that joint angles tended to be larger when stance width was narrower, with the most significant effects on ankle dorsiflexion. A greater trunk/thigh length ratio (relatively long trunk) also tended to be associated with lower ankle and knee angles, while a greater thigh/shank length ratio (relatively long thigh) tended to be associated with higher ankle and knee angles, for the two narrower stance widths. The most practical implication of our findings is that individuals with limited ankle dorsiflexion, or with particularly long legs / thighs, may benefit from a wider stance width when squatting.
Methods to eliminate nonlinearity of electrostatic control sensors of the wave solid-state gyroscope

The wave solid-state gyroscope with a ring resonator and electrostatic control sensors is considered. We deduce a mathematical model which describes nonlinear oscillations of the resonator when the control voltage is applied to the electrodes. Various schemes and modes of supplying voltage to the gyroscope sensors are studied. It is shown that reference voltage causes cubic nonlinearity, and alternating voltage causes quadratic nonlinearity of control forces in one mode of the supplying voltage. In another mode, apart from the cubic nonlinearity caused by the reference voltage, there are both the constant component and quadratic nonlinearity. To linearize the resonator oscillations, special supplying voltage modes for the control electrodes are presented. The formed control modes compensate for the nonlinear resonator oscillations caused by the electrostatic sensors. The proposed technique can be used to eliminate nonlinear oscillations and to linearize force characteristics of control sensors for wave solid-state gyroscopes with ring resonators.
Effects of Cognitive Reserve on Cognitive Performance in a Follow-Up Study in Older Adults With Subjective Cognitive Complaints. The Role of Working Memory

Objective: Analyze the effects of CR on cognitive performance in adults with subjective cognitive complaints at follow-up. Method: We analyzed the factorial structure of the three constructs defined in cognitive performance (Episodic memory, Working memory, and General cognitive performance) separately to search for evidence of the invariance of the measurement model. We then developed four structural nested models to analyze the relationship between CR and cognitive performance, measured at baseline and after approximately 18 months, in 266 participants older than 50 years with subjective cognitive complaints. Results: The nested models revealed the following main results: direct effects of CR on all cognitive constructs at baseline and also indirect effects on the same constructs at follow-up, and indirect effects of CR on other cognitive constructs at follow-up via working memory at follow-up. Conclusion: The findings show that the proposed model is useful for measuring the influence of CR on cognitive performance in follow-up studies and that CR has a positive influence on cognitive performance at follow-up via working memory. CR may enhance mechanisms of information processing, favoring performance of tasks involving other cognitive constructs in older adults with subjective cognitive complaints.
How to agentify the Internet-of-Things?

Despite the smooth weaving of the Internet-of-Things into people's daily lives, many challenges, such as diversity and multiplicity of things' development technologies and communication standards, and users' reluctance due to privacy invasion, are slowing down this weaving. This paper tackles the challenge of things' passive nature that has confined them into a data-supplier role. Empowering things with additional capabilities would make them proactive so, that, they can for instance, reach out to peers exposing collaborative attitude and (un)form dynamic communities when necessary. In this paper, this empowerment takes shape through thing agentification that relies on norms (specialized into business and social) to regulate the operations of things and commitments to ensure thing compliance with these norms. No-compliance would lead to sanctions over things, which should affect their credibility and reputation. A proof-of-concept and missing-child case study technically illustrate thing agentification.
Typical phone use habits: intense use does not predict negative well-being

Not all smartphone owners use their device in the same way. In this work, we uncover broad, latent patterns of mobile phone use behavior. We conducted a study where, via a dedicated logging app, we collected daily mobile phone activity data from a sample of 340 participants for a period of four weeks. Through an unsupervised learning approach and a methodologically rigorous analysis, we reveal five generic phone use profiles which describe at least 10% of the participants each: limited use, business use, power use, and personality- & externally induced problematic use. We provide evidence that intense mobile phone use alone does not predict negative well-being. Instead, our approach automatically revealed two groups with tendencies for lower well-being, which are characterized by nightly phone use sessions.
A transformation method for consensus of general linear multi-agent systems

This paper is concerned with the consensus of general linear multi-agent systems with directed topology. A transformation method is proposed for analysis and control of consensus. The definition and properties of the transforma­tion are first discussed. The consensus in the multi-agent is investigated through the stability of the transformed system, and the relation between the two systems is established. This approach provides a natural way to derive necessary and sufficient conditions for consensus, and further it can be used to analyse the consensus types. Moreover, compared to conventional methods, by this transformation a more general control design approach for each general agent is presented this paper. Numerical examples with four cases are given to verify the effectiveness of the proposed method.
Robust stability, stabilization and Hœ control for a class of nonlinear uncertain stochastic time-varying delayed systems

This paper mainly discusses the robust stability, stabilization and H∞ control for a class of nonlinear uncertain stochastic time-varying delayed systems. Firstly, by using the linear matrix inequality(LMI)method, a sufficient condition is obtained for the robust stability and stabilization of the considered systems. Then, the robust H∞ state-feedback controller is designed, such that the system with admissible uncertainties and nonlinearities is not only internally stochastically stable but also satisfies robust H∞ performance. A sufficient condition for the existence of the desired robust H∞ controller is obtained via linear matrix inequalities(LMIs).
A Mental Timeline for Duration From the Age of 5 Years Old

Both time and number can be represented in spatial terms. While their representation in terms of spatial magnitude (distance or size) might be innate, their representation in terms of spatial position (left/right or up/down) is acquired. In Western culture, the mental timeline represents past/future events or short/long duration on the left/right sides of space, respectively. We conducted two developmental studies to pinpoint the age at which the mental timeline for duration begins to be acquired. Children (aged 5–6, 8, or 10 years old) and adults performed temporal bisection tasks in which relative spatial position (left/right) was manipulated by either arrow direction (Experiment 1) and/or lateralized stimulus location (Experiments 1 and 2). Results first confirmed previous findings that the symbolic representation of spatial position conveyed by arrow stimuli influences the perception of duration in older children. Both 8 and 10 year olds judged the duration of leftward arrows to be shorter than that of rightward arrows. We also showed for the first time that as long as position is manipulated in a non-symbolic way by the visual eccentricity of the stimuli, then even 5–6 year olds’ perception of duration is influenced by spatial position. These children judged the duration of left-lateralized stimuli to be shorter than that of either right-lateralized or centrally located stimuli. These data are consistent with the use of a mental timeline for stimulus duration from the age of 5 years old, with short duration being represented on the left side of space and long duration on the right. Nevertheless, the way in which left and right were manipulated determined the age at which spatial position influenced duration judgment: physical spatial location influenced duration perception from the age of 5 years old whereas arrow direction influenced it from the age of 8. This age-related dissociation may reflect distinct developmental trajectories of automatic versus voluntary spatial attentional mechanisms and, more generally highlights the importance of accounting for attentional ability when interpreting results of duration judgment tasks.
Isolated sign language recognition with fast hand descriptors

Recognition of sign language, the main mode of communication of the hearing impaired, has attracted the attention of researchers working in the field of computer vision in recent years. In this study, we propose a fast alternative method to the Improved Dense Trajectories (IDT) method for sign language recognition. In our proposed method, Histogram of Oriented Gradients (HOG), Histogram of Optical Flow (HOF) and Motion Boundary Histograms (MBH) are obtained from the cropped hand regions. Then, Fisher Vectors (FV) are coded and used in classification with Linear Support Vector Machine (SVM) for each descriptor from each sign video. It has been shown that our method can achieve similar performance ten times faster than IDT.
A mean-field linear-quadratic leader-follower stochastic differential game

In this paper, a linear-quadratic leader-follower (LQLF) differential game is considered, where the game system is governed by a mean-field stochastic differential equation (MF-SDE). By stochastic maximum principle, the optimal solution to the LF stochastic differential game is expressed as a feedback form of the state and its mean with the aid of two systems of Riccati equations.
Is Oxygen Uptake Measurement Enough to Estimate Energy Expenditure During High-Intensity Intermittent Exercise? Quantification of Anaerobic Contribution by Different Methods

Purpose: The aim of the present study was to compare the contributions of the anaerobic pathway as determined by two different methods and energy expenditure during a typical high-intensity intermittent exercise (HIIE) protocol. Methods: A descriptive research design was utilized in which thirteen physically active men performed six experimental sessions consisting of an incremental test (session 1), submaximal tests at 40, 50, 60, 70, 75, 80, 85, 90% of velocity associated with maximum oxygen uptake (vV˙O2max) with two intensities per session (sessions 2–5), and the HIIE protocol (session 6; 10 efforts of 1 min at vV˙O2max interspersed by 1 min of passive recovery). The estimation of anaerobic energy system contribution was calculated by: (a) the excess post-exercise oxygen consumption plus delta lactate method and (b) the accumulated oxygen deficit method using the difference between predicted oxygen demand from the submaximal tests of varying intensities and accumulated oxygen uptake during HIIE. Estimation of aerobic energy system contribution was calculated through the measurement of oxygen consumption during activity. Total EE during the entire HIIE protocol (efforts + recovery) and for the efforts only were calculated from each method. Results: For efforts + recovery and efforts only, anaerobic contribution was similar for both methods, and consequently total EE was also equivalent (p = 0.230 for both comparisons). During efforts + recovery, aerobic:anaerobic energy system contribution was (68 ± 4%: 32 ± 4%), while efforts only was (54 ± 5%: 46 ± 5%) with both situations demonstrating greater aerobic than anaerobic contribution (p < 0.001 for both). Conclusion: Anaerobic contribution seems to be relevant during HIIE and must to be taken into account during total EE estimation; however, the type of method employed did not change the anaerobic contribution or total EE estimates.
Compact 2-way H-plane power dividers for a rectangular waveguide in Ku band

Frequency bandwidth and performance of power dividers depend on their amplitude and phase imbalances besides their return loss. In this paper, for compact 2-way H-plane power dividers, 2 structures are proposed. Furthermore, designs for different ratios of output powers i.e. |S21 / S31|<sup>2</sup> almost equal to 0, 1.5, 3, 4.5 and 6 (dB) are presented in both structures and their simulation results are compared. Result of simulations approve that by increasing the power ratio of |S21 / S31|<sup>2</sup> the phase and amplitude imbalances of designed power dividers get worse. Nevertheless, for one of the proposed structures, in frequency band of 16–18GHz, designing a power divider with power ratio of 10 Log (|S21 / S31|<sup>2</sup>)= 6 ± 0.45 (dB), and phase imbalance ≤ ±4.3 degrees, and |Sn| ≤ −24 (dB) is achievable.
Rapid prototyping of flow-based detection methods using complex event processing

Detection of network attacks is the first step to network security. Many different methods for attack detection were proposed in the past. However, descriptions of these methods are often not complete and it is difficult to verify that the actual implementation matches the description. In this demo paper, we propose to use Complex Event Processing (CEP) for developing detection methods based on network flows. By writing the detection methods in an Event Processing Language (EPL), we can address the above-mentioned problems. The SQL-like syntax of most EPLs is easily readable so the detection method is self-documented. Moreover, it is directly executable in the CEP system, which eliminates inconsistencies between documentation and implementation. The demo will show a running example of a multi-stage HTTP brute force attack detection using Esper and its EPL.
HIV-1 diversity among young women in rural South Africa: HPTN 068

Background South Africa has one of the highest rates of HIV-1 (HIV) infection world-wide, with the highest rates among young women. We analyzed the molecular epidemiology and evolutionary history of HIV in young women attending high school in rural South Africa. Methods Samples were obtained from the HPTN 068 randomized controlled trial, which evaluated the effect of cash transfers for school attendance on HIV incidence in women aged 13–20 years (Mpumalanga province, 2011–2015). Plasma samples from HIV-infected participants were analyzed using the ViroSeq HIV-1 Genotyping assay. Phylogenetic analysis was performed using 200 pol gene study sequences and 2,294 subtype C reference sequences from South Africa. Transmission clusters were identified using Cluster Picker and HIV-TRACE, and were characterized using demographic and other epidemiological data. Phylodynamic analyses were performed using the BEAST software. Results The study enrolled 2,533 young women who were followed through their expected high school graduation date (main study); some participants had a post-study assessment (follow-up study). Two-hundred-twelve of 2,533 enrolled young women had HIV infection. HIV pol sequences were obtained for 94% (n = 201/212) of the HIV-infected participants. All but one of the sequences were HIV-1 subtype C; the non-C subtype sequence was excluded from further analysis. Median pairwise genetic distance between the subtype C sequences was 6.4% (IQR: 5.6–7.2). Overall, 26% of study sequences fell into 21 phylogenetic clusters with 2–6 women per cluster. Thirteen (62%) clusters included women who were HIV-infected at enrollment. Clustering was not associated with study arm, demographic or other epidemiological factors. The estimated date of origin of HIV subtype C in the study population was 1958 (95% highest posterior density [HPD]: 1931–1980), and the median estimated substitution rate among study pol sequences was 1.98x10-3 (95% HPD: 1.15x10-3–2.81x10-3) per site per year. Conclusions Phylogenetic analysis suggests that multiple HIV subtype C sublineages circulate among school age girls in South Africa. There were no substantive differences in the molecular epidemiology of HIV between control and intervention arms in the HPTN 068 trial.
Resistance-based self-sensing system of active self-melting bolt towards autonomous healing structure

Bio-inspired self-healing and self-sensing capability makes current robots more fault tolerant. On the other hand, conventional self-healing components lack self-sensing capability of their fault states and progress of healing due to system complexity. For achieving this challenge, we devised active self-melting bolt with self-sensing system of its fracture and temperature. The system utilizes electric resistance values of the bolt module itself for minimizing additional components and wiring. The system is composed of two subsystems: fracture detecting system and strength feedback system. We describe its principle and manufacturing process for the proposed system. Its feasibility was partially validated by preliminary tensile test using motor-driven tendon unit previously developed by our research group.