Miracle-dz/UniFAR-FTUs huggingface dataset:
Design and Development of IoT-based SMART Monitoring System for Hydro-Powered Generator

Copious and accessible renewable energy for hydroelectric generation resources creates an attractive system, converting hydro energy into electrical energy. Due to the increase in the utilization of renewable energy resources, such as hydro energy, day by day it is making certain issues in terms of monitoring, especially in remote areas where the generator and other key components are located and established. This study intends to show the potential of developing and prototyping an IoT-based SMART monitoring system for Hydro Powered-Generator, with the integration of the Internet of Things (IoT). The focus of this paper is on designing and constructing a device that can help in real-time monitoring with less power consumption using the deep sleep mode mechanism. The monitoring system with the use of ESP modules will give data(s) such as pH level, voltage, and current harvested from the turbine and a data image using the Esp32 Camera Module. The following monitored data(s) are stored in the database and can be interfaced anytime through a user-friendly web application.
Model-Free Sensor Fusion for Redundant Measurements Using Sliding Window Variance

In this paper, a model-free data fusion method for combining redundant sensor data is presented. The objective is to maintain a reliable tool center point pose measurement of a long-reach robotic manipulator using a visual sensor system with multiple cameras. The fusion method is based on weighted averaging. The weight parameter for each variable is computed using the sliding window variance with N latest observations. After each sliding window, the window length N is updated, and simple transition smoothing is included. For experimental validation, two sets of pose trajectory data from redundant visual sensors were obtained: 1) using a camera located near the tip of a long-reach manipulator running a simultaneous localization and mapping (SLAM) algorithm and 2) marker-based tracking with cameras located near the base of the manipulator. For pose tracking, a fiducial marker was attached near the SLAM camera. The proposed methodology was examined using a real-time measurement setup and offline data analysis using the recorded data. The results demonstrate that the proposed system can increase the overall robustness and fault tolerance of the system, which are desired features for future autonomous field robotic machines.
A Model-Based Reinforcement Learning Approach for Robust PID Tuning

Proportional-Integral-Derivative (PID) controller is widely used across various industrial process control applications because of its straightforward implementation. However, it can be challenging to fine-tune the PID parameters in practice to achieve robust performance. The paper proposes a model-based reinforcement learning (RL) framework to tune PID controllers leveraging the probabilistic inference for learning control (PILCO) method. In particular, an optimal policy given by PILCO is transformed into a set of robust PID tuning parameters for underactuated mechanical systems. The robustness of the devised controller is verified with simulation studies for a benchmark cart-pole system under server disturbances and system parameter uncertainties.
Analysis of Acoustic Correlates of Marathi Prosodic Features for Human-Machine Interaction

The prosodic feature study gives insight into the suprasegmental properties of speech. Researchers have been studying acoustic features of prosody worldwide to design a model for prosody in various languages to make human-machine interaction natural. This study focuses on the interface between linguistics and technology, particularly for less studied languages like Marathi, to improve human-machine interaction applications by investigating acoustic correlates of various prosodic features of Marathi emotional utterances. The Marathi language, spoken in the Indian states of Maharashtra and Goa, has received relatively little attention for prosody. Due to a lack of appropriate resources, studying the prosodic features of the Marathi language was difficult. With the help of seven male and four female actors, we created a database of 440 Marathi utterances in the four main emotion styles—anger, happiness, fear, and neutral. The acoustic correlates of prosody were calculated from the recorded dataset using PRAAT software. According to this study, the prosodic characteristics of Marathi emotional utterances alter in response to emotions. However, anger and happiness; and fear and neutral emotions share somewhat similar acoustic properties.
Evasion-Aware Neyman-Pearson Detectors: A Game-Theoretic Approach

Network security relies heavily on the detection of adversarial behaviors. Traditional detection methods, such as anomaly detection and signature detection, are inadequate for detecting increasingly intelligent, deceptive, and stealthy attacks. They are designed to be capable of evading well-known detection strategies strategically. This work aims to develop an evasion-aware detection theory to counteract such adversaries. We focus on extending a fundamental class of Neyman-Pearson (NP) hypothesis testing techniques, which have been widely used for anomaly detection and intrusion detection problems in network security. We propose game-theoretic models to capture evasion-aware NP detectors. By analyzing both the equilibrium behaviors of the attacker and the NP detector, we characterize their performance using Equilibrium Receiver-Operational-Characteristic (EROC) curves. We show that the evasion-aware NP detectors outperform the passive ones in the way that the former can act strategically against the attacker's behavior and adaptively modify their decision rules based on the received messages. We use a case study of anomaly detection to corroborate the analytical results. This work creates a theoretical underpinning for building next-generation evasion-aware detection systems that can better cope with ever-developing cyber attacks.
Isotropic Solutions of the Einstein‐Liouville Equations

The gravitational field generated by a gas whose one‐particle distribution function obeys the Liouville equation is examined under the following assumptions: First, the distribution is locally isotropic in momentum space with respect to some world‐velocity field; second, if the particles have rest‐mass zero, the gas is irrotational. It is shown that the model is then either stationary or a Robertson‐Walker model. The time dependence of the radius in the Robertson‐Walker models is given in terms of integrals containing the distribution function.
Impact of Frequency Offset on Artificial Noise Suppression in SIMO Physical Layer Security Systems

Artificial noise (AN) is an effective physical security measure against eavesdropping in wireless communication. In previous literatures, AN is generally analyzed in multiple transmit antenna systems and is suppressed by zero-forcing algorithm, which is implemented by using the spatial degrees of freedom. In this paper, an AN suppression model under single-input multi-output (SIMO) systems is presented, and the impact of imperfect frequency synchronization on the AN suppressed performance is analyzed. Specifically, we first analyze the AN suppression performance of single branch with imperfect frequency synchronization. Then the output signal to interference plus noise ratio (SINR) after multi-branch merging is derived. Finally, the secrecy capacity of AN based on SIMO systems is extracted on the basis of the obtained SINR. Theoretical and simulation results show that imperfect frequency synchronization reduces the SINR of each branch, and thus degrades both the output SINR and secrecy capacity in SIMO systems. Moreover, when the residual AN power is greater than noise power, no diversity gain will be achieved by multi-branch merging.
Features of metacognitive beliefs of adolescents with a high level of personal anxiety

The article contains an analysis of the problems of personal anxiety among adolescents. Anxiety is considered as a property of the personality, which is manifested in the cognitive aspect, emotional reaction, physical reaction and behavior of the individual. The general purpose of the study was to identify the metacognitive beliefs of adolescents with a high level of personal anxiety and was realized thanks to the implementation of such tasks as: identifying adolescents with a high level of personal anxiety, studying personal attitudes towards symptoms, determining and comparing the metacognitive beliefs of adolescents with different levels of personal anxiety, determining predictive power of metacognitions of young people with a high level of personal anxiety. The results of a study of the prevalence of reactive and personal anxiety among adolescents are presented, a comparative analysis of one's own opinion regarding the presence of symptoms and test results of adolescents with a high level of personal anxiety is carried out. A new approach to the study of personal anxiety from the perspective of metacognitive beliefs is proposed, which is built on the principles of cognitive-behavioral psychology. Metacognition is defined as the basis of automatic thoughts, emotional and physical reactions, and the role of metacognitive processes in the interpretation of information about the level of security, the formation of judgments, assessments. The article proves that the metacognitions of adolescents with a high level of personal anxiety deprive them of flexibility in behavior, limiting the variability of life experience. The metacognitive portrait of young people with a high level of personal anxiety is characterized, in particular: the belief that anxiety is a protection against difficult emotions in anticipation of negative events; a positive attitude towards one's own anxious experiences is reinforced by a desire to prevent negative outcomes. As a result of the conducted research, the prospects for developing a method of targeted psychological influence within the cognitive-behavioral approach have been opened
Formulation of a biocellulose mask containing the essence of Aloe vera (L.) Burm.f combination with vitamin E as anti-aging

Most ageing processes are accelerated due to an increasing amount of endogenic stress from outdoor or indoor activity overload. The essence of aloe vera is formulated in the form of a biocellulose mask. It is one of the solutions to deliver essence within polymeric substances, obtained through the fermentation process with the help of Acetobacter xyllinum. The aim of this study is to enhance anti-ageing activity derived from Aloe vera (L) essence combined with vitamin E, thus in the form of a biocellulose mask that will prolong skin contact and reduce the main cotton sheet mask problem of deforestation, hence its eco-friendly benefit. Material and methods: Twelve volunteers around 25 to 45 years old are subjected to a biocellulose mask containing Aloe vera essence combined with vitamin E for at least 4 weeks to achieve a balanced skin criterion including wrinkles, spots, facial pores, and moisture. Aloe vera and vitamin E constituents within F0; F1, F2; F3, [0%, 0%]; [0%, 1%]; [5%, 0 %] and [5 %, 1 %] as per the following. Results: Results showed that bio-cellulose masks containing 5 % Aloe vera with 1 % of vitamin E essence in F3 provide a beneficial anti-ageing activity rather than other biocellulose mask preparations. Conclusion: Biocellulose mask through the fermentation process can improve skin conditions, the formula combined with the well-known activity of aloe vera as an exfoliating agent and antioxidant vitamin E, it can not only provide skin rejuvenation but also provide anti-ageing activity
Corrosion Inhibitive Potentials of Some N-Alkyl Benzimidazoles and their Corresponding Ionic Liquids on a Mild Steel Surface: Experimental and Theoretical Approach

U2 and U4 were successfully synthesized from C 7 H 6 N 2 N-alkylation (general and useful route to quaternary ammonium salts NH4Cl from tertiary amines) with alkyl bromides. The products were further alkylated to the corresponding ILs: U5 and U7. All the synthesized compounds were characterized by spectroscopic techniques, and their compositions were established through elemental analysis. The synthesized compounds were investigated as inhibitors for MS corrosion, using 1 M HCl as a model solution. WL experiments, surface analysis, quantum chemical calculations and MD simulation methods were used for evaluating the inhibitors anticorrosion properties. The results showed that ILs possessed remarkable inhibition properties under the studied conditions. U5 displayed the highest IE of 95.22%, at 200 ppm. ILs corrosion IE(%) was ascribed to their adsorption onto the MS surfaces, which followed the Langmuir’s isotherm. SEM revealed the formation of a barrier film by the inhibitors on the MS surface. Finally, the experimental results were corroborated by theoretical quantum chemical calculations and MD simulation studies. The studied inhibitor molecules interaction energies with the Fe surface followed the order U5 > U7 > U2 > U4, which is consistent with the experimental data.
Model-based object recognition by wave-oriented data processing

Object recognition can be parametrized systematically through physically robust wave objects by linking features (observables) in scattered field data with features on the object (target) giving rise to the data. The wave objects are broadly separated into global (mode) and local (wavefront) categories. Their parametrization requires different wave-oriented signal- processing algorithms which are implemented conveniently in relevant subdomains of the configuration (space-time) spectrum (wavenumber-frequency) phase space. Projection of scattering data onto the phase space is achieved via Gaussian-windowed Fourier transforms, wavelet transforms, and windowed model-based (superresolution) algorithms. Example results are presented here for time-domain modes excited by an open cavity as well as by periodic and quasi-periodic structures, with data processed in the time-frequency phase space. Additionally, we consider frequency-domain modes (leaky modes supported by a dielectric slab) which are processed in the space-wavenumber phase space. For some situations, it is more appropriate to process the entire database simultaneously (without windowing), and we have used such techniques for certain modal and wavefront parametrizations. Concerning modal 'footprinting', results are presented for superresolution processing of measured short-pulse scattering data from resonant targets embedded in foliage (foliage penetrating radar); in these examples we extract late-time target resonant frequencies. We have also applied superresolution algorithms to wavefront-based processing, and results are presented here for model targets.
Toke: Rural Economic Institution in Indonesia

This study discussed toke as an economic institution in the village. Sociologically, toke is always studied through a patron-client approach that causes peasant households to always be in poverty. While the author's experience received social and economic support from toke. This is an ethnographic study, the researcher stayed with toke for more than a year. Researchers conducted engaged participation in all toke activities, observation of the entire area of Parit Baru village and in-depth interviews with selected informants. The study found that toke is a village economic institution that plays a role not only economically but also socially by ensuring the continuity of household consumption through debt. Toke requires 4 rounds of capital to stay on as a toke and always add clients through debt. If toke tidan is able to meet the demand for a loan of money from its client, then automatically the existing debt is considered to be paid off. This research contributes to rural socioeconomic studies, particularly to client patron theory. That the toke is not only a sucker for farmers but also as a guarantor of the slimness of household consumption.
On the Role of Structure in Manipulation Skill Learning

: We propose a new policy class, Composable Interaction Primitives (CIPs), specialized for learning sustained-contact manipulation skills like opening a drawer, pulling a lever, turning a wheel, or shifting gears. CIPs have two primary design goals: to minimize what must be learned by exploiting structure present in the world and the robot, and to support sequential composition by construction, so that learned skills can be used by a task-level planner. Using an ablation experiment in four simulated manipulation tasks, we show that the structure included in CIPs substantially improves the efficiency of motor skill learning. We then show that CIPs can be used for plan execution in a zero-shot fashion by sequencing learned skills.
String solitons in the M5-brane worldvolume with a Nambu-Poisson structure and Seiberg-Witten map

We analyze BPS equations for string-like configurations derived from the M5-brane worldvolume action with a Nambu-Poisson structure constructed in ref. [1, 2]. We solve the BPS equations up to the first order in the parameter g which characterizes the strength of the Nambu-Poisson bracket. We compare our solutions to previously constructed BPS string solitons in the conventional description of M5-brane in a constant three-form background via Seiberg-Witten map, and find agreement.
Chronic stress is associated with reward and emotion-related eating behaviors in college students

Introduction Stress is related to altered olfactory perception and eating behaviors. The current study investigated the association between chronic stress, food reward and perception of food and non-food odors among college students. Methods Sixty-one participants completed the Perceived Stress Scale (PSS) and the Brief Daily Stressors Screening Tool (BDSST). The detective threshold and suprathreshold perception (pleasantness, intensity, and familiarity) of two food (chocolate, strawberry) odors and a non-food (rose) odor were measured. Food reward and macronutrient preference were measured using the computerized Leeds Food Preference Questionnaire and the Macronutrient and Taste Preference Ranking task, respectively. Reward-related eating, emotional eating and eating-related inhibitory control were measured by the Dutch Eating Behavior Questionnaire (DEBQ) and the Reward-Based Eating Drive Scale (RED) scales. Results Neither the perceived stress or the severity of daily life stressor exposure was related to odor sensitivity, however, the PSS score was significantly correlated with pleasantness for strawberry odor (r = 0.329, p = 0.013). Chronic stress (PSS and BDSST scores) was significantly correlated with the DEBQ emotional eating and reward-related eating measured by RED (all ps < 0.01). Moreover, the BDSST score was negatively correlated with subjective liking for low-calorie sweet foods (r = −0.46, p < 0.001). Discussion Together, our preliminary results suggest disassociated effect of chronic stress on odor perception and eating behaviors.
The impact of bariatric surgery on macronutrient malabsorption depends on the type of procedure

Introduction Bariatric surgery, currently the most effective treatment for morbidly obese patients, may induce macronutrient malabsorption depending on the type of procedure. Macronutrient malabsorption affects the supply of substrates to the colon, subsequent microbial fermentation and possibly colonic health. Methods Using isotope technology, we quantified the extent of macronutrient and bile acid malabsorption and its impact on colonic protein fermentation in patients after Roux-en-Y gastric bypass (RYGB) and sleeve gastrectomy (SG) and in controls. Participants consumed a single test meal (day 0) that contained intrinsically labeled (13C, 15N, and 2H) egg protein for quantification of protein digestion, malabsorption and fermentation, respectively, together with a transit marker and a marker for bile acid malabsorption. They collected breath samples up to 6 h and all urine and stool for 48 and 72 h, respectively. Food intake was registered from day –3 to day 2. Results Malabsorption of fat, protein and carbohydrates differed between groups (p = 0.040; p = 0.046; and p = 0.003, respectively) and was slightly higher in RYGB but not in SG patients compared to controls. Protein fermentation was increased in both RYGB and SG patients compared to controls (p = 0.001) and was negatively correlated to 2H-recovery as a marker of transit (ρ = −0.47, p = 0.013). Conclusion The limited macronutrient malabsorption likely does not affect the nutritional status of the patient. However, the higher protein fermentation may affect colonic health and warrants further investigation.
Incidence and risk factors for surgical site infection following enucleation in dogs

Introduction Surgical site infections (SSI) increase morbidity, increase treatment costs, and can delay onset of necessary adjunctive therapy. The goal of this retrospective study was to determine the incidence of and risk factors of SSI after enucleation in dogs. Methods Medical records were searched at one veterinary teaching hospital and identified 280 dogs that underwent enucleation and had an adequate follow-up to assess SSI. Multiple preoperative (e.g., reason for enucleation), peri-operative (e.g., surgical approach and surgeon experience level), and post-operative (e.g., use of post-operative antibiotics or anti-inflammatory medications) variables were assessed as risk factors for development of SSI. Results The incidence of SSI after enucleation was 5%, and no risk factors for SSI were identified. Dogs that received cephalexin as a prophylactic post-operative antibiotic were statistically more likely to develop SSI versus those that received a different post-operative antibiotic (p = 0.045). However, the clinical significance of this finding is unclear as administration of prophylactic post-operative antibiotics overall did not reduce the risk of SSI in the population evaluated here. Discussion No risk factors were identified to guide clinical decision-making for prevention of SSI. Additionally, the results do not support the use of prophylactic antibiotics after enucleation in dogs.