Miracle-dz/UniFAR-FTUs huggingface dataset:
Design of a wideband patch antenna and performance enhancement using an AMC reflector surface for on-body communication at 2.45 GHz

ABSTRACT Wireless biotelemetry enables the formation of communication link from living body to an external monitoring device. Isolation of near field electromagnetic (EM) waves from body tissue, and wide bandwidth to avoid frequency detuning in different biological environments are the important parameters of on-body antennas. In this paper, a conformal defected ground patch antenna with artificial magnetic conductor (AMC) is introduced for on-body communication. Initially, a quarter wave wide band antenna with a shorting pin is designed to operate at 2.45 GHz. It resonates effectively on body tissue but most of the near field EM radiations are absorbed by tissue. Poor radiation efficiency of 10% and high specific absorption rate (SAR) value of 7.73 W/Kg were obtained. Thus, to reduce the effect of tissue loading on antenna performance an AMC-based structure is added. Better impedance matching, high efficiency (65%) and directivity (7.3 dBi) is achieved with AMC structure. Furthermore, unidirectional radiation pattern with SAR value of 1.43W/Kg is attained. Wide bandwidth of 600 MHz on phantom enables the antenna to withstand frequency detuning effect due to body postures and movements. Antenna robustness is analysed by bending the structure at different radii along X-axis and Y-axis.
Multi-functional hybrid active power converter and its industrial application for electrolytic copper-foil

To meet the requirements of high-power compensating occasion such as electrochemical industries, a multifunctional hybrid active power converter (HAPC) with LC series filter is studied to effectively integrate functions of rectification and power compensation. HAPC can be used as a high-power pulse width modulation rectifier to supply its dc load, meanwhile, it can also compensate large amount of reactive and harmonic current without increasing the voltage rating of itself. A compound current control method for HAPC is introduced so as to improve the dynamic tracking performance. The current and voltage dual closed-loop system of HAPC is built in s domain, and the detailed control parameters are designed to tune control performance further. Finally, a set of 800 kVA HAPC system for electrolytic copper-foil is developed. The results show that the HAPC system can achieve expected operation performance and largely improves power quality of power grid.
A Selective Screening Strategy Performed in Pre-School Children and Siblings to Detect Familial Hypercholesterolemia

(1) Background: Familial hypercholesterolemia (FH), a most common genetic disorder, is underdiagnosed and untreated, especially in children. Individuals with heterozygous familial hypercholesterolemia mostly present without clinical symptoms and are not informed about their high risk for myocardial infarction. Early diagnosis and treatment can prevent premature atherosclerosis and cardiovascular events in patients with FH. The aim was to evaluate the detection rate of pre-school children with FH at school doctor visits in Vienna and, moreover, to examine the frequency of FH identified in the children’s siblings by this type of screening. (2) Methods: The selective FH- screening was implemented at the school enrolment examinations in the public primary schools of Vienna. The study period included the school years starting in 2017 to 2020. FH was suspected if a questionnaire on hypercholesterolemia, or cardiovascular events in the family history or on the presence of xanthomas or xanthelasma, was positive. Subsequently, lipid testing was performed on pre-school children and their siblings and elevated lipid screening was defined as either positive by LDL-C ≥ 160 mg/dL and/or non-HDL-C ≥ 190 mg/dL or as borderline by LDL-C ≥ 130 mg/dL and/or non-HDL-C ≥ 160 mg/dL. (3) Results: 66,108 pre-school children participated in the school enrolment examination in 868 public elementary schools in Vienna. In 512 (4%) children, the questionnaire caused suspicion of FH. 344 families agreed their participation in the study. Out of 344 (52% male) tested pre-school children, 20 individuals (40% male) had elevated blood lipid levels with a mean LDL-C of 155 ± 29 mg/dL and a non-HDL-C of 180 ± 24 mg/dL. Out of 291 (44% male) tested siblings, 17 individuals (41% male) showed elevated lipids with a mean LDL-C of 144 ± 19 mg/dL, and a non-HDL-C of 174 ± 19 mg/dL. (4) Conclusions: Screening is the key for early diagnosis and treatment of FH. We have implemented a pre-school screening strategy in cooperation with school physicians. We could identify 20 pre-school children and 17 siblings with an elevated lipid screening test. Full implementation of FH-screening in the pre-school examination visits in Vienna would help to detect high-risk children.
Mediating Multilingual Immigrant Learners’ L2 Writing Through Interactive Dynamic Assessment

: Dynamic Assessment (DA) has lately taken the floor as an alternative by embedding instruction into assessment. Grounded in the dialogic teacher-learner interaction during an in tandem work, DA asserts that diagnosing the learners’ matured abilities and needs, mediating them accordingly, and then observing their maturing abilities and microgenesis are crucial. This assertion paves the way to reveal each learner’s Zone of Proximal Development (ZPD). Despite some influential studies on the use of DA in language education, more studies are warranted to explore the use of DA in different contexts and with different participants. Therefore, this case study recruited two multilingual immigrants/refugees who were underachievers in L2 writing classes. They were provided individual interactive DA for ten weeks, and the dialogic interactions between the teacher and the students were analyzed. Initial results revealed that the mediational moves mainly rested on teacher-agency, but over time more learner-agency-oriented mediational moves were also adopted. Furthermore, these students started to narrow the gap between themselves and their classmates. Lastly, a semi-structured interview was conducted to illustrate the participants’ perspectives towards DA in the L2 writing context, and the related data revealed recurrent themes that had bidirectional relation with DA’s theoretical premises.
Review of 'direct plate' processes & assessment of the impact on primary imaging of printed wiring boards

Environmental, cost, and performance criteria are providing the impetus for printed wiring board (PWB) fabricators to evaluate and adopt direct plate processes as replacement for the traditional electroless copper metallization of conductor vias. This paper surveys direct plate processes and their advantages and disadvantages compared to the electroless copper process. Special emphasis is given to the impact of direct plate processes on the application and processing of photoresists. Surface preparation and other processing requirements are discussed.
Comment évaluer la performance RH ? Question universelle, réponses contingentes

Even if measuring HR performance has become a universal issue for firms, answers are still confusing. Furthemore, academics and praticioners still have difficulties to leran to each other. Following thes two statements, the AA. constructed a participative research with a exchange group gathering HR mangers during one year. Observing that the evaluating pratcices and the way HR are positioned in the firm are strongly linked, They use Ulrich model (1996) to study evaluating tool's choice. They conclude that technical criteria are less useful than pertinece of the evaluating tools with missions of the HR function and the consistency of the fifferent componments of evaluating process
The Impact of Energy Commodity Prices on Selected Clean Energy Metal Prices

The United Nations Framework Convention on Climate Change Paris Agreement has been announced as a crucial step towards combating the global threat of climate change. In the light of ambitious plans for further renewable energy sources development, high demand for nonenergy materials critical for RES is greatly expected. In conclusion, future energy security will be surely based on nonenergy commodities critical for them. As this article directly relates to issues related to new technologies and energy security in new form, the main purpose of this study is to examine the impact of energy commodity prices, namely crude oil, natural gas and coal prices on selected metal prices such as aluminium, chromium, cobalt, copper, lead, nickel, silver, tin, or zinc, both before and over the Paris Agreement period. We are looking for new insights in terms of relationships between traditional fossil fuels and metals used in clean energy technologies potentially established or strengthened shortly after the Paris Agreement was adopted. Currently, the analyses of the impact of institutional conditions such as global agreements (institutional factors) on the emerging or strengthening of relationships between energy and nonenergy resources are very limited. Hence, an autoregressive distributed lag and error correction model are employed.
An LADRC Controller to Improve the Robustness of the Visual Tracking and Inertial Stabilized System in Luminance Variation Conditions

Disturbance from luminance variation in the identification of visual sensors causes instability in the control system of target tracking, which leads to field of vision (FOV) motion and even the target missing. To solve this problem, a linear active disturbance reject controller (LADRC) is adopted to the visual tracking and inertial stable platform (VTISP) for the first time to improve the system’s robustness. As a result, the random disturbance from identification can be smoothed by the tracking differentiator (TD). An improved linear extended state observer (LESO) modified by the TD is provided to obtain the high-order state variables for feedback. That makes the system avoid noise in a differential process from the MEMS gyroscope and enhances the response time and stability in tracking control. Finally, simulation and experimental studies are conducted, and the feasibility of the LADRC is verified. Moreover, compared with the other controller in the VTISP for remote sensing, the superiority of the LADRC in system response time and stability is proved by the experiments.
A STACKED ENSEMBLE TECHNIQUE WITH GLOVE EMBEDDING MODEL FOR DEPRESSION DETECTION FROM TWEETS

With the increasing volume of web content on social network sites like Facebook, Twitter, etc. identifying the attitude of people becomes an easy task. That attitude can be used as an input to find the mental status of that person through their texts. According to WHO, depression is a general mental disorder, which has already affected more than 264 million people. With the help of sentiment analysis, it is possible to detect depression at an early stage from their tweets as they represent their attitude. Machine Learning Classification algorithms help to classify the texts as Depressed or non-depressed, but their accuracy is limited when researchers are using only traditional Bag of Words vectorizers to extract features. Instead of this, word embedding models can be used which represent words as real-valued vectors in a distinct vector space that is already defined and provides better accuracy. In this paper, we try to implement eight machine learning techniques for depression detection from tweets namely SVM, Logistic Regression, ExtraTree, Bagging, Random Forest, AdaBoost, XG boosting, and Gradient Boosting which employs different word embeddings like Word2Vec, FastText, and Glove on the dataset which is used to train the classifiers and performed a comparative evaluation of word embedding models with different classifiers. This study proposes a new Stacked ensemble technique with a glove embedding model for Depression detection from Tweets which provides higher accuracy than standalone models.
An Information-Theoretic Approach for Detecting Community Structure Based on Network Representation

Community structure is a network characteristic where nodes can be naturally divided into densely connected groups. Community structures are ubiquitous in social, biological, and technological networks. Revealing community structure in the network helps in the understanding of the topological associations and interactions of elements in the network, as well as helping to mine their potential information. However, this has been proven to be a difficult challenge. On the one hand, this is because there is no unified definition of the quality of a community; on the other hand, due to the complexity of the network, it is impossible to traverse all the possibilities of community partitions to find the best one. Aiming at performing high-accuracy community detection, an information-theoretic approach AMI-NRL was proposed. The approach first constructs a community evolution process based on the representation of the target network, then finds the most stable community structure during the evolution using an average-mutual-information-based criterion. The experiments show that the approach can effectively detect community structures on real-world datasets and synthetic datasets.
Research on defect recognition method of substation inspection images based on faster R-CNN

Aiming at the problems of low efficiency and poor accuracy in manual identification of tens of thousands of substation inspection images in the power grid, one method and system for identifying defects in substation inspection image data based on Faster R-CNN is proposed. The inspection images are preprocessed through data analysis module, image annotation module, image cleaning module, firstly. A convolutional neural network (CNN) is used to perform feature extraction on the processed images to obtain the target features, secondly. A Region Proposal Network (RPN) is introduced, which generates multiple candidate anchor frames on the target feature images, thirdly. Region of Interest (ROI) pooling is performed on the multiple candidate anchor frames to obtain a feature matrix of a fixed size, fourthly. Then, the frame regression and classification recognition are applied to obtain the defect recognition result and target anchor frame position. Finally, high-precision identification of 25 types of defects of substation inspection images such as oil leakage, insulator damage, mark damage, metal corrosion， is realized. The average accuracy of the method is as high as 93.44%, which is about 27% and 23% higher than the traditional systems with R-CNN and Fast R-CNN algorithms. The time of single image recognition is shortened to (150ms) millisecond level. This method greatly saves the detection time, which can effectively reduce manpower input, improve work efficiency more effectively, and provide a foundation for the digital transformation of the power grid.
Management of inflow forecasting studies

In hydroelectric systems, water inflow is important to coordinate a cascade and define the energy price. This paper presents a method for managing inflow forecasting studies with a specific module for advanced assessment. The main goal is to provide a structure that facilitates the analysis of water inflow prediction models. A case study has been applied to five mathematical models based on linear regression, artificial neural networks, and hydrologic simulation. These models present daily and monthly inflow forecasts for a set of hydroelectric plants and monitoring stations. The benefits of the proposed method are analyzed in four situations: water inflow prediction, performance evaluation of a specific model, research tool for inflow forecasting, and comparison tool for distinct models. The results show that implementation of the proposed method provides a useful tool for managing inflow forecasting studies and analyzing models. Therefore, it can assist researchers and engineering professionals alike by improving the quality of water inflow predictions.
Neural Embeddings for the Elicitation of Jurisprudence Principles: The Case of Arabic Legal Texts

In the domain of law and legal systems, jurisprudence principles (JPs) are considered major sources of legislative reasoning by jurisprudence scholars. Generally accepted JPs are often used to support the reasoning for a given jurisprudence case (JC). Although eliciting the JPs associated with a specific JC is a central task of legislative reasoning, it is complex and requires expertise, knowledge of the domain, and significant and lengthy human exertion by jurisprudence scholars. This study aimed to leverage advances in language modeling to support the task of JP elicitation. We investigated neural embeddings—specifically, doc2vec architectures—as a representation model for the task of JP elicitation using Arabic legal texts. Four experiments were conducted to evaluate three different architectures for document embedding models for the JP elicitation task. In addition, we explored an approach that integrates task-oriented word embeddings (ToWE) with document embeddings (paragraph vectors). The results of the experiments showed that using neural embeddings for the JP elicitation task is a promising approach. The paragraph vector distributed bag-of-words (PV-DBOW) architecture produced the best results for this task. To evaluate how well the ToWE model performed for the JP elicitation task, a graded relevance ranking measure, discounted cumulative gain (DCG), was used. The model achieved good results with a normalized DCG of 0.9 for the majority of the JPs. The findings of this study have significant implications for the understanding of how Arabic legal texts can be modeled and how the semantics of jurisprudence principles can be elicited using neural embeddings.
Effect of the addition of cellulolytic bacteria to ruminal bacteria on in vitro fermentation characteristics

26 Background : Digestibility of fiber in the rumen is not due to enzymatic activity of individual 27 bacteria, but rather to their interaction, which complements their enzymatic functioning. Thus, 28 efficiency of fiber digestion depends on the diversity and density of cellulolytic bacteria. 29 Objective: To estimate in vitro production of biogas, methane, and fermentative characteristics of 30 cobra grass ( Brachiaria hibrido ) inoculated with ruminal bacteria (RB) in coculture with isolated 31 cellulolytic bacteria (ICB) from bovine (ICB bov ) or water buffalo (ICB buf ). Methods : ICB bov and 32 ICB buf were isolated from ruminal cellulolytic bacteria consortia using specific culture media for 33 cellulolytic bacteria. Both were morphologically characterized, and a Gram stain was performed. 34 In the in vitro gas production test, the substrate was cobra grass and the inocula were ruminal 35 bacteria (RB), ICB bov , ICB buf , Coculture bov (RB + ICB bov ) and Coculture buf (RB + ICB buf ). 36 Production of biogas and methane (CH 4 ), as well as dry matter degradation (DMD) and neutral 37 detergent fiber degradation (NDFD) were measured. A completely randomized design was used. 38 Results : ICB were Gram positive cocci. Accumulated biogas production at 72 h from ICB bov and 39 ICB buf was on average 42.11% of that produced by RB. The Coculture bov produced 14.24% more 40 biogas than RB. CH 4 production was lower in ICB bov and ICB buf than in RB, Coculture bov and 41 Coculture buf . DMD and NDFD were not different among RB, Coculture bov and Coculture buf . ICB bov 42 degraded 37.10 and 96.34% more DMD and NDFD than ICB buf (p<0.05). Conclusion : The use of 43 ICB from bovine or water buffalo in coculture with RB does not improve in vitro production of 44 biogas, DMD or NDFD with respect to RB alone.
Multifunctional shape memory electrodes for dielectric elastomer actuators enabling high holding force and low-voltage multisegment addressing

Dielectric elastomer actuators (DEAs) are an attractive form of electromechanical transducer, possessing high energy densities, an efficient design, mechanical flexibility, high speed, and noiseless operation. They have been incorporated into a variety of elegant devices, such as microfluidic devices, tunable optics, haptic displays, and minimum-energy grippers. Dielectric elastomer minimum energy structures (DEMESs) take advantage of the prestretch of the DEA to bend a non-stretchable but flexible component to perform mechanical work. The gripper is perhaps the most intuitive type of DEMES, capable of grasping objects but with only small to moderate forces. We present a novel configuration of a DEA using electrodes made of a conductive shape-memory polymer (SMP), incorporated into the design of a gripper. The SMP electrodes allow the DEA to be rigid in the cold state, offering greater holding force than a conventional gripper. Joule heating applied to the SMP electrodes softens them, allowing for electrostatic actuation. Cooling then locks in the actuated position without the need for continued power to be supplied. Additionally, the Joule heating voltage is at least one order of magnitude less than electrostatic actuation voltages, allowing for addressing of multiple actuator elements using commercially available transistors. The shape memory gripper incorporates this addressing into its design, enabling the three segments of each finger to be controlled independently.
Wind power harvester based on an aerodynamic double pendulum

Dynamics of an aerodynamic double pendulum coupled with a linear generator is considered. A cubic nonlinear spiral spring is installed in the first joint of the pendulum. Numerical simulation of the behavior of the pendulum is performed. It is shown that it is possible to choose parameters in such a way as to ensure the instability of the equilibrium and the existence of limit cycle oscillations. Such oscillations are required for the system to be capable of wind power harvesting. The influence of characteristics of the joint spring upon the amplitude and frequency of the cycles is analyzed. In particular, it is shown that the amplitude non-monotonically depends on the parameter characterizing the cubic nonlinearity of the stiffness. In the same time, frequency monotonically increases as this parameter increases. The influence of the system parameters upon the output power is estimated.
Superconducting Bearing Design for Outer Rotor Flywheel Using Lumped Parameter Techniques

This paper describes the application of lumped parameter modeling techniques to designing high temperature superconducting bearings for outer-rotor flywheel energy storage systems. The lumped parameter models decrease computational time by 99% compared to Finite Element Analysis (FEM) without compromising fidelity needed to capture the non-linear and hysteretic force-displacement behavior between a levitated permanent magnet and bulk superconductor. The techniques formulated can be used to quickly evaluate lifting capacity and translational stiffness for a superconducting bearing design. The validity of the modeling approach has been verified by comparing results from FEM studies and experimental tests. 