Miracle-dz/UniFAR-FTUs huggingface dataset:
A new system for measurement of the pulse transit time, the pulse wave velocity and its analysis

Arterial stiffness is a strong determinant of cardiovascular risk. Pulse wave velocity (PWV) is an index of arterial stiffness, and its prognostic value has been repeatedly emphasized. The work presented in this paper is concerned with the design of a new system for measurement of the pulse wave velocity (PWV) and analysis. It is in fact related to the description of the hardware setup and the software development in order to measure and analyze the (PWV). In the proposed system, the determination of the PWV is carried out through the measurement of the pulse wave transit time (PWTT) using the electrocardiogram (ECG) and the photoplethysmogram (PPG) and the distance separating the site of ejection of the systolic pulse and the site of measuring the PPG signal. The hardware setup therefore consists of an optical device to detect the PPG and electrodes to detect ECG, and different boards to process and digitalize these signals to be acquired in the PC and analyzed. The developed software is concerned with first, the acquisition and processing of both ECG and PPG signals then the determination of the PWV and finally its analysis for different subjects and conditions. The analysis of the PWV is carried out for subjects of different ages in different physiological conditions according to heart activity. The obtained results show that there is a high correlation (r=0.88), between heart rate variability (HRV) and PWV. They also show that PWV increases with age. The analysis of the PWV variations with age is also carried out through different regression models. The obtained result shows that the cubic regression model best fits these variations.
Automatic Short Answer Grading Using Paragraph Vectors and Transfer Learning Embeddings

automatic short answer grading (ASAG) is the process of assessing short answers by utilizing computational approaches. Recent research attempts to solve this problem based on semantic similarity and deep learning models. The objective of this paper is to evaluate the proposed models in grading short answers by computing the semantic similarity between the student and a key answer. We suggest training the paragraph vectors and transfer learning models on a domain-specific corpus instead of using the pre-trained models. Then, the trained models are used to generate embeddings that represent the student and reference answers as vectors. We computed the similarity between the vectors of the reference and student’s answer.
Data Analyzing by Attention to Weighted Multicollinearity in Logistic Regression Applicable in Industrial Data

The Middle Easts largest industrial complex produces ˚�at steel sheets with specific properties such as low thickness, high strength and suitable formabil ity in order to reduce the vehicle weight and fuel consumption and prevention of environmental pollution. The aim of this study is to investigate the effect of some important explanatory variables on suitable formability of manufacturing steel sheets accor ding to primary data set. Existence or lack of existence of crack on steel sheet is considered as a binary response variable. It is determined by bending test with the angle of zero degree. Existence of multicollinearity between mentioned explanatory variables has an effect on the probability of crack existence. Because of special condition of the response variable, which is binary, the suitable regression is logistic, and correction techniques based on least squares do not work. Developments in weighted multicollinearity diagnostics are used to assess maximum likelihood logistic regression parameter estimates. Then principal component, a biased estimation method, is used in a way that it has additional scaling parameter which can
The Importance Of Continuous Training For Pre-University Music Teachers

Continuing professional training is a goal pursued at the level of each country and ensuring solid skills is a permanent concern of today's society, in order for the individual to well adapt to the social, economic, cultural changes we face. Thus, teacher training becomes a challenge for universities that train future specialized teachers in a specific field, and the interest is focused on both initial and continuous training, on the improvement of teaching-learning and assessment strategies in the process of education. This research presents the results of a study carried out with teachers from the pre-university music environment from several counties of Romania and highlights the need for improvement in the field of all musical specializations. Didactic competence is necessary for any teacher, regardless of the subject, and it is formed throughout the professional life, by attending training courses, in order to upgrade teacher skills in the field of education sciences.
Proteomic and Metabolomic Changes in Psoriasis Preclinical and Clinical Aspects

Skin diseases such as psoriasis (Ps) and psoriatic arthritis (PsA) are immune-mediated inflammatory diseases. Overlap of autoinflammatory and autoimmune conditions hinders diagnoses and identifying personalized patient treatments due to different psoriasis subtypes and the lack of verified biomarkers. Recently, proteomics and metabolomics have been intensively investigated in a broad range of skin diseases with the main purpose of identifying proteins and small molecules involved in the pathogenesis and development of the disease. This review discusses proteomics and metabolomics strategies and their utility in research and clinical practice in psoriasis and psoriasis arthritis. We summarize the studies, from in vivo models conducted on animals through academic research to clinical trials, and highlight their contribution to the discovery of biomarkers and targets for biological drugs.
Experimental examination of lensless digital holographic microscopy imaging capabilities based on custom-designed spatial resolution targets

Lensless digital holographic microscopy (LDHM) as a rapidly developing technique of microscale objects investigation requires precise metrological verification examining the accuracy of the novel solutions. LDHM method finds numerous applications in biological specimen and technical objects studies that show diverse optical and geometrical characteristics. Hereby, we introduce custom-designed resolution targets providing an extended quantitative experimental examination of LDHM imaging capabilities in its uniquely wide field-of-view. Proposed structures, manufactured via two-photon polymerization, incorporate the axial thickness and refractive index variation to the qualitative and quantitative imaging analysis.
Application of Maximum Likelihood Methods to Population Genetic Data for the Estimation of Individual Fertilities

SUMMARY The fitness of plants or animals within a population is largely determined by the number of offspring they produce. In natural populations lacking familial structure either one or both parents are often unknown. To circumvent this problem, parents and offspring can be genotyped for a set of genetic markers. Likelihood models are proposed to estimate the fertility of either male or male and female parents in a population where fertility is defined broadly as a fraction of progeny in the population fathered or mothered by some individual. Models are developed for three cases: the mother is known and the male fertilities differ depending on the maternal parent; the mother is known and the male fertilities are the same for all maternal parents; neither parent is known and fertilities are estimated for parent pairs. It is established that a unique maximum likelihood solution exists under conditions that are commonly met. For situations in which these conditions are not met, a method is presented to determine estimates of a set of independent linear combinations of the parameters that can be uniquely estimated. Two algorithms are examined which can be used to find the parameter estimates. The variance of the estimator, likelihood ratio tests for constraints on the fertility parameters, and a goodness-of-fit test are developed. Finally, a worked example is presented.
Consistency of model selection and parameter estimation

The relationship between consistency of model selection and that of parameter estimation is investigated. It is shown that the consistency of model selection is achieved at the cost of a lower order of consistency of the resulting estimate of parameters in some domain. The situation is different when selecting autoregressive moving average models, since the information matrix becomes singular when overfitted. Some detailed analyses of the consistency are given in this case.
Millimeter-wave channel modeling in a VANETs using coding techniques

The Vehicular ad-Hoc Network (VANET) is envisioned to ensure wireless transmission with ultra-high reliability. In the presence of fading and mobility of vehicles, error-free information between Vehicle to Vehicle (V2V) and Vehicle to Infrastructure (V2I) requires extensive investigation. The current literature lacks in designing an ultra-reliable comprehensive tractable model for VANET using millimeter wave. Ultra-reliable communication is needed to support autonomous vehicular communication. This article aims to provide a comprehensive tractable model for VANET over millimeter waves using Space-Time-Block-Coding (STBC) concatenated with Reed Solomon (RS) coding. The designed model provides the fastest way of designing and analyzing VANET networks on 60 GHz. By using the derived BER expressions and Reed Solomon coded doppler expression ultra-reliable vehicular networks can be build meeting the demands of massive growing volume of traffic. The performance of the model is compared with previous BER computational techniques and existing VANET communication systems, i.e., IEEE 802.11bd and 3rd generation partnership project vehicle to everything (3GPP V2X). The findings show that our proposed approach outperforms IEEE 802.11bd and the results are comparable with V2X NR. Packet Error Rate (PER), Packet Reception Ratio (PRR) and throughput are used as performance metrics. We have also evaluated the model on higher velocities of vehicles. Further, the simulation and numerical findings show that the proposed system surpass the existing BER results comprising of various modulation and coding techniques. The simulation results are verified by the numerical results there-by, showing the accuracy of our derived expressions.
μ‐synthesis for a compact disc player

SUMMARY This paper considers the design and implementation of robust multivariable controllers for a compact disc mechanism.The design objective is to achieve good track-following and focusing performance in the presence of track disturbances, external mechanical shocks and structured norm-bounded plant uncertainty. This robust performance problem has been solved in the k-framework using the DK-iteration scheme. Limits of implementation necessitate the use of sophisticated model reduction techniques and the use of two parallel digital signal processors. ( 1998 John Wiley & Sons, Ltd.
Cellular response guards against severe COVID-19 an immunocompromised dialysis patient with undetectable humoral response to vaccination: A case report

Corona Virus Disease-19 (COVID -19) is still a menacing pandemic, especially in vulnerable patients with co- morbidities as old age, Diabetes Mellitus, immunosuppression and kidney failure on dialysis. Vaccination against Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV2) seems to offer protection in these patients by boosting both humoral and cellular immunity
Study of Strained-SiGe Channel P-MOSFET Using Silvaco TCAD: Impact of Channel Thickness

Compressively strained SiGe is an interesting channel material for sub 45 nm p-MOSFETs because of its superior hole mobility (up to 10x over bulk Si channels) and compatibility with current Si manufacturing technologies. In this work, the impact of heterostructure composition and SiGe channel thickness on the electrical characteristics of p-MOSFET are studied. Using strained Si0.8Ge0.2 p-MOSFET, the thickness was altered to a few thicknesses of 3 nm, 5 nm, 7 nm, and 9 nm respectively. The optimal thickness was then used for Ge compositions (x = 0.2). The project was realized utilizing computer-aided Silvaco TCAD tools, with ATHENA tools creating the p-MOSFET structure and ATLAS tools doing the device simulation. The strained-Si1-xGex p-MOSFET and the Si p-MOSFET were compared in terms of their performances. The ID-VG and ID-VD characteristics, as well as the threshold voltage, VTH extraction, were the focus of the device simulation. The 7 nm thickness strained-Si0.8Ge0.2 p-MOSFET exhibited lower VTH than other SiGe thicknesses and the Si p-MOSFET which is VTH = 0.074 V. The lower threshold voltage of the strained-Si0.8Ge0.2 with 7 nm thickness indicating that the strained-Si1-xGex contributed to the decreased power consumption. In addition, the extracted IDsat for the strained-Si0.8Ge0.2 p-MOSFET with 7nm thickness provided higher IDsat compared to conventional Si p-MOSFET and other SiGe thicknesses devices. As compared to Si p-MOSFETs, the output characteristics of the strained-Si1-xGex demonstrated a drain current improvement by a factor of 1.01.
Altered effective connectivity within default mode network in major depression disorder

Understanding the neural basis of Major Depressive Disorder (MDD) is important for the diagnosis and treatment of this mental disorder. The default mode network (DMN) is considered to be highly involved in the MDD. To find directed interaction between DMN regions associated with the development of MDD, the effective connectivity within the DMN of the MDD patients and matched healthy controls was estimated by using a recently developed spectral dynamic causal modeling. Sixteen patients with MDD and sixteen matched healthy control subjects were included in this study. While the control group underwent the resting state fMRI scan just once, all patients underwent resting state fMRI scans before and after two months’ treatment. The spectral dynamic causal modeling was used to estimate directed connections between four DMN nodes. Statistical analysis on connection strengths indicated that efferent connections from the medial frontal cortex (MFC) to posterior cingulate cortex (PCC) and to right parietal cortex (RPC) were significant higher in pretreatment MDD patients than those of the control group. After two-month treatment, the efferent connections from the MFC decreased significantly, while those from the left parietal cortex (LPC) to MFC, PCC and RPC showed a significant increase. These findings suggest that the MFC may play an important role for inhibitory conditioning of the DMN, which was disrupted in MDD patients. It also indicates that disrupted suppressive function of the MFC could be effectively restored after two-month treatment.
Vanishing Bile Duct Syndrome in a Patient With Recurrent Hodgkin Lymphoma

Vanishing bile duct syndrome (VBDS) is an acquired syndrome characterized by clinical and laboratory signs of cholestasis with pathologic findings of interlobular bile duct paucity in liver biopsy specimens. VBDS can result from a variety of conditions including infections, autoimmune diseases, adverse drug reactions, and neoplastic processes. Hodgkin lymphoma (HL) is a rare cause of VBDS. The mechanism by which HL leads to VBDS remains unknown. Development of VBDS in patients with HL portends an extremely poor prognosis due to the risk of progression to fulminant hepatic failure. Treatment of the underlying lymphoma has been demonstrated to offer increased probability of recovery from VBDS. The decision to treat and choice of treatment of the underlying lymphoma is often complicated by the hepatic dysfunction characteristic of VBDS. We present the case of a patient who presented with dyspnea and jaundice in the context of recurrent HL and VBDS. We additionally review the literature on HL complicated by VBDS with specific focus on treatment paradigms for management of these patients.
A Study on the Extraction of the Minutiae and Singular Point for Fingerprint Matching

The personal identification procedure through the fingerprints is divided as the classification process by the type of the fingerprints and the matching process to confirm oneself. Many existing researches for the classification and the matching of the fingerprint depend on the number of the minutiae of the fingerprints and the flow patterns by their direction information. In this paper, we focus on extracting the singular points by using the flow patterns of the direction information from identification. The extracted singular points are utilized as a standard point for the matching process by connecting with the extracted information from the singular point embodied. The orthogonal coordinates which is generated by the axises of the standard point can increase the accuracy of the fingerprints matching because of minimizing the effects on the location changes of the fingerprint images.
Multivariate Interaction Analysis of Zea mays L. Genotypes Growth Productivity in Different Environmental Conditions

Evaluating maize genotypes under different conditions is important for identifying which genotypes combine stability with high yield potential. The aim of this study was to assess stability and the effect of the genotype–environment interaction (GEI) on the grain yield traits of four maize genotypes grown in field trials; one control trial without nitrogen, and three applying different levels of nitrogen (0, 70, 140, and 210 kg ha−1, respectively). Across two growing seasons, both the phenotypic variability and GEI for yield traits over four maize genotypes (P0725, P9889, P9757 and P9074) grown in four different fertilization treatments were studied. The additive main effects and multiplicative interaction (AMMI) models were used to estimate the GEI. The results revealed that genotype and environmental effects, such as the GEI effect, significantly influenced yield, as well as revealing that maize genotypes responded differently to different conditions and fertilization measures. An analysis of the GEI using the IPCA (interaction principal components) analysis method showed the statistical significance of the first source of variation, IPCA1. As the main component, IPCA1 explained 74.6% of GEI variation in maize yield. Genotype G3, with a mean grain yield of 10.6 t ha−1, was found to be the most stable and adaptable to all environments in both seasons, while genotype G1 was found to be unstable, following its specific adaptation to the environments.
A level set moving mesh method in static form for one dimensional PDEs

In this paper, we propose an adaptive mesh approach for time dependent parial differential equations, based on a so-called moving mesh PDE(MMPDE) and level set method. It means that the velocity of mesh nodes is calculated by MMPDE and is employed as veocity in the level set equation. Then, at each time level, the mesh points are considered as the level contours of the level set function. Finally the method is merged with local time step technique.
Analysis of Tools for the Development of Conversational Agents

: Conversational agents are being increasingly adopted in various domains, such as e-commerce and customer services, and as a direct communication channel between companies and end-users. Several tools have been developed to facilitate their deﬁnition and deployment. They exploit existing cloud infrastructures and artiﬁcial intelligence (AI) techniques to efﬁciently process users’ input and extract conversational information. Major Information Technology (IT) companies, such as Google, IBM, Microsoft, and Amazon, have provided powerful tools to develop conversational agents. Still, choosing the most appropriate tool is not easy, as it may require high costs associated with automatic natural language processing (NLP) services and expertise in software engineering and AI. Therefore, this paper aims to analyze different tools to help developers and non-developers to choose the optimal tool for their speciﬁc scenario of creating a conversational agent.
The H ∞ control problem: a state space approach

DURING THE LAST DECADE, much attention has been drawn to control theory especially as an approach to robust compensator design. In the past years a huge number of scientific publications, and among these several monographies, were published on this and related subjects. In the late 1980s there was a breakthrough in ~t~® control theory, the so-called time domain or state space approach, which gave very elegant results leading to simple design techniques. There has since been a demand for a thorough textbook to describe these new methods in detail. control theory originated in the early 1980s where the control community had been aware for some time of the poor robustness properties of classical observer-based controller methods and LQG design. This led to the formulation of the robust stability problem which was intensely studied in the following years. There were several approaches which lead to solutions of this problem. These were based on frequency domain methods and transfer function descriptions as presented in Francis (1987). Later on, the significance of ~i~® control theory to a wide variety of control problems such as for example loop shaping became apparent, since the ~g'~ methods are well suited to treat a rather general class of design problems with frequency domain specifications. However, the widespread popularity that ~® has attained today is mainly due to a more recent development, namely the time domain or state space methods which were developed in the late 1980s. In this line of research it became evident that solvability of the so-called ~C® standard problem (which comprises the robust stability problem and several other problems as special cases) is equivalent to solvability of two algebraic Riccati equations and a coupling condition. Moreover, a complete characterization of the whole class of solutions to the ~ control problem was obtained in closed form. The present book intends to describe the current state of this approach to ~® control. In the introductory part of the book the deficiencies of classical control with respect to robustness issues are pointed out, and the ~® control problem is introduced. It is shown, however, by means of an example that a solution to the ~ control problem does not necessarily have good stability margins. Hence, it is emphasized that the formulation of the control problem itself does not guarantee robustness. Robustness is obtained only if it designed for! The robustness issue is further addressed as stabilization of uncertain systems and as graph topology convergence, and the mixed sensitivity problem is introduced as an approach to the nominal performance/robust stability problem. The exposition given in the book requires a number of mathematical prerequisties which are collected in a separate chapter. Among these are: properties of linear continuous or discrete time systems, theory for rational matrices and theory
Substation outdoor instrumentation detection algorithm based on improved YOLOv5

With the increasing popularity of substation inspection robots, the localization and detection of outdoor inspection pictures gradually becomes the focus and difficulty of research. For outdoor substation meters, in different weather conditions, for the current stage of detection algorithm model complexity is high, easy to the detection of the target caused by low recognition rate, is not conducive to the rapid deployment of practical applications and other problems, proposed an improved YOLOV5-based substation detection algorithm, the algorithm uses YOLOv5 + CBAM attention mechanism module to detect meter dials, for different weather conditions The algorithm uses YOLOv5+CBAM attention mechanism module to detect meter dials, which is of great significance to identify meter dials accurately and quickly under different weather conditions and further realize intelligent inspection of substations.