Miracle-dz/UniFAR-FTUs huggingface dataset:
Repellent potentials of Securidaca longepedunculata Fresen (Polygalaceae) crude extract and essential oil against mosquitoes

This study aimed to evaluate the bioactivities of the plant, Securidaca longepedunculata Fresen crude extract and essential oil against two different species of mosquitoes; Anopheles gambiae s.l. and Culex quinquefasciatus. Ten (4 to 7 days old) non-blood fed female mosquitoes, from each of the species were exposed to test planttreated chamber linked to an inner untreated chamber for 10 minutes. Parameter assessed was behavioural response of test insects to treatment (test plants). There was a significant difference (P<0.05) between the behavioural response of both test insects to essential oil. Both crude extract and essential oil at 0.3 and 0.5 mg/ml concentration recorded higher percentage repellency against Anopheles gambiae s.l. than the standard treatment, DEET (N, N-diethyl-m-toluamide), while only 0.5mg/ml concentration of crude extract, recorded percentage repellency higher than what was recorded in DEET against Culex quinquefasciatus. These findings show the repellent potentials inherent in the test plant, thus qualifying it as a suitable alternative to synthetic chemical repellents. However further investigation is suggested to examine the mode of action of extracted substances which could facilitate the formulation of a better herbal repellent.
Lymphatics and its Role in Inflammation, Lymphoedema, Cancer and Immunity

Advances in our understanding of the structure and function of the lymphatic system have made it possible to identify its role in a variety of disease processes. Because it is involved not only in fluid homeostasis but also in immune cell trafficking, the lymphatic system can mediate and ultimately alter immune responses. Our rapidly increasing knowledge of the molecular control of the lymphatic system will inevitably lead to new and effective therapies for patients with lymphatic dysfunction. In this review, we discuss the anatomy and physiological function of lymphatic vessel function and explore how the lymphatic system contributes too many disease processes, including cancer and lymphedema. This review highlights the most recent developments in lymphatic biology and how the lymphatic system contributes to the pathogenesis of various diseases involving immune and inflammatory responses and its role in disseminating tumor cells.
Towards An Efficient Evaluation of the Usability of Android Apps by Cognitive Models

: Mobile apps offer new specific design challenges that may change some aspects of the learning process of the user. When less information can be presented at once due to smaller screen sizes, more context information has to be kept active in memory. Moreover, apps are often used as secondary task and thus have to be more robust to distraction, interruption and lower availability of attentional and other memory-related resources. How can we evaluate the cognitive suitability of mobile applications? Our goal is to develop a methodology that helps designers to test alternative design variants of their application in order to optimize it. Specific cognitive modeling approaches can address these challenges and can explain human behavior relevant to usability criteria. Furthermore, modeling approaches in this domain can help us to understand the cognitive mechanisms driving our behavior. This paper focuses on three central questions: (1) How can software developers and cognitive modeler contribute to each other’s work? (2) How do cognitive models have to look like to be well suited to mobile apps? (3) How can implemented apps be connected to cognitive models?
Design Optimization of a Very High Power Density Motor with a Reluctance Rotor and a Modular Stator Having PMs and Toroidal Windings

This paper proposes a new high power density permanent magnet (PM) motor design for traction applications to achieve the 50kW/L target set by the US Department of Energy by increasing the torque capability and operating speed compared to conventional PM machine topologies. A large-scale multi-objective design optimization based on 2D finite element analysis (FEA) and differential evolution algorithm was conducted to achieve the best trade-off among high efficiency, high power density and high power factor. The torque-speed envelopes are also checked for the Pareto front designs to make sure they have a constant power speed ratio of at least 3:1. An open frame lab prototype (OFLP) motor has been fabricated and tested to validate the principle of operation and design optimization approach, and to identify the potential challenges in manufacturing and testing. Ongoing work on further pushing the electromagnetic performance to the limit and improving the manufacturing and cooling techniques are also discussed.
A novel RYR1 sequence variant in central core disease: A case report

DOI: 10.4328/ACAM.20875 Received: 2021-09-28 Accepted: 2021-10-27 Published Online: 2021-11-02 Corresponding Author: Askeri Türken, Gazi Yaşargil Training and Research Hospital, Division of Physical Therapy and Rehabilitation, Diyarbakır, Turkey. E-mail: askeriturken@hotmail.com P: +90 532 776 12 40 / +90 412 258 00 60 F: +90 412 258 00 50 Corresponding Author ORCID ID: https://orcid.org/0000-0003-0638-8918 Abstract Muscular dystrophies are inherited diseases that cause progressive muscular weakness. Dystrophies are diagnosed with a biopsy, which histologically shows fiber size, areas of muscle necrosis, amounts of fat and connective tissue, however, genetic screening is definitive for the diagnosis of disease. Congenital myopathies are neuromuscular disorders that affect skeletal muscles used for movement. Muscles are relaxed by repeated contractions. In this case, a patient with central core disease is presented with novel alteration in the ryanodine receptor 1(RYR1) gene after a 24-year delayed diagnosis. The mutation seen in our case occurred in the central region and caused central core disease. In conclusion, in the diseases, differential diagnosis should be considered a transition to a correct diagnosis, as they can imitate each other in cases such as complaints, laboratory and imaging.
Individual Producer Responsibility in the WEEE Directive - From Theory to Practice?

In the current discourse over what constitutes successful Extended Producer Responsibility (EPR) policy implementation, there is an on-going debate over the ability of programme design to include an appropriate incentive mechanism to stimulate producers to improve the design of their products for reduced life cycle impacts, and especially the impacts and costs from the end-of-life management. At the centre of the debate is the Directive on Waste Electrical and Electronic Equipment (WEEE) which has the explicit goal to encourage the design and production of electrical and electronic products which facilitate dismantling, recovery and in particular the reuse and recycling of WEEE. Individual Producer Responsibility (IPR) is the main mechanism to achieve this goal, whereby each producer is responsible for financing the waste from his own products. This thesis presents an account of the transposition outcome of the WEEE Directive into EU Member State legal text and the practical implementation that has emerged as a result. It explores the factors that have led to the current impasse regarding IPR implementation in Europe, and together with the investigation of more successful IPR implementation and industry practice, suggests a characterisation of possible ways of implementing IPR given today’s reality. (Less)
A Comparative Study of Arousal and Valence Dimensional Variations for Emotion Recognition Using Peripheral Physiological Signals Acquired from Wearable Sensors*

Wearable sensors have made an impact on healthcare and medicine by enabling out-of-clinic health monitoring and prediction of pathological events. Further advancements made in the analysis of multimodal signals have been in emotion recognition which utilizes peripheral physiological signals captured by sensors in wearable devices. There is no universally accepted emotion model, though multidimensional methods are often used, the most popular of which is the two-dimensional Russell’s model based on arousal and valence. Arousal and valence values are discrete, usually being either binary with low and high labels along each dimension creating four quadrants or 3-valued with low, neutral, and high labels. In day-to-day life, the neutral emotion class is the most dominant leaving emotion datasets with the inherent problem of class imbalance. In this study, we show how the choice of values in the two–dimensional model affects the emotion recognition using multiple machine learning algorithms. Binary classification resulted in an accuracy of 87.2% for arousal and up to 89.5% for valence. Maximal 3-class classification accuracy was 80.9% for arousal and 81.1% for valence. For the joined classification of arousal and valence, the four-quadrant model reached 87.8%, while the nine-class model had an accuracy of 75.8%. This study can be used as a basis for further research into feature extraction for better overall classification performance.
Leveraging Unsupervised Machine Learning to Discover Patterns in Linguistic Health Summaries for Eldercare

The Center for Eldercare and Rehabilitation Technology, at University of Missouri, has researched the use of smart, unobtrusive sensors for older adult residents’ health monitoring and alerting in aging-in-place communities for many years. Sensors placed in the apartments of older adult residents generate a deluge of daily data that is automatically aggregated, analyzed, and summarized to aid in health awareness, clinical care, and research for healthy aging. When anomalies or concerning trends are detected within the data, the sensor information is converted into linguistic health messages using fuzzy computational techniques, so as to make it understandable to the clinicians. Sensor data are analyzed at the individual level, therefore, through this study we aim to discover various combinations of patterns of anomalies happening together and recurrently in the older adult’s population using these text summaries. Leveraging various computational text data processing techniques, we are able to extract relevant analytical features from the health messages. These features are transformed into a transactional encoding, then processed with frequent pattern mining techniques for association rule discovery. At individual level analysis, resident ID 3027 was considered as an exemplar to describe the analysis. Seven combinations of anomalies/rules/associations were discovered in this resident, out of which rule group three showed an increased recurrence during the COVID lockdown of facility. At the population level, a total of 38 associations were discovered that highlight the health patterns, and we continue to explore the health conditions associated with them. Ultimately, our goal is to correlate the combinations of anomalies with certain health conditions, which can then be leveraged for predictive analytics and preventative care. This will improve the current clinical care systems for older adult residents in smart sensor, aging-in-place communities.
A METHOD OF DESIGN OF NEURAL NETWORKS BUILT ON FPGA

Artificial intelligence technologies are based on the use of neural networks. At the same time, the actual issue is the implementation of neural networks on various software and hardware platforms. In this paper, we consider an effective method to design fully connected neural networks or convolutional neural networks and to implement these networks on FPGAs using the Xilinx System Generator for DSP and Matlab/Simulink package. The developed method is design of neural networks using the Xilinx System Generator for DSP library imported into the Matlab/Simulink environment and using the built-in MatlabC language to generate a given ANN neural networks structure automatically. The artificial neural networks designed according to this method are easily reconfigurable. Also such neural networks allow solving the following tasks: image recognition, optimal filtering. This method based on neural networks gives an opportunity to improve recognition procedures of technical conditions of monitor and diagnostics of complex objects. Also such methods could be a practical alternative of strict mathematical methods to solve problems of identification of objects of various types. Based on the results of the work, the following conclusions can be done. Using developed method it is impossible to implement even the input layer consisting of 6400 neurons (image 80x80). The structure of the neuron could be parallelized the multiplication and accumulation operations to speed up the work. At the same time the requirements to FPGA resources increase.
Proposal of higher-order tensor independent component analysis for signal separation in multiple-input multiple-output respiration/heartbeat remote sensing*

This paper proposes higher-order tensor independent component analysis (HOT-ICA). HOT-ICA is a tensor ICA that makes effective use of the relationships among the axes of a separating tensor. We deal with multiple-target signal separation in a multiple-input multiple-output (MIMO) radar system to detect respiration and heartbeat. Numerical physical experiments demonstrate the significance of the HOT-ICA which keeps the tensor structure unchanged to fully utilizes the high-dimensionality of the separation tensor.
Cognitive science: an interdisciplinary approach to mind and cognition1

e mind is usually considered to be machinery which computes inner representations and employs them to act. ese representations could refer to both physically existing objects, or events occurring in the proximal surrounding, and hypothetical entities (Fodor, 1975). For instance, when perceiving an object characterized by meowing, having whiskers, tail, four paws, and fur, we immediately categorize it as “cat,” and reach out to pet it (unless we do not like cats). What is more, categorizing the object as a cat allows us to use our prior knowledge and say that it is a mammal and a vertebrate, that it occupies terrestrial niches, and could be our companion. us, one could de"ne cognition as mental activity
Child and adolescent schizophrenia — biological background for diagnosis and treatment

Diagnosing and treatment of children’s schizophrenia (COS) and early onset schizophrenia (EOS) is often challenging due to lack of diagnostical and therapeutical criteria and considerable comorbidity. The growing number of neuroimaging data indicate a presence of many structural brain abnormalities that may confirm neurodevelopmental hypothesis of schizophrenia. We still couldn’t find any of biological markers which would allow to determine vulnerability for schizophrenia in child and adolescancy period. The markers that are considered, belong to the wide group of neuropsychological, neurophisiological and other functional brain disturbances. The treatment of COS and EOS is based on the same rules as these used in the adult schizophrenia treatment. Atypical neuroleptics are considered as the most safe treatment for children and adolescent suffering from schizophrenia. Psychiatry 2010; 7, 4: 161–167 key words: early and very early onset of schizophrenia, neuroimaging studies, pharmacotherapy Wstęp Schizofrenia jest chorobą, której typowe objawy ujawniają się zazwyczaj na początku trzeciej dekady życia. Jednak w ostatnich latach coraz większą uwagę zwraca się na specyfikę obrazu psychopatologicznego schizofrenii w okresie dzieciństwa i adolescencji. Co więcej, uważa się, że badania neurobiologiczne oraz farmakogenetyczne w tej grupie wiekowej mogą pozwolić na lepsze zrozumienie czynników etiopatogenetycznych schizofrenii ze względu na możliwość wyodrębnienia bardziej homogennej grupy pacjentów (bez utrwalonych, przewlekłych objawów). W okresie dziecięcym i adolescencji wyodrębnia się: schizofrenię o początku w dzieciństwie (COS, childhood onset of schizophrenia lub VEOS, very early onset of schizophrenia), występujące u osób poniżej 13. roku życia, oraz schizofrenię o wczesnym początku (EOS, early onset of schizophrenia), która dotyczy osób pomiędzy 13. a 18. rokiem życia. Jak dotąd zarówno w europejskiej klasyfikacji The International Statistical Classification of Diseases and Related Health Problems, 10th Revision (ICD-10), jak i amerykańskiej Diagnostic and Statistical Manual of Mental Disorders, 4th Edition (DSM-IV) nie ma oddzielnych kryteriów diagnostycznych dla schizofrenii o początku w dzieciństwie. Jednak, mimo że objawy klinicznie są podobne do tych występujących u dorosłych osób, u dzieci i młodzieży podkreśla się ich bardziej niespecyficzny i zmienny charakter [1]. Najbardziej typowe różnice w klinicznych objawach pomiędzy schizofrenią występującą u dorosłych osób (AOS, adult onset of schiozphrenia) a EOS przedstawiono w tabeli 1. Należy również podkreślić, że im wcześniejszy wiek zachorowania, tym bardziej niespecyficzne objawy mogą towarzyszyć manifestacji klinicznej chobrought to you by CORE View metadata, citation and similar papers at core.ac. uk provided by Via Medica Journals
Entropies , convexity , and functional inequalities

Our aim is to provide a short and self contained synthesis which generalise and unify various related and unrelated works involving what we call Φ-Sobolev functional inequalities. Such inequalities related to Φ-entropies can be seen in particular as an inclusive interpolation between Poincaré and Gross logarithmic Sobolev inequalities. In addition to the known material, extensions are provided and improvements are given for some aspects. Stability by tensor products, convolution, and bounded perturbations are addressed. We show that under simple convexity assumptions on Φ, such inequalities hold in a lot of situations, including hyper-contractive diffusions, uniformly strictly log-concave measures, Wiener measure (paths space of Brownian Motion on Riemannian Manifolds) and generic Poisson space (includes paths space of some pure jumps Lévy processes and related infinitely divisible laws). Proofs are simple and relies essentially on convexity. We end up by a short parallel inspired by the analogy with Boltzmann-Shannon entropy appearing in Kinetic Gases and Information Theories.
An overview of smart technologies for clothing design and engineering

Purpose – The paper aims to provide an overview of the area of smart textiles.Design/methodology/approach – The paper describes and discusses new and developing materials and technologies used in the textile industries.Findings – Significant progress has been achieved in the area of technical textiles. Fibres, yarns, fabrics and other structures with added‐value functionality have been successfully developed for technical and/or high performance end‐uses. The basic building blocks are already in place in the field of smart textiles and clothing.Practical implications – As progress in science and engineering research advances, and as the gap between designers and scientists narrows, the area of smart clothing is likely to keep on expanding for the foreseeable future. Growth is predicted to occur in two distinct directions: performance‐driven smart clothing and fashion‐driven smart clothing. There are challenges that have to be addressed.Originality/value – The paper provides information of value to those i.
Prediction of Machine Tool Thermal Error Compensation Based on SVMR and ARM11

In order to improve the process precision of the machine tool, further development of SVMR was achieved by QT Creator. Support vector machine was applied to the ARM11 development board, SVMR model was online trained and real-time predicted the values of machine tool thermal error. Compared with the widely used BP neural network, this method has the characteristics of high compensation precision and strong generalization ability. Experiment research has proved that the stronger effectiveness and higher accuracy using this method.
The comparison of word definitional ability between monolingual and bilingual (Greek-Turkish) speakers of Thrace

The purpose of this study was to investigate (a) the preferred definition type produced by Greek monolingual and Turkish-Greek bilingual speakers of Thrace, (b) their definitional ability (c) the effect of semantic characteristics, grammatical categories and morphological structure of words and finally (d) the effect of variables such as, age (school-age children, university students and adults), gender, adult educational level and career orientation (humanities vs medical science) on definition productions. The sample consisted of 368 individuals, 184 monolingual speakers of Greek and 184 bilingual speakers (L1 Turkish, L2 Greek) who were asked to define 16 words orally. The results indicated that bilinguals produced more formal definitions than bilinguals. More specifically, concrete nouns were better defined than abstract while in simple words were used more formal definitions, both in monolingual and bilingual groups. Monolingual speakers used more formal definitions in verbs while bilinguals used more formal definitions in adjectives. Concerning the age, both in monolingual and bilingual group, females outperformed males in respect to the content of definitions. Concerning the career orientation, students in Medical science produced more formal definitions than other groups. This was also observed in bilingual group. The results of this study expand the extant literature on definitional skill development.
A novel self-aligned surface-silicide passivation technology for reliability enhancement in copper interconnects

By exposing the giant-grain Cu interconnects in SiH/sub 4/ ambient at 200/spl deg/C and annealing it in Ar ambient at 450/spl deg/C, we have succeeded in performing self-aligned surface-silicide passivation on the Cu interconnects. The surface-silicide passivated giant-grain Cu interconnect exhibits one order of magnitude longer lifetime against electromigration than the non-passivated giant-grain Cu interconnect.
An improved new transformer type arc suppression reactor

In this paper, to accurately compensate the arc suppression coil, the structure of the transformer is improved. Here, a fixed inductive element is connected in series with the short-circuit winding, which combines with the leakage inductance of the original transformer to form a new short circuit impedance. The improved transformer reduces the manufacturing cost and difficulty of the controllable inductor, reduces the requirements for the winding of the reactor, and makes the manufacturing easier.
Modeling of vapor bubble growth at subatmospheric pressures

In this paper, the results of numerical calculations of a vapor bubble growth in superheated water at different pressures are presented. Modeling is based on a previously developed by the authors semi-analytical solution. The results are verified by experimental data obtained at atmospheric and subatmospheric pressures. The presented simulation results and experimental data are in good agreement. The advantage of the solution over the earlier ones (based on the thermal growth model) is shown.
Research on the Intention to Adopt a Railway as an International Transportation Mode in Korea: A Focus on Transcontinental Railways (KTAR)

The purpose of this research is to identify the factors affecting the intention to adopt a transcontinental railway in Korea. We develop an empirically testable model that demonstrates the effects of factors including cost, service, and efficiency of railway transportation, on modal shift intention to railway, attitude of a Railway, and intention to adopt a Transcontinental Railway (KTAR) as a railway transportation mode in the end. A survey method enables us to analyze the model with a structural equation modeling. The empirical analysis reveals that two most influential factors-the modal shift to railway transportation and the attitude of a Railway-play roles in determining intention to adopt the Transcontinental Railway (KTAR). Of the factors of transportation mode, transportation cost has a greater impact than transportation service and transportation efficiency on the intention to adopt a Transcontinental Railway (KTAR).