Miracle-dz/UniFAR-FTUs huggingface dataset:
EEG correlates of verbal and conscious processing of motor control in sport and human movement: a systematic review

ABSTRACT Studies from the sport and human movement sciences have proposed that electroencephalographic (EEG) measures of left-temporal alpha power and left-temporal-frontal connectivity reflect verbal, conscious processing during the learning and control of motor skills. The aim of this systematic review was to synthesize these studies, bring awareness to key methodological considerations, and suggest future research agendas and practices to help generate new knowledge on this topic. An extensive search of electronic databases (PubMed, PsychInfo, GoogleScholar, and SportDiscus) was conducted to identify peer-reviewed literature relating to EEG, conscious movement control and verbal processing. Thirty-eight studies met the inclusion criteria and were retained for quality assessment and synthesis of results. Results suggested that only 36% of studies measuring left-temporal alpha power and only 47% of studies measuring left-temporal-frontal connectivity supported their putative association with verbally-guided, conscious motor processing. There were great methodological inconsistencies across studies and overall studies scored moderate for quality criteria. In conclusion, we question the use of these EEG indices as markers of verbally-guided conscious control until more substantive evidence of their efficacy is provided and stronger methodologies are adopted. We outline six recommendations that can be used to guide such work in the future.
Training Samples Enriching Approach for Classification Improvement of VHR Remote Sensing Image

Training samples are usually required to train a classifier for supervised classification of very high spatial resolution (VHR) remote sensing images. However, labeling samples is often a labor-intensive and time-consuming task. To solve this problem, this study integrates histogram distribution analysis, double-window flexible pace search (DFPS), and box–whisker plot (BP) techniques into an iterative algorithm to enrich training samples. The major steps of the proposed algorithm are given as follows. First, to acquire the feature distribution of a class, a histogram of each class (HOC) based on the raw classification map is generated. Second, to cover the spectral heterogeneity of an intraclass, some pixel points in each bin of HOC are selected as the coarse training sample set (CTS). Third, to further purify the CTS, DFPS, and BP techniques are adopted to exclude outlier samples and select the representative samples to signify the corresponding class. Finally, the refined training samples are used to retrain the classifier, and the preceding steps are constructed as an iterative algorithm. Experiments were performed on three real VHR remote sensing images to demonstrate the superiorities of the proposed approach in improving classification performance with respect to the maps obtained directly by the initial training set. In addition, compared with cognate state-of-the-art methods, the proposed approach achieved an approximately 2%–13% improvement in classification accuracy. Code available here:https://github.com/ImgSciGroup/IEEE-GRSL-GSEA-Code.
Knowledge, attitudes, and perception of 398 cancer patients toward participation in clinical trials: A single-center study from New Delhi, India

Background and Objective: Clinical trials are considered to be the gold standard research methodology for evaluating the efficacy and safety of healthcare interventions. Materials and Methods: A cross-sectional study was conducted using standardized self-administered questionnaires prepared by the research team and statistician. The questionnaires were offered to cancer patients presented at a tertiary care center. Results: We surveyed 398 cancer patients, 193 (48.5%) males and 205 (51.5%) females with a mean (±standard deviation) 55.39 (±13.59) of age in years. Out of total, only 59 (14.82%) had the prior knowledge of the clinical trial. Forty-three (10.80%) participants were willing to participate in clinical trials. Conclusion: Cancer patients had preconceived notions and myths that linger in our society that clinical trial participation will harm them. The researchers/oncologists need to explore the rationale, objectives, and benefits of taking part in clinical trials and make it easy to understand by cancer patients.
THE STRATEGIES USED BY ENGLISH TEACHER TO TEACH VOCABULARY AT GENTA ENGLISH COURSE PARE-KEDIRI

This study was aimed to find out the used of strategies used by English teacher to teach vocabulary. for those who are learning English, it is essential to learn about vocabulary mastery in order they can use it to communicate and to express their ideas, opinions, thoughts by using words, sentences, paragraphs through written form without having face to face with other people directly. The design of this research in qualitative descriptive. This research was conducted in Genta English course. The students were 10 students. It consist of 9 female and 1 male. To know the result of the student activity, the researcher used observation checklist, field note and interview. Teacher strategies in teaching vocabulary is the ways or steps that help learners to learning vocabulary by acting one of the strategies as steps formula, so that strategy become a facility which increasing learners understanding in learning vocabulary. It means use the strategies is good in teaching vocabulary. Keyword: English teacher’s strategies, teaching vocabulary INTRODUCTION The student not only can study English at school, but also they learn English in non-formal education. The purpose of non-formal education is to complete, to change, and to add the student’s knowledge that they ever or never get from formal education. Moreover, some people who want to get job and best education in the future actually take non-formal education to increase their English ability. Non-formal education is any organized and systematic activity, outside the school system, conducted independently or the important part of the larger activity that is intentionally made to serve the specific student to get the goal of their study. In this era non-formal education that can help the students to get the different teaching and learning process from formal education that they get at the school. There are four skills that should be mastered by students in learning English. They are speaking, listening, reading, and writing. Besides the four English skills, to support the mastery of the four language skills the students should have well understanding of English component such as vocabulary, pronunciation, and grammar. Vocabulary as one of English component is very important to learn. Before the students master the four skills they have to know 13 some vocabularies to support them in learning English. Richard (2005:5) says that vocabulary is core component of listening, speaking, reading and writing. Vocabulary is very important to be learnt by the students who want to master a language.
Enhancing the Biocompatibility and Biodegradability of Linear Poly(ethylene imine) through Controlled Oxidation

(Bio)degradable poly(ethylene imine-co-glycine)s (P(EI-co-Gly)) were synthesized through efficient and controlled oxidation of linear poly(ethylene imine) (LPEI) using hydrogen peroxide in a methanol/water mixture. Temperature, peroxide concentration, and reaction time were varied to adjust the degree of oxidation (DO). At low temperatures, the oxidation process was found to be well-controlled with almost 85% of ethylene imine units converted to the corresponding amide. Importantly, oxidation of more than 10% of the LPEI rendered the polymers water-soluble. The oxidation reaction and molecular structure of P(EI-co-Gly)s were studied in detail by various nuclear magnetic resonance (NMR) methods, infrared (IR) spectroscopy, and size exclusion chromatography (SEC). The introduction of backbone amide groups to the P(EI-co-Gly)s facilitated its (bio)degradation under acidic conditions or by proteases. Moreover, the P(EI-co-Gly)s exhibited negligible cytotoxicity, particularly relative to LPEI. The interaction .
Rotor Temperature Virtual Sensing for Induction Machines Using a Lumped-Parameter Thermal Network and Dual Kalman Filtering

Accurate knowledge of the induction machine rotor temperature is important for both condition monitoring and motor performance. Lumped-parameter thermal networks allow to flexibly model the temperature distribution with low computational effort. However, their accuracy highly depends on the accuracy of their thermal parameters. Moreover, these parameters are determined offline and held constant during operation. In this article, a rotor temperature virtual sensing strategy is proposed, combining a lumped-parameter thermal network with stator windings temperature measurements. The latter measurement data can be easily collected and together with the thermal network serve as input to a dual Kalman filter to estimate both the rotor temperature evolutions and the thermal model parameters. The advantage of the presented approach is that the thermal model does not need exact identification for the considered motor. One can start from a thermal model identified from intrusive rotor measurement data on a comparable motor that is subsequently transferred to the motor to be monitored. This results in a fast and convenient way to estimate the rotor temperature in real-time. Experimental results on a 4-pole 5.5 kW induction machine demonstrate the validity of the presented strategy to accurately monitor the rotor temperature within an error range of approximately $\pm 6^{\;\circ }{\rm C}$.
Modern radiotherapy in the treatment of localized prostate cancer

* Accepted papers are articles in press that have gone through due peer review process and have been accepted for publication by the Editorial Board of the Serbian Archives of Medicine. They have not yet been copy-edited and/or formatted in the publication house style, and the text may be changed before the final publication. Although accepted papers do not yet have all the accompanying bibliographic details available, they can already be cited using the year of online publication and the DOI, as follows: the author’s last name and initial of the first name, article title, journal title, online first publication month and year, and the DOI; e.g.: Petrović P, Jovanović J. The title of the article. Srp Arh Celok Lek. Online First, February 2017. When the final article is assigned to volumes/issues of the journal, the Article in Press version will be removed and the final version will appear in the associated published volumes/issues of the journal. The date the article was made available online first will be carried over.
Where do Clinical Language Models Break Down? A Critical Behavioural Exploration of the ClinicalBERT Deep Transformer Model

The introduction of Bidirectional Encoder Representations from Transformers (BERT) was a major breakthrough for transfer learning in natural language processing, enabling state-of-the-art performance across a large variety of complex language understanding tasks. In the realm of clinical language modeling, the advent of BERT led to the creation of ClinicalBERT, a state-of-the-art deep transformer model pretrained on a wealth of patient clinical notes to facilitate for downstream predictive tasks in the clinical domain. While ClinicalBERT has been widely leveraged by the research community as the foundation for building clinical domain-specific predictive models given its overall improved performance in the Medical Natural Language inference (MedNLI) challenge compared to the seminal BERT model, the fine-grained behaviour and intricacies of this popular clinical language model has not been well-studied. Without this deeper understanding, it is very challenging to understand where ClinicalBERT does well given its additional exposure to clinical knowledge, where it doesn't, and where it can be improved in a meaningful manner. Motivated to garner a deeper understanding, this study presents a critical behaviour exploration of the ClinicalBERT deep transformer model using MedNLI challenge dataset to better understanding the following intricacies: 1) decision-making similarities between ClinicalBERT and BERT (leverage a new metric we introduce called Model Alignment), 2) where ClinicalBERT holds advantages over BERT given its clinical knowledge exposure, and 3) where ClinicalBERT struggles when compared to BERT. The insights gained about the behaviour of ClinicalBERT will help guide towards new directions for designing and training clinical language models in a way that not only addresses the remaining gaps and facilitates for further improvements in clinical language understanding performance, but also highlights the limitation and boundaries of use for such models.
In vitro culture of sempre-vivas species (Comanthera): a review

Abstract The term “sempre-viva” denotes plants whose structures retain their natural form and color after being cut and dried. For these reasons, they are commercially valuable for ornamental purposes. However, due to extractive overexploitation of their inflorescences, some of these species are considered endangered. The genus Comanthera includes the sempre-vivas species with greatest economic importance in Brazil. Previous studies have shown that tissue culture is a workable strategy for in vitro propagation and conservation of species of this genus. However, these studies are still incipient. Therefore, the objective of this review is to summarize the findings on the in vitro cultivation of species of the Comanthera genus, to serve as the basis for future research. The text is structured in two main topics: micropropagation and in vitro conservation.
Distribution of variations in anatomy of the circle of Willis: results of a cadaveric study of the Malawian population and review of literature

Introduction the circle of Willis is an anatomical structure of clinical importance particularly in the evaluation of neurovascular diseases. Individuals show considerable variations in the anatomical configuration of the circle of Willis. A cross-sectional study was conducted to determine the distribution of morphological variations of the circle of Willis in Malawians and compare with other ethnic groups. Methods brains were collected from twenty-four recently deceased black Malawians during autopsy at Queen Elizabeth Central Hospital, a referral teaching hospital in Blantyre, Malawi and fixed in 10% buffered formalin. Digital images of the interpeduncular region (exposing the circle of Willis) were taken with an 18.4 megapixels camera from the base of the brain. Whole-circle and segmental parameters of the circle of Willis were assessed using the Osiris computer programme and classified based on a 22-type classification scheme. Results the following morphological variations were observed: hypoplasia, aplasia, asymmetry and accessory vessels. Typical circle of Willis was seen in 26% of the cases. Only six of the original twenty-two types were observed. Consistent with most previous studies, types 1, 3, 4, 6, 8 and 9 were common while types 10-22 were rare. Three variants not previously described in the original scheme (unilateral PcoA aplasia, AcoA duplication, and PcoA aplasia with contralateral PcoA hypoplasia) were observed in this study. Conclusion anatomical variations of the circle of Willis in Malawians seem to be distributed in similar frequencies and patterns as in other more-diverse populations. Circle of Willis variants with potential predilection for atherogenesis and aneurysm formation exist in the Malawian population. These should be considered in clinical practice.
On the Necessity of Using Element No.155 in the Chemical Physical Calculations: Again on the Upper Limit in the Periodic Table of Elements

It is shown how the properties of di erent elements of the Periodic System of Elements can be obtained using the properties of the theoretically predicted heaviest element No.155 (it draws the upper principal limit of the Table, behind which stable elements cannot exist). It is suggested how the properties of element No.155 can be used in the synthesis of superheavy elements. An analysis of nuclear reactions is also produced on the same basis.
Scalable Wireless Wearing Monitoring System for Harsh Industrial Environment

A scalable system for wireless wear monitoring in a distributed harsh industrial environment, in which installation of the electronic equipment near the distributed wearing measuring locations is unfeasible, has been successfully designed, developed and deployed. The system is composed of a novel LC-type passive wireless wear sensor system, a sensor readout coil, an electronic equipment, a readout unit for a scalable multisensor system and a control and monitoring system. The capacitor structure, employed as a sensing device in the LC sensor manufactured on low cost PCB, provides a linear response to the wear level. This allowed us to define a measuring and calibration method to suppress the cable effects from each distributed readout coil to the electronic equipment readout unit. It was possible to achieve a multiple simultaneous measurements in different sensors distributed along an industrial process without significant cabling influence. Concerning the sensor data analysis, a double Holt-Winters method with trend was used to reduce noise effects and an “experience based learning” tool was implemented in order to solve any misbehavior or time lag. Laboratory measurements and on-site operation results in an article mill indicate 1 mm precision and about 0, 5 MHz/mm sensitivity of the LC-type passive wireless wear sensor system.
Difficulties and Strategies in Learning English: An Analysis of Students From English and Non-English Education Department in Indonesia

Two different contextual backgrounds may yield other influences. This research aimed to examine the difficulties of the English Language Education Department (ELED) students and non-English Language Education Department (non-ELED) in learning English language and their strategies to cope with their difficulties. This research utilized a qualitative approach and employed interviews as a means to gather data. In this research, the researcher involved 6 participants 3 from ELED and non-ELED, respectively. Both ELED and Non-ELED Students shared common problems in learning English related to the issues of vocabulary shortage, grammar difficulties, pronunciation problems, low speaking and listening skills. The noticeable difference was seen on the difficulty in developing ideas that is only faced by ELED students while difficult in all aspects of writing skills faced by non-ELED students. The strategies implemented by both ELED and non-ELED students included jotting down the unknown words, learning English using Google, learning English through social media, reading journals, using subtitles, watching movies that use English as a medium of communication, listening to English movies, singing English songs, joining English courses, making imitation, and practising their English writing and speaking skills. The strategies to deal with the difficulties that were implemented by ELED students were reading online comic, memorizing vocabulary, reading English article or essays, listening to podcast, telling a story using English language, increasing confidence, and memorizing form of verbs. Meanwhile, the strategies that just implemented by non-ELED students are joining English activity programs, doing English exercises, getting used to the English language, and using the correct English language.
Class Size and Learning: Has India Spent Too Much on Reducing Class Size?

This paper examines the efficacy of class-size reductions as a strategy to improve pupils’ learning outcomes in India. It uses a credible identification strategy to address the endogeneity of class-size, by relating the difference in a student’s achievement score across subjects to the difference in his/her class size across subjects. Pupil fixed effects estimation shows a relationship between class size and student achievement which is roughly flat or non-decreasing for a large range of class sizes from 27 to 51, with a negative effect on learning outcomes occurring only after class size increases beyond 51 pupils. The class-size effect varies by gender and by subject-stream. The fact that up to a class-size of roughly 40 in science subjects and roughly 50 in non-science subjects, there is no reduction in pupil learning as class size increases, implies that there is no learning gain from reducing class size below 40 in science and below 50 in non-science. This has important policy implications for pupil teacher ratios (PTRs) and thus for teacher appointments in India, based on considerations of cost-effectiveness. When generalised, our findings suggest that India experienced a value-subtraction from spending on reducing class-sizes, and that the US$3.6 billion it spent in 2017-18 on the salaries of 0.4 million new teachers appointed between 2010 and 2017 was wasteful spending rather than an investment in improving learning. We show that India could save US$ 19.4 billion (Rupees 1,45,000 crore in Indian currency) per annum by increasing PTR from its current 22.8 to 40, without any reduction in pupil learning.
The Fault Diagnosis of Diesel Fuel Supply System Based on BP Neural Network Optimized by Genetic Algorithm

As an important power source of diesel engine, the fuel supply system has the characteristics of high failure rate and being difficult to be detected, which is critical to detect and diagnose the fault for the reliable and stable operation of diesel engine. In the paper, principal component analysis (PCA) was used to process the initial data, back-propagation (BP) neural network was used to diagnose fault of diesel engine, BP diagnosis efficacy was analyzed, then the BP neural network fault diagnosis system was optimized by being introduced in the genetic algorithm , and the comparison results of training error and diagnostic analysis showed that: the fault diagnosis of BP neural network optimized by genetic algorithm is more accurate than that of traditional BP, which can effectively improve the fault diagnosis accuracy and reduce the training time.
Experimental measurement of base tilting effects in magnetically actuated FeC-PDMS micropillar structures

Polymer micropillar structures have been used as microsensors and microactuators in scientific studies. In these studies, the deformation of the micropillar is used to estimate the forces applied on the micropillars from the external environment, or the forces generated by the micropillars. The accuracy of such force calculations depends on the accurate estimation of the structure’s spring constant which requires a correct understanding of micropillar deformation under loading. For a micropillar sitting on top of a flexible polymer base, base deformation, or tilting, is a major contributor to the total pillar deformation and the total spring stiffness of the structure. In this work, we visualize and quantify the base tilting effects for magnetic FeC-PDMS micropillar structures. We compare and verify our experimental observations against those predicted by an analytical model developed accounting for the base tilting effects. In our experiments, for pillars with smaller aspect ratios of L/D ≈ 3, pillar bending and base tilting account for 87% and 13% of the total angular deformation, whereas for pillars with larger aspect ratios of L/D ≈ 7, pillar bending and base tilting account for 94% and 6% of the total angular deformation, respectively. As predicted by analytical models, the contribution of the base tilting effect, largely ignored in many studies, becomes more significant for micropillars with smaller aspect ratios.