Miracle-dz/UniFAR-FTUs huggingface dataset:
A Children's Music Therapy to Enhance the Self-Esteem of Children with Attention Deficit Hyperactivity Disorder (ADHD) in Elementary School

Abstract Elementary school students with Attention Deficit Hyperactivity Disorder (ADHD) possessed low self-eesteem that impacted on their academic failure. This study aims to describe the use of a children’s music therapy to enhance the self-esteem of ADHD students. Using a qualitative case study to garner the data from ADHD students, this study included pre-field stages, activities during the field, and post empirical stages. Data were analyzed using observations and interviews. The results of the research show that the children’s music therapy can be used as an alternative in developing the self-esteem of ADHD children in an elementary school. It can be seen from their development of several aspects including ability (competence), meaning (significance), goodness (virtue), and strength (power). Therefore, elementary school teachers are advised to use the music therapy to enhance the self-esteem of ADHD children. As a medium of healing and to overcome anxiety, such therapy could allow students to gain self-acceptance, get acceptance by others, be able to complete tasks, be able to make decisions, be able to control themselves, and have better self-awareness. Keywords: a children's music therapy , self-esteem, attention deficit hyperactivity disorder. Abstrak Siswa sekolah dasar dengan Attention Deficit Hyperactivity Disorder (ADHD) memiliki harga diri yang rendah yang berdampak pada kegagalan akademik mereka. Penelitian ini bertujuan untuk mendeskripsikan penggunaan terapi musik anak untuk meningkatkan harga diri siswa ADHD. Menggunakan studi kasus kualitatif untuk mengumpulkan data dari siswa ADHD, penelitian ini meliputi tahap pra-lapangan, kegiatan selama lapangan, dan tahap pasca empiris. Teknik analisis data menggunakan observasi dan wawancara. Hasil penelitian menunjukkan bahwa terapi musik anak dapat digunakan sebagai salah satu alternatif dalam mengembangkan harga diri anak ADHD di sekolah dasar. Hal ini dapat dilihat dari perkembangannya dari beberapa aspek antara lain kemampuan (competence), makna (significance), kebaikan (virtue), dan kekuatan (power). Oleh karena itu, guru sekolah dasar disarankan untuk menggunakan terapi musik untuk meningkatkan harga diri anak ADHD. Sebagai media penyembuhan dan mengatasi kecemasan, terapi tersebut dapat memungkinkan siswa untuk memperoleh penerimaan diri, mendapatkan penerimaan oleh orang lain, mampu menyelesaikan tugas, mampu mengambil keputusan, mampu mengendalikan diri, dan memiliki kesadaran diri yang lebih baik. Kata kunci: terapi musik anak, harga diri, attention deficit hyperactivity disorder.
Algılanan Etkinlik Fayda Ölçeği Ebeveyn Formu’nun Türkçe’ye Uyarlama Çalışması

Individuals participate in recreation activities in line with different wishes and needs. Children's participation in recreation is generally with family support. The present study aimed to adapt the "Perceived Activity Benefit Scale" developed by Ooi et al (2020) for Turkish language and culture. The original scale has 14 items and 3-factors which enable the parents to evaluate the benefits of children’ recreation participation in terms of character development, talent development and overcoming difficulties. 331 parents selected by purposeful sampling method participated in the study. The data were analyzed using IBM SPSS 24.0 and IBM SPSS Amos 22.0 programs. The linguistic adaptation of the data collection tool was provided by translation-retranslation method, its validity was provided by confirmatory factor analysis, and its reliability was provided by internal consistency and test-retest reliability methods. NFI, CFI, GFI, RMSEA fit index values were calculated in the study. As a result, it was determined that the data collection tool is valid and reliable for Turkish Language and Culture with 14 items and 3 factors according to the fit index values.
Adhesion enhancement in a dimpled surface with axisymmetric waviness and rate-dependent work of adhesion

ABSTRACT Surfaces showing macroscopic adhesion are rare in industry but are abundant in Nature. Adhesion enhancement has been discussed mostly with geometrical systems (e.g. patterned surfaces), more rarely with viscoelasticity, and has the goal of increasing hysteresis and the detachment force at separation. Soft materials are common, and these have viscoelastic properties that result in a rate-dependent increase in toughness. Here the detachment of two half-spaces is studied, one being flat and the other having a dimple in the limit of short-range adhesion and rate-dependent work of adhesion, in the presence of axisymmetric single-scale waviness, which itself results in adhesion enhancement, similarly to the Guduru model of rough spheres. The dimpled surface shows pressure-sensitive adhesion, and when waviness is added, the roughness-induced toughening is enhanced. It is shown that when a rate-dependent work of adhesion is also accounted for, as in the present paper, assuming a power-law dependence of the effective work of adhesion on the crack tip velocity, the two enhancements are not completely multiplicative, as the “viscoelastic” one tends to prevail and indicates a new avenue of research for pressure-sensitive adhesion.
Network intrusion detection using machine learning approaches: Addressing data imbalance

Natural Sciences and Engineering Research Council of Canada Canada, Grant/Award Number: RGPIN‐ 2020‐06482 Abstract Cybersecurity has become a significant issue. Machine learning algorithms are known to help identify cyberattacks such as network intrusion. However, common network intrusion datasets are negatively affected by class imbalance: the normal traffic behaviour constitutes most of the dataset, whereas intrusion traffic behaviour forms a significantly smaller portion. A comparative evaluation of the performance is conducted of several classical machine learning algorithms, as well as deep learning algorithms, on the well‐ known National Security Lab Knowledge Discovery and Data Mining dataset for intrusion detection. More specifically, two variants of a fully connected neural network, one with an autoencoder and one without, have been implemented to compare their performance against seven classical machine learning algorithms. A voting classifier is also proposed to combine the decisions of these nine machine learning algorithms. All of the models are tested in combination with three different resampling techniques: oversampling, undersampling, and hybrid sampling. The details of the experiments conducted and an analysis of their results are then discussed.
NBER WORKING PAPER SERIES THE CAUSAL EFFECT OF HEAT ON VIOLENCE: SOCIAL IMPLICATIONS OF UNMITIGATED HEAT AMONG THE INCARCERATED

Correctional facilities commonly lack climate control, producing a setting absent endogenous responses to hot weather like avoidance, adjustment, and mitigation. We study daily weather variation across the state of Mississippi, and show that high temperatures increase intense violence among the incarcerated. Days with unsafe heat index levels shift both the intensive and extensive margins of violence, raising daily violent interactions by 20%, and the probability of any violence by 18%. Our setting cleanly identifies the effect of heat on violence, and highlights previously unobserved social costs of current facility infrastructure. Rising global temperatures could substantially increase violence absent adjustment. Anita Mukherjee 5279 Grainger Hall 975 University Ave Madison, WI 53706 anita.mukherjee@wisc.edu Nicholas J. Sanders Cornell University MVR Hall Ithaca, NY 14853 and NBER njsanders@cornell.edu “I pray thee, good Mercutio, let’s retire. The day is hot; the Capulets, abroad; And if we meet we shall not escape a brawl, For now, these hot days, is the mad blood stirring” (Romeo and Juliet)
STUDY OF STUDENT LEARNING APPROACH IN TWO DIFFERENT SUBJECTS ON THE SAME YEAR

Biggs’ R-SPQ-2F questionnaire has been widely used since its release in 2001 to assess the student approach to learning, identifying two main approaches: Deep and Surface Approaches. The results of the questionnaire help to evaluate the teaching system as students’ approach to learning depends, among other factors, on the current teaching context and therefore, it is not a fixed quality of the learner. Based on this, the approaches of 74 first-year students of the Degree in Biotechnology at Universitat Politècnica de València have been analysed under two different teaching frames: a first-term subject in Genetics and a second-term subject in Business Economics. Although some students maintain their approach to learning, differences between both subjects have been found significant for the main scales and most of the secondary ones, although not for language used as medium of instruction or gender. The item reliability analysis showed a high consistency for the main scales, but not for the secondary scales of the questionnaire. These data contribute to reinforce the theory that students stablish a learning approach according to the demands of the subject and context and modify their approach to learning.
Youth Participatory Action Research as a Catalyst for Health Promotion in a Rural South African School

Rural schools in South Africa face many social and environmental challenges which impact negatively on learner wellbeing and performance. Given the severity and history of these problems, the situation is unlikely to change in the near future. Yet, schools are supposed to be enabling environments, providing holistic support to learners from communities plagued by severe economic, health and social challenges. A different strategy is clearly needed to promote the health and wellbeing of learners. Youth participatory action research (YPAR) appears to offer a plausible approach to kick start improved, health-promoting responses from within the school. We facilitated a YPAR process with volunteer learners from Grade10 to find out how they could begin to transform their rural school. Using arts-based methods, the learners were successful in raising awareness of the negative effects they were suffering as a result of the poor social-emotional climate in the school, the unsanitary facilities and the lack of opportunities to engage in physical exercise. The actions they took to address these issues were a catalyst for ongoing positive change in the school. The findings add to literature about how YPAR can make schools more enabling spaces.
Differences in ontogenetic and diurnal microhabitat selection by sympatric live‐bearing fish species with different reproductive modes

1. A pregnancy imposes a heavy reproductive burden on females. Some live- bearing species have evolved reproductive adaptations to reduce this burden, which may influence their ability to use specific microhabitats. 2. We investigate whether two such reproductive adaptations, placentation (embryo provisioning via a placenta) and superfetation (the ability to carry multiple broods at various developmental stages), influence microhabitat selection by five sympatric Costa Rican live- bearing fish species (family Poeciliidae). Theory predicts that placentation and superfetation should both reduce the reproductive burden of females during pregnancy, improve their body streamlining, and swimming performance, and consequently allow them to use more performance- demanding microhabitats. Here we apply underwater visual fish surveys to
Comparative study of multiple sclerosis patients based on distance from the advanced health center

Aim: There are several reasons for presenting to a hospital for multiple sclerosis (MS), a neurodegenerative disorder. We aimed todetermine how distance affects presentation by patients with MS to an advanced health center in Malatya, Turkey.Materials and Methods: The study was performed on 109 patients at the Neurology Department of Inonu University Hospital in 2017.The patients were divided into group-1, who lived in Malatya, and group-2, who live in the upstate region. Demographic and clinicaldata were analyzed retrospectively from medical records. Chi-square tests, independent sample T-tests, and Mann–Whitney U-testswere used to analyze the data.Results: The duration of the disease was longer among patients who lived in Malatya. In terms of mean expanded disability statusscale scores, patients who lived in Malatya had higher scores and patients who lived upstate exhibited more clinical complaints.Among patients who lived upstate, there were more motor problems, vertigo, cognitive impairment, psychiatric disturbances, andvisits for blood tests.Conclusion: Distance affected admission to MS outpatient clinics. We should be more careful in terms of attack when assessingthe reasons of patients present from outside the province. More meaningful results can be obtained by following more patients forlonger periods.
Modern Forms of Populism and Social Policies: Personal Values, Populist Attitudes, and Ingroup Definitions in Support of Left-Wing and Right-Wing Welfare Policies in Italy

We analyzed the relationship between modern forms of populism and citizen support for exclusive welfare policies and proposals, and we focused on support for left-wing- and right-wing-oriented welfare policies enacted or proposed during the Lega Nord (LN)–Five Star Movement (FSM) government in Italy (2018–2019). In light of the theoretical perspective of political ideology as motivated by social cognition, we examined citizens’ support for the two policies considering adherence to populist attitudes, agreement on the criteria useful to define ingroup membership, and personal values. We also took into account the role of cognitive sophistication in populism avoidance. A total of 785 Italian adults (F = 56.6; mean age = 35.8) completed an online survey in the summer of 2019 based on the following: support for populist policies and proposals, political ideologies and positioning, personal values, and ingroup boundaries. We used correlation and regression analyses. The results highlight the relationships between populism and political conservatism. Populism was related to the vertical and horizontal borders defining the “people”; cognitive sophistication was not a relevant driver. We identified some facilitating factors that could promote adherence to and support for public policies inspired by the values of the right or of the left, without a true ideological connotation.
A Temporal–Spatial Deep Learning Approach for Driver Distraction Detection Based on EEG Signals

Distracted driving has been recognized as a major challenge to traffic safety improvement. This article presents a novel driving distraction detection method that is based on a new deep network. Unlike traditional methods, the proposed method uses both temporal information and spatial information of electroencephalography (EEG) signals as model inputs. Convolutional techniques and gated recurrent units were adopted to map the relationship between drivers’ distraction status and EEG signals in the time domain. A driving simulation experiment was conducted to examine the effectiveness of the proposed method. Twenty-four healthy volunteers participated and three types of secondary tasks (i.e., cellphone operation task, clock task, and 2-back task) were used to induce distraction during driving. Drivers’ EEG responses were measured using a 32-channel electrode cap, and the EEG signals were preprocessed to remove artifacts and then split into short EEG sequences. The proposed deep-network-based distraction detection method was trained and tested on the collected EEG data. To evaluate its effectiveness, it was also compared with the networks using temporal or spatial information alone. The results showed that our proposed distraction detection method achieved an overall binary (distraction versus nondistraction) classification accuracy of 0.92. In terms of task-specific distraction detection, its accuracy was 0.88. Further analysis on the individual difference in detection performance showed that drivers’ EEG performance differed across individuals, which suggests that adaptive learning for each individual driver would be needed when developing in-vehicle distraction detection applications. Note to Practitioners—Driver distraction detection is crucial for safety enhancement to avoid crashes caused by nondriving-related activities, such as calling and texting while driving. Related previous studies mainly focus on detection by monitoring head and eye movement using computer vision technologies or by extracting indicators from driving performance measures for driver state inference. However, complex traffic environments (e.g., dynamically changing light distribution on driver’s face and nighttime driving with low illumination) strongly limit the effectiveness of computer vision technologies, and the driving performance characteristics may also be caused by factors other than distraction (e.g., fatigue). To solve these problems, this article seeks to develop a deep learning-based approach to map the unique relationship between driver distraction and the bioelectric electroencephalography (EEG) signals that are not affected by traffic environments. The proposed method can be integrated into the driver assistance systems and autonomous vehicles to deal with emergency situations that need drivers to handle. The timely detection of distraction by our method will significantly facilitate its practical applications in collision avoidance or danger mitigation in the handover process.
Integration of refugees involving organizational managers’ experiences

Abstract This article investigated the organizational integration of refugees from the experience of company managers in the city of São Paulo, Brazil. A basic qualitative research was developed, based on interpretative paradigm assumptions, and the data were collected through a semi-structured interview applied to five managers in charge of refugees in their workplace. The interviews data underwent qualitative content analysis. The results showed potential integration benefits, such as experience sharing, new talents, gratitude, engagement, improvements in the company’s reputation, productivity, creativity, and organizational development from the inclusion of new languages. However, factors such as language, diploma revalidation, skill limitation, and low schooling levels were seen as obstacles to efficient integration. The research also found that employers are highly dependent on voluntary assistance from organizations for hiring and integrating refugees, which indicates that, without the presence of these mediators, the possibilities of recruiting the refugee workforce may be affected. The study contributes to broadening the discussion on the organizational integration of refugees, a topic that is still little explored in the field of administration. It also intends to awaken in managers a more sensitive view about people in a situation of refuge and how their effective integration can impact their businesses and individuals.
Issues-360TM: an analysis of transformational learning in a controversial issues engagement initiative

ABSTRACT Purpose Unprecedented global challenges of the twenty-first century have highlighted the need for novel programs to train students in the skills necessary to address increasingly complex controversial science issues. Issues-360TM was developed as an innovative year-long co-curricular, issues engagement initiative designed to address this need. Design/methodology Two cohorts of undergraduate students (48) completed three self-reflections over the course of the year. These qualitative measures were inductively coded and analyzed, then triangulated with quantitative outcome measures. Findings Students demonstrated transformational movement across four levels of learning: questioning-self, open-mindedness, stakeholder awareness, and critical thinking (consistent with Mezirow’s meta-theory of transformational learning), and acquisition of five skills: active listening, emotional regulation, respectfulness, empathy and confidence. Theoretical implications This study shows that an innovative curriculum combining Transformational Learning Theory with skills training moves students through Mezirow’s ‘levels of learning’ while also enhancing their controversial issues engagement skills. Practical implications Evidence-based programing can prepare the next generation of agricultural and environmental professionals with the engagement skills necessary to meaningfully address the controversial science-based issues facing society. Originality/value In an environment where scientific issues are increasingly polarized, the innovative design of the Issues 360TM program enhances students’ ability to approach controversial issues with an open mind and the skills to meaningfully engage with others on contested environmental and agricultural issues. Few, if any, studies have demonstrated or tested the efficacy of educational programs combining skills training with Transformational Learning as foundational approaches to develop an effective undergraduate curriculum for controversial issues engagement.
Gambaran Pengetahuan, Sikap Dan Tindakan Penerapan Protokol Kesehatan Covid-19 Warga Di Wilayah Percontohan Program Rt Siaga Kota Surabaya

COVID-19 telah ditetapkan sebagai Kedaruratan Kesehatan Masyarakat yang Meresahkan Dunia (KKMMD). Provinsi Jawa Timur dan Kota Surabaya merupakan salah satu daerahi dengan angka kasus terbanyak dan telah dikategorikan sebagai zona merah. Total kasus konfirmasi positif COVID-19 di Jawa Timur sebanyak 3.642 Kasus. Namun di Kota Surabaya ada sebanyak 1.975 Kasus. Hal tersebut dari penerapan protokol kesehatan COVID-19 di masyarakat yang dipengaruhi oleh pengetahuan, sikap dan tindakan dari masyarakat. Tujuan penelitian ini adalah untuk mengetahui gambaran pengetahuan, sikap dan tindakan penerapan protokol kesehatan COVID-19 warga di wilayah program RT Siaga Surabaya. Penelitian ini menggunakan data primer dengan kuesioner yang berasal dari Program RT Siaga Kota Surabaya. Jumlah sampel responden dalam penelitian ini adalah 70 responden. Data dianalisis secara univariat dengan menyajikan distribusi frekuensi variabel. Karakteristik responden sebagian besar di usia 31-40 tahun dan berjenis kelamin laki-laki. Sebanyak 69 responden (99%) memiliki pengetahuan penerapan protokol kesehatan dalam kategori baik. Sebanyak 70 responden (100%) memiliki pemahaman sikap penerapan protokol kesehatan kategori baik sedangkan yang memiliki tindakan penerapan protokol kesehatan dalam kategori baik sebanyak 68 responden (97%). Pengetahuan, sikap dan tindakan warga di wilayah program RT Siaga Kota Surabaya sebagian besar menunjukkan kategori baik terhadap penerapan protokol kesehatan COVID-19.
Liquid crystalline non-linear S-shaped oligomers consisting of azobenzene and biphenylene units: synthesis, characterisation and influence of central spacer

ABSTRACT A series of non-linear S-shaped liquid crystal oligomers wherein the molecule consists of biphenylene moiety as a central core unit and two symmetrical side arms azobenzene moieties joined to catechol as a linkage group have been successfully synthesised and characterised. The members in this series possess different inner spacer with carbon number n ranging from 4 to 9 while the outer spacer length located in azobenzene moieties are remains unaltered. The members with even parity exhibit monotropic phase, whereas homologues with odd parity display enantiotropic phase. The appearance of nematic, smectic A and smectic B phases was validated with texture observation under polarised light and X-ray diffraction (XRD). The XRD study on the S-shaped oligomer indicates that the arrangement of smectic phase exists as an intercalated structure. The S-shaped oligomer shows photoisomerisation properties in solution whereby the trans to cis isomerisation for this molecule is accomplished 1140 s, whereas reverse process under thermal back reaction occurred in 4620 min. Graphical Abstract