Miracle-dz/UniFAR-FTUs huggingface dataset:
Prediction of LQ45 Index in Indonesia Stock Exchange: A Comparative Study of Machine Learning Techniques

LQ45 is an Indonesia Stock Exchange Index (ISX) incorporate of 45 companies that meet certain criteria to target investors for selecting certain stocks. The prediction of stock price direction in the financial world is a major issue. The implementation of machine learning and other algorithms for market price analysis and forecasting is a very promising field. Different types of classification algorithms were used to predict the stock market. However, when individual studies are considered separately there is no clear consensus that algorithms work best. In this research, a comparison framework is proposed, which aims to benchmark the performance of a wide range of classification models and use them to predict the LQ45 index. The data in this research contains the transaction level and capitalization size are obtained from the Indonesian Stock Exchange (ISX). For analysis purposes, we set out 10 classifiers that can be used to build classification models and test their performance in the LQ45 dataset. The performance criterion chosen to measure this effect is accuracy, recall, and precision. The results showed that the random forest algorithm had the best performance for predicting the LQ45 index. Whilst the classification and regression trees, C4.5, support vector machine, and logistic regression algorithms also perform well. Besides, the models based on traditional statisticalbased learners that are Naïve Bayes and linear discriminant analysis seem to underperform for predicting the LQ45 index. These results are not only beneficial to enrichment the machine learning techniques literature but also have a significant influence on the stock market prediction in terms of the ability to predict the LQ45 index.
ORIGIN OF THE GALACTIC DIFFUSE X-RAY EMISSION: IRON K-SHELL LINE DIAGNOSTICS

This paper reports detailed K-shell line profiles of iron (Fe) and nickel (Ni) of the Galactic Center X-ray Emission (GCXE), Galactic Bulge X-ray Emission (GBXE), Galactic Ridge X-ray Emission (GRXE), magnetic Cataclysmic Variables (mCVs), non-magnetic Cataclysmic Variables (non-mCVs), and coronally Active Binaries (ABs). For the study of the origin of the GCXE, GBXE, and GRXE, the spectral analysis is focused on equivalent widths of the Fe i-Kα, Fe xxv-Heα, and Fe xxvi-Lyα lines. The global spectrum of the GBXE is reproduced by a combination of the mCVs, non-mCVs, and ABs spectra. On the other hand, the GRXE spectrum shows significant data excesses at the Fe i-Kα and Fe xxv-Heα line energies. This means that additional components other than mCVs, non-mCVs, and ABs are required, which have symbiotic phenomena of cold gas and very high-temperature plasma. The GCXE spectrum shows larger excesses than those found in the GRXE spectrum at all the K-shell lines of iron and nickel. Among them the largest ones are the Fe i-Kα, Fe xxv-Heα, Fe xxvi-Lyα, and Fe xxvi-Lyβ lines. Together with the fact that the scale heights of the Fe i-Kα, Fe xxv-Heα, and Fe xxvi-Lyα lines are similar to that of the central molecular zone (CMZ), the excess components would be related to high-energy activity in the extreme envelopment of the CMZ.
Wavelet Sub-bands Features-based ECG Signal Quality Assessment Scheme for Computer-aided Monitoring System

Electrocardiogram (ECG) signal quality assessment (SQA) is a crucial step for improving the performance and reliability of medical diagnostics in computer-aided monitoring systems. Most of the existing ECG SQA methods utilize QRS complex and R-peak information-based features, where the quality assessment performance degrades due to improper detection of R-peaks. Unlike the existing machine learning-based ECG SQA approaches, this work proposes an efficient wavelet sub-bands features-based SQA scheme by avoiding the utilization of R-peak-based features. Sub-band levels features are extracted by incorporating the frequency localization property of wavelet transform (WT). Furthermore, the features are applied to machine learning-based classifier to assess the signal quality. Simulation study and results show that the proposed scheme exhibits an assessment accuracy of 98.11% on the simulated dataset, 99.12% on single channel ECG dataset of Physionet: Computing in Cardiology Challenge (PCinCC) and 97.32% on real arrhythmia dataset: Massachusetts Institute of Technology-Beth Israel Hospital database (MITDB). An in-depth study of the results illustrates that the proposed ECG SQA technique can be utilized for improving the reliability of modern automated computer-aided cardiac monitoring systems.
Technology Adoption and Leapfrogging: Racing for Mobile Payments

Paying with a mobile phone is a cutting-edge innovation transforming the global payments industry. However, some advanced economies like the U.S. are lagging behind in mobile payment adoption. We construct a dynamic model with sequential payment innovations to explain this puzzle, which uncovers how advanced economies’ past success in adopting card-payment technology holds them back in the mobile-payment race. Our calibrated model matches the cross-country adoption patterns of card and mobile payments and also explains why advanced and developing countries favor different mobile payment solutions. Based on the model, we conduct several quantitative exercises for welfare and policy analyses.
In vitro comparisons of different mixtures of sodium tetradecyl sulfate-based sclerotherapy foam

Poster: "ECR 2014 / C-2279 / In vitro comparisons of different mixtures of sodium tetradecyl sulfate-based sclerotherapy foam" by: "H. Ninalowo1, J. Koizumi2, B. Endale1, B. Janne d'Othee1; 1Baltimore, MD/US, 2Isehara-City, Kanagawa-pref. /JP"
Socially Responsible HRM, Employee Attitude, and Bank Reputation: The Rise of CSR in Bangladesh

Applying the organisational climate of corporate social responsibility (CSR) and human resource management (HRM) behavioural theories, this paper examines the associations among socially responsible HRM (SRHRM), organisational citizenship behaviour (OCB), turnover intention, and bank reputation. The proposed model, including seven hypotheses, was examined on a sample of 711 Bangladeshi bank employees. The results suggest that SRHRM has significant positive effects on both OCB and bank reputation, and a significant negative influence on turnover intention. OCB was positively significant for bank reputation but was estimated as insignificant for bank employees’ turnover intention. Moreover, perceived bank reputation was significant and negative on Bangladeshi employees’ turnover intention. Finally, a partial mediation effect was found for OCB on the direct relationship between SRHRM and bank reputation. This paper recommends that banks should aim at higher levels of OCB and reputation and lower turnover intentions should encourage SRHRM in their strategic approaches for HRM and CSR. The implications of the results of this study can help financial organisations to recognise the significance of SRHRM and its favourable effects on employee motivation and institutional reputation.
Relational Dynamics between Customer Engagement, Brand Experience, and Customer Loyalty: An Empirical Investigation

Abstract Despite the paramount importance of work on customer engagement and brand experience, there is a vital research gap regarding inspecting the relational dynamics between these constructs across the contexts, principally in the setting of banking industry. This study, therefore, aims to foster the understanding of engagement and experience in bettering banks’ ties with their customers so that a sustained loyal customer base is developed and managed over time. Toward the end, this study also investigates gender’s moderating role on the proposed relationships. This research work has emphasized various important customer engagement and brand experience issues and their inferences, which may be very supportive in formulating the strategies essential for the growth of the retail banking sector.
Diffuse reflectance spectra of methylene blue adsorbed on different types of clay samples

Abstract Diffuse reflectance (DR) spectra in the visible (VIS) and near-infrared (NIR) region of methylene blue (MB) adsorbed on clay samples of different mineral composition and varying MB/clay ratios were analyzed. This type of investigation is not affected by unadsorbed MB molecules and can be used in clay-mineral determination. When the MB dye/clay loading was increased, enhancement of bands in the DR-VIS and DR-NIR was observed. The distribution of various MB aggregates was interpreted according to mineral composition and MB loading. The NIR spectrum of H2O overtone provides insights about the intercalated MB aggregation, consistent with VIS spectra. Critical MB concentration for formation of dimeric structure was between 0.7 and 1.75 mmol/100 g followed with suppression of monomers. Different orientations of vectors of polarized light allowed calculations of the possible orientation and tilting angle of MB molecules on the surface of the clay particles in accordance with XRD data.
Exploring the Emotional Responses of Undergraduate Students to Assessment Feedback: Implications for Instructors

Summative assessments tend to be viewed as high-stakes episodes by students, directly exposing their capabilities as learners. As such, receiving feedback is likely to evoke a variety of emotions that may interact with cognitive engagement and hence the ability to learn. Our research investigated the emotions experienced by undergraduate students in relation to assessment feedback, exploring if these emotions informed their learning attitudes and behaviours. Respondents were drawn from different years of study and subject/major. A qualitative approach was adopted, using small group, semi-structured interviews and reflective diaries. Data were analysed thematically and they revealed that receiving feedback was inherently emotional for students, permeating their wider learning experience positively and negatively. Many students struggled to receive and act upon negative feedback, especially in early years, when it was often taken personally and linked to a sense of failure. Negative emotional responses tended to reduce students’ motivation, self-confidence, and self-esteem. Some students, especially in later years of study, demonstrated resilience and engagement in response to negative feedback. By contrast, positive feedback evoked intense but fleeting emotions. Positive feedback made students feel cared about, validating their self-worth and increasing their confidence, but it was not always motivational. The paper concludes with recommendations for instructors, highlighting a need to communicate feedback carefully and to develop student and staff feedback literacies.
Frontend Innovation And Top Income Inequality: Evidence From Emerging Markets

This paper contributes to the literature on income inequality, by extending existing models to examine the effect of front-end innovation (FEI) on top income inequality. We use a fixed effect panel regression, on annual country level data for twenty four emerging markets, over a twenty four (1995–2018) year period, and find an insignificant correlation between income inequality, and FEI. The instrumental variable estimates however, shows a significant association between measures of FEI and top income shares. Further, we confirm that FEI is weakly related with broad measures of income inequality. Our instrumentation strategy, and robustness checks, suggests that this correlation partly reflects a causality, from FEI to top income inequality. Finally, we show that FEI is necessary for the survival of new ventures, in the crucial early years. Overall, our findings confirm that FEI, is a significant determinant of increases, in entrepreneurial income share.
Growth and antioxidative responses to excess cadmium in Kenaf (Hibiscus cannabinus L).

In order to study the mechanisms responsible for cadmium (Cd) detoxification in Kenaf (Hibiscus cannabinus L), the growth and antioxidative responses of the plant grown on a Cd polluted soil were investigated. Kenaf seeds were grown in artificially contaminated soils containing increasing concentrations of Cd as CdCl2 (0, 150, 300, 450 and 600 mg Cd kg) for 14 weeks in a screenhouse. Growth parameters (plant height and stem girth), Cd concentration, oxidative lipid peroxidation, glutathione (GSH) content, activity of antioxidant enzymes, superoxide dismutase (SOD), catalase (CAT) and ascorbate peroxidase (APX) were measured using established techniques. Cd inhibits growth as shown by decrease in plant height and stem girth at all concentrations used compared with control. Plant Cd concentrations increased with soil Cd concentrations, with maximum Cd uptake being 73.37±8.82 mg kg dry weight at 600 mg Cd kg. The content of malondialdehyde (indication of lipid peroxidation) showed a significant (p<0.05) increase in Kenaf shoots at 150 and 300 mg Cd kg level of treatment, while the content of non-enzymatic antioxidant, GSH, showed a significant (p< 0.05) depletion at all treatment levels compared with control. Activity of SOD was increased while the activities of CAT and APX were inhibited at all Cd concentrations used. Results show that Cd induces oxidative stress in Kenaf and that both enzymatic and non-enzymatic antioxidants play significant roles in Cd detoxification in Kenaf.
Evaluation of the Soft Error Assessment Consistency of a JIT-based Virtual Platform Simulator

Luciano Ost, Loughborough University, Epinal Way Loughborough Leicestershire LE11 3TU, UK. Email: l.ost@lboro.ac. uk Abstract Soft error resilience has become an essential design metric in electronic computing systems as advanced technology nodes have become less robust to high‐charged particle effects. Designers, therefore, should be able to assess this metric considering several software stack components running on top of commercial processors, early in the design phase. With this in mind, researchers are using virtual platform (VP) frameworks to assess this metric due to their flexibility and high simulation performance. In this regard, herein, this goal is achieved by analysing the soft error consistency of a just‐in‐time fault injection simulator (OVPsim‐FIM) against fault injection campaigns conducted with event‐driven simulators (i.e. more realistic and accurate platforms) considering single and multicore processor architectures. Reference single‐core fault injection campaigns are performed on RTL descriptions of Arm Cortex‐M0 and M3 processors, while gem5 simulator is used to multicore Arm Cortex‐A9 scenarios. Campaigns consider different open‐source and commercial compilers as well as real software stacks including FreeRTOS/Linux kernels and 52 applications. Results show that OVPsim‐FIM is more than 1000� faster than cycle‐accurate simulators and up to 312� faster than event‐driven simulators, while preserving the soft error analysis accuracy (i.e. mismatch below to 10%) for single and multicore processors.
An Impact Study on Organic Agriculture - SWOC Analysis

Ecological changes, mechanization and industrial developments result in an increasing artificial facilities and the impact of human activities leads to the demolition and loss of natural resources and its habitats. Organic agriculture is the method of food production using the naturally available resources particularly organic and by avoiding any type of artificially made chemicals, fertilizers, pesticides, fungicides, weedicides, etc. Also to sustaining the ecosystem and pollution less agriculture production, there is a need of organic agriculture at present days. Tamil Nadu Agricultural University (TNAU) imparts training at every month on organic agriculture to the interested farmers. This study was conducted with a structured interview schedule with 200 trained farmers with the specific objective to analysis the organic agriculture farmers with the various dimensions via. , strength, weakness, oppurtunities and challenges (SWOC). The study revealed that high quality products and use of agricultural wastes effectively were the strength Promoting high life style and contract farming tie-up were the foremost opportunities expressed by organic farmers with mean score of 2.70 and 2.40 respectively.
Which factors are predicting the mortality in patients with COVID-19 in the intensive care unit?

Aims: COVID-19 infection is a global health problem; clinical and laboratory parameters have been developed to predict this disease-related mortality/morbidity. Some of these parameters are clinical parameters, while some are laboratory parameters. This study aims to determine whether Acute Physiology and Chronic Health Evaluation (APACHE) II, Glasgow Coma Scale (GCS), age, presence of comorbidity, and absolute lymphocyte count effectively predict mortality in patients admitted to intensive care unit (ICU) due to COVID-19. Methods: We have included 108 PCR-positive COVID-19 patients admitted to the ICU between 1 October and 31 November 2020 in our research. Demographic characteristics of all patients, APACHE II values within the first 24 hours of admission to ICU, the GCS, the presence of comorbidity, lymphocyte count during ICU admission, duration of ICU stay, and the mortality rates were recorded. Results: The average age of 108 individuals evaluated in the study was 67±13.61 years, and 56.5% of the patient group consisted of the geriatric age range. Seventy (64.8%) of the patients were female, eighty-nine (82.4%) patients had at least one comorbidity. In the multivariate analysis, it was determined that lymphocyte value, APACHE II score, and the presence of any comorbidity are independent prognostic factors for mortality when accepted to ICU. Conclusion: In our study, we have determined that age, APACHE II value, presence of comorbidity, and baseline lymphocyte counts are independent predictors of mortality.
Neural stem cells reversed disease symptoms in an experimental autoimmune encephalomyelitis mouse model of multiple sclerosis

Background Multiple sclerosis (MS) is an autoimmune inflammatory disease of the central nervous system (CNS). MS affects millions of people and causes a great economic and societal burden. Currently used treatment drugs have side effects and only address the symptoms but not the causes of MS. In this study, a novel approach of transplanting neural stem cells (NSCs) derived from human primitive mesenchymal stem cells (MSCs) was investigated in an experimental autoimmune encephalomyelitis (EAE) mouse model of MS. Methods Primitive MSCs were differentiated into NSCs using selective media. The cells were labeled with PKH26 and injected into the tail vein of EAE mice. The animals were evaluated for changes in neurobehavior and weight twice daily. Two weeks following cell transplantation, the animals were sacrificed to collect the blood, lymphatic and CNS tissues for analysis. FACS analysis was used to track labeled cells and infiltrates. Histochemical analysis was performed to determine the levels of myelination. Expression of inflammation, neural, astrogliosis, neuroprotection, and myelination markers was investigated by using immunohistochemical and qRT-PCR analyses. Results Neurobehavioral assays showed that EAE disease process was halted by transplantation of both MSCs and NSCs. However, NSCs showed greater efficacy in reversing the disease symptoms, which resulted in near complete recovery of EAE animals. Post-transplantation analyses also showed homing of transplanted cells into the CNS with concomitant induction of anti-inflammatory response resulting in reduction of immune infiltrates. Luxol fast blue staining intensity of CNS tissues was significantly improved in treated mice as compared to EAE animals, suggesting endogenous remyelination. NSC transplantation also modulated Treg and Th17 cells in EAE mice to levels comparable to healthy controls. In addition, several of the markers associated with neuroprotection (i.e. Igf, Bdnf, and Trkb), myelination (i.e. Erk2, Krox-20, Oct-6, Mpz, Mbp, and Mog) and neurogenesis (i.e. Tuj1 and Nestin) were upregulated, suggesting endogenous regeneration in treated animals. Conclusions Cell transplantation was more effective at an earlier point of EAE disease (EAE stage 1) than later (EAE stage 2). These promising results provide basis for large-scale clinical studies to treat MS using NSCs derived from primitive MSCs.
The Use of Android Comics Based on Local Potentials of Embung Tambakboyo to Improve Students’ Critical Thinking Ability

This research aims to find out the improvements in junior high school students’ critical thinking ability through Android comics. This research conducted was quantitative research using non-equivalent control group design. The number of samples involved were 68 junior high school students selected by purposive sampling and grouped into experiment and control class. The media used is Android comics based on local potentials of Embung Tambakboyo that contains material of interactions living creatures with its environment. Students' critical thinking ability are analyzed based on pretest and posttest results. The N-Gain results obtained by the experiment class and control class showed the increased value for each class in the high and middle categories. Thus, it can be concluded that Android comics based on local potentials of Embung Tambakboyo that was developed could improve the critical thinking ability in science learning better than the learning media that is commonly used in schools.
From Claims to Violence: Signaling, Outbidding, and Escalation in Ethnic Conflict

Do radical political demands increase the risk of ethnic civil conflict? And why do ethnic movements make radical demands in the first place? We contend that when movements are fragmented, individual organizations use far-reaching claims relative to the status quo to attract attention from the government, boost intra-organizational discipline, and outbid rivals. Yet, such radical claims also increase the risk of conflict escalation. We test our arguments at both the ethnic group and organizational levels, using a new dataset on ethno-political organizations and their political demands. Our results show that the scope of demands increases the more organizations exist within an ethnic movement and that radical demands increase the risk of civil conflict onset. This effect is specific to the dyadic government-movement interaction, irrespective of other ethnic groups in the country. Moreover, at the organizational level, radicalization in demands increases the likelihood that an organization becomes engaged in civil conflict.
Sport-related concussion practices of medical team staff in elite football in the United Kingdom, a pilot study

ABSTRACT Objectives To explore sport-related concussion (SRC) awareness, behaviours, and attitudes of medical team staff working in elite football in the United Kingdom. Including usage and awareness of the FA concussion guidelines, concussion education rates of players and coaching staff, and collection of baseline concussion assessments. Methods Cross-sectional questionnaire study distributed online by organisations including or representing medical staff working in elite football in the United Kingdom. Results 120 responses were gathered. High awareness rates of the FA guidelines were found (97%) with variable rates of player and coaching staff concussion education. Baseline concussion assessments were collected by 78%. Of those, 99% collected SCAT5 with low rates of other neuro-psychometric testing (17%). Confidence of pitch-side SRC recognition was high (93% feeling very confident or confident). Introduction of a ‘concussion’ substitute was seen as strongly positive for player welfare (85% strongly agreeing or agreeing). Conclusions Awareness of FA concussion guidelines, and collection of SCAT5 baseline testing was high. Player and coaching staff concussion education rates were low, as was the use of neuro-psychometric testing beyond the use of the SCAT5. There was strong support the introduction of a ‘concussion’ substitute being a positive thing for player welfare.