Miracle-dz/UniFAR-FTUs huggingface dataset:
A Comparative Analysis of Machine Learning Models for Banking News Extraction by Multiclass Classification With Imbalanced Datasets of Financial News: Challenges and Solutions

, include one module for extracting and storing news articles, and another module for classifying these text documents into a specific domain(s). In the current study, we have performed extensive experiments to classify the financial news articles into the predefined four classes Banking, Non-Banking, Governmental, and Global. The idea of multi-class classification was to extract the Banking news and its most correlated news articles from the pool of financial news articles scraped from various web news portals. The news articles divided into the mentioned classes were imbalanced. Imbalance data is a big difficulty with most classifier learning algorithms. However, as recent works suggest, class imbalances are not in themselves a problem, and degradation in performance is often correlated with certain variables relevant to data distribution, such as the existence in noisy and ambiguous instances in the adjacent class boundaries. A variety of solutions to addressing data imbalances have been proposed recently, over-sampling, down-sampling, and ensemble approach. We have presented the various challenges that occur with data imbalances in multiclass classification and solutions in dealing with these challenges. The paper has also shown a comparison of the performances of various machine learning models with imbalanced data and data balances using sampling and ensemble techniques. From the result, i t’s clear that the performance of Random Forest classifier with data balances using the over-sampling technique SMOTE is best in terms of precision, recall, F-1, and accuracy. From the ensemble classifiers, the Balanced Bagging classifier has shown similar results as of the Random Forest classifier with SMOTE. Random forest classifier's accuracy, however, was 100% and it was 99% with the Balanced Bagging classifier.
Investigation of Eye-Tracking Scan Path as a Biomarker for Autism Screening Using Machine Learning Algorithms

Autism spectrum disorder is a group of disorders marked by difficulties with social skills, repetitive activities, speech, and nonverbal communication. Deficits in paying attention to, and processing, social stimuli are common for children with autism spectrum disorders. It is uncertain whether eye-tracking technologies can assist in establishing an early biomarker of autism based on the children’s atypical visual preference patterns. In this study, we used machine learning methods to test the applicability of eye-tracking data in children to aid in the early screening of autism. We looked into the effectiveness of various machine learning techniques to discover the best model for predicting autism using visualized eye-tracking scan path images. We adopted three traditional machine learning models and a deep neural network classifier to run experimental trials. This study employed a publicly available dataset of 547 graphical eye-tracking scan paths from 328 typically developing and 219 autistic children. We used image augmentation to populate the dataset to prevent the model from overfitting. The deep neural network model outperformed typical machine learning approaches on the populated dataset, with 97% AUC, 93.28% sensitivity, 91.38% specificity, 94.46% NPV, and 90.06% PPV (fivefold cross-validated). The findings strongly suggest that eye-tracking data help clinicians for a quick and reliable autism screening.
A Prognostic Nomogram via Competing Risk Model with Patterns of Extracranial Metastasis in Elderly NSCLC Patients with Synchronous Brain-metastasis: A Large Population-based Study

Introduction: To determine whether the patterns of extracranial metastasis (ECMs) provide supplementary prognositc information to DS-GPA in elderly NSCLC patients with synchronous BM. Methods: This study included 4974 NSCLC patients with initial BM diagnosed from 2010 to 2015 using the Surveillance Epidemiology and End Results (SEER) program. Patients were divided randomly into training and hold-out test sets. Patterns of ECMs were established based on the difference of survival via competing risk analysis in the training set. A nomogram prediction of 6-month, 12-month, and 18-month disease-specific survival (DSS) was built using independent prognostic factors. Results: Three patterns of ECM were recognized: MA (neither liver, bone, nor lung involvement), MB (without liver involvement), and MC (with liver involvement). Comparing MA, MB and MC showed significant correlation to survival (SHR, 1.126, 95% CI, 1.053-1.205, P<0.001; SHR, 1.46, 95% CI, 1.339-1.592, P<0.001, respectively). In the hold-out test set, the AUC of the ROC curve for the 6-month DSS prediction reached 0.778, whereas reaching 0.757 in the training set. The calibration curves did not deviate from the reference line. Decision curve analyses revealed the net benefit of the nomogram for clinical utility. Conclusions: These results help clinicians make decisions for brain-metastatic NSCLC in the era of precision therapy. The risk stratification of extracranial involvements indicates differential treatment for elderly NSCLC patients with synchronous brain-metastasis.
Selenium-Based Fluorescence Probes for the Detection of Bioactive Molecules

Chemistry of organoselenium reagents have now become an important tool of synthetic organic and medicinal chemistry. These reagents activate the olefinic double bonds and used to archive the number of organic transformations under mild reaction conditions. A number of organoselenium compounds have been identified as potent oxidants. Recently, various organoselenium species have been employed as chemical sensors for detecting toxic metals. Moreover, a number of selenium-based fluorescent probes have been developed for detecting harmful peroxides and ROS. In this review article, the synthesis of selenium-based fluorescent probes will be covered including their application in the detection of toxic metals and harmful peroxides including ROS.
The microbiota is a potential mediator of the crosstalk between γδ T cells and tumors

γδ T cells are one of the immune cell types that express antigen receptors. γδ T cells are able to recognize pathogens or cancer cells independently of human leukocyte antigen restriction, which is an important feature of αβ T cells. Therefore, γδ T cells are considered the bridge between innate and adaptive immunity. These cells exhibit important roles in immune surveillance, exert immune defense against tumors and have become promising effector cells for cancer immunotherapy. However, in particular circumstances, the tumor microenvironment seems to render γδ T cells immunosuppressive and even tumor-promoting, emphasizing the importance of regulating γδ T functions in realizing their translation into practical cancer immunotherapy. In recent years, increasing evidence has demonstrated that the intratumoral and peritumoral microbiota can have complex effects on tumor immunology. Thus, understanding the role of microbiota in the crosstalk between γδ T cells and tumors will provide insights for developing adjuvant immunotherapy with precise regulation of tumor-related microbiota. In the present review, the effects of microbiota on γδ T cell receptor repertoire and the roles of microbiota in some common tumors will be discussed, with implications for future cancer therapy.
Online pair-programming: elementary school children learning scratch together online

Abstract The COVID-19 pandemic raised the need to examine online learning methods also in young children. This study examined elementary school children’s performance and attitudes during and toward an online programming learning activity utilizing the pair-programming Agile method that may foster 21st-century skills, including collaboration and computational thinking. Forty 4th–6th grade children with basic programming knowledge of Scratch were randomly assigned to either a pair-programming or solo-programming condition. Overall, children in both conditions enjoyed the online learning activity and completed it successfully. In particular, pair-programming seemed to entail an extra benefit to girls who generally preferred working in pairs. Nevertheless, children in the pair condition took longer to complete all tasks, perceived the third task, which was completed individually, as more difficult, and were less active when their partner was more competent. Implications for post-COVID-19 learning are discussed.
DESIGN AND ANALYSIS OF A COMPACT UWB-MIMO ANTENNA WITH FOUR NOTCHED BANDS

In the paper, a very compact UWB-MIMO antenna with four rejected bands property is introduced and investigated. With a T-shape stepped stub on back ground, impedance bandwidth of 3–11GHz and isolation of −15 dB are achieved. By etching four pairs of symmetrical L-formed slots into the radiators, four bands are isolated. With only a size of 21mm × 27mm, the proposed UWBMIMO antenna system has low port coupling of −15 dB and wide working bandwidth of 3–11GHz (S11 ≤ −10 dB or VSWR ≤ 2) except 3.5GHz WiMAX band, 5.3GHz lower frequency band of WLAN, 5.8GHz upper frequency band of WLAN, and 7.4GHz X-band. Moreover, other characteristics, such as radiation patterns, antenna gain, antenna efficiency, and ECC (envelope correlation coefficient) are also studied.
Governing individuals’ imaginaries and conduct in personal finance: The mobilization of emotions in financial education

Today’s regime of financialized capitalism requires individuals to engage with financial products and services to ensure their financial security and welfare. Within this regime, institutional actors formulate and communicate imaginaries of the future that prompt individuals to embrace particular financial logics, understandings, and practices in managing their personal finance. Financial literacy and education is an important institutional field where such imaginaries are formulated and communicated to the public. This article examines the notions and themes articulated in programs of financial education currently conducted by state and non-state organizations in Israel, considering the ways in which proper conduct in key financial activities (debt and credit, saving and investment, and insurance) is defined, explained, and justified. We argue that, replete with explicit and implicit references to emotions and emotional states associated with practices of everyday finance, these programs mobilize them to govern individuals’ imaginaries of the future and financial conduct according to the model of the desired responsible financial subject. This emotional dimension represents a significant component in the cultural political economy of the constitution of financial subjectivities and the culture of financialization, that naturalizes the behavioral and dispositional requirements and demands that everyday finance poses to the general public.
Torque Limiters for Aerospace Actuator Application

Safety and reliability of electrical actuators are essential for success of all electric and more electric aircrafts (MEA). Torque limiters improve the reliability of electromechanical actuators (EMA) by restricting the amount of force experienced by the actuator drive train components. If transmitted torque in the shaft exceeds a limit, it gives way in a controlled manner. This protects the actuator from potential failure and jamming. In this paper, different types of existing torque limiters are investigated for their suitability in aerospace EMA application and further integration within the electric motor. They classified based on the torque transmission mechanism and each type is described in detail. Operating principle and basic characteristics are reported. Comparative evaluation of commercially available devices is presented. It is found that those based on friction based and permanent magnet are most suitable due to their good torque density, reliability and high speed capability. Further, based on the characteristics, integration of torque limiter within the actuator motor is investigated in this paper. An example actuator motor is considered for integration. Different integration options suitable for the different types of torque limiting devices are described. Reduction in overall volume is shown for the integration options. Such integration can lead to improved reliability as well as higher power density resulting in next-generation actuator electrical drives for MEA.
WHAT DRIVES PERSISTENTLY HIGH INFLATIONARY PRESSURES IN VIETNAM? SOME EVIDENCE FROM THE NEW KEYNESIAN CURVE FRAMEWORK

In this study, we revisit the inflation process in Vietnam through the New Keynesian Phillips Curve (NKPC) model. We use monthly and quarterly data frequencies to track the forces driving inflationary pressures up to a quarter. Interest rate, an important determinant of inflation, is often found to give theoretically inconsistent result. Hence, we examine different interest rates, including, the central bank policy rate, lending interest rate and one-month interbank interest rates. Further, there is no unified approach to measuring the output gap – an important variable of the model - in the literature which may affect the results. Therefore, in this study, output gap is measured using two different approaches, namely, the linear trend model and the Hodrick-Prescott (HP) filter to see whether different measurement approaches matter for the signs and significance of this variable. Our key findings show that while the effects of interest rate vary by its type, measurement of output gap does not matter for the determination of inflation in Vietnam. What matters is whether the inflation model is quarterly or monthly. We explain the main determinants of inflation and provide some policy implications in the paper.
Clinical Significance of miR-21-5p in Predicting Occurrence and Progression of Uremic Vascular Calcification in Patients with End-Stage Renal Disease

Purpose Vascular calcification (VC) is a common complication of end-stage renal disease (ESRD). This study aimed to examine changes in the expression of miR-21-5p in ESRD patients with VC and to explore its clinical value in predicting the occurrence and progression of uremic VC. Materials and Methods 120 ESRD patients were divided into patients without VC group (n=38) and patients with VC group (n=82). All patients were followed up for 2 years to evaluate VC progression. qRT-PCR was used to detect serum miR-21-5p levels. Receiver operating characteristic curves were constructed to assess diagnostic value. Kaplan-Meier and log-rank methods were utilized to calculate associations between VC progression and risk factors. Results Serum miR-21-5p levels were significantly higher in ESRD patients with VC than in those without VC and increased progressively with increasing disease severity. Serum miR-21-5p levels were able to distinguish patients with VC from those without VC, with an area under the curve value of 0.883, a sensitivity of 81.7%, and a specificity of 84.2%. After 2 years of follow-up, miR-21-5p expression had increased in patients with worse VC severity, compared with those with stable VC severity. Patients with high miR-21-5p levels were more likely to develop more severe VC, indicating an association between miR-21-5p and VC progression (log-rank p=0.002). Multivariable Cox regression analysis suggested that serum miR-21-5p is an independent predictive factor of VC progression in ESRD patients (hazard ratio=2.064, 95% confidence interval=1.225–3.478, p=0.006). Conclusion miR-21-5p is overexpressed in the serum of ESRD patients with VC. Our results suggest that overexpression of miR-21-5p is closely associated with VC progression.
Effects of Adper™ Scotchbond™ 1 XT, Clearfil™ SE Bond 2 and Scotchbond™ Universal in Odontoblastic Activity

: This study aimed to assess in vitro cytotoxicity for Adper™ Scotchbond™ 1 XT (SB1), Clearﬁl™ SE Bond 2 (CSE) and Scotchbond™ Universal (SBU), using MDPC-23 cell cultures. The metabolic activity, protein content, cell death types and cellular morphology were evaluated. All extracts determined a signiﬁcant reduction in cell metabolism and viability. CSE extracts signiﬁcantly reduced cell’s metabolic activity at its higher concentrations (50% and 100%). All adhesives determined a reduction in the number of viable cells. Changes were dependent on the adhesive, concentration and incubation time. CSE was the most cytotoxic and showed a higher degree of reactivity. and investigation, and and data and writing—
Efficient Spread Betting Markets: A Literature Review

Are simple trading strategies profitable? It is a question that has been on the minds of academics and practitioners for decades. In this paper, we review the longstanding literature on trading strategies in spread betting (also known as handicap betting), a popular sports betting microstructure. We review over 600 strategy implementations and find that market efficiency and systematic misperceptions are not mutually exclusive per se. Predictable glitches occur, but they are too small to be profitably exploited which is consistent with efficient markets. Furthermore, while controlling for data mining issues is becoming mainstream in finance, it has not yet made its way into this literature. We provide evidence that the hurdle rate of |z| > 3 which has been put forward in the broader finance literature should also be used in betting market research.
Efficacy of Telemedicine Utilization for Cardiac Outpatients' Care during the Pandemic of COVID-19: A Large Center Experience in the Wave of the Pandemic

Introduction Synchronous telemedicine using teleconferencing may play a role in clinical care. In a tertiary care center, video conferencing-enhanced virtual clinics were established via a new application platform. They were introduced during COVID-19 pandemic to connect patients to trained health-care providers via a secured line. While maintaining patients' privacy, they were theorized to offer effective communications and continuous clinical care. In this cross-sectional cohort study, we ought to examine the impact of service and the assistance they may offer to cardiac patients in the outpatient setup. Methods A prospective cohort study looking at all video-conferencing virtual clinics' visits during the pandemic with primary focus on cardiac outpatient clinic, addressing primary endpoints of need for admission or emergency visits from cardiac demises during the pandemic and secondary endpoint of patient satisfaction based on patients' experiences. Results A total of 6000 live care video-based chats were made over 10 months period from March 10th, 2020, to January 30th, 2021, among which 277 patients were evaluated in the virtual cardiac clinic, of these 193 (69.7%) were males, with mean age of 48 ± 15.60 (22.3%), patients were requested to present to clinic for further evaluation and testing, 20 (7.2%) patients were asked to visit the emergency room, of whom 8 (2.8%) patients were hospitalized. All 8 were admitted for high-risk findings that require immediate medical attention, 4/8 underwent cardiac catheterization, mean duration of admission was 2 ± 1 days. When compared to regular walk-in care, there was a statistical difference in admission rate and emergency visits p = 0.001 and p = 0.0001, respectively, both were statistically higher in the virtual clinic. The satisfaction rate in a 5-scale grading system was 97% of 4 and above recommending the continuation of the service beyond pandemic time. Conclusions Video-enhanced virtual cardiology clinic works safely and efficiently during COVID-19 pandemic with a difference in admission rate and ER visits when compared to walk-in clinic. It can be used during nonpandemic time to reduce load on hospital and clinic crowdedness. It also decreases the chances of COVID-19 transmission indirectly by reenforcing physical distance.
Beep4Me: Automatic Ticket Validation to Support Fare Clearing and Service Planning

An integrated transport service fare system, supported by an agreement for ticket revenue sharing among service providers, is an essential component to improve the experience of the users who can find single tickets for the integrated transport services they look for. A challenge is to find a model to share the revenue which all providers agree on. A solution is to adopt data-driven approaches where user-generated data are collected to extract information on the extent each transport service was used. This is consistently used. However, it suffers from incomplete data, as not all users always validate their ticket when checking out or when switching lines. We studied all technologies available to support automatic ticket validation in order to record when the users access and exit each service line. The contributions of this work are the following: we give an in-depth description of the inner workings of this novel approach describing how we take advantage of each technology; we present the developed solution (Beep4Me), which adds new functionalities to an existing mobile ticketing platform; and we describe our testing framework, which includes most cases users might encounter during a trip. Our results demonstrate how it is possible to collect key data related to validations which can be used first for clearing purposes and then for network planning/fleet optimization.
An efficient high-power femtosecond laser based on periodic-layered-Kerr media nonlinear compression and a Yb:YAG regenerative amplifier

Abstract We demonstrate an efficient ultrafast source with 195 fs pulse duration, 54 W average power at 200 kHz repetition rate and near diffraction-limited beam quality. The compact setup incorporates a thin-disk Yb:YAG regenerative amplifier (RA) and a subsequent nonlinear pulse compression stage with periodic-layered Kerr media (PLKM), which is one of the multiple-thin-solid-plate schemes based on nonlinear resonator theory. In virtue of the formation of quasi-stationary spatial soliton in PLKM, the near diffraction-limited beam quality of the RA remained almost undisturbed after post-compression. The nonlinear pulse compression module is simple and efficient with a transmission of 96%. To the best our knowledge, for pulse energy over 200 μJ, this is the highest output power reported for the multiple-thin-solid-plate scheme. This source manifests an economical combination to mitigate the bandwidth limitations of Yb-based high-power chirped pulse amplifiers.
Novel Motor-Sparing Ultrasound-Guided Neural Injection in Severe Carpal Tunnel Syndrome: A Comparison of Four Injectates

Nerve hydrodissection uses fluid injection under pressure to selectively separate nerves from areas of suspected entrapment; this procedure is increasingly viewed as potentially useful in treating carpal tunnel syndrome (CTS). The usage of normal saline (NS), 5% dextrose water (D5W), platelet-rich plasma (PRP), and hyaluronic acid (HA) as primary injectates for hydrodissection without an anesthetic can limit anesthetic-related toxicity and preserve the motor functions of the median nerve. Here, we describe a novel motor-sparing neural injection and compare the effect of these four injectates for severe CTS. We retrospectively reviewed the outcomes of 61 severe CTS cases after a single neural injection with NS, D5W, PRP, or HA. Outcomes were evaluated on the 1st and 6th months postinjection, including the Boston Carpal Tunnel Questionnaire (BCTQ) scores and the nerve cross-sectional area (CSA). The results revealed that PRP, D5W, and HA were more efficient than NS at all measured time points (p < 0.05), except for CSA at the 1st month between the NS and D5W groups. Single-injections of PRP and D5W seemed more effective than that of HA within 6 months postinjection for symptom and functional improvement (6th-month BCTQ-symptom, D5W vs. HA, p = 0.047; 1st-month BCTQ-symptom, PRP vs. HA, p = 0.018; 1st- and 6th-month BCTQ-function, D5W vs. HA, p = 0.002 and 0.016, respectively; 1st-month BCTQ-function, PRP vs. HA, p < 0.001). For reducing CSA, PRP and HA seemed more effective than D5W (HA > PRP > D5W on the 1st month and HA vs. D5W, p = 0.001; PRP > HA > D5W on the 6th month and PRP vs. D5W, p = 0.012).