Miracle-dz/UniFAR-FTUs huggingface dataset:
Tax Enforcement and Corporate Social Responsibility: Evidence from a Natural Experiment in China

ABSTRACT This study investigates the effect of tax enforcement on corporate social responsibility (CSR) performance. By using the Third Phase of China’s Golden Tax Project as an exogenous shock to conduct a difference–in–differences estimation, we find that tax enforcement has a sizable positive effect on CSR performance, which is mainly achieved through improving the performance of corporations in fulfilling their responsibilities to their employees, suppliers, customer and consumer rights, and the environment. Our findings are robust to different specifications and endogeneity problems. One possible mechanism driving our results is that tax enforcement reduces corporate tax evasion, which further promotes CSR performance. Our results are particularly significant for firms in highly competitive industries or firms with high levels of business risk. Furthermore, the improved CSR performance influenced by tax enforcement ultimately increases the total factor productivity, market value, and shareholder returns of firms.
Unobservable Potentials to Explain Single Photon and Electron Interference

We show single photon and electron interferences can be calculated without quantum-superposition states by using tensor form (covariant quantization). From the analysis results, the scalar potential which correspond to an indefinite metric vector forms an oscillatory field and causes the interferences. The results clarify the concept of quantum-superposition states is not required for the description of the interference, which leads to an improved understanding of the uncertainty principle and resolution of paradox of reduction of the wave packet, elimination of infinite zero-point energy and derivation of spontaneous symmetry breaking. The results conclude Quantum theory is a kind of deterministic physics without "probabilistic interpretation".
Providing a Roadmap for Future Research Agenda: A Bibliometric Literature Review of Sustainability Performance Reporting (SPR)

The concept of sustainability reporting is now an essential tool through which organisations demonstrate accountability to their stakeholders. The increasing market pressure coupled with the awareness of the consequences of organisations’ activities suggests the need for organisations to report their sustainability credentials. Sustainability performance reports should provide adequate information on organisations’ social, economic, and environmental performance. However, the current process through which organisations communicate their sustainability performance to stakeholders is questionable and remains a significant concern. This study assessed the current state and direction of research on sustainability performance reporting by conducting a bibliometric literature review of peer-reviewed studies on sustainability performance reporting published between 1987 and 2022. The findings highlight the misconceptions between sustainability and CSR when reporting organisations’ sustainability performance. Furthermore, businesses and scholars prioritise reporting instead of communication with stakeholders. The observed lack of engagement with stakeholders indicates that the reported performance may not reflect the impact of business activities on the three dimensions of sustainability. Rather than adopting a one-way information dissemination approach, this study concludes that the desired performance can only be achieved through two-way communication with stakeholders.
Real- Time EEG Data Processing Using Independent Component Analysis (ICA)

The paper proposes a real-time processing system for multichannel electroencephalogram (EEG) signals. The processing algorithm is based on independent component analysis. The algorithm is initially tested and simulated offline for functionality and performance verification. A Simulink discrete real-time design is then modeled based on the processing algorithm. Finally, we discuss some of the systems limitations as well as several options for translating the designed Simulink model to a real-time processing system.
Impact of Political Violence on People in Istanbul: The Role of Resilience in Posttraumatic Stress and Psychological Health

ABSTRACT The study investigated the effects of political violence on people exposed to terrorist attacks in Istanbul between 2015 and 2016, and the role of resilience in both psychological stress and posttraumatic stress. The data was collected from 172 people using the Resilience Scale for Adults (RSA), General Health Questionnaire-12 (GHQ-12), and Traumatic Stress Symptoms Checklist (TSSC). Only 25.9% of the participants who were directly exposed to terrorist attacks and 13.8%who were exposed indirectly, had probable posttraumatic stress disorder (PTSD). The frequency of probable PTSD was higher in participants who were present at the explosion area during the attack, provided either physical or emotional aid to a terror survivor, and who escaped from the attacks by chance. “Perception of future” and “perception of self” had a negative correlation with both TSSC PTSD scores and psychological stress scores. “Perception of future,” “family coherence,” “perception of self,” and “social resources” were negatively correlated with TSSC PTSD scores. In addition, “perception of future” and “perception of self” were negatively correlated with psychological stress scores. The psychological impact of ongoing exposure to violence is destructive; in a context of persistent violence, intervention strategies focused on resilience are essential for patient care.
IoT Multi-Vector Cyberattack Detection Based on Machine Learning Algorithms: Traffic Features Analysis, Experiments, and Efficiency

Cybersecurity is a common Internet of Things security challenge. The lack of security in IoT devices has led to a great number of devices being compromised, with threats from both inside and outside the IoT infrastructure. Attacks on the IoT infrastructure result in device hacking, data theft, financial loss, instability, or even physical damage to devices. This requires the development of new approaches to ensure high-security levels in IoT infrastructure. To solve this problem, we propose a new approach for IoT cyberattack detection based on machine learning algorithms. The core of the method involves network traffic analyses that IoT devices generate during communication. The proposed approach deals with the set of network traffic features that may indicate the presence of cyberattacks in the IoT infrastructure and compromised IoT devices. Based on the obtained features for each IoT device, the feature vectors are formed. To conclude the possible attack presence, machine learning algorithms were employed. We assessed the complexity and time of machine learning algorithm implementation considering multi-vector cyberattacks on IoT infrastructure. Experiments were conducted to approve the method’s efficiency. The results demonstrated that the network traffic feature-based approach allows the detection of multi-vector cyberattacks with high efficiency.
Nanoscale junctionless devices using ringFET structure on bulk silicon substrate

ABSTRACT In this article, we have demonstrated junctionless operation in ringFET structure on <100> silicon bulk substrate using three-dimensional numerical simulations, for channel lengths below 100 nm. On current, OFF/leakage current, ON to OFF current ratio, transconductance, threshold voltage, subthreshold slope, output resistance and unity gain frequency of the device are extracted. Channel length, drain radius, epi-layer thickness and epi-layer doping of the device are varied to investigate their impact on the device performance, using the above performance metrics. A brief comparison with the junction-based ringFET device is also provided.
High-fidelity aeroelastic analyses of wind turbines in complex terrain: fluid–structure interaction and aerodynamic modeling

Abstract. This paper shows high-fidelity fluid–structure interaction (FSI) studies applied to the research wind turbine of the WINSENT (Wind Science and Engineering in Complex Terrain) project. In this project, two research wind turbines are going to be erected in the south of Germany in the WindForS complex-terrain test field. The FSI is obtained by coupling the CFD URANS–DES code FLOWer and the multiphysics FEM solver Kratos Multiphysics, in which both beam and shell structural elements can be chosen to model the turbine. The two codes are coupled in both an explicit and an implicit way. The different modeling approaches strongly differ with respect to computational resources, and therefore the advantages of their higher accuracy must be correlated with the respective additional computational costs. The presented FSI coupling method has been applied firstly to a single-blade model of the turbine under standard uniform inflow conditions. It could be concluded that for such a small turbine, in uniform conditions a beam model is sufficient to correctly build the blade deformations. Afterwards, the aerodynamic complexity has been increased considering the full turbine with turbulent inflow conditions generated from real field data, in both flat and complex terrains. It is shown that in these cases a higher structural fidelity is necessary. The effects of aeroelasticity are then shown on the phase-averaged blade loads, showing that using the same inflow turbulence, a flat terrain is mostly influenced by the shear, while the complex terrain is mostly affected by low-velocity structures generated by the forest. Finally, the impact of aeroelasticity and turbulence on the damage equivalent loading (DEL) is discussed, showing that flexibility reduces the DEL in the case of turbulent inflow, acting as a damper that breaks larger cycles into smaller ones.
Corporate social responsibility and stock price crash risk: does analyst coverage matter?

ABSTRACT The debate about whether corporate social responsibility (CSR) and analyst coverage facilitate financial transparency is still open among academics and practitioners to date. Drawing from the information asymmetry view, this paper aims to investigate the impact of CSR on stock price crash risk, and to examine the moderating effect of analyst coverage on the ‘CSR – crash risk’ nexus. Using a sample of 8037 firm-year observations from Chinese-listed firms between 2010 and 2018, we find that CSR is negatively associated with crash risk. Analyst coverage cannot catalyse the positive role of CSR in reducing financial opacity, and thereby weakens the negative association between CSR and stock price crash risk. This implies that analysts fail to sufficiently disseminate firm-specific information, which in turn aggravates the information gap between insiders and outside investors. Our results remain robust after considering potential endogeneity and alternative CSR measures. The current study advances the understanding of ‘CSR – crash risk’ relationship with the moderating effect of analyst coverage. We also provide important references for investors and policymakers to better understand abnormal stock price fluctuations.
Adolescent Knowledge, Attitudes and Practices of Healthy Eating: Findings of Qualitative Interviews among Hong Kong Families

To tackle unhealthy eating among adolescents, it is crucial to understand the dietary knowledge, attitudes, and practices (KAP) on which adolescent eating habits are based. This qualitative study identifies the gaps in KAP by exploring what Chinese adolescents know, perceive, and practice regarding healthy eating to better inform targeted interventions for this important health problem. Parent–adolescent dyads were purposively sampled based on, for example, the dietary intake, age, and gender of the adolescent and household income, and each completed a 30 to 60 min interview. Twelve themes were synthesized: knowledge: (1) dietary recommendations, (2) health outcomes of healthy eating, (3) nutrition content in food, and (4) access to healthy meals; attitudes: (5) outcome expectation for healthy eating, (6) food preferences, and (7) self-efficacy regarding adopting healthy eating; and practices: (8) going grocery shopping for healthy food, (9) eating home-prepared meals. (10) eating out in restaurants or consuming takeaway food, (11) fruit and vegetable consumption, and (12) snacking, perceived unhealthy eating to be low risk, made unhealthy choices regarding snacking and eating out, and had insufficient fruit and vegetable intake. Programs should emphasize the positive short-term health outcomes of healthy eating and empower adolescents to acquire food preparation skills to sustain healthy eating habits.
Atezolizumab plus Bevacizumab versus Sorafenib for Unresectable Hepatocellular Carcinoma: Results from Older Adults Enrolled in the IMbrave150 Randomized Clinical Trial

Introduction: The efficacy of systemic first-line treatments in older adults with unresectable hepatocellular carcinoma (HCC) has not been well-studied. We compared the safety and efficacy of atezolizumab plus bevacizumab versus sorafenib as a first-line treatment in younger versus older patients with unresectable HCC. Methods: This global, phase 3, open-label, randomized clinical trial (IMbrave150) recruited patients aged ≥18 years with locally advanced metastatic or unresectable HCC, an Eastern Cooperative Oncology Group performance status score of 0 or 1, and Child-Pugh class A liver function who had not previously received systemic therapy for liver cancer. Patients received either 1,200 mg atezolizumab plus 15 mg/kg bevacizumab intravenously every 3 weeks or 400 mg sorafenib orally twice daily until loss of clinical benefit or unacceptable toxicity. Primary endpoints were overall survival (OS) and progression-free survival (PFS). Secondary outcomes were the incidence of adverse events and time to deterioration of patient-reported outcomes (PROs). This subgroup analysis evaluated safety and efficacy endpoints in patients <65 years, ≥65 to <75 years, and ≥75 years. Results: Of 501 patients, 165 patients were randomized to sorafenib and 336 were randomized to atezolizumab plus bevacizumab (175 patients <65 years; 106 patients ≥65 to <75 years; 55 patients ≥75 years). Across all age groups, patients receiving atezolizumab plus bevacizumab had longer median OS (<65: 18.0 vs. 12.2 months [HR, 0.57; 95% CI: 0.40–0.82]; ≥65 to <75: 19.4 vs. 14.9 months [HR, 0.80; 95% CI: 0.52–1.23]; ≥75: 24.0 vs. 18.0 months [HR, 0.72, 95% CI: 0.37–1.41]) and PFS than those receiving sorafenib. Time to deterioration for multiple PROs was delayed for patients receiving atezolizumab plus bevacizumab, including older adults. There were no clinically meaningful differences in toxicity between age groups. Conclusion: Atezolizumab plus bevacizumab is safe and effective in adults <65, ≥65 to <75, and ≥75. Treatment was well-tolerated even in elderly patients.
Human choices, slope and vegetation productivity determine patterns of traditional alpine summer grazing

Abstract Grazing behaviour influences animal productivity and the conservation of grassland ecosystem services. We used GPS tracking and remote sensing (NDVI index) to monitor the grazing patterns of lactating cows on the ‘Malga Ombretta’ summer farm (1,957 m asl) in the Dolomites, eastern Italian Alps, from 5th July to 5th August 2018. The pasture area (35 ha) was grazed by a mixed herd of Simmental and Alpine grey cows (stocking density = 0.6 LU/ha) under traditional management: each morning the farmer led the cows to graze in a selected sub-area of pasture, and during the afternoon he left them free to graze unrestricted until they returned to the barn for the night. GPS positions were collected every minute from 9 Simmental and 4 Alpine Grey cows with low milk production during the time they were outdoors. The farmer’s choice of where to drive the herd to graze in the morning determined the distances the cows walked/day, which varied from 2.0 to 8.9 km, and favoured the use of higher and steeper areas that the cows tended otherwise to avoid. When free in the afternoon, the cows selected areas with higher NDVI values than those selected by the farmer in the morning, and Alpine Grey cows used slightly higher slopes and altitudes than Simmental cows, suggesting better adaptation to mountain pastures. The study revealed highly heterogenous grazing patterns dependent on multiple factors that can be assessed at fine temporal and spatial scales using GPS and remote sensing technologies to improve grazing management. HIGHLIGHTS Daily distances walked and grazing patterns were influenced differently by the farmer’s decisions and the animals’ choices in response to environmental features. The NDVI index of vegetation productivity suggested that cows grazed more productive areas when free than when driven by the farmer. GPS tracking and remote sensing shed light on how human and animal choices regarding grazing are influenced by environmental features.
Design and Characterization of a Planar Structure Wideband Millimeter-Wave Antenna With Wide Beamwidth for Wearable Off-Body Communication Applications

This letter presents the design of a planar single-layer wideband antenna featuring wide beamwidth has well as high and stable in-band gain. The proposed antenna is a planar monopole fed by a bottom-grounded coplanar waveguide to realize wide beamwidth in both the xz- and yz-planes. Simultaneous optimization of all adjustable antenna parameters, carried out at the full-wave electromagnetic simulation level. The constructive interference of the radiated fields resulting in impedance bandwidth of more than 2 GHz, from 27 to 29 GHz. Along with a stable realized gain (>11 dBi) in the operating frequency band. The proposed antenna maintains a directional radiation pattern in the broadside direction. Merging the radiated modes of the slots and the parasitic patch elements also extends the antenna beamwidth to roughly ±35° with respect to the broadside direction. Following a detailed theoretical analysis, the antenna is validated numerically and experimentally, both in the free space and on a human volunteer chest and arm.
Crystal chemistry and Raman spectroscopy study of bennesherite, Ba2Fe2+Si2O7, and rare accessory Ba minerals from Caspar quarry, Bellerberg volcano, Germany

Abstract Barium melilite – bennesherite, Ba2Fe2+Si2O7, known only from pyrometamorphic rocks of the Hatrurim Complex in Israel, has been recognised in a carbonate–silicate xenolith from the Bellerberg volcano area in Germany. The empirical formula of the German specimen is as follows: (Ba1.32Ca0.43Sr0.23Na0.05K0.02)Σ2. 05(Fe2+0.79Ti0.06Mg0.05Al0.04Mn0.03Zn0.01)Σ0. 98Si1.97O7. The Raman spectrum of bennesherite exhibits the presence of the main vibrations related to Fe2+O4 tetrahedra and disilicate Si2O7 groups at the T1 and T2 sites, at 589 cm–1 and in the range 618–673 cm–1, respectively. Detailed spectroscopic analyses performed for bennesherite in two different and random orientations confirm the reduction of bands intensity and the number of some components in several spectral ranges. Moreover, the presence of a heavy Ba atom indicates a decrease in band frequencies compared to melilites with Ca at the X position. A single-crystal X-ray diffraction experiment, despite attempts, could not be carried out due to the poor quality and small size of the bennesherite crystals however, a combination of composition and Raman data allowed for accurate phase identification. Detailed mineralogical investigations distinguished rare Ba minerals in association with bennesherite, such as walstromite, fresnoite and celsian, along with various ferrous melilites. Some of the detected phases are described from xenoliths of the Bellerberg volcano for the first time. The uniqueness of the Bellerberg volcano mineralisation is reflected in the interaction of alkaline magma with xenoliths of different compositions, which suggests that this locality still deserves attention as a source of new and unique minerals.
Impact of a learning portfolio on reflective, clinical and communication skills in undergraduate dental students- A pilot study

Student portfolios are a collection of evidence, prepared by the student and evaluated by the faculty member to demonstrate mastery, comprehension, application, and synthesis of a given set of concepts. The purpose of this study was to investigate the effect of portfolio on student’s self-reflection, clinical competency and communication skills in daily clinical practice and to know students perception on faculty feedback. A randomized controlled, triangulation study was conducted in Melaka-Manipal Medical College with thirty consenting Year IV BDS students as participants. There was statistically significant improvement for all the outcomes tested in the portfolio group compared to traditional logbook group.
ICSI Protocol Advisor: A decision support system for infertility protocol suggestion

Intra-Cytoplasmic Sperm Injection (ICSI) is one of the most common infertility treatments in which ovarian stimulation is carried out to extract the eggs from the ovaries. There are three, short, long, and pure treatment protocols of ovarian stimulation that vary by the type of medicine, the dosage of medicine, and the treatment term. Today, physicians choose an appropriate treatment protocol based on the patient's condition, such as age, and hormonal condition. This could be a relatively subjective and inaccurate method, particularly if the physician is not highly experienced. The present study investigates whether a decision support system can propose a more objective treatment protocol based on the patients’ data and data mining methods like logistic regression, decision tree, and SVM. Such a system draws upon classification methods to propose proper treatment protocols for ICSI. Moreover, a separate module was developed to calculate the success rate of the proposed protocols. The system was tested with real data of treated patients at a Hospital in Tehran, Iran. The results showed the proposed system can predict the most proper treatment protocol with an accuracy of 81.90%. The proposed system can help inexperienced physicians to feel more confident about their advice.
Magneto-mechanical Behavior of Magnetic Shape Memory Alloy and Its Application in Hydraulic Valve Actuator

： Magnetic shape memory alloy(MSMA) has recently emerged as a new type of multifunctional material exhibiting excellent performance as fast response and large strain. With a combination of the characteristics of ordinary smart materials and conventional shape memory alloy, it is qualified for high performance actuator. Constitution equations are derived based on the magnet-strain effect of MSMA, and temperature is introduced as an influential factor to modify the model. The present equations are improved to cover the shortage of inaccuracy in calculating the strain when the material is preloaded. Experiments are conducted to explore the magnetic field induced strain, and data are applied to establish nero-network based models to build the nonlinear relations between strain, stress and other related parameters. It is shown in the results that the energy density of MSMA is 70 kJ/m 3 and energy conversion efficiency is 80%. Taking high speed on/off valve as an example, the characteristics of MSMA hydraulic valve actuator are considered. Valve design, magnetic field and fluid flow simulations are carried out. On analysis of dynamics of valve actuation system, the results show that the response frequency of the poppet valve system driven directly by MSMA can reach as high as 200 Hz, and the dynamic response time is nearly 5 ms.