Miracle-dz/UniFAR-FTUs huggingface dataset:
Determinants of the choice of a big four auditor in the Vietnamese Stock Market

Article history: Received May 15 2020 Received in revised format May 16 2020 Accepted June 29 2020 Available online June 29 2020 The study was conducted to examine the determinants on the choice of a Big Four auditor of listed firms in the Vietnamese stock market. Data were hand-collected from 511 non-financial firms in the period 2015 – 2017. The research results show that ownership concentration and foreign ownership had a positive significant impact on the choice of a high-quality Big Four auditor. Meanwhile, board size was negatively associated with the selection of large auditing firms. However, there was no statistical evidence on the effect of the proportion of independent directors and CEO duality on the likelihood of choosing a Big Four auditor. by the authors; licensee Growing Science, Canada 20 © 20
Performance Analysis and Optimization of Bidirectional Overlay Cognitive Radio Networks With Hybrid-SWIPT

This paper considers a cooperative cognitive radio network with two primary users (PUs), and two secondary users (SUs) that enables two-way communications of primary, and secondary systems in conjunction with non-linear energy harvesting based simultaneous wireless information, and power transfer (SWIPT). With the considered network, SUs are able to realize their communications over the licensed spectrum while extending relay assistance to the PUs. The overall bidirectional end-to-end transmission takes place in four phases, which include both energy harvesting (EH), and information transfer. A non-linear energy harvester with a hybrid SWIPT scheme is adopted in which both power-splitting, and time-switching EH techniques are used. The SUs aid in relay cooperation by performing an amplify-and-forward operation, whereas selection combining technique is adopted at the PUs to extract the intended signal from multiple received signals broadcasted by the SUs. Accurate outage probability expressions for the primary, and secondary links are derived under the Nakagami-$m$ fading environment. Further, the system behavior is analyzed with respect to achievable system throughput, and energy efficiency. Since the performance of the considered system is strongly affected by the spectrum sharing factor, and hybrid SWIPT parameters, particle swarm optimization is implemented to optimize the system parameters so as to maximize the system throughput, and energy efficiency. Simulation results are provided to corroborate the performance analysis, and give useful insights into the system behavior concerning various system/channel parameters.
Optimal Relay Placement in Magnetic Induction-Based Internet of Underwater Things

The advances in developing the Internet of Underwater Things (IoUT) can lead to numerous applications, namely, environmental monitoring, underwater navigation, and surveillance. Magnetic Induction (MI) is a promising communication solution for IoUT networks. In this article, we focus on a deep-ocean monitoring network, where the underwater relays communicate using MI induction. Placement of the relays in such a system is an exciting and challenging task. Therefore, we propose an optimal relay placement solution for relays in MI-based IoUT networks to improve network throughput. First, we formulate the relay placement problem as a non-convex optimization problem. Then, we propose a global optimization technique based on Reverse Convex Programming (RCP) to solve the non-convex function. Finally, we compare the results of the proposed scheme with the uniform deployment to show its effectiveness.
Augmenting Medical Diagnosis Decisions? An Investigation into Physicians' Decision-Making Process with Artificial Intelligence

Systems based on artificial intelligence (AI) increasingly support physicians in diagnostic decisions, but they are not without errors and biases. Failure to detect those may result in wrong diagnoses and medical errors. Compared with rule-based systems, however, these systems are less transparent and their errors less predictable. Thus, it is difficult, yet critical, for physicians to carefully evaluate AI advice. This study uncovers the cognitive challenges that medical decision makers face when they receive potentially incorrect advice from AI-based diagnosis systems and must decide whether to follow or reject it. In experiments with 68 novice and 12 experienced physicians, novice physicians with and without clinical experience as well as experienced radiologists made more inaccurate diagnosis decisions when provided with incorrect AI advice than without advice at all. We elicit five decision-making patterns and show that wrong diagnostic decisions often result from shortcomings in utilizing metacognitions related to decision makers’ own reasoning (self-monitoring) and metacognitions related to the AI-based system (system monitoring). As a result, physicians fall for decisions based on beliefs rather than actual data or engage in unsuitably superficial evaluation of the AI advice. Our study has implications for the training of physicians and spotlights the crucial role of human actors in compensating for AI errors.
Leveraging the light-matter interaction in angle-resolved photoemission spectroscopy

The light-matter interaction is central to the photoemission process, with an ultraviolet photon providing the necessary impulse required to eject those electrons which we collect in an effort to understand the electronic structure of matter. As such, selection rules impose constraints on those electronic orbits to which one is sensitive. Photoemission-based techniques then present an opportunity to access information beyond spectroscopic characterization of a material’s level structure; an orbital description of the underlying wavefunctions is also viable. We present here a numerical scheme within which such information can be garnered, with specific application to several experiments on candidate materials. The Fe-based superconductors are an ideal platform for application of this methodology. The electronic structure is characterized by a large number of closely spaced, moderately correlated states. The competition and cooperation between several competing energy scales pose a considerable challenge for both theory and experiment. The unique sensitivity to both spin and orbital degrees of freedom which photoemission provides therefore allow for a comprehensive exploration of the various energy scales in these compounds. Taking advantage of this sensitivity, we have mapped the momentum and energy dependence of spin-orbit entanglement in representative compounds, FeSe and LiFeAs. Despite the surface sensitivity which inhibits access to the crystal bulk in photoemission, there is a strong inclination to assert a correspondence between the bulk electronic structure, and that measured experimentally, a contentious claim which is frequently the cause of misinterpretation. We explore the surface issue in detail, and discover an interference mechanism which provides justification for the unanticipated success of valence-band photoemission in quasi two-dimensional mate-
A Quantitative Resilience Measure Framework for Power Systems Against Wide-Area Extreme Events

A framework for quantitative evaluation of the power system resilience considering multimicrogids effects is proposed in this article. The main contribution of the proposed approach is that it incorporates various features underlined in the concept of the power system resilience, such as loss of load probability, expected demand not supplied, system fragility, system recovery difficulties, and system adaption ability after experiencing a destructive event. In addition to the power system aspects, the proposed resilience framework employs the type and severity of natural disasters to achieve realistic results. To model the impact of multiple-microgrids, at first, the discrete-time multistate transition model of the power system under an extreme event is obtained. Then the probability of system states (normal, microgrid, and emergency) is calculated using the time-independent transition matrix and according to the time-homogeneous Markov chain. The effectiveness of the proposed method is tested on the IEEE 30-bus test case and real electricity network of Great Britain in five episodes each with 2000 scenarios.
Spatial distribution, exposure, and potential health risk assessment from nitrate in drinking water from semi-arid region of South India

Abstract Elevated nitrate concentration in groundwater is a worldwide problem. Continuous exposure to high levels of nitrate in groundwater may cause adverse health effects among residents who use groundwater for consumption. Therefore, this study was conducted to identify the nitrate distribution and its potential health risk assessment from semi-arid region of Peddavagu in Central Telangana (PCT), South India. Groundwater samples were collected from thirty five locations and analyzed for nitrate and other water quality parameters. Nitrate (NO3-) in groundwater was observed to vary from 17 to 120 mg/L, with a mean of 58.74 mg/L. About 57% of samples exceeded the maximum acceptable limit of Indian drinking water standard. About, 40% of groundwater samples drinking water quality index (DWQI) is good, while 60% of groundwater falls in poor quality for drinking purposes. Health risk maps were created based on hazard quotient to quantify the potential health risk of the residents using US Environmental Protection Agency (US EPA) health risk assessment model. Health risk assessment revealed that mean total hazard index (HItotal) for men, women, and children were found as 1.42E + 00, 1.67E + 00, and 1.95E + 00, respectively. Results exhibited that children are at high health risk than men and women in the PCT. Further, the human exposure to the NO3- contaminated water was above the critical limit of non-carcinogenic risk.
Separate aromatic compounds by forming adducts with thiourea : how to select the inductor

This thesis constitutes a framework from which a compound may be selected that is capable of inducing aromatic compounds into forming adducts with thiourea. An aromatic compound which will form an adduct with thiourea without the presence of an inductor was discovered by the author. This discovery led to the development of a new theory on hydrogen bonding. This theory consists of a weak hydrogen bond contact between a methyl group in 1,2,4-trimethylbenzene and a sulfur atom in thiourea. Also, a hydrogen bond contact was recognized between a chlorine atom in the isomers of trichlorobenzene and an N-H group in thiourea. A crystallographic structure analysis was completed for the adduct containing 1,2,4-trimethylbenzene. The results from this analysis support the theory on hydrogen bonding which was introduced by the author. Two distinct requirements were recognized as necessary conditions for a compound which is capable of inducing aromatic compounds into forming adducts with thiourea. An inductor must possess the ability to (1) either induce hydrogen bonding through the sulfur atom in thiourea or to accept hydrogen bonding through the N-H group, and (2) geometrically accommodate the aromatic compounds within the channels that are formed through the hydrogen bond contacts. Included in this thesis is a summary of the crystallographic data for the adduct containing 1,2,4-trimethylbenzene. Also included are recommendations for future research which will enhance the understanding of the mechanisms for the process of adduct-formation. STATEMENT OF PERMISSION TO COPY 1O In presenting this thesis in partial fulfillment of the requirements for an advanced degree at Montana State University, I agree that the Library shall make it freely available for inspection. I further agree that permission for extensive copying of this thesis for scholarly purposes may be granted by my major professor, or, in his absence, by the Director of Libraries. It is understood that any copying or publication of this thesis for financial gain shall not be allowed without my written permission.
Leveraging Scalable Data Analysis to Proactively Bolster the Anti-Phishing Ecosystem

Despite an abundance of defenses that work to protect Internet users from online threats, malicious actors continue to deploy relentless large-scale phishing aacks that target these users. Eectively mitigating phishing aacks remains a challenge for the security community due to aackers’ ability to evolve and adapt to defenses, the crossorganizational nature of the infrastructure abused for phishing, and discrepancies between theoretical and realistic anti-phishing systems. Although technical countermeasures cannot always compensate for the human weakness exploited by social engineers, maintaining a clear and up-to-date understanding of the motivation behind—and execution of—modern phishing aacks is essential to optimizing such countermeasures. In this dissertation, I analyze the state of the anti-phishing ecosystem and show that phishers use evasion techniques, including cloaking, to bypass anti-phishing mitigations in hopes of maximizing the return-on-investment of their aacks. I develop three novel, scalable data-collection and analysis frameworks to pinpoint the ecosystem vulnerabilities that sophisticated phishing websites exploit. e frameworks, which operate on realworld data and are designed for continuous deployment by anti-phishing organizations, empirically measure the robustness of industry-standard anti-phishing blacklists (PhishFarm and PhishTime) and proactively detect and map phishing aacks prior to launch (Golden Hour). Using these frameworks, I conduct a longitudinal study of blacklist performance and the rst large-scale end-to-end analysis of phishing aacks (from spamming through monetization). As a result, I thoroughly characterize modern phishing websites and identify desirable characteristics for enhanced anti-phishing systems, such as more reliable methods for the ecosystem to collectively detect phishing websites and meaningfully share the corresponding intelligence. In addition, ndings from these studies led to actionable security recommendations that were implemented by key organizations within the ecosystem to help improve the security of Internet users worldwide.
Mechanical stress compromises multicomponent efflux complexes in bacteria

Significance The field of mechanobiology examines how physical forces modulate cell physiology and has traditionally focused on eukaryotic organisms. Here we show that in bacteria, mechanical stresses can interrupt the structure and function of a molecular assembly used by Gram-negative bacteria to survive and grow in the presence of toxins. This work provides evidence that bacteria, like mammalian cells, can respond to mechanical forces through molecular complexes at the cell surface in ways that are relevant to growth. Our observations further suggest that mechanical forces may be used synergistically with other antimicrobials. Physical forces have a profound effect on growth, morphology, locomotion, and survival of organisms. At the level of individual cells, the role of mechanical forces is well recognized in eukaryotic physiology, but much less is known about prokaryotic organisms. Recent findings suggest an effect of physical forces on bacterial shape, cell division, motility, virulence, and biofilm initiation, but it remains unclear how mechanical forces applied to a bacterium are translated at the molecular level. In Gram-negative bacteria, multicomponent protein complexes can form rigid links across the cell envelope and are therefore subject to physical forces experienced by the cell. Here we manipulate tensile and shear mechanical stress in the bacterial cell envelope and use single-molecule tracking to show that octahedral shear (but not hydrostatic) stress within the cell envelope promotes disassembly of the tripartite efflux complex CusCBA, a system used by Escherichia coli to resist copper and silver toxicity. By promoting disassembly of this protein complex, mechanical forces within the cell envelope make the bacteria more susceptible to metal toxicity. These findings demonstrate that mechanical forces can inhibit the function of cell envelope protein assemblies in bacteria and suggest the possibility that other multicomponent, transenvelope efflux complexes may be sensitive to mechanical forces including complexes involved in antibiotic resistance, cell division, and translocation of outer membrane components. By modulating the function of proteins within the cell envelope, mechanical stress has the potential to regulate multiple processes required for bacterial survival and growth.
Scheduling and Power Allocation Dampens the Negative Effect of Channel Misreporting in Massive MIMO

We study the sensitivity of multi-user scheduling performance to channel magnitude misreporting in systems with massive antennas. We consider the round-robin scheduler combined with max-min and waterfilling power controls, respectively. We show that user scheduling combined with power allocation, in general, dampens the negative effect of channel misreporting compared to the purely physical layer analysis of channel misreporting without scheduling. We discover several interesting results. First, we observe a periodicity in rate-loss behavior as the number of misreporting users increases. Second, we find that the waterfilling power control is more robust to channel misreporting compared with max-min power control. Third, for homogeneous users with equal average signal-to-noise ratios (SNRs), channel underreporting is harmful but overreporting is beneficial for max-min power control; the opposite impact is found for waterfilling power control. For heterogeneous users with various average SNRs, however, both underreporting and overreporting harm the system for both power control policies, demonstrating the complex interactions across network layers due to channel misreporting.
Mining of rich iron ore deposits of complex structure under the conditions of rock pressure development

The purpose of research is to increase the ore mass extraction ratio when mining rich iron ores by changing the shape of the stope chamber, as well as to substantiate its stable parameters under the conditions of the rock pressure manifestation. Used in mines existing methodologies for determining the structural elements of mining system are based on calculated equivalent spans of outcropping the stope chambers, which have a rectangular or tent shape. For the first time using the ANSYS software package, it has been determined that the formation of a compensation chamber of quasi-parabolic shape can significantly reduce the stresses concentration around the stope block. Thus, the formation of a stope chamber of a quasi-parabolic shape makes it possible to reduce vertical stresses as compared to horizontal ones without increasing horizontal pressure. When mining the extraction block, it is proposed to form the stope chamber of a quasi-parabolic shape with geometric parameters that directly depend on the parameters of the deposit, the depth of mining, and the direction of main stresses action. Dependences have been determined of the stresses value on the depth of mining and the physical properties of rocks, as well as on the length along the strike of the ore deposit. Thus, depending on the mining depth and length along the strike, rock pressure on the stope chamber of a quasi-parabolic shape decreases under non-uniform loading. The formation of a stope chamber of a quasi-parabolic shape will increase by 1.2 – 1.5 times the volume of pure ore that is recovered from the block.
SI-POF Supporting Power-Over-Fiber in Multi-Gbit/s Transmission for In-Home Networks

We propose the integration of power-over-fiber (PoF) in home networks with multi Gbit/s data transmission based on wavelength-division-multiplexing (WDM) in step-index plastic optical fibers (SI-POF). Different powering architectures are described. The efficiencies of different components are discussed to address the maximum remote energy that can be delivered. Experimental results show the ability of the system to deliver several mW of optical power with negligible data signal quality degradation and with BER of 1 × 10−10. The potential of utilizing PoF in combination with low-loss WDM-POF to optically powering multiple devices for specific in-home applications and IoT ecosystems is discussed. A PoF scalability analysis is detailed.
DOES CEO EDUCATION INFLUENCE THE TARGET LEVERAGE AND SPEED OF ADJUSTMENT?

This study addresses the importance of unobservable factor (CEO education) as the determinant of firm leverage along two stages: target leverage and speed of adjustment towards target leverage. Based on two-step GMM system, this study sheds light on the role of CEO education in these two stages and reveals how it influences the firms total leverage, long-term leverage and short-term leverage. In the first stage, the results indicate that CEOs education is negatively associated with firms leverage that measures by total leverage and long-term leverage; meanwhile, it has a positive impact on short-term leverage. In the second stage, CEOs education is only positively related to the speed of adjustment towards short-term leverage. The reason for this is that when the cost of financial capital is high, highly educated CEOs are more entrenched to use more leverage. Furthermore, when the cost of adjustment is low, highly educated CEOs perceive that the benefits of adjusting towards target leverage exceed the costs of adjusting towards target leverage. The results are consistent with the Upper Echelons Theory regarding the reflection of the CEOs on the firms' strategic decisions. Taken together, this paper findings highlight the importance of considering unobservable factors into account when examining the firm leverage, which has received relatively little attention to date.
The Effects of COVID-19 Pandemic on Anxiety in Secondary School Students

Introduction: COVID-19 pandemic and lockdown period may have serious negative effects on education in secondary schools. The aim of the present study was to investigate the effects of COVID-19 pandemic on anxiety levels in Nigerian secondary school students. Materials and Method: One hundred thirty-five senior and 152 junior secondary school students were included in the study. Data was collected by using a survey. The GAD-7 was used to assess the anxiety level of the students against the Covid-19 pandemic. The examination anxiety was measured by using STAI. Results: Female students had more examination anxiety compared to male students. The examination anxiety was lower in isolated group than in non-isolated group. Whether they have relative with COVID-19 or not has no effect on anxiety. Most of both senior (79%) and junior (74%) students had sleep problems. They had higher anxiety than students without sleep changes in senior secondary school students. Most of both senior (71%) and junior (61%) students had different feeding changes. They had higher COVID-19 and examination anxieties than in students without feeding changes in junior secondary school students. Also, there were positive correlations between COVID-19 and examination anxieties in both senior and junior secondary school students. Conclusion: Gender is important factor for COVID-19 and examination anxieties. Isolation proses has partial effect in increase examination anxiety. Also, sleep and feeding changes or problems can increase anxiety and fear in secondary school students. These factors should be taken into consideration for new strategies in education and examination systems.