Miracle-dz/UniFAR-FTUs huggingface dataset:
Photoeffects in Nonuniformly Irradiated p‐n Junctions

A theoretical basis is provided for the interpretation of photoeffects observed in nonuniformly irradiated p‐n junctions. Differential equations describing the junction photovoltage are developed through an application of the continuity and diffusion equations. Solutions of the small‐signal steady‐state photoeffect equation indicate that the effects of nonuniform irradiation become increasingly important as the ratio of the lateral to the transverse resistance increases. α, a parameter introduced in this paper and designated as the lateral‐fall off parameter, is a measure of this resistance ratio. The lateral photovoltage resulting from nonuniform irradiation can be eliminated by reverse biasing the junction into saturation. Experimental curves in agreement with the predictions of the analysis are presented.
English lexical stresses in non-native speech under adverse conditions

The Lombard effect is well documented in the literature on speech production in noise in various languages, but relevant research on non-native speech production is scarce. The present study examined the effects of noise on English lexical stresses produced by Cantonese second-language speakers of English (ESL speakers). Results show distinct patterns in maintaining lexical stress contrasts in trisyllabic words by ESL and native speakers of English. Our findings confirm the Lombard effect in ESL speech production in noise. Patterns of phonetic modifications appear language-specific, which may be attributed to ESL speakers’ limited experience in second-language communication under adverse conditions and also to influences of their first-language phonology.
Comparative Studies of HfO2, Y2O3, and CeO2 Insulators in Metal-Nd2Ti2O7 Ferroelectric-Insulator-Semiconductor Structures

High-k insulator films of HfO2, Y2O3, and CeO2, were prepared on Nd2Ti2O7 (NT) ferroelectric to form metal-ferroelectric-insulator-semiconductor structures. The NT is a candidate ferroelectric material for use in a metal-ferroelectric-insulator-semiconductor field effect transistor (FET) with low permittivity and a high coercive field. Our work involves understanding the relationships between retention property and permittivity and the insulation properties of insulator layer, including interface. HfO2 possesses a relatively low leakage current and a better retention property than Y2O3 and CeO2. The insulating property from a stable interface was found to be the most important controlling factor for the ferroelectric FET.
Particle swarm optimization - mass-spring system analogon

A concept for the optimization of nonlinear cost functionals, occurring in electrical engineering applications, using particle swarm optimization (PSO) is proposed. PSO is a stochastic optimization technique, whose stochastic behavior can be controlled very easily by one single factor. Additionally, this factor can be chosen to end up with a deterministic strategy, that does not need gradient information. The PSO concept is quite simple and easy to implement (just a few code lines are needed). In this paper, an analogy between the movement of a swarm member and a mass-spring system is developed and tested against other stochastic algorithms. It will be shown how infeasible regions in the parameter space can be treated efficiently and, finally, the particular PSO implementation is used to optimize problems occurring in electrical engineering.
Exploring GEMM Operations on Different Configurations of the Gemmini Accelerator

The General Matrix to Matrix Multiplication (GEMM) has recently been employed to improve Deep Neural Networks (DNN) performance. This paper explores GEMM operations of different matrix dimensions and dataflow options including weight stationery (WS) and output stationery (OS) on various systolic array sizes (8×8, 16×16, 32×32, and 64×64) of the Gemmini full-stack open-source DNN accelerator generator. The GEMM operation performance in a baseline Rocket CPU core is compared with two Gemmini configurations: with and without a hardware image to column (im2col) block. The different configurations with different systolic array sizes are synthesized using an FPGA device and compared in terms of hardware area, maximum frequency, and vector-less power consumption. Overall, a Gemmini configuration with a 16×16 array, a hardware im2col module, and a WS dataflow recorded the highest performance per area of 1.04×, 2.31×, and 8.84× compared with 8×8, 32×32, and 64×64 array configurations respectively.
Extensive Attention Mechanisms in Graph Neural Networks for Materials Discovery

We present our research where attention mechanism is extensively applied to various aspects of graph neural net- works for predicting materials properties. As a result, surrogate models can not only replace costly simulations for materials screening but also formulate hypotheses and insights to guide further design exploration. We predict formation energy of the Materials Project and gas adsorption of crystalline adsorbents, and demonstrate the superior performance of our graph neural networks. Moreover, attention reveals important substructures that the machine learning models deem important for a material to achieve desired target properties. Our model is based solely on standard structural input files containing atomistic descriptions of the adsorbent material candidates. We construct novel methodological extensions to match the prediction accuracy of state-of-the-art models some of which were built with hundreds of features at much higher computational cost. We show that sophisticated neural networks can obviate the need for elaborate feature engineering. Our approach can be more broadly applied to optimize gas capture processes at industrial scale.
Obfuscated Malware Detection in IoT Android Applications Using Markov Images and CNN

The threat of malware in the Internet of Things (IoT) is ever-present given that many IoT systems today rely on the Android operating system. There has been a consistent rise in Android malware recently, with new variants adopting sophisticated detection avoidance techniques, including various forms of obfuscation. Hence, there is a need to improve the effectiveness of Android malware detection as obfuscation becomes more prevalent in the wild. In this article, we present a novel approach for obfuscated malware detection in IoT Android applications based on the visualization of app executables with Markov images. The app images are trained using a convolutional neural network (CNN) to detect obfuscated malware and for the identification of the obfuscation type. We evaluate the performance of the proposed system by experimenting with four different classification models using 12000 Android applications. The CNN model created to distinguish between malware and benign apps obtained an accuracy of 99.41%. The model for identifying obfuscated malware from benign applications obtained 99.65% accuracy while the model created to identify obfuscated malware from non-obfuscated malware yielded an accuracy of 99.81%. The model for classifying obfuscated malware into 14 different obfuscation categories obtained an accuracy of 99.67%. These results show that CNN models trained from Markov images generated using application byte code can be highly effective for obfuscated malware detection and classification. Moreover, our proposed system provides a more sustainable and cost-effective method for obfuscated malware detection compared to the manual feature-engineering-based approaches that are more prevalent in the current literature.
A Survey on IoT Positioning Leveraging LPWAN, GNSS, and LEO-PNT

Location data is an important piece of information in many Internet of Things (IoT) applications. Global navigation satellite systems (GNSSs) have been established as the standard for large-scale localization. However, the rapidly increasing need to locate IoT devices in recent years has exposed several shortcomings of traditional GNSS approaches. These limitations include the weak signal propagation in indoor and dense environments, the inability to calculate or obtain a location remotely, and a high energy consumption. Therefore, several industries have shown an increasing demand for alternative and innovative positioning solutions that are more suited in an IoT context. Hence, we conduct a survey on state-of-the-art, large-scale, and energy-efficient positioning techniques for IoT applications. More specifically, we analyze the performance of terrestrial-based low power wide area network (LPWAN) techniques, novel GNSS solutions, and innovative positioning techniques leveraging low Earth orbit (LEO) satellite constellations. A comparison is made in terms of 16 dimensions, including energy consumption, positioning accuracy, coverage, and scalability. The analysis shows that interoperability between technologies is key to enable energy-efficient communication and positioning applications in the emerging market of satellite IoT.
Unraveling the Direct and Indirect Effects of Supervisory Working Alliance on Supervisory Satisfaction: The Mediating Role of Supervisee Disclosure in Supervision

This research examined the direct and indirect links of supervisory working alliance on supervisory satisfaction. Participants were 291 supervisees who had participated in individual counseling practicum courses either in undergraduate or graduate Psychological Counseling and Guidance program in Turkish universities. Data were collected using the Brief Form of the Supervisory Working Alliance Inventory (BSWAI-T), Supervisee Disclosure in Supervision Scale (SDSS), and Supervisory Satisfaction Questionnaire (SSQ). Research results indicated that supervisory working alliance made direct contributions to supervisory satisfaction. In addition, the supervisory working alliance contributed indirectly to supervisory satisfaction via supervisee disclosure in supervision. Supervisory working alliance and supervisee disclosure in supervision explained 56% of the variance in supervisory satisfaction. This study offers novel insights into the role of supervisee disclosure in supervision as an underlying mechanism that operates on the influence of supervisory working alliance on supervisory satisfaction. Implications for the supervision process and counselor training are discussed.
Data-Driven Futures of International Refugee Law

As refugee law practice enters the world of data, it is time to take stock as to what refugee law research can gain from technological developments. This article provides an outline for a computationally driven research agenda to tackle refugee status determination variations as a recalcitrant puzzle of refugee law. It first outlines how the growing field of computational law may be canvassed to conduct legal research in refugee studies at a greater empirical scale than traditional legal methods. It then turns to exemplify the empirical purchase of a data-driven approach to refugee law through an analysis of the Danish Refugee Appeal Board’s asylum case law and outlines methods for comparison with datasets from Australia, Canada, and the United States. The article concludes by addressing the data politics arising from a turn to digital methods, and how these can be confronted through insights from critical data studies and reflexive research practices.
Scaling of complex phenomena in system thermal hydraulics

A methodology is described that can be used for the extrapolation of thermal-hydraulic phenomena measured in differently scaled integral test facilities to nuclear reactor plant conditions. The use of a system code in this context is confirmed to be of fundamental importance, provided that the code's scaling capability has been demonstrated. The starting data base for the proposed study consists of the measured quantities and corresponding RELAP5/MOD2 code calculation results related to a boiling water reactor small-break loss-of-coolant accident (SBLOCA) counterpart test activity, a pressurized water reactor (PWR) natural-circulation type test activity, and a PWR SBLOCA counterpart test activity. The proof that this methodology can be used for evaluating uncertainties in predicting transient behavior in nuclear power plants is the main result of this study. Data have been obtained that give a value of the foreseeable error ranges in the provision of plant behavior in the three cases considered.
Multiscale model for turbulent flows

A model is devised for computing general turbulent flows. The model is an improvement over two-equation turbulence models in a critically important manner, that is, the new model accounts for disalignment of the Reynolds-stress-tensor and the mean-strain-rate-tensor principal axes. The improved representation of the Reynolds-stress tensor has been accomplished through the introduction of a multiscale description of the turbulence, i.e., two energy scales are used corresponding to upper and lower partitions of the turbulence energy spectrum. A novel feature of the formulation is that the differential equation for the Reynolds-stress tensor is of first order, which in effect corresponds to what can be termed an "algebraic stress model" with convective terms. As a consequence of its mathematical simplicity, the model is very efficient and easy to implement computationally. The model is applied to a wide range of turbulent flows including homogeneous turbulence, compressible and incompressible two-dimensional boundary layers, and unsteady boundary layers including periodic separation and reattachment. Comparisons with corresponding experimental data show that the model reproducesall salient features of the flows considered/Perturbation analysis of the viscous sublayer shows that integration through the sublayer can be accomplished with no special viscous modifications to the closure coefficients appearing in the model.
Zika Virus: A Systematic Review of Teratogenesis, Congenital Anomalies, and Child Mortality

Zika virus infection (ZIKV) was one of the most catastrophic epidemics. ZIKV in nonpregnant women is mild and sometimes asymptomatic. However, infection during pregnancy leads to congenital malformations in the fetus, while maternal signs of infection are preceded by a rash. The maternal-fetal infection begins with a rash that occurs early during pregnancy. The most severe pathologies were related to the first trimester of gestation, including microcephaly, musculoskeletal, genitourinary, craniofacial, ocular, and pulmonary manifestations. The prognosis may not be encouraging. Herd immunity increases CD8+ (cytotoxic T-lymphocytes) earlier and decreases in the resolution phase. However, CD4+ (T-helper cells) remains higher after infection. Recent ongoing vaccine development shows good immunity, control of the vector (Aedes mosquitoes), and treatment. ZIKV, anomalies, mortality, herd immunity, and vaccine were our main keywords. This systematic review demonstrates the teratogenesis of ZIKV in children, congenital anomalies, mortality, and a view of the future and behavior of ZIKV.
QUADRATIC TRANSFORMATIONS INVOLVING HYPERGEOMETRIC FUNCTIONS OF TWO AND HIGHER ORDER

Abstract. By applying various known summation theorems toa general transformation formula based upon Bailey’s transforma-tion theorem due to Slater, Extonhas obtained numerousand newquadratic transformations involving hypergeometric functions oforder greater than two (some of which have typographical errors). We aim at ﬁrst deriving a general quadratic transformation for-mula due to Exton and next providing a list of quadratic formulas(including the corrected forms of Exton’s results) and some moreresults. 1. Introduction and PreliminariesAs a consequence of Bailey’s transform method, Slater [4, p. 60]gave the following general hypergeometric transform(1.1)X ∞n=0 ((a)) n ((d)) n ((v)) 2n x n y n ((h)) n ((g)) n ((f)) 2n n! × U+D+V F E+F+G (u), (d)+n, (v)+2n(e), g)+n, f)+2n; x Received November 15, 2005.2000 Mathematics Subject Classiﬁcation: Primary 33C20, 33C60; Secondary33C70, 33C65.Key words and phrases: Generalized hypergeometric series p F q , Summationformulas for p F q , Quadratic transformations.
The Practice and Willingness of Women Towards Opportunistic Screening for Breast and Cervical Cancers in Sichuan Province, China: A Cross-Sectional Study

Purpose To understand the practices and willingness of Chinese women to undergo opportunistic screening for breast cancer (BC) and cervical cancer (CC). Patients and Methods From July to August 2021, a cross-sectional study of 1446 women from six cities in Sichuan Province, China, was conducted. A questionnaire was used to investigate practices, willingness, and barriers to opportunistic screening for BC and CC. Furthermore, potential factors for opportunistic screening willingness were analyzed using the chi-squared test and logistic regression. Results During their lifetime, 312 (21.6%) and 388 (26.8%) women had undergone opportunistic screening for BC and CC, respectively. There were 1069 (73.9%) women willing to accept physician-recommended screening during a medical visit, while 835 (57.7%) were willing to have a voluntary screening at a healthcare institution. The main barriers to reluctance to participate in physician-recommended and voluntary screenings were “no symptoms; hence, no need for screening” and “unwillingness or difficulty in paying screening cost”. Ethnic minorities, lower education levels, and menopause were inversely associated, whereas awareness of the screening methods and eligibility for screening were positively associated with physician-recommended and voluntary screenings (P < 0.05). Furthermore, awareness of “two-cancers” screening was positively associated with physician-recommended screening (P < 0.05). Conclusion BC and CC opportunistic screening rates in Sichuan Province were low. The willingness to undergo physician-recommended screening was high, while that towards individual initiative screening was low. Public health education should be strengthened to increase cancer prevention awareness and knowledge of cancer screening, especially for women with low education, ethnic minorities, and post-menopause, for whom tailored interventions are suggested. In addition, novel ways of sharing screening costs need to be explored.
Determination of metrological structural resolution of a CT system using the frequency response on surface structures

A novel method for the determination of the structural resolution of a computed tomography (CT) system is presented. The method uses the frequency response of the CT system while measuring the surface of an Aperiodic Spatial Frequency Standard (ASFS). The geometry of the standard allows it to investigate a broader range of possible structural resolutions using just one standard. Simulations and experiments, using CT with different acquisition parameters and a fringe projection system, show that the method is a promising alternative for determining the structural resolution of a measurement system.
A COMPARISON BETWEEN THEORETICAL AND MEASURED WAVES ABOVE A SUBMERGED RANKINE BODY

Abstract : A comparison is made of theoretical and measured wave patterns produced by a submerged Rankine body (7:1) moving at constant speed. The measurements were made for a range of Froude numbers, but for a single depth/ length ratio (1:3). Calculations were made for both the far and near fields. The former utilize the stationary phase approximation and the latter involve numerical integrations and include the local disturbance. In general, the agreement between theory and experiment is as good as the agreement between measurements taken at the same Froude number but for two different body lengths (4.5 and 9.0 feet). It is concluded from these tests that first-order wave theory predicts the shape and amplitude of the waves produced by a fully submerged body with sufficient accuracy for almost all practical purposes.
Intraperitoneal Versus Intravenous Dexmedetomidine for Postoperative Analgesia Following Laparoscopic Sleeve Gastrectomy Surgery: A prospective, Randomized Controlled trial

ABSTRACT Background Postoperative pain control is a major challenge after laparoscopic sleeve gastrectomy. We conducted this study to evaluate the efficacy of dexmedetomidine either intraperitoneal (IP) or intravenous (IV) as an adjuvant to intraperitoneal bupivacaine in patients undergoing sleeve gastrectomy. Methods A total of 105 patients were randomized in this prospective, controlled study. All patients received 40 ml bupivacaine 0.25% IP. Control group (n = 35): received 50 ml normal saline IV. IV dexmedetomidine group (n = 35): received 50 ml normal saline plus dexmedetomidine 1 µg/kg IV. IP dexmedetomidine group (n = 35): received IP dexmedetomidine 1 µg/kg plus bupivacaine 0.25%, and 50 ml normal saline IV. Time to first rescue analgesia was the primary outcome. Whereas the total consumption of tramadol and visual analog scale (VAS) were the secondary outcomes. Results The first time of rescue analgesia was prolonged in IP dexmedetomidine compared to IV dexmedetomidine and control group (P ˂ 0.0001). The total amount of rescue tramadol was lower in IP dexmedetomidine compared to IV dexmedetomidine and control group (P ˂ 0.0001). VAS was comparable between the three groups at the recovery room, 2, 4, and 24 h postoperatively, while a statistically significant difference was found at 6, 12, and 18 h postoperatively. Extubation and recovery times were prolonged in IV dexmedetomidine group (P ˂ 0.0001, 0.0001; respectively). Conclusions IP dexmedetomidine as an adjuvant to IP bupivacaine is as efficacious as IV dexmedetomidine compared to IP bupivacaine alone. However, the IP administration has the longest duration of analgesia and the lowest postoperative analgesic consumption. Clinical trial registration number Clinical Trials.gov (NCT04370392).
Factors that influence success when training videofluoroscopic swallowing study analysts

ABSTRACT Background: The literature relating to videofluoroscopic swallowing study (VFSS) training is sparse. The available evidence suggests that the learner, environment, and training design might influence VFSS analysts’ skill development. Aims: To identify the factors that VFSS analysts perceive to influence VFSS training. Methods & Procedures: In this qualitative study we interviewed nine speech pathologists from three countries who train VFSS analysts. The interviews followed a semi-structured guide to obtain data describing the trajectory of skill development and the influence of the learner, environment, and training design. We completed a thematic analysis using a simultaneously deductive and inductive approach. Outcomes & Results: Participants indicated that they believed that a trainee’s clinical experience, cognitive attributes, and learning preferences may influence their skill development. Trainers perceived a need to balance increasing the complexity of the task against maintaining the trainee’s confidence. The opportunity to practise and receive feedback was considered important. Barriers to practice were discussed. Training was perceived to have increased in complexity as the field of dysphagia has matured. Participants discussed the interacting demands of time and competency in this evolving environment. Conclusions & Implications: VFSS analytical skill development requires an investment of time by the trainee, trainer, and service. Trainers perceived that the trajectory of training and the time taken to reach competency varied according to the trainee, trainer, training design, and training environment factors. Future research into the impact of these influences and training content is needed to identify ways to provide sufficient practice and support learner differences to reduce the costs and time associated with training.