Miracle-dz/UniFAR-FTUs huggingface dataset:
Presages of contemporary theatre studies theories in Vladimír Jindra's structuralist theory of scenography

The study provides detailed analysis of the work of Czechoslovak theoretician of scenography, Vladimír Jindra (1920–1979). It focuses on Jindra's at the time innovative taxonomy of scenography which substantially supported the shift in today's worldwide understanding of the notion of scenography as a complex theatrical discipline. The aim of the study is to connect Jindra's work with contemporary theoretical approaches to theatre, especially rooted in multimodal and cognitive analysis of scenography. Special attention is given to the elements of Jindra's work that predated Multimodal Metaphor Theory. The study shows that his conception of scenography is connected to the structuralists' understanding of the socalled 'stage metaphor'. This exploration should therefore show the reader not only the progressiveness of Jindra's thinking about scenography, but also outline a view on possible future research in the field of multimodal and cognitive approaches to theatrical scenography.
Anchor Loss Reduction for Square-Extensional Mode MEMS Resonator Using Tethers With Auxiliary Structures

In this article, a new approach by introducing auxiliary structures in the tethers of a microelectromechanical system (MEMS) resonator is presented to reduce anchor loss. A capacitive square-extensional (SE) mode resonator with folded beam tether is adopted to verify the feasibility of the proposed approach in both finite-element method (FEM) analysis and measurement. In FEM simulations, a perfectly matched layer (PML) boundary condition is applied to estimate anchor loss of the designed MEMS resonators. With the aid of the auxiliary structures, quality factors (<inline-formula> <tex-math notation="LaTeX">${Q}\text{s}$ </tex-math></inline-formula>) of the designed SE mode MEMS resonators are significantly improved. The measured <inline-formula> <tex-math notation="LaTeX">${Q}$ </tex-math></inline-formula> of the fabricated SE mode resonator is improved by approximately 62% after introducing auxiliary structures in the tethers of the resonator without any further treatments on the resonator structure or tether design. The proposed approach provides a simple and effective way to suppress anchor loss and hence improve <inline-formula> <tex-math notation="LaTeX">${Q}$ </tex-math></inline-formula> for the presented MEMS resonators.
Recurrence of piriformis syndrome: One year follow up post ultrasound guided injection therapy

Background. Piriformis syndrome is a common cause of low back pain sometimes underdiagnosed due to a lack of distinguishing symptoms and patterns. Two methods of ultrasound-guided intramuscular injection (using a local anesthetic agent and combined with corticosteroids) have become the treatments of choice. However, some studies suggest these methods may result in recurrence even though data regarding the prevalence of recurrence and triggering factors are still lacking. Objective. To identify the prevalence of and factors triggering the recurrence of piriformis syndrome treated with steroid and local anesthetic injections. Methods. This is a prospective cohort following patients diagnosed with piriformis syndrome and treated with either a local anesthetic or a combination with the addition of corticosteroids. Demographic, risk factors, and the onset of pain recurrence data were taken and analyzed. Results. From the 66 patients included in this study, 68.2% (n:45) reported recurrence of pain, with the majority occurring within the first three months post-injection. Subjects treated with combination therapy had a pain-free interval 13.45 weeks longer than subjects treated with a local anesthetic injection. There were no significant differences in risk factors between both groups. Conclusion. Recurrence of piriformis syndrome was most commonly found within the first and third months of treatment. Both methods did not differ significantly, even though combination therapy tends to give longer pain-relief intervals.
On preconditioned BiCGSTAB solver for MLPG method applied to heat conduction in complex geometry

ABSTRACT Meshless local Petrov–Galerkin (MLPG) method is a promising meshfree method for continuum problems in complex domains, especially for large deformation, moving boundary and phase change problems. For large-scale problems, iterative methods for solving the discretized equations are more suitable than direct methods. Krylov subspace solvers of conjugate gradient type are the most preferred iterative solvers. The convergence rate of these methods depends on preconditioner used. Recently, proposed schedule relaxation Jacobi (SRJ) method can be used as a stand-alone solver and as a preconditioner. In the present work, the SRJ method is tested as a stand-alone solver and as a preconditioner for BiCGSTAB solver in the MLPG method, and its performance has been compared with successive overrelaxation (k) preconditioner. Two-dimensional linear steady-state heat conduction in complex shape geometry has been used as the model test problem.
Robustness of the International Wheat Trade Network

Grain is the material basis for human survival and development, wheat is one of the three significant grains, and the robustness of the wheat trade has seriously affected world grain security. In the article, we analyze the robustness of the International Wheat Trade Network (IWTN) from three perspectives: global, regional, and national. We quantify the topological properties and evolution characteristics of IWTN from 1987 to 2020, and analyze the stability of IWTN using random attacks and target attacks. The import satisfaction of major wheat trading countries and trade communities is quantified through import stability indicators. Firstly, the results show that IWTN satisfies the scale-free property and that global wheat trade transactions continue to increase. Secondly, IWTN under random attack forms a “convex” curve regarding network efficiency. It shows that IWTN has better resistance to external shocks, and higher robustness. However, under the targeted attack, the network collapses when the node failure rate reaches 40%. Regardless of the attack mode, the decreasing trend of network efficiency and connectivity is the same in different years as the number of failed nodes gradually increases, and no year shows outstanding stability. Thirdly, different communities in the wheat trade are more satisfied with the wheat imports of their internal countries, and most of the wheat trade occurs within the same trading community. Fourthly, among the top five global wheat importers in 2020, Italy and Turkey have diversified sources of imports, but trade imports are relatively concentrated. In contrast, China, Egypt and Indonesia have relatively balanced wheat trade imports from their respective trading countries and are less at risk of being affected in the event of supply risks.
Design of a Load Modulated Balanced Amplifier with a Two-Stage Control Power Amplifier

While an ideal Doherty power amplifier has a linear response, the load modulated balanced amplifier (LMBA) has a compressive response under ideal conditions. This inherent nonlinear characteristic is due to the lower power contribution of the single auxiliary device as the balanced amplifier transistors approach compression. This article presents an LMBA with a two-stage control signal amplifier in place of the single auxiliary device. The idea is to preserve a high and constant gain across the high- and low-power regions by tuning the two-stage gain control signal to match the balanced amplifier gain. An optimal load trajectory can be found for a high-efficiency design by appropriately terminating the second harmonic while ensuring an optimal impedance match in all devices. At the same time, by setting an optimal output power from the auxiliary device, sufficient power is provided to linearize the response of the main power amplifier beyond the output back-off power boundary. As proof of concept, a prototype is designed and implemented. The experimental measurements demonstrate a drain efficiency of 59%–64% at maximum output power and 46%–52% at 7.5 dB output back-off power over the target frequency range of 3.3–3.8 GHz.
The moderating effect of educational support on the relationship between self-efficacy and intention in cyber entrepreneurship

PurposeThis study investigates the influence of cyber entrepreneurial self-efficacy (CESE) and educational support (ES) on cyber entrepreneurial intentions (CEIs) among individuals in the United Arab Emirates (UAE). Additionally, in the context of cyber-entrepreneurship (CE), it examines the potential moderating effect of ES on the relationship between self-efficacy and intention.Design/methodology/approachOnline surveys were administered via the SurveyMonkey platform to UAE-based individuals who graduated from top-ranking universities within the past five years. A total of 283 valid responses were obtained, and the hypotheses were evaluated using partial least squares structural equation modeling.FindingsThe findings reveal that CESE and ES both exhibit a significant positive relationship with CEIs. However, the study also indicates that ES does not moderate the relationship between CESE and CEIs.Originality/valueThis research contributes to the existing academic literature by applying the theory of planned behavior to CE for individuals in the UAE. Furthermore, in contrast with prior studies, this study demonstrates that ES significantly impacts CEIs. From a practical standpoint, this study offers valuable insights to policymakers and educational institutions regarding the importance of utilizing ES to increase the number of cyber entrepreneurs in the UAE.
Leadership Competencies in Non-Profit Organizations: Insights from Qualitative Research

The ever-changing environment required non-profits to adapt more effective leadership skills. This study provides an understanding of the characteristics of competent non-profit organization leaders. A qualitative phenomenology methodology was used, with 15 individual in-depth interviews with leaders from a non-profit organization in Saudi Arabia, leading the data collection process. Thematic analysis was applied to generate themes. The results revealed six main leadership competencies in the non-profit sector: 1) passion and altruism, 2) organizational advocacy, 3) instilling community support, 4) focus and strategy, 5) trust and delegation, and 6) continuous self-learning and agility. The findings suggest that leaders in different non-profit leadership organizations should possess six categories of competency to overcome internal and external challenges effectively. The study’s findings contribute to the understanding and exploration of the nature of leadership competencies in non-profit organizations, and can be beneficial to similar contexts.
Statistical Database of Human Motion Recognition Using Wearable IoT—A Review

Wearable sensors and the Internet of Things (IoT) will be two buzzwords that will be heard commonly in the coming decades. The combination of these two technologies soon will create a great revolution in applications that require motion recognition, such as health care, sports, and entertainment. The development of technology has made wearable sensors one of the most basic tools for human motion analysis. We believe that IoT is the most powerful complement to the use of wearable sensors in the analysis of human body motion. Using wearable IoT, all necessary human data will be collected and delivered via the Internet to the experts who can make accurate decisions about the type of activity, falling situations, freezing of gait (fog), and so on. In this article, the human motion analysis is presented in a chart and is divided into two parts: movement measurement and movement classification. However, this article focuses on movement classification that includes three subsections, gait analysis (GA), gesture recognition (GR), and human activity recognition (HAR), and is closely related to human motion recognition. In this article, our goal is to first acquaint the reader with the important steps required to classify the movement of the human body by wearable sensors and then by using tables to determine the most used algorithms and methods for each step. After briefly reviewing IoT concepts, directions for further research will be provided.
Disentangling Price, Risk and Model Risk

We propose a method to assess the intrinsic risk carried by a financial position $X$ when the agent faces uncertainty about the pricing rule $\pi_{\mathbb{P}}$ assigning its present value. We introduce a general class of Value\&Risk (V\&R) measures as a function of $(p,X,\mathbb{P})$, where $p$ is the observed initial value of $X$ or is assigned by $\pi _{\mathbb{P}}(X)$ under the probability $\mathbb{P}$. \newline Our approach is inspired by a new interpretation of the quasiconvex duality in a Knightian setting, where a family of probability measures replaces the single reference probability and is then applied to value financial positions. Diametrically, our construction of V\&R measures is based on the selection of a basket of claims to test the reliability of models.
Ab initio study on interlayer exchange coupling in (Zn,Ni)O multilayers

ABSTRACT Interlayer exchange coupling in (Zn, Ni)O multilayers is investigated by density functional theory calculations. We mainly study the effect of the nonmagnetic spacer and carrier in controlling the IEC between the magnetic layers separated by ZnO layers. It is found that, for the pure ZnO layers, the coupling between the two magnetic (Zn,Ni)O layers is always ferromagnetic, which is well interpreted by the RKKY interaction based on a gaped two-band model. However, the antiferromagnetic coupling is observed by N doping, which is in connection with the ZnO layers's thickness and the N atoms's sites. The p–d hybridization mechanism plays an important role in switching FM coupling to AFM coupling.
Evaluating the efficiency of scallop shell/iron oxide (II) nanocomposite in removal of direct red 81 dye from aquous solutions: kinetic, isotherm and thermodynamic studies

These dyes have the potential for mutagenicity, carcinogenicity, and unwanted color on the one hand, and on the other hand, cause the production of toxic by-products in aqueous media. The aim of the present work is to synthesize scallop shell/iron oxide(II) nanocomposite and evaluate its effi- ciency in removing Direct red 81 (DR81) dye from aqueous solutions. Iron oxide nanoparticles were prepared by co-precipitation method and then the scallop was coated with iron oxide. The proper- ties of synthesized nanocomposite were identified using Fourier-transform infrared spectroscopy, field-emission scanning electron microscopy, and X-ray diffraction. Effect of dye concentration (20–120 mg/L), contact time (0–240 min), adsorbent dosage (0.5–2.5 g), pH (3–11), and temperature (25°C–55°C) was investigated on decolorization efficiency of the process. Under optimal condi- tions (an initial DR81 concentration of 25 mg/L, pH of 3, adsorbent dose of 0.5 g, and contact time of 90), more than 98% of the dye was removed. The results showed that the efficiency decreases with increasing concentration. Moreover, by increasing the contact time and adsorbent dosage, dye adsorption percentage was enhanced. The maximum adsorption coefficient was 46.4 mg/g. In addition, Freundlich and Langmuir models were used to analyze the experimental isotherm data. The kinetic data of the adsorption process were in good agreement with the pseudo-second- order kinetic model (0.995). The experimental data of the adsorption process followed the Langmuir model ( R 2 = 0.91). The results show that Fe 2 O 3 nanoparticles coated with scallop shell as an environmentally friendly adsorbent can be effective in the adsorption of DR81.
Teaching The Superposition Method With Internet Based Instructional Software

In the Mechanics of Materials course, one method used to determine beam deflections and support reactions for statically determinate and indeterminate beams is based on the concept of superposition. To help explain the theory and art of the superposition method, a series of 14 animated movies has been developed that present examples and strategies for applying superposition principles to common types of beams. To evaluate its effectiveness, experiments were conducted in which the customary lectures were replaced by use of this instructional software. Students who used the superposition software were compared to students in five other Mechanics of Materials sections on the basis of (a) score on a superposition problem included in the common final exam, (b) total score on the common final exam, and (c) a survey questionnaire consisting of a number of subjective rating items. Those students who used the superposition software were statistically comparable to the other students on all these outcome measures. In addition, there was evidence that low ability students benefited from the software in the form of increased motivation, in comparison to students in some of the other sections.
Observations of the Diurnal evolution of lake-effect precipitation occurrence

Lake-effect snow storms are important components of the climate of the U.S. Upper Midwest, resulting in some locations near the Great Lakes receiving double the average wintertime snowfall of locations several 10s of km inland (e.g., Scott and Huff 1996, Braham and Dungey 1984). The economic and societal impacts of these storms depend critically on the timing of their occurrence relative to activities of the 35 million people living in the Great Lakes basin (GLERL 2002). This study utilizes hourly precipitation data collected in the snow belt regions of Lakes Superior and Michigan to determine the typical diurnal behavior of lake-effect precipitation occurrence.
Orthogonal Discriminant Sparse Maximum Margin Analysis

Feature extraction is a crucial step for face recognition. In this paper, a new feature extraction method called orthogonal discriminant sparse maximum margin analysis (ODSMMA) is proposed for face recognition. ODSMMA defines two parameterless discriminant weighted matrices through the sparse representation. ODSMMA can efficiently preserve the margin between the same class and maximizes the margin between different classes simultaneously without setting any parameters. Moreover, by taking the advantage of the maximum margin criterion, ODSMMA is able to extract the orthogonal discriminant vectors in the feature space and does not suffer the small sample size problem. Experimental results on ORL database indicate the effectiveness of the proposed method
The Maia Detector and Event Mode

A decade ago, prototypes of the Maia detector successfully demonstrated a fresh approach to X-ray fluorescence microscopy (XFM) imaging that combined a massively parallel detector architecture with dedicated pulse shaping and capture on each channel, asynchronous acquisition of X-rays as an event stream, and real-time processing of the event data [1, 2]. Today, a number of XFM beamlines that raster scan a sample through a focused X-ray beam to construct images of element concentration and chemical state use a 384-detector array version of Maia for high-throughput, high-definition XFM. The beamlines include those at the Australian Synchrotron (AS) in Melbourne [3], the PETRA III synchrotron at DESY, Hamburg [4], the CHESS synchrotron at Cornell University in Ithaca [5], and the NSLS-II at Brookhaven National Laboratory (BNL) in New York.
The Prospective Relationship of Attachment Theory and Dispositional Forgiveness: An Exploration of a Somali Population in the United States

: Background: Attachment theory can be a valuable tool in understanding the differences in the propensity to forgive hurt. Attachment theory has been associated with the ability to forgive or respond to hurt. Both concepts involve trust, communication, empathy, and emotion regulation. This article examines the relationship between attachment style and dispositional forgiveness among a population of Somalis in the United States. Method: Fifty Somalis at the Somalis Community Association in Columbus, Ohio, participated in the study. Forgiveness was conceptualized utilizing Enright Forgiveness Inventory (Enright et al ., 2000), while attachment style was measured using the Relationship Scale Questionnaire (RSQ), 30-item statements describing characteristic styles of close relationships. Further, descriptive statistics and frequencies were run to get an overview of the sample. Data were entered into the SPSS 17.0 and analyzed using an alpha level set at 0.05. Correlation coefficients were run to determine the association between forgiveness and the various types of attachment styles. Result: The result of this study indicates that there was no significant relationship between attachment style and dispositional forgiveness among the Somalian community in Columbus, Ohio. Discussions of the results, as well as a consideration of potential future directions, are explored. Conclusion: In a close-knit, communal, and homogenous Somalis group, where family and community are considered more important than the individual, forgiveness may be more related to variables such as family and group harmony than internal personality variables.
LASSO order selection for sparse autoregression: a bootstrap approach

ABSTRACT Autoregressive models are widely employed for predictions and other inferences in many scientific fields. While the determination of their order is in general a difficult and critical step, this task becomes more complicated and crucial when the time series under investigation is realization of a stochastic process characterized by sparsity. In this paper we present a method for order determination of a stationary AR model with a sparse structure, given a set of observations, based upon a bootstrapped version of MAICE procedure [Akaike H. Prediction and entropy. Springer; 1998], in conjunction with a LASSO-type constraining procedure for lag suppression of insignificant lags. Empirical results will be obtained via Monte Carlo simulations. The quality of our method is assessed by comparison with the commonly adopted cross-validation approach and the non bootstrap counterpart of the presented procedure.
Postmenopausal Status Exacerbates Stress-Related Neurological Disorders in Rats

Aims: This study was aimed at assessing the effects of social instability stress (SIS) and immobilization stress (IS) in postmenopausal (PM) conditions. Postmenopause is a physiological state often associated with mild neuronal disorders (NDs) such as anxiety and irritability. The aging of the worldwide population, coupled with multiple stressors, can lead to significant public health concerns, including severe NDs. Place and Duration of Study: Tests and analyses were carried out within the confines of the Laboratory of Animal Physiology of the University of Yaoundé I (Cameroon) for 3 months. Study Design: To induce PM syndrome, an 84-day ovariectomized Wistar rat model was used. Methodology: Random sampling of 4 groups of 6 rats, each aged between 8 and 10 weeks, was used. SIS and IS were induced during PM installation. Behavioral status, biochemical, and histopathological analyses were carried out. Results: SIS combined with IS exacerbates NDs induced by low estrogen levels. Furthermore, ovariectomized stressed rats are more depressed and anxious than the control. They presented severe hippocampal inflammation, oxidative stress, and memory impairment owing to low levels of ACh and reduced neuronal expression in the hippocampus. Overall, PM status makes NDs linked to stress worse in rats. Conclusion: Stress promotes oxidative stress, neuroinflammation, and neuronal death, leading to greater affective and cognition disorders when estrogen levels are low. Thus, there is a need to focus on the management of stress during menopausal life.