Miracle-dz/UniFAR-FTUs huggingface dataset:
Preparing undergraduate students to support K-12 computer science teaching through school-university partnerships: reflections from the field

ABSTRACT Background and Context A key challenge in advancing computer science education in K-12 schools is teacher preparation and support. School-university partnerships and service-learning programs where undergraduates assist teachers represent one promising approach to supporting K-12 computer science teaching. Objectives In this work, we examine the computer science content and pedagogical practices that undergraduates knowledgeable in computing reported implementing in order to support K-12 teachers in their classrooms as part of a university service-learning course. Method Data were collected from 60 undergraduates enrolled in the course over nine semesters. Data included weekly reflective entries, course observations, observations in K-12 classrooms, and collection of artifacts. Data were analyzed using qualitative techniques and descriptive statistics to identify dimensions of high-quality computer science content and pedagogy reported by undergraduates. Findings Findings indicated that undergraduates were able to connect knowledge of computing to pedagogy and technology to assist teachers in the implementation of computer science instruction. Specifically, undergraduates worked with partner teachers to employ high quality content and practices that made computer science accessible to students. Implications Findings from this work are important as different models are considered for how to provide professional development and/or support K-12 teachers in building knowledge needed for sustainable computer science teaching.
Relaxation Effects of Aromatherapy Intervention on Female and Male Anxiety: A Randomized Control Trial

Background: The control or reduction of anxiety before surgery is one of the most important components of preoperative care. The question is whether anxiety differs in male and female candidates for surgery. Objectives: The current study aimed to evaluate the effect of aromatherapy with Citrus aurantium on anxiety in men and women candidates for surgery. Methods: This single-blind randomized clinical trial was performed on 60 patients and controlled by placebo. The patients were divided into 30 subjects in the control group and 30 subjects in the aromatherapy group (inhaling C. aurantium essential oil). The patients completed the Spielberger state-trait anxiety inventory before and after the intervention. After collecting information, the questionnaire information was analyzed using SPSS software (version 16). Results: After aromatherapy, 20% of men had mild state and trait anxiety. Moreover, 80% of men had relatively mild state and trait anxiety. In the group of women, 20% of the cases had mild state and trait anxiety. Furthermore, 73.3% of women had relatively mild state and trait anxiety. Additionally, 6.7% of women had relatively severe anxiety. Anxiety reduced after the intervention among men and women (P < 0.001). In addition, the severity of anxiety among women in the control group increased after placebo intervention (P < 0.05). Moreover, the effect of C. aurantium aroma was further observed in women than men; however, there was no statistically significant difference (P > 0.05). Conclusions: The results of this study indicated that inhaling the C. aurantium aroma reduces anxiety in patients. Aromatherapy also has the potential to be replaced by chemical drugs due to fewer side effects and risks, and cost-effectiveness.
Proximate Fixed-Time Prescribed Performance Tracking Control of Uncertain Robot Manipulators

This article solves the problem of proximate fixed-time prescribed performance trajectory tracking for robot manipulators in the presence of bounded external disturbances and parametric uncertainties. A novel prescribed performance function (PPF) is first presented. A sliding surface with the prescribed performance tracking errors is constructed and a nonsingular proximate fixed-time terminal sliding mode prescribed performance control (FTSMPPC) is developed. It is proved that the position tracking error satisfies the prescribed performance boundaries all the time and globally converges to a preset small region centered on the origin within fixed time and then converges to the origin asymptotically. The proposed FTSMPPC provides faster transient performance quantified and higher steady-state accuracy by the proposed PPF. The effectiveness and improved performances of the presented approach are validated by simulations and experiments.
Beyond Digestion: Can Animals Shape the Landscape According to Their Species–Specific Salivary Secretions?

Several functions are acknowledged for saliva secretion in different animal species following prehension and mastication of feed. Most of such are linked to the specific role of lubrication and softening of the bolus to allow taste perception and easy swallowing. Moreover, enzymatic components are produced in the saliva, some of which are destined to contribute to the digestion of different nutrients (to various extents according to animal species) and to exert antimicrobial activity (lysozyme). In addition, the buffering power and the virtuous recycle of water, electrolytes, and other metabolites are of particular importance for proper digestion and for nutrition–related aspects. Moreover, salivation appears to be involved in a number of other functions. Recent studies on salivary production and roles point to salivary glands as target organs of neuroendocrine regulation in response to many external stimuli coming from the outer world, for which feed still represents the chief external stimulus. Various animal species establish an adaptive strategy when coming into contact with different feeding stuffs and/or dietary substances by modifying both the composition and amount of saliva produced. In the light of recent updates, this review provides a focus on the functional roles of saliva secretions, showing the broad involvement of salivary response in several mechanisms beyond the digestive function and influencing feed selection.
Consumer technology brands and the source of their performance

Abstract Over the past 20 years, consumer technology products have significantly impacted consumers’ purchasing patterns and behaviors. The companies catering to this market have demonstrated unprecedented innovation and financial performance. Therefore, it is important to understand how consumers process such brands in forming their product preferences. Consumer technology brands comprise certain products—smartphones, tablets, smartwatches, music devices, and laptops—that fulfill a complex mix of numerous functional and emotional needs, such as joy, socialization, group acceptance, and group recognition. This study proposes a conceptual framework to explain how brand loyalty for such products is built upon certain relevant brand perceptions. In an empirical post hoc study involving 320 technology product customers, measurements for the constructs involved were established, and a multi-category approach was adopted wherein respondents evaluated Apple, HP, Samsung, and Sony products. A statistical structural model is presented wherein the relationships proposed in the hypotheses are tested and supported. It is established that brand perceptions of innovativeness, benefits, and identification are likely to be strong antecedents of brand loyalty. Unlike previous literature, this study measures perceived benefits at the parent-brand level rather than at that of the product–category.
An Efficient On-Demand Hardware Replacement Platform for Metamorphic Functional Processing in Edge-Centric IoT Applications

The paradigm of Internet-of-things (IoT) systems is changing from a cloud-based system to an edge-based system. These changes were able to solve the delay caused by the rapid concentration of data in the communication network, the delay caused by the lack of server computing capacity, and the security issues that occur in the data communication process. However, edge-based IoT systems performance was insufficient to process large numbers of data due to limited power supply, fixed hardware functions, and limited hardware resources. To improve their performance, application-specific hardware can be installed in edge devices, but performance cannot be improved except for specific applications due to a fixed function of an application-specific hardware. This paper introduces an edge-centric metamorphic IoT (mIoT) platform that can use various hardware modules through on-demand partial reconfiguration, despite the limited hardware resources of edge devices. In addition, this paper introduces an RISC-V based metamorphic IoT processor (mIoTP) with reconfigurable peripheral modules. We experimented to prove that the proposed structure can reduce the server access of edges and can be applied to a large-scale IoT system. Experiments were conducted in a single-edge environment and a large-scale environment combining one physical edge and 99 virtual edges. According to the experimental results, the edge-centric mIoT platform that executes the reconfiguration prediction algorithm at the edge was able to reduce the number of server accesses by up to 82.2% compared to our previous study in which the prediction process was executed at the server. Furthermore, we confirmed that there is no additional reconfiguration time overhead even for the large IoT systems.
The Importance of Learning Style in Case Formulation–Driven Cognitive Behavioral Therapy: A Case Study

Rather than structuring treatment based on diagnoses, case formulation–driven cognitive behavior therapy (CF-CBT) focuses on building an individualized formulation or map of how a patient’s presenting problems are being maintained and uses this formulation to guide treatment planning. A case formulation can include comorbid diagnoses, underlying mechanisms, relevant historical, biological, and social factors, and problems unrelated to a diagnosis (e.g., unemployment). Therapy is also a learning context, and clients vary in their learning styles and preferences. The success of treatment depends not only on what a client learns but also on how a client learns. Frequently, learning style is not considered when developing a case formulation or providing CBT. The present case study, based on a man with social anxiety disorder who was treated using CF-CBT, demonstrates the importance of including learning style to target both what and how the client learns.
Multiresolution Daubechies finite wavelet domain method for transient dynamic wave analysis in elastic solids

The multiresolution capability provided by the family of Daubechies wavelets is exploited to develop a new computational approach, termed as multiresolution finite wavelet domain method for the fast and hierarchical prediction of transient dynamic problems with focus on wave propagation in one‐ and two‐dimensional structural configurations. In the developed method, both scaling and wavelet functions are employed as basis functions for the approximation of displacements in the governing dynamic equations. Because of the orthogonal and the multiresolution properties of Daubechies wavelets, a two‐scale system of mass uncoupled dynamic equations, representing the coarse and the fine spatial wave component solutions is derived. Numerical results concerning wave propagation in one‐ and two‐dimensional elastic structures demonstrate substantial computational gains of the method in comparison with other well‐established numerical methods. Moreover, additional benefits of the involved coarse and fine solutions enabling the analysis and characterization of the resultant wave response are revealed and discussed.
Fermentation kinetics in kombucha tea with tea kind variation based on its processing

Ardheniati M, Andriani MAM, Amanto BS. 2009. Fermentation kinetics in kombucha tea with tea kind variation based on its processing. Biofarmasi 7: 48-55. Tea (Camellia sinensis) is one of agriculture commodities which contains powerful substance, especially in health sector. The kinds of tea in Indonesia are green tea and black tea. Kombucha tea is made from water and tea boiled with fermentation process about 8-12 days. It consists of complex material changed by Acetobacter xylinum bacteria and Saccharomyces cerevisiae leavened. The purpose of the research was to find out the impact of the kinds of tea toward kombucha tea fermentation kinetics with the parameter of specific growth pace (Âµ), cell growth result (Yx/s), product formation (Yp/s), generation time (td), and the amount of multiplication (N). This research was done in UPT Central Laboratory of MIPA Faculty, Sebelas Maret University, Surakarta. The fermentation process optimization was done with the amount of inoculum of 10% (v/v), the temperature of 30oC and the initial sugar content of 10% (b/v). The analysis toward sugar content reduction, acetate acid content, pH value, and kombucha tea microbiology was done about 8 days of fermentation with 24 hours interval. The data generated were treated by a descriptive analysis and t-test investigation, so that the difference of fermentation kinetics between green kombucha tea and black kombucha tea could be found. The results of the research showed that the fermentation kinetic of green kombucha tea had an aerobe and anaerobe specific growth pace of 0.055/hour and 0.015/hour, respectively, cell growth result 1.901x107 cfu/mg, product formation 0.064, the efficiency of acetic acid production toward sugar reduction 11.814%, the generation time in aerobe and anaerobe condition 12.6 and 46.2 hours, respectively, and the amount of multiple of 3.583 times. Meanwhile, the fermentation kinetic of black kombucha tea showed an aerobe and anaerobe specific growth pace of 0.054/hour and 0.018/hours, respectively, cell growth result 2.425x107 cfu/mg, product formation 0.081, the efficiency of acetic acid production toward sugar reduction 11.510%, the generation time in aerobe and anaerobe condition 12.8 hours and 38.5 hours, respectively, and the amount of multiple 3.583 times. From t-test investigation, it was found that the aerobe specific growth pace, the efficiency of acetic acid production toward sugar reduction, the aerobe generation time, the cell growth, and the product formation were not significantly different. Meanwhile, the anaerobe specific growth pace, the anaerobe generation time, and the amount of multiple were significantly different.
DOA Estimation in Low SNR Environment through Coprime Antenna Arrays: An Innovative Approach by Applying Flower Pollination Algorithm

The design of the modern computing paradigm of heuristics is an innovative development for parameter estimation of direction of arrival (DOA) using sparse antenna arrays. In this study, the optimization strength of the flower pollination algorithm (FPA) is exploited for the DOA estimation in a low signal to noise ratio (SNR) regime by applying coprime sensor arrays (CSA). The enhanced degree of freedom (DOF) is achieved with FPA by investigating the global minima of highly nonlinear cost function with multiple local minimas. The sparse structure of CSA demonstrates that the DOF up to O(MN) is achieved by employing M+N CSA elements, where M and N are the numbers of antenna elements used to construct the CSA. Performance analysis is conducted for estimation accuracy, robustness against noise, robustness against snapshots, frequency distribution of root mean square error (RMSE), variability analysis of RMSE, cumulative distribution function (CDF) of RMSE over Monte Carlo runs and the comparative studies of particle swarm optimization (PSO). These reveal the worth of the proposed methodology for estimating DOA.
Genetic diversity and population structure of three Hydroides species (Sedentaria, Serpulidae) in the Persian Gulf and Gulf of Oman, with the possible indication of heteroplasmy

The Persian Gulf, an enclosed sea connected to the Gulf of Oman through the narrow Strait of Hormuz, is known as the world’s hottest sea. Owing to its harsh environmental conditions, genetic isolation has been proposed for the Gulf’s biota. During the present study, population genetic and phylogeographic analyses were carried out focusing on potential barriers to dispersal in some polychaete populations between the Persian Gulf and the Gulf of Oman. Ninety-three specimens from three defined spatial populations of three Hydroides species, H. bulbosa, H. elegans and H. operculata, were sequenced for regions of two nuclear ribosomal (18S and ITS2) and two mitochondrial (COI and Cyt-b) genes to compare the genetic structure among the sampled populations. Haplotype networks of the three species showed no significant genetic differentiation and were consistent with their geographic distribution patterns. Population genetic analyses such as pairwise FST, nucleotide diversity and neutrality tests revealed some levels of intraspecific genetic diversities, suggesting different demographic histories. The genetic diversity observed in the more conservative genes (18S, Cyt-b, COI) in populations of H. elegans and H. operculata could reflect a more diverse genetic structure along their entire distribution range unlike the endemic species, H. bulbosa that presented a unique haplotype for each of those genes. Using Extended Bayesian Skyline plot analyses, populations of H. bulbosa and H. operculata showed signs of recent demographic expansion within the post-glacial transgression time frame of the Persian Gulf, while populations of H. elegans remained relatively constant. Another finding of the present study is the possible indication of heteroplasmy in H. elegans where two distinct mitochondrial lineages with about 11% of genetic divergence seem to coexist in the same individuals. We discuss also the alternative explanation of NUMTs (nuclear mitochondrial DNA), but regard it as substantially less likely.
Queries and Cues: Textual Stimuli for Reflective Thinking in Digital Mind-Mapping

Mind-mapping is useful for externalizing ideas and their relationships surrounding a central problem. However, balancing between the exploration of different aspects (breadth) of the problem with respect to the detailed exploration of each of its aspects (depth) can be challenging, especially for novices. The goal of this paper is to investigate the notion of “reflection-in-design” through a novel interactive digital mind-mapping workflow that we call “QCue. ” The idea behind this workflow is to incorporate the notion of reflective thinking through two mechanisms: (1) offering suggestions to promote depth exploration through user’s queries (Q) and (2) asking questions (Cue) to promote reflection for breadth exploration. This paper is an extension of our prior work (Chen et al., 2020, “Qcue: Queries and Cues for Computer-Facilitated Mind-Mapping,” Proceedings of Graphics Interface 2020, GI 2020, Canadian Human-Computer Communications Society/Société canadienne du Dialogue Human-Machine, pp. 125–136) where our focus was mainly on the algorithmic development and implementation of a cognitive support mechanism behind QCue enabled by ConceptNet (a graph-based rich ontology with “commonsense” knowledge). In this extended work, we first present a detailed summary of how QCue facilitated the breadth-depth balance in a mind-mapping task. Second, we present a comparison between QCue and conventional digital mind-mapping, i.e., without our algorithm through a between-subjects user study. Third, we present new detailed analysis on the usage of different cognitive mechanisms provided by QCue. We further consolidate our prior quantitative analysis and build a connection with our observational analysis. Finally, we discuss in detail the different cognitive mechanisms provided by QCue to stimulate reflection in design.
Investigation of Groundwater Depletion in the State of Qatar and Its Implication to Energy Water and Food Nexus

Groundwater is a precious freshwater resource heavily relied upon by agricultural activities in many parts of the world, and especially by countries with limited water resources located in arid regions. Groundwater resources are under severe pressures due to population increase, urbanisation and socio-economic development, with potential for causing long-term threats to human life and natural ecosystems. This study attempts to investigate the impacts of local and regional climatic trends, and establish key forcing functions that have changed local groundwater resources. The main questions answered through this study include: Are these changes beneficial or detrimental? If they are detrimental, what is the future outlook for impacts on the ecosystem? What are the corrective actions needed to avert the long-term risks in arid environments? In view of this, the methodology developed in this study focuses on a joint time-series statistical analysis using ground data as well as Gravity Recovery and Climate Experiment (GRACE) satellite data. Results show a substantial depletion in the groundwater thickness (0.24 ± 0.20 cm/year) during the period of observation (2002–2020). Long-term temperature data indicates that the annual mean temperature increased significantly by 1.02 °C between 1987 and 2016, while total rainfall exhibited a slight decreasing trend. In addition to groundwater extraction, fluctuations in monthly rainfall, soil moisture, evapotranspiration and relative humidity support the groundwater thickness reduction of GRACE datasets. The use of desalinated water and wastewater reuse in the agriculture sector may reduce the pressure on groundwater resources. Optimization, adaptation and mitigation in the EWF nexus will further improve the sustainability of the EWF resources.
The evidence is in: Repetitive transcranial magnetic stimulation is an effective, safe and well-tolerated treatment for patients with major depressive disorder

Despite more than 25 years of research establishing the antidepressant efficacy of repetitive transcranial magnetic stimulation, there remains uncertainty about the depth and breadth of this evidence base, resulting in confusion as to where repetitive transcranial magnetic stimulation fits in the therapeutic armamentarium in the management of patients with mood disorders. The purpose of this article is to provide a concise description of the evidence base supporting the use of repetitive transcranial magnetic stimulation in the context of the stages of research that typically accompanies the development of evidence for a new therapy. The antidepressant efficacy for the use of repetitive transcranial magnetic stimulation in the treatment of depression has been established through a relatively traditional pathway beginning with small case series, progressing to single-site clinical trials and then to larger multisite randomised double-blind controlled trials. Antidepressant effects have been confirmed in numerous meta-analyses followed more recently by large network meta-analysis and umbrella reviews, with evidence that repetitive transcranial magnetic stimulation may have greater efficacy than alternatives for patients with treatment-resistant depression. Finally, repetitive transcranial magnetic stimulation has been shown to produce meaningful response and remission rates in real-world samples of greater than 5000 patients. The evidence for the antidepressant efficacy of repetitive transcranial magnetic stimulation therapy is overwhelming, and it should be considered a routine part of clinical care wherever available.