Miracle-dz/UniFAR-FTUs huggingface dataset:
Zonal Mean Winds Induced by Solar Diurnal Tides in the Lower Thermosphere

The generation of the mean zonal winds in the lower thermosphere is discussed, on the basis of momentum transport by dissipating solar diurnal tidal waves. The most important factor to control the amplitude of tidal waves and the magnitude of the induced mean winds in the lower thermosphere is the dissipative effect due to small scale motions in the mesosphere and the lower thermosphere which is parameterized in the form of eddy diffusion or the form of Rayleigh friction. In both cases of parameterizations, the behavior of the tidal wave agrees well with observations. The induced mean zonal winds in case of eddy diffusion-type parameterization are found to be three times larger than those of the case of Rayleigh friction-type parameterization. The weaker zonal flow is interpreted to result from the removal of net momentum. As the observed mean zonal winds distribution is not definitive, we cannot decide which parameterization is suitable for the present problem. However, the present results confirm that the dissipating solar diurnal tidal wave contributes greatly to the configulation of the mean zonal winds in the lower thermosphere.
Effectiveness of an Intervention to Enhance First Aid Knowledge among Early Childhood Education Students: A Pilot Study

Empowering early childhood education students from the beginning with the necessary knowledge and skills to act swiftly in emergency situations could be crucial in saving lives in certain cases. In order to improve the first aid knowledge and skills of early childhood education students, a pre/post study was conducted with a two-week intermediate intervention involving 13 early childhood education students. Their knowledge and skills in first aid were assessed using an ad-hoc instrument before and after the intervention. The results demonstrate a statistically significant improvement in all items related to first aid general knowledge, first aid kits, and CPR maneuvers, as well as in the overall scale. These findings provide evidence that early childhood education students can be equipped through low-cost interventions to acquire and apply certain essential first aid skills, such as dialing emergency services, understanding the purpose of first aid kit items, and recognizing vital signs in individuals, that may be crucial in saving lives in the future.
In Python available: St. Nicolas House Algorithm (SNHA) with bootstrap support for improved performance in dense networks

The St. Nicolas House algorithm (SNHA) finds association chains of direct dependent variables in a data set. The dependency is based on the correlation coefficient, which is visualized as an undirected graph. The network prediction is improved by a bootstrap routine. It enables the computation of the empirical p-value, which is used to evaluate the significance of the predicted edges. Synthetic data generated with the Monte Carlo method were used to firstly compare the Python package with the original R package, and secondly to evaluate the predicted network using the sensitivity, specificity, balanced classification rate and the Matthew's correlation coefficient (MCC). The Python implementation yields the same results as the R package. Hence, the algorithm was correctly ported into Python. The SNHA scores high specificity values for all tested graphs. For graphs with high edge densities, the other evaluation metrics decrease due to lower sensitivity, which could be partially improved by using bootstrap,while for graphs with low edge densities the algorithm achieves high evaluation scores. The empirical p-values indicated that the predicted edges indeed are significant.
Iterative Learning of Optimal Control for Nonlinear Processes With Applications to Laser Additive Manufacturing

Our target application is a laser additive manufacturing (LAM) process that suffers from too wide end points. To overcome this drawback, we propose to extend an algorithm of iterative learning of optimal control (ILOC) to nonlinear systems. We demonstrate its application for a LAM process, not only by simulations but also by comparing the results of 3-D metallic printing with and without learning. Extending previously published results, we provide proof of convergence of an ILOC algorithm for a wide class of nonlinear systems.
Extracellular circulating miRNAs as potential non-invasive biomarkers in non-small cell lung cancer patients

Non-small cell lung cancer (NSCLC) comprises 85% of all lung cancers and is a malignant condition resistant to advanced-stage treatment. Despite the advancement in detection and treatment techniques, the disease is taking a deadly toll worldwide, being the leading cause of cancer death every year. Current diagnostic methods do not ensure the detection of the disease at an early stage, nor can they predict the risk of its development. There is an urgent need to identify biomarkers that can help predict an individual’s risk of developing NSCLC, distinguish NSCLC subtype, allow monitor disease and treatment progression which can improve patient survival. Micro RNAs (miRNAs) represent the class of small and non-coding RNAs involved in gene expression regulation, influencing many biological processes such as proliferation, differentiation, and carcinogenesis. Research reports significant differences in miRNA profiles between healthy and neoplastic tissues in NSCLC. Its abundant presence in biofluids, such as serum, blood, urine, and saliva, makes them easily detectable and does not require invasive collection techniques. Many studies support miRNAs’ importance in detecting, predicting, and prognosis of NSCLC, indicating their utility as a promising biomarker. In this work, we reviewed up-to-date research focusing on biofluid miRNAs’ role as a diagnostic tool in NSCLC cases. We also discussed the limitations of applying miRNAs as biomarkers and highlighted future areas of interest.
The Efficacy and Safety of Different Noninvasive Therapies in the Treatment of Central Poststroke Pain (CPSP): A Network Meta-Analysis and Systematic Review.

OBJECTIVE To evaluate the efficacy and safety of noninvasive therapies in the treatment of central poststroke pain (CPSP) by network meta-analysis and to provide an evidence-based basis for clinical practice. METHODS PubMed, Cochrane Library, EMBASE, CNKI, Wanfang, and VIP were searched for clinical randomized controlled studies on noninvasive therapy for CPSP. The retrieval time limit was from the establishment of each database to July 2022. The bias risk assessment tool recommended by Cochrane was used to evaluate the quality of the included randomized controlled trials (RCTs). Stata 14.0 was used for network meta-analysis, and Review Manager 5.3 software was used for traditional meta-analysis. RESULTS Twelve RCTs involving 8 treatment schemes and 641 patients were finally included. The results of the network meta-analysis showed the following rankings in visual analysis scale (VAS): super laser injury on stellate ganglia (SLI) > transcranial direct current stimulation (tDCS) > music therapy (MT) > repetitive transcranial magnetic stimulation (rTMS) > continuous theta burst stimulation (cTBS) > transcutaneous acupoint electrical stimulation (TAES) > common therapy (CT). The total clinical efficiency ranked as follows: psychological training of mindfulness (PT) > rTMS > CT. Clinical adverse reactions ranked as follows: rTMS > MT > CT > SLI. CONCLUSIONS Noninvasive complementary therapy can effectively alleviate the pain of CPSP patients, and the efficacy and safety of SLI are relatively significant. However, due to the limitations of this study, the efficacy ranking cannot fully explain the advantages and disadvantages of clinical efficacy. In the future, more multicentre, large sample, double-blind clinical randomized controlled trials are needed to supplement and demonstrate the results of this study.
Implementation of fraud triangle theory: A systematic literature review

Fraud triangle theory popularized by Cressey (1953) and adopted by Statement of Auditing Standards No. 99, states that fraud occurs when there are three elements, namely: pressure, opportunity, and rationalization. This theory is criticized because it is considered unable to describe all the motivations of fraud perpetrators. This study aimed at developing Homer (2020) research, expanding it with criticism and developing variables in the fraud triangle. This research did not only focus on types of fraud based on the fraud tree but also added academic fraud. Methodologically, this research was a systematic literature review using six steps in determining the samples. This study summarized 25 Scopus articles using at least one element of the fraud triangle. From the 25 included studies, 80 percent reviewed the three elements of the fraud triangle in their research. As much as 60 percent of research results supported that the three elements of the fraud triangle can increase fraud motivation. Although the fraud triangle theory has received much criticism, researchers are trying to develop the fraud triangle theory by adding other variables and with theoretical support. This review recommends filling the research gap in developing the fraud triangle theory by looking at previous researches.
Sensitivity of a Mediterranean Tropical-Like Cyclone to Physical Parameterizations

The accurate prediction of Mediterranean tropical-like cyclones, or medicanes, is an important challenge for numerical weather prediction models due to their significant adverse impact on the environment, life, and property. The aim of this study is to investigate the sensitivity of an intense medicane, which formed south of Sicily on 7 November 2014, to the microphysical, cumulus, and boundary/surface layer schemes. The non-hydrostatic Weather Research and Forecasting model (version 3.7.1) is employed. A symmetric cyclone with a deep warm core, corresponding to a medicane, develops in all of the experiments, except for the one with the Thompson microphysics. There is a significant sensitivity of different aspects of the simulated medicane to the physical parameterizations. Its intensity is mainly influenced by the boundary/surface layer scheme, while its track is mainly influenced by the representation of cumulus convection, and its duration is mainly influenced by microphysical parameterization. The modification of the drag coefficient and the roughness lengths of heat and moisture seems to improve its intensity, track, and duration. The parameterization of shallow convection, with explicitly resolved deep convection, results in a weaker medicane with a shorter lifetime. An optimum combination of physical parameterizations in order to simulate all of the characteristics of the medicane does not seem to exist.
Ensemble-Based Storm Surge Forecasting Models

AbstractAccurate prediction of storm surge is a difficult problem. Most forecast systems produce multiple possible forecasts depending on the variability in weather conditions, possible temperature levels, winds, etc. Ensemble modeling techniques have been developed with the stated purpose of obtaining the best forecast (in some specific sense) from the individual forecasts. In this work a statistical methodology of evaluating the performance of multiple ensemble forecasting models is developed. The methodology is applied to predicting storm surge in the New York Harbor area. Data from three hurricane events collected from multiple locations in the New York Bay area are used. The methodology produces three key findings for the particular test data used. First, it is found that even the simplest possible way of creating an ensemble produces results superior to those of any single forecast. Second, for the data used and the events under study the methodology did not interact with any event at any location s.
Physicochemical and hygienic-sanitary quality of honey marketed in Chókwè city

The present study aimed to evaluate the hygienic-sanitary conditions and the physical-chemical parameters of honey bees with emphasis on understanding the risks to health. The experiment was conducted in a completely randomized design with 5 samples, 3 from artisanal production (A, B and C) and 2 from industrial production (Youngs honey (D) and Goldcrest (E)). Analyzes such as titratable acidity by titration with 0.1N sodium hydroxide solution (NaOH), soluble solids content, refractometry, pH, potentiometry, humidity, gravimetry and ash by incineration were carried out for the physical-chemical characterization. The hygienic-sanitary characterization was performed for molds and yeasts using the Spread Plate method. Data were evaluated using the statistical software RStudio 4.2. 1 at 5% significance of the Tukey test. The pH was fixed in the range of 3.28 to 4.30, soluble solids from 76.36 to 77.10 ºBrix, titratable acidity at the level of 4.14 to 6.10 meq/mL, moisture content of 12.07 to 17.12% and ash from 0.29 to 4.34%. The microbiological characterization showed the presence of molds in the range of 1.5x10 to 4.9x10. On the other hand, an uncountable load was verified in the yeast count in samples A and B, exceeding the limit established by the Technical Regulation of Quality and Identity of Honey. In terms of physical-chemical properties, no significant differences were found between artisanal and industrialized honey. The level of mold in all samples met recommended standards for honey and there was evidence of compliance with good manufacturing and hygienic-sanitary practices.
Probabilistic Skill of Subseasonal Precipitation Forecasts for the East Africa–West Asia Sector during September–May

The skill of submonthly forecasts of rainfall over the East Africa–West Asia sector is examined for starts during the extended boreal winter season (September–April) using three ensemble prediction systems (EPSs) from the Subseasonal-to-Seasonal (S2S) project. Forecasts of tercile category probabilities over the common period 1999–2010 are constructed using extended logistic regression (ELR), and a multimodel forecast is formed by averaging individual model probabilities. The calibration of each model separately produces reliable probabilistic weekly forecasts, but these lack sharpness beyond a week lead time. Multimodel ensembling generally improves skill by removing negative skill scores present in individual models. In addition, the multimodel ensemble week-3–4 forecasts have a higher ranked probability skill score and reliability compared to week-3 or week-4 forecasts for starts in February–April, while skill gain is less pronounced for other seasons. During the 1999–2010 period, skill over continental subregions is the highest for starts in February–April and for starts during El Niño conditions and MJO phase 7, which coincides with enhanced forecast probabilities of above-normal rainfall. Overall, these results indicate notable opportunities for the application of skillful subseasonal predictions over the East Africa–West Asia sector during the extended boreal winter season.
Closed-Loop Supply Chain Adoption and The Mediating Effect of Green Capabilities - Evidence from Malaysia

The concept of a closed-loop supply chain (CLSC) is concerned with the recovery of value from returned consumer products via resales. The rapidness of economic growth gives manufacturers no option but to shorten the product life cycle. Consequently, new versions following product upgrades happen too fast, increasing product returns in the form of End-of-Life (EOL) or End-of-Use returns. This issue has become crucial with a lack of processes for effectively handling product returns in Malaysia; thus, firms often use a third party, although this is considered improper by global standards. Therefore, this research aims to clarify the connection between Institutional Theory and the Natural Resource-Based View (NRBV) Theory in light of CLSC adoption in Malaysia. The findings highlight the role of government in overpowering competitors and customers in adopting a CLSC. The study’s limitations include presenting a formation of ideas that haven’t been previously linked in a research framework, setting the stage for more research in this area.
Brief report: Employees’ perceptions of stress and support during a pandemic mandated telework

COVID-19 has forced the knowledge-based workforce into full-time remote work, amplifying every-day stressors. The crisis has resulted in employees having to juggle work and home life simultaneously, while forcing many organizations with little to no experience to implement and manage teleworking. This brief study explores employee perceived stress as it relates to perceived support and age within an American workforce during the COVID-19 pandemic. In a global era of uncertainty and crisis, the findings suggest that employees’ perceived stress is negatively related to age and perceived organizational support, but not related to perceived supervisor support. The pre-pandemic world will likely be a way of the past. Organizations across sectors now have a need to ensure that perceived organizational support is not neglected during the pandemic to ensure that these employers are poised to manage the aftermath.
Electrooxidation of Hypercoordinated Derivatives of Silicon and Reactivity of Their Electrogenerated Cation Radicals: 1-Substituted Silatranes

Electrochemical oxidation of 1-R-substituted silatranes 1 (R = Me, vinyl, (CH2)2CN, CH2Ph, CH2(C10H7), Ph, C6H4Me, p-Cl-C6H4, Cl)—classical representatives of pentacoordinated silicon compounds—and the formation of their short living cation radicals upon reversible or quasi-reversible one-electron withdrawal were studied by means of cyclic and square-wave voltammetry, faradaic impedance spectroscopy and real-time temperature-dependent EPR spectroelectrochemistry supported by DFT B3PW91/6-311++G(d,p) (C-PCM, acetonitrile) calculations. The main reaction responsible for the decay of 1+• is shown to be their deprotonation, and ways of increasing the stability of these species are proposed.
Mixed coherent states in coupled chaotic systems: Design of secure wireless communication

A general coupling design is proposed to realize a mixed coherent (MC) state: coexistence of complete synchronization, antisynchronization, and amplitude death in different pairs of similar state variables of the coupled chaotic system. The stability of coupled system is ensured by the Lyapunov function and a scaling of each variable is also separately taken care of. When heterogeneity as a parameter mismatch is introduced in the coupled system, the coupling function facilitates to retain its coherence and displays the global stability with renewed scaling factor. Robust synchronization features facilitated by a MC state enable to design a dual modulation scheme: binary phase shift key (BPSK) and parameter mismatch shift key (PMSK), for secure data transmission. Two classes of decoders (coherent and noncoherent) are discussed, the noncoherent decoder shows better performance over the coherent decoder, mostly a noncoherent demodulator is preferred in biological implant applications. Both the modulation schemes are demonstrated numerically by using the Lorenz oscillator and the BPSK scheme is demonstrated experimentally using radio signals.
Perceived COVID-19 stress and online aggression among Chinese first-year college students: a moderated mediation model

Purpose Few studies have explored factors that may account for potential mechanisms between perceived coronavirus disease 2019 (COVID-19) stress and online aggression. The current study examined a moderated mediation model with anxiety as a mediator and perceived anonymity as a moderator. Methods A cross-sectional study was conducted. 3,069 participants across China completed scales assessing perceived COVID-19 stress, anxiety, online aggression, and perceived anonymity. Results Perceived COVID-19 stress was positively related to online aggression. The association between perceived COVID-19 stress and online aggression was mediated by anxiety. Besides, the relationship between perceived COVID-19 stress and online aggression, as well as the relationship between anxiety and online aggression were moderated by perceived anonymity. Conclusion This study explains the possible potential mechanisms for reducing online aggression in the context of COVID-19. In order to intervene in online aggression, psychological strategies are supposed to be drawn to reduce anxiety and perceived anonymity.
Teachers’ emotional consequences of COVID-19 pandemic in the context of their relationship with the school principal

ABSTRACT This study aims to investigate teachers’ perspectives regarding the emotional consequences of the COVID-19 pandemic and their coping strategies, in the context of their relationship with the principal. The study posed three questions: (1) What emotions and feelings are described by teachers during the COVID-19 pandemic? (2) How do the teachers perceive their relationship with the principal in the context of their emotional experience? (3) What strategies did the teachers employ in order to handle their distress during the COVID-19 pandemic? Based on 14 semi-structured interviews with Israeli teachers, three key themes were found. (1) Teachers who experienced burnout and a lack of motivation. (2) Teachers who faced stress and work overload due to technical and pedagogical challenges. (3) Teachers who described experiencing professional growth and emphasised the significance of a supportive relationship with the principal. The findings provide valuable insights and suggest practical implications for supporting teachers during challenging times.
Mitigation of attacks and errors on community structure in complex networks

The community structure is one property of complex networks and depicts the potential functionality of networked systems. Attacks and errors exist broadly in daily life, and the tolerance or the robustness of networks against these failures is crucial to systems. The robustness of communities has drawn a lot of attention in recent studies. Intuitively, a robust community should keep much similarity with the original partition under structural fluctuations. Most previous studies focused on evaluating the robustness of communities through the fraction of correct-detected members. However, the ability of this criterion in reflecting the variation of integral network communities is weak, and several specific structures tend to get the same evaluating value in terms of this criterion. In this paper, we propose a metric (RNMI) to evaluate the community robustness based on the normalized mutual information. Then, a simulated annealing algorithm is devised to mitigate the damage on communities under attacks or errors. Experimental results on various networks show that the robustness of communities can be improved while greatly preserving the intrinsic allocation. Furthermore, we study the different optimal structures against attacks and errors to reveal the uncorrelation between them, and design a weighed metric to obtain balanced optimal solutions.