Miracle-dz/UniFAR-FTUs huggingface dataset:
Source models of the Harzer explosion from regional observations of fundamental-mode and higher mode surface waves

Abstract For shallow source depths, the moment-tensor elements with isotropic radiation patterns, M zz and M xx + M yy , are not resolvable in moment-tensor inversions of long-period surface-wave data because their respective Green9s functions have similar frequency dependence. Examination of Green9s functions at higher frequencies shows that, while resolution for some momenttensor elements improves, it is still not possible to resolve the isotropic-radiating moments from fundamental-mode data recorded at regional distances. On the other hand, the addition of higher mode Rayleigh-wave amplitudes can improve the resolution of these moments significantly, since there are appreciable differences between the higher mode Green9s functions. An extension of Romanowicz9s algorithm is presented to invert fundamental-mode and higher mode data for the second-order moment tensor. A source of “noise” in the estimation of the moment tensor for underground explosions is the spallation of geologic strata at ground zero, since this too can be a significant source of higher modes. The inversion proposed in this paper accounts for possible higher mode excitation due to spall using the source model of Day et al . The inversion is applied to regional recordings of the Harzer explosion of 6 June 1981 at the Nevada Test Site. The results of the inversion demonstrate a trade-off between the second-order moment tensor representation and the single, directed force used to represent spall. Observations and numerical simulations of spall provide estimates of spall source parameters, which in turn constrain the moment-tensor representation of Harzer. The results of this study demonstrate the clear need for observations to characterize the spall source associated with underground explosions. Furthermore, they demonstrate the potential benefit of using higher modes to refine estimates of the explosion moment with reduced uncertainties compared to moment determinations from fundamental-mode data alone.
IMPROVING COMPANY PERFORMANCE IN RURAL AREAS: INSTITUTIONAL THEORY APPROACH

Development in rural areas has become the focus of governments in many countries. This study aims to analyze the effect of institutional pressure and strategic orientation on financial performance. This study also examines social performance as a mediating variable. The research was conducted at village institutions, namely Village-Owned Enterprises in four regions in Riau Province, Indonesia. A total of 239 Village-Owned Enterprises were studied with 526 respondents, namely VOE managers. Questionnaires were distributed directly and via the internet. Questionnaires were sent via WhatsApp to the VOE manager. Structural analysis of the equation model with Warp PLs shows that all hypotheses are supported. Institutional pressure and strategic orientation affect financial performance, and social performance is a mediator variable Keywords: institutional pressure, strategic orientation, social performance, financial performance
The association between gut microbiome and PCOS: evidence from meta-analysis and two-sample mendelian randomization

Background Increasing evidence from observational studies and clinical experimentation has indicated a link between the gut microbiotas (GMs) and polycystic ovary syndrome (PCOS), however, the causality and direction of causality between gut microbiome and PCOS remains to be established. Methods We conducted a comprehensive search of four databases–PubMed, Cochrane Library, Web of Science, and Embase up until June 1, 2023, and subjected the results to a meta-analysis. In this study, a bidirectional two-sample Mendelian randomization (MR) analysis was employed to investigate the impact of gut microbiota on polycystic ovary syndrome (PCOS). The genome-wide association study (GWAS) data for PCOS comprised 113,238 samples, while the GWAS data for gut microbiota were derived from the MiBioGen consortium, encompassing a total sample size of 18,340 individuals. As the largest dataset of its kind, this study represents the most comprehensive genome-wide meta-analysis concerning gut microbiota composition to date. Single nucleotide polymorphisms (SNPs) were selected as instrumental variables at various taxonomic levels, including Phylum, Class, Order, Family, and Genus. The causal associations between exposures and outcomes were assessed using four established MR methods. To correct for multiple testing, the false discovery rate (FDR) method was applied. The reliability and potential biases of the results were evaluated through sensitivity analysis and F-statistics. Results The meta-analysis incorporated a total of 20 studies that met the criteria, revealing a close association between PCOS and specific gut microbiota species. As per the results from our MR analysis, we identified six causal associations between the gut microbiome and polycystic ovary syndrome (PCOS). At the genus level, Actinomyces (ORIVW = 1.369, FDR = 0.040), Streptococcus (ORIVW = 1.548, FDR = 0.027), and Ruminococcaceae UCG-005 (ORIVW = 1.488, FDR = 0.028) were identified as risk factors for PCOS. Conversely, Candidatus Soleaferrea (ORIVW = 0.723, FDR = 0.040), Dorea (ORIVW = 0.580, FDR = 0.032), and Ruminococcaceae UCG-011 (ORIVW = 0.732, FDR = 0.030) were found to be protective factors against PCOS. Furthermore, the MR-PRESSO global test and MR-Egger regression indicated that our study results were not affected by horizontal pleiotropy (p > 0.05). Finally, the leave-one-out analysis corroborated the robustness of the MR findings. Conclusion Both our meta-analysis and MR study indicates that there is a causal relationship between the gut microbiome and PCOS, which may contribute to providing novel insights for the development of new preventive and therapeutic strategies for PCOS.
Autophagy Inhibition with Chloroquine Increased Pro-Apoptotic Potential of New Aziridine-Hydrazide Hydrazone Derivatives against Glioblastoma Cells

Tumor therapy escape due to undesired side effects induced by treatment, such as prosurvival autophagy or cellular senescence, is one of the key mechanisms of resistance that eventually leads to tumor dormancy and recurrence. Glioblastoma is the most frequent and practically incurable neoplasm of the central nervous system; thus, new treatment modalities have been investigated to find a solution more effective than the currently applied standards based on temozolomide. The present study examined the newly synthesized compounds of aziridine–hydrazide hydrazone derivatives to determine their antineoplastic potential against glioblastoma cells in vitro. Although the output of our investigation clearly demonstrates their proapoptotic activity, the cytotoxic effect appeared to be blocked by treatment-induced autophagy, the phenomenon also detected in the case of temozolomide action. The addition of an autophagy inhibitor, chloroquine, resulted in a significant increase in apoptosis triggered by the tested compounds, as well as temozolomide. The new aziridine–hydrazide hydrazone derivatives, which present cytotoxic potential against glioblastoma cells comparable to or even higher than that of temozolomide, show promising results and, thus, should be further investigated as antineoplastic agents. Moreover, our findings suggest that the combination of an apoptosis inducer with an autophagy inhibitor could optimize chemotherapeutic efficiency, and the addition of an autophagy inhibitor should be considered as an optional adjunctive therapy minimizing the risk of tumor escape from treatment.
Factors Influencing Suicidal Ideation in Korean Youth: A Secondary Data Study Using Longitudinal Data from the Korean Youth Panel Survey

Background: Suicide is one of the most serious social problems in Korea. We examined suicidal ideation factors among Korean youth. Methods: For risk factor identification, data from the 2008 and 2018 Korean Youth Panel Survey were analyzed (n =6,568) using univariate multiple logistic regression analysis. Negative life events, feelings of hopelessness, early-life adversity, alcohol consumption, smoking, counseling experience, perceived stress, and current health status were independent variables, whereas suicidal ideation was the dependent variable. Results: Proximal (negative life events and feelings of hopelessness), distal (early-life adversities significantly influenced suicidal ideation), and health-related (alcohol consumption, counseling experience, perceived stress, and current health status) factors significantly influenced suicidal ideation among Korean youth. Conclusion: Mental health professionals must include distal risk factors, along with the common proximal and health-related risk factors, to provide targeted interventions.
Laser absorption spectroscopy for plasma-assisted thermochemical treatment. Part II.: Impact of the carbon and water contaminants on a low-pressure N2–H2 discharge

The density evolution of HCN , NH3 , H2O and CO molecules over time was monitored by laser absorption spectroscopy in a low pressure DC pulsed discharge in N2–H2 gas mixtures with addition of CH4 or O2. The discharge was maintained in an industrial-scale, active screen (AS) plasma nitrocarburizing (ASPNC) reactor with a steel AS. The measured species densities were analysed using a simplified kinetic model that includes three characteristic times for chemical processes in the ASPNC reactor. The shortest time (1–4 min) was associated with the gas residence time in the reactor, the middle one (about 20 min) was assigned to surface reactions on the AS and workload, whereas the largest one (about 3–5 h) was assigned to surface reactions on the cold reactor walls. The work highlights the importance of monitoring the gas composition during plasma nitrocarburizing processes in order to maintain defined treatment conditions and compensate for continuously changing chemical kinetics at the internal reactor surfaces.
Detection of Traffic Sign using Inception V3 in Comparison with VGG-19 to Measure Accuracy

To find traffic signs using Inception V3 and compare the performance VGG-19 algorithm for the detection of traffic signs. The sample size is estimated using G-power software, a total of 44,028 samples are acquired by fixing the parameters such as power and error rate as 0.80 and 0.05 respectively. The traffic sign detection consists of 44,028 sample images of different traffic signs used for training 38,302 (80%) and testing 5,726 (20%) the predictive model in python and the statistical analysis is performed in SPSS. The inception V3 algorithm is used and compared with the VGG-19 algorithm. The predictive model using the Inception V3 results in a higher accuracy of 94.38% than the VGG-19 based model with an accuracy of 90.12% and with a significance value of p=0.123 (p<0.05). The results show that the Inception V3 based model provides significantly better results than the VGG-19 based model in the detection of traffic signs.
Ultimate bearing capacity of shallow foundations under inclined and eccentric loads. I: Purely cohesive soil

The problem of determining the bearing capacity of a strip footing resting on the surface of a homogeneous half space and subjected to an inclined, eccentric load is solved within the framework of the yield design theory, assuming the soil to be purely cohesive according to Tresca's strength criterion. The soil foundation interface is also cohesive, in terms of the homologous strength criterion. Both the static and kinematic approaches of the yield design theory are used to derive lower and upper bounds for the ultimate bearing capacity. For an inclined centered load, an almost exact solution is derved; for increasing values of the load eccentricities, the ultimate bearing capacity can only be bracketed but neverthless determined within a sufficient degree of accuracy from an engineering standpoint. In a companion paper, the same problem is solved for a soil and an interface with a tension cut-off. These two solutions represent extreme conditons for the tensile resistance of the purely cohesive soil and could be used to bracket the variations of the bearing capacity as a function of the soil tensile strength
On Generalized Pata Type Contractions

In this paper, the existence of fixed point for Pata type Zamfirescu mapping in a complete metric space is proved. Our result give existence of fixed point for a wider class of functions and also prove the existence of best proximity point to the result on “A fixed point theorem in metric spaces”, given by vittorino Pata.
Concept of an Intervention for Sustainable Weight Loss in Postmenopausal Women with Overweight—Secondary Analysis of a Randomized Dietary Intervention Study

Introduction: The approach of an individual diet has great potential for sustainable weight reduction. Social support, participation and empowerment are also key factors for high motivation and compliance. So, the impact of an individual diet in combination with group sessions on weight loss in postmenopausal women with overweight was investigated. Methods: In this reanalysis of a controlled intervention study, postmenopausal women (n = 54; BMI 30.9 ± 3.4 kg/m2; 59 ± 7 years) were recruited receiving an energy restricted diet for 12 weeks, followed by a six-month follow-up phase. The women received 51 individual meal plans based on their habits and were trained in four group sessions. Results: Forty-six women completed the intervention phase, and 29 completed the follow-up. Average weight loss was −5.8 ± 3.0 kg (p < 0.001) after 12 weeks and was still significant at follow-up (−4.9 ± 5.4 kg, p < 0.001). Also, decreases in fat-free mass (−1.1 ± 1.2 kg, p < 0.001) and resting energy expenditure (−1096 ± 439 kJ/24 h, p < 0.001) were observed. Conclusions: The individual nutrition approach with a focus on nutritype in combination with group sessions was effective for long-lasting weight loss in postmenopausal women. An important factor is close individual and group support.
Introduction To Surface And Superlattice Excitations

Thank you very much for reading introduction to surface and superlattice excitations. Maybe you have knowledge that, people have look hundreds times for their chosen novels like this introduction to surface and superlattice excitations, but end up in harmful downloads. Rather than enjoying a good book with a cup of coffee in the afternoon, instead they juggled with some harmful bugs inside their computer.
Environmental Planning and Non-Communicable Diseases: A Systematic Review on the Role of the Metabolomic Profile

Non-communicable diseases (NCDs) are the major cause of death worldwide and have economic, psychological, and social impacts. Air pollution is the second, contributing to NCDs-related deaths. Metabolomics are a useful diagnostic and prognostic tool for NCDs, as they allow the identification of biomarkers linked to emerging pathologic processes. The aim of the present study was to review the scientific literature on the application of metabolomics profiling in NCDs and to discuss environmental planning actions to assist healthcare systems and public managers based on early metabolic diagnosis. The search was conducted following PRISMA guidelines using Web of Science, Scopus, and PubMed databases with the following MeSH terms: “metabolomics” AND “noncommunicable diseases” AND “air pollution”. Twenty-nine studies were eligible. Eleven involved NCDs prevention, eight addressed diabetes mellitus, insulin resistance, systemic arterial hypertension, or metabolic syndrome. Six studies focused on obesity, two evaluated nonalcoholic fatty liver disease, two studied cancer, and none addressed chronic respiratory diseases. The studies provided insights into the biological pathways associated with NCDs. Understanding the cost of delivering care where there will be a critical increase in NCDs prevalence is crucial to achieving universal health coverage and improving population health by allocating environmental planning and treatment resources.
Cosine similarity-based adversarial process

An adversarial process between two deep neural networks is a promising approach to train a robust model. In this paper, we propose an adversarial process using cosine similarity, whereas conventional adversarial processes are based on inverted categorical cross entropy (CCE). When used for training an identification model, the adversarial process induces the competition of two discriminative models; one for a primary task such as speaker identification or image recognition, the other one for a subsidiary task such as channel identification or domain identification. In particular, the adversarial process degrades the performance of the subsidiary model by eliminating the subsidiary information in the input which, in assumption, may degrade the performance of the primary model. The conventional adversarial processes maximize the CCE of the subsidiary model to degrade the performance. We have studied a framework for training robust discriminative models by eliminating channel or domain information (subsidiary information) by applying such an adversarial process. However, we found through experiments that using the process of maximizing the CCE does not guarantee the performance degradation of the subsidiary model. In the proposed adversarial process using cosine similarity, on the contrary, the performance of the subsidiary model can be degraded more efficiently by searching feature space orthogonal to the subsidiary model. The experiments on speaker identification and image recognition show that we found features that make the outputs of the subsidiary models independent of the input, and the performances of the primary models are improved.
Maximum Likelihood Estimate in Discrete Hierarchical Log-Linear Models

Hierarchical log-linear models are essential tools used for relationship identification between variables in complex high-dimensional problems. In this thesis we study two problems: the computation and the existence of the maximum likelihood estimate (henceforth abbreviated MLE) in high-dimensional hierarchical log-linear models. When the number of variables is large, computing the MLE of the parameters is a difficult task to accomplish. A popular approach is to estimate the composite MLE rather than the MLE itself, that is, estimate the value of the parameter that maximizes the product of local conditional likelihoods. A more recent development is to choose the components of the composite likelihood to be local marginal likelihoods. We first show that the estimates obtained from local conditional and marginal likelihoods are identical. Second, we study the asymptotic properties of the composite MLE obtained by averaging the local estimates, under the double asymptotic regime, when both the dimension p and sample size N go to infinity. We compare the rate of convergence to the true parameter of the composite MLE with that of the global MLE under the same conditions. We also look at the asymptotic properties of the composite MLE when p is fixed and N goes to infinity and thus recover the same asymptotic results for p fixed as those of Liu and Ihler (2012). The existence of the MLE in hierarchical log-linear models has important consequences for statistical inference: estimation, confidence intervals and testing as we shall see. Determining
Professional Stress Prevention Program for Employees Working Remotely in Crisis

: This article highlights the problem of professional stress of workers in the mass transition to remote work caused by the difficult conditions of our time in a pandemic COVID-19. Based on the results of theoretical analysis of scientific literature, the classification of the main models of stress is given. The content, features, factors, consequences of professional stress of workers working remotely in general in a pandemic in particular are highlight. Personal indicators of professional stress of employees are revealed. The role of personal qualities of employees in the emergence of professional stress as a buffer that mediates the impact of stressors, enhancing their action, or inhibiting it, negatively affecting the mental health, psychological safety of employees and the quality of their professional activities are shown. The results of an empirical study show that the influence of stressors, which is significantly enhanced in the forced transition to remote work, causing violations in the communicative, emotional, volitional and need-motivational spheres of personality of employees in general and depending on gender and age and professional features of employees in particular. The expediency of taking into account the personal characteristics of employees to prepare them for the prevention and overcoming of professional stress, developing the ability of employees to conscious and active stress management and counteracting stressors is stated. The article presents the components of the program of professional stress prevention for employees working remotely in crisis (cognitive, motivational, volitional, communicative). The data on approbation of the program is given, which testify to its positive influence on the dynamics of stress subjective perception. Prospects for further research aimed at large-scale implementation of the program in postgraduate education are outlined.
Neural Mechanisms Related to the Enhanced Auditory Selective Attention Following Neurofeedback Training: Focusing on Cortical Oscillations

Selective attention can be a useful tactic for speech-in-noise (SiN) interpretation as it strengthens cortical responses to attended sensory inputs while suppressing others. This cortical process is referred to as attentional modulation. Our earlier study showed that a neurofeedback training paradigm was effective for improving the attentional modulation of cortical auditory evoked responses. However, it was unclear how such neurofeedback training improved attentional modulation. This paper attempts to unveil what neural mechanisms underlie strengthened auditory selective attention during the neurofeedback training paradigm. Our EEG time–frequency analysis found that, when spatial auditory attention was focused, a fronto-parietal brain network was activated. Additionally, the neurofeedback training increased beta oscillation, which may imply top-down processing was used to anticipate the sound to be attended selectively with prior information. When the subjects were attending to the sound from the right, they exhibited more alpha oscillation in the right parietal cortex during the final session compared to the first, indicating improved spatial inhibitory processing to suppress sounds from the left. After the four-week training period, the temporal cortex exhibited improved attentional modulation of beta oscillation. This suggests strengthened neural activity to predict the target. Moreover, there was an improvement in the strength of attentional modulation on cortical evoked responses to sounds. The Placebo Group, who experienced similar attention training with the exception that feedback was based simply on behavioral accuracy, did not experience these training effects. These findings demonstrate how neurofeedback training effectively improves the neural mechanisms underlying auditory selective attention.