Miracle-dz/UniFAR-FTUs huggingface dataset:
“Resistance!”: Collective Action Cues in Conspiracy Theory-Endorsing Facebook Groups

Conspiracy theories on social media have been suspected of contributing to mobilization and radicalization. Yet, few studies have examined the prevalence of psychological variables that may serve to motivate normative and non-normative collective action in this material. Drawing from the “social identity model of collective action,” the current study uses a mixed-methods approach to examine the prevalence of collective action cues in conspiracy theory-endorsing social media spaces. Towards this end, I examined four German Facebook groups (Covid-19-Skeptic, Far-Right, Chemtrail, and Political Affairs) during the first months of the Covid-19 pandemic. The results of qualitative content analysis (N = 828 posts), a hierarchical cluster analysis, and the examination of popularity cues showed that: (a) collective action cues were frequent; (b) most posts transmitted alternative views (Cluster 1) or absolutist ideologies (Cluster 2) with few collective action cues—yet, more than one-third of the posts were either mobilizing (Cluster 3) or wrathful (Cluster 4), entailing multiple collective action cues including cues theoretically linked to non-normative action; (c) mobilizing and wrathful posts were more engaging than alternative views and absolutist ideologies; (d) the types of posts and levels of engagement varied between the examined groups such that the Chemtrail and the Far-Right group disseminated more content with a higher mobilizing potential. The Far-Right group was also the most active in responding to its members. The results of this study are novel in that they demonstrate the prevalence of cues that have been linked to non-normative collective action in psychological research within conspiracy theory-endorsing Facebook groups.
Seasonal occurrence of Riptortus pedestris (Hemiptera: Alydidae) attacking mungbean in Southern PART of Bangladesh

The bean bug, Riptortus pedestris (Hemiptera: Alydidae) , is a polyphagous species that is an important pest of mungbean, soybean and other leguminous crops in Asian countries. As it is distributed in Asian countries, like Korea, Japan, China, India, and Taiwan and caused damage on leguminous crops, but the status of bean bug are still unknown in Bangladesh even though it is first recorded in mungbean ( Vigna radiata L) field during 2017 in our preliminary study. Therefore a series of field survey was conducted in southern part of the country during three consecutive seasons of 2018, 2019 and 2020 to know the pest status of bean bug and their intensity of infestation in mungbean. Three years study revealed that a new pest R. pedestris is recorded in mungbean field which causes damage on tender stem, leaf and pod. Adult and nymph R. pedestris occurrence began at first week of April in mungbean. Peak population densities of both nymphs (4-6 bugs/10 plants) and adults (5-7 bugs/10 plants) are recorded at mid-April. Then the number of bean bug gradually decreased in mugbean field. Seasonal average number of bean bug nymph and adult is 2.13-3.07 and 2.47-4.20 per plant. Nymph population is recorded from 15.33 to 22.67% plants where adults are found in 18.67 to 30.67% plants. The abundance of adult population significantly 64.27% increased in 2020 compare to 2018 cropping season while infestation of mungbean by nymph was also 47.88% increased. This is the first report of the occurrence of R. pedestris on mungbean in southern part of Bangladesh. Since pest abundance increasing day by day in southern part of the country, therefore more research should be recommended to assess crop loss by this pest and to develop appropriate management option.
Machine learning‐based test oracles for performance testing of cyber‐physical systems: An industrial case study on elevators dispatching algorithms

The software of systems of elevators needs constant maintenance to deal with new functionality, bug fixes, or legislation changes. To automatically validate the software of these systems, a typical approach in industry is to use regression oracles, which execute test inputs both in the software version under test and in a previous software version. However, these practices require a long test execution time and cannot be re‐used at different test phases. To deal with these issues, we propose Dispatching AlgoRIthm Oracle (DARIO), a test oracle that relies on regression machine‐learning algorithms to detect both functional and non‐functional problems of the system. The machine‐learning algorithms of this oracle are trained by using data from previously tested versions to predict reference functional and non‐functional performance values of the new versions. An empirical evaluation with an industrial case study demonstrates the feasibility of using our approach. A total of five regression learning algorithms were validated by using mutation testing techniques. For the context of functional bugs, the accuracy when predicting verdicts by DARIO ranged between 95% and 98%, across the different scenarios proposed. For the context of non‐functional bugs, were competitive too, having an accuracy when predicting verdicts by DARIO ranged between 83% and 87%.
Role of Chromium Versus Metformin Supplementations as Adjuvant for Ovulation Induction By Clomiphene Citrate in Infertile Patients With Polycystic Ovary Syndrome : Randomized Controlled Trial

Aim: This study aimed to explore the effect of chromium picolinate compared to Metformin supplementation with ovulation induction in polycystic ovary syndrome, In particular, its effect on insulin sensitivity, ovarian response and pregnancy rate. Materials and Methods: This study was conducted as a prospective study, aimed to compare the effect of Chromium and Metformin supplementations on ovulation rate in Polycystic ovary patients undergoing ovulation induction. The present study included 140 women divided into 2 groups each is 70 infertile women diagnosed as polycystic ovary syndrome according to Rotterdam criteria 2017: (oligo-ovulation or anovulation, clinical or biochemical signs of hyperandrogenism, polycystic ovaries on ultrasound). Results: Fasting blood sugar (FBS) and fasting insulin level were significantly decreased in metformin group than in Chromium picolinate group after 3 months of treatment ( p=0.006 ) ( p=0.026 ) respectively. Testosterone significantly decreased in both groups at follow up as compared to basal level ( P-value <0.001, <0.001 respectively with no significant difference between the studied groups regarding testosterone reduction ( P-value=0.416 ) after 3 months of treatment. The two study groups were not significantly different regarding ovulation and pregnancy rates( P-value 0.157, 0.550 ) respectively after 3 months of treatment. The patients who received metformin experienced more side effects compared to those receiving chromium picolinate ( p=0.001 ). Conclusion: I n view of the aforementioned findings, we recommend that metformin could be replaced by chromium picolinate in some PCOS patients, as its better tolerated than metformin due to lower side effects and no significant differences were observed between the two groups regarding ovulation and pregnancy rates.
Inflation Dynamics in Advanced Economies: A Decomposition into Cyclical and Non-Cyclical Factors

Inflation and unemployment rate were largely disconnected between 2000 and 2019 in advanced economies. We decompose core inflation into two parts based on the cyclical sensitivity of CPI components and document several salient facts: (i) both the cyclical and non-cyclical parts had surges across advaced economies in 2011, when unemployment rates had limited changes; (ii) the non-cyclical part had a downward trend between 2012 and 2019, which existed across countries, sectors, goods, and services; (iii) global indexes such as oil price, shipping costs, and a global supply chain pressure index do not explain the downward trend; and (iv) the cyclical part, after controlling for the impact of economic slack, also had a downward trend between 2012 and 2019. These patterns help disentangle competing explanations for the disconnect between inflation and unemployment rate. The approach has potential to help understand forces shaping price pressures during the pandemic and in the post-pandemic period ahead. JEL Classification Numbers: E30, E31, E32
The Influences of Services Marketing Mix (7ps) on Loyalty, Intentions, and Profitability in the Egyptian Travel Agencies: The Mediating Role of Customer Satisfaction

ABSTRACT Services marketing mix (7Ps) has a significant role in promoting customer’s satisfaction and loyalty. The present study, using structural equation modeling WarpPLS version (7) is used, aims at investigating the influences of (7Ps) on tourist’s loyalty. In addition, it measures the mediator effect of tourist’s satisfaction, consumer purchase intentions, and company profitability. Findings revealed that all dimensions have positively affected tourist’s satisfaction directly, and tourist’s loyalty indirectly. Consumer purchase intentions and company profitability are partial mediators between tourist’s satisfaction and tourist’s loyalty. The present study provides a deep understanding of services marketing mix strategies that stay needed for keeping a long-term link between managers of travel services and tourists. Several implications for travel agencies managers were suggested to achieve customer loyalty and consequently guarantee their company profitability.
Respons Pengguna Instagram terhadap Periklanan Paid Promote di Instagram dengan Metode CRI Berkonsep AISAS

Instagram is a social media that has a shopping feature. Instagram can be used for digital advertising, and among them is paid promotion. Paid promotion is a service to promote goods/services on social media. This service offers advantages such as a broad market segment, low cost, and easy technical implementation. Many online shops are willing to spend a lot of money to be promoted. Unfortunately, online shop owners usually do not know how Instagram users respond when they see a paid promotion. Therefore, the purpose of this study is to find out how Instagram users respond to the paid promotion on Instagram. User response data was taken from a questionnaire, then analyzed using the CRI method with the AISAS concept by using 4 models: AISAS, AISS, AIAS, and AIS. As the result, four models showed the CRI is below 50% (AISAS: 2,8%; AIAS: 3%; AISS: 4,5%; AIS: 8,4%). Considering the result, the respondents do not give a good response to the paid promotion service.
Effect of integrated nutrient management on black gram (Vigna mungo (L.) growth, yield and subsequent soil fertility in middle gangetic plains of India

The field trial was conducted during the Kharif 2019 on the research farm of TCA Dholi at the Dr. Rajendra Prasad Central Agriculture University Pusa campus in Samastipur (Bihar). The test was conducted in Factorial RBD and to investigate Effect of Integrated Nutrient Management on black gram ( Vigna mungo (L.) nutrient treatment.
Environmental DNA as a tool for biodiversity monitoring in aquatic ecosystems – a review

The monitoring of changes in aquatic ecosystems due to anthropogenic activities is of utmost importance to ensure the health of aquatic biodiversity. Eutrophication in water bodies due to anthropogenic disturbances serves as one of the major sources of nutrient efflux and consequently changes the biological productivity and community structure of these ecosystems. Habitat destruction and overexploitation of natural resources are other sources that impact the equilibrium of aquatic systems. Environmental DNA (eDNA) is a tool that can help to assess and monitor aquatic biodiversity. There has been a considerable outpour of research in this area in the recent past, particularly concerning conservation and biodiversity management. This review focuses on the application of eDNA for the detection and relative quantification of threatened, endangered, invasive and elusive species. We give a special emphasis on how this technique developed in the past few years to become a tool for understanding the impact of spatial-temporal changes on ecosystems. Incorporating eDNA based biomonitoring with advances in sequencing technologies and computational abilities had an immense role in the development of different avenues of application of this tool.
Lowering the Turnaround time for Aircraft component MRO services: A case study at KLM Engineering & Maintenance

In this thesis a framework is built to find flow improvement measures to lower the turnaround time for aircraft component MRO processes. This framework is tested in a case study at KLM EM the 'TAT-waiting time' and the 'On time start', to monitor the waiting time. Furthermore, it was found that the shop has a single piece flow, the process follows a single path, the equipment is not critical and that the work-scope is determined during the process. When these characteristics are put in the flow improvement framework, it can be seen that lean, lean in MRO and quick response manufacturing fit best for the case process. However, in the case process the work-scope determination should be moved forward to be able to plan the work better and create a pull process. The selected improvement theories were researched in more detail on flow improvement measures. By using a simulation model it was found that with a supermarket system with a capacity constraint, an increase in technician capacity, lower disruption times and amounts, it is possible to lower the total TAT of the case process to 10 days on average. It can therefore be concluded that the improvement framework works for this case. For further research it is recommended to investigate the use of other simulation software and expand the simulation model to the total component MRO supply chain. Furthermore, it is advised to test the framework on other processes within KLM E&M and at other aircraft component MRO companies.
Comparative Review of Statistical Parameters for Men's and Women's Basketball Leagues in Serbia

Basketball is one of the most popular sports. During a basketball game, statisticians note a large amount of information, helping coaches and players to improve their game and to analyse opponents in order to prepare for the following games. Due to amount and complexity of the information, basketball is the ideal discipline for the application of data mining techniques, especially neural networks that enable one to extract conclusions and knowledge from these data. In this paper, we compared the First senior leagues for men and for women in Serbia during the 2011/2012 season, and from these statistics, we calculated influence of certain parameters on a game's outcome. We concluded that the most influential parameter, in both leagues, is the offensive rebound. In men basketball then follows the three-point shot, the two-point shot and the one-point shot. In women's basketball, after the defensive rebound, the two-point shot follows, and then turnovers.
Pulmonary Veins Morphometric Characteristics and Spatial Orientation Influence on Its Cryoballoon Isolation Results

The aim of this paper is to evaluate the effect of pulmonary vein (PV) morphometric characteristics and spatial orientation on the results of cryoballoon ablation (CBA). Methods: A randomized, prospective, single-center controlled study was conducted, enrolling 230 patients with drug-refractory atrial fibrillation (AF). We compared procedural and long-term outcomes in patients who underwent their first procedure of pulmonary vein isolation (PVI) for AF with either radiofrequency ablation (RFA) (n = 108) or CBA (n = 122) and assessed their interaction with the different pattern of PV anatomy, morphometric characteristics, and spatial orientation. The primary efficacy endpoint was any documented atrial arrhythmia recurrence (AF, atrial flutter, or atrial tachycardia) lasting over 30 s during a 12-month follow-up after a 90-day blanking period and discontinuation of antiarrhythmic drugs. The procedure’s endpoint was the achievement of PVI. Before the intervention, all patients underwent computed tomography (CT) to assess the PV anatomical variant, maximum and minimum diameters of the PV’s ostia, their cross-sectional area, orifice ovality index, and PV tilt angles. Results: The mean follow-up period was 14 months (12; 24). Long-term efficacy in the cryoablation group was 78.8% and in the RFA group—83.3% (OR = 0.74; 95% CI 0.41–1.3; p = 0.31). The RFA results did not depend on PV anatomy. The «difficult» occlusion of the right inferior PV (RIPV) occurred in 12 patients and was associated with a more horizontal PV position in the frontal plane; the mean tilt angle was −15.2 ± 6.2° versus −26.5 ± 6.3° in the absence of technical difficulties (p = 0.0001). In 11 cases (9%), during ablation of the right superior PV (RSPV), phrenic nerve injury (PNI) occurred and was associated with the maximum and minimum RSPV diameter, 20.0–20.4 mm (OR = 13.2; 95% CI: 4.7–41.9, p < 0.05) and 17.5–20 mm (OR = 12.5; 95% CI 3.4–51, p < 0.05), respectively. Patients with arrhythmia recurrence were characterized by significantly larger diameters and ovality of the left superior PV (LSPV). The spatial orientation of the PV does not affect the long-term results of cryoablation. Conclusion: Preprocedural evaluation of PV morphology and orientation using cardiac CT might help choose the optimal technology for the individual patient.
Skipout: An Adaptive Layer-Level Regularization Framework for Deep Neural Networks

Regularization methods can surprisingly improve the generalization ability of deep neural networks. Among numerous methods, the branch of Dropout regularization is very popular in practice. However, Dropout-like regularization variants have some deficiencies: blindness of regularization, dependency of regularization on layer types, and how to determine the parameters of regularization. In this paper, we propose Skipout framework to tackle these drawbacks by breaking the chain of co-adapted units in consecutive layers. Skipout is a layer-level regularization method that categorizes the layers of a deep network adaptively during training. It divides them into robust and critical layers based on the network architecture and the given task. Instead of turning off some units as in Dropout methods, Skipout recognizes the robust layers and skips them out untrained while sustaining to train the critical layers. The trick of Skipout is in backpropagating the cumulated residual errors via the robust layers, where the activation functions of their units are temporarily set to identity. The units of robust layers are dually activated: by their own functions in the forward pass and by identity in the backward pass. Therefore, Skipout takes advantage of vanishing gradient solutions via robust layers. Moreover, its implementation is simple and applicable to both convolutional and fully-connected layers. Experiments on diverse benchmark datasets and different deep models confirm that Skipout framework can improve the generalization performance of deep neural networks.
Alkalinization and moist heat treatments of substrates for cultivation of edible mushrooms in pupunha and cocoa residues

In search of a healthier diet, the consumption of edible mushrooms has been expanding, as well as the use of agro-industrial residues for cultivation and the use of less costly techniques. In this work, residues of pupunha palm ( Bactris gasipaes Kunth.) and cocoa ( Theobroma cacao L.) were tested as a substrate to produce Pleurotus pulmonarius CCB19, as well as two forms of disinfection: Moist heat (autoclaving) and alkalinization with calcium hydroxide solution. Substrate compositions based on the pupunha palm residue (P) mixed with the cocoa testa (T) were tested in three different proportions (100% P; 90% P + 10% T; and 80% P + 20%T). The production time, biological efficiency (BE), production rate (PR), and diameter of the mushroom caps were analyzed. These parameters did differ neither with substrates formulations, nor with disinfection methods. The results showed the potential of P and T to be used as substrate in mushroom cultivation and alkalinization technique is as effective as autoclaving for substrate disinfection. From the study, it is concluded that alkalinization technique is a good alternative for the production of edible mushrooms by the small rural producer, since it is less expensive and easier to handle.
Pin the Protein on the Membrane: Using Numerical Simulations to Explore Membrane-Protein Systems

Pin the Protein on the Membrane: Using Numerical Simulations to Explore Membrane-Protein Systems Kayla Sapp Chair of the Supervisory Committee: Professor Lutz Maibaum Department of Chemistry The structure of the membrane gives rise to important biological phenomena. In this dissertation we focus on the shape of the membrane and its interactions through two different coupling schemes to membrane bound proteins. We develop a model based on the continuum description of the membrane that is used to investigate height-coupled and curvature-coupled membrane-protein systems. For these systems we use coupled Langevin equations to model the dynamics for the Fourier modes of the membrane and protein position in the xy-plane. We investigate similarities and differences in these two coupling schemes in how they alter membrane fluctuations, protein-protein interactions, and lateral protein diffusion. We further expand on previous dynamic membrane-protein models by deriving from the FokkerPlanck formalism a consistent Langevin equations that accurately models the dynamics of systems with protein diffusing along the membrane surface. We investigate how the model differs from previous in the discussion of later protein diffusion.
Microbial quality and handling practices of raw cow milk in North Shewa Zone, Oromia, Ethiopia

Background: Milk is universally accepted as a complete diet that plays a key role to ensure food security. However, the quality of raw cow milk is affected at various stages due to inadequate dairy infrastructure and limited knowledge of hygienic handling practices. Thus, the study aimed to evaluate the microbial quality of raw cow milk and handling practices in the North Shewa zone, Oromia, Ethiopia. Methodology: Purposive sampling was used to select study districts and participants based on the available dairy production potential, milk market, and collection center. Four hundred participants were selected; 50 raw cow milk samples were collected from households and collection spots in study areas. Results: Microbial analysis indicated that the mean values of total cell counts were higher in households (4.836±0.206 in log10 CFU/ml) than 4.391±0.15 at collection spots. Similarly, the mean values of Staphylococcus aurous were 2.470±0.038 at the household level and 2.249±0.093 at collection spots. The mean values of E.coli, yeast count and mould count were however, higher at collection spots (5.414±0.100, 3.372±0.091, 2.670±0.037) than household level (3.343±0.122, 2.944±0.074, 2.479±0.039), respectively. Conclusions: The higher total counts and mean values of microbial loads of economic and public health significance; like Staphylococcus aurous and E. coli at household level and collection spots indicated poor hygienic raw cow milk handling practices. Therefore, awareness should be created among the dairy cattle producers and milk collectors to minimize economic losses through milk spoilage with soil microbes and the risk of consumer safety due to zoonotic pathogens.