Miracle-dz/UniFAR-FTUs huggingface dataset:
Differential Effects of the COVID-19 Pandemic on Crowdfunding Project Performance: Role of Project Design Features

COVID-19 (Corona Virus Disease 2019), as a global emergency, has significantly resulted in a downturn in the economy and is threatening the survival of business ventures. This study aims to explore how the online crowdfunding market, which serves as an important supplement for traditional financing channels, performs under this shock. Specifically, this study is interested in determining the extent to which online crowdfunding projects are affected and investigating factors that help projects to alleviate the negative effects. Based on a novel panel data set collected from kickstarter.com, we employ a regression-discontinuity-in-time design to empirically examine the impacts of the shock. The results showed that the pandemic threatens crowdfunding projects by decreasing both the number of backers and the amount of funds. Furthermore, we found that projects provide hedonic benefits (compared with utilitarian benefits), projects produced and delivered in digital form (compared with physical goods), and projects that adopt a narrative style with lower psychological distances are more likely to maintain the ability of fundraising.
ANTIBIOTIC SUSCEPTIBILITY PROFILE OF aureus AND BREASTFEEDING MOTHERS ATTENDING POSTNATAL CARE AT GENERAL *Abdullahi

Department of Microbiology, Umaru Musa Yaradua University Corresponding author ABSTRACT Several microorganisms may contaminate nipples of breastfeeding mothers and become potential to cause mastitis. The aim o susceptibility profile of Staphylococcus aureus and Pseudomonas aeruginosa from nipples of breastfeeding mothers. Fourty (40) samples were collected using sterile one use swab sticks from breast nipples of brea immunization unit of General Hospital Katsina. The samples collected were inoculated on Nutrient agar and Mannitol salt agar by streak plate method. The cultured plates were then incubated for 24 hours at 37oC after whic Biochemical tests were carried out on the isolates to identify the bacteria. Antimicrobial susceptibility test was carried out for the bacterial isolates using Disc diffusion method. The zones of inhibition observed w collected were culture positive. Staphylococcus bacterium associated with nipple contamination compared to (15%). Breast-feeding mothers of contaminated nipples with the bacteria. The antibiotics with highest sensitivity to Staphylococcus aureus was ciprofloxacin, while the ones with the least sensitivity were gentamicin and streptomycin. Staphy Ampiclox and Cefuroxine. Similarly, Pseudomonas aeruginosa was highly sensitive to ciprofloxacin, while the organism has least sensitivity to amoxicillin. the highest sensitivity to both organisms are ciprofloxacin, followed by Perfloxacin and amoxicillin.
EFFECTS OF HONEY AND COCONUT OIL ON 4 HYDROXYAMINOQUINOLINE N PANCREATIC CARCINOGENESIS IN RATS

Kiru, A.I., 1 Umar A.M., 1 Wudul Department of Biochemistry, Bayero University, Department of Biochemistry, Federal University of Technology Minna, Niger State, Nigeria Department of Biochemistry, Federal University Dutsin *Corresponding Author: ABSTRACT Recently, there are many studies focusing on the use of natural products for cancer prevention and treatment. This research work evaluated the effects of honey and coconut oil on 4-Hydroxyaminoquinoline N rat models. Twenty Wistar albino rats were divided into four groups of five rats ea Three groups of rats were injected with 15mg of 4HAQO through the tail vein weekly, for three weeks. One week after 4HAQO administration, groups III and IV rats were administered with either honey or coconut oil daily for 12 weeks. Sixteen weeks after first administration of 4HAQO all surviving rats were sacrificed, blood samples were assayed for glucose and pancreatic enzyme (lipase and amylase) levels. Excised pancreases were fixed in formalin, stained with hematotoxylin 4-Hydroxyaminoquinoline to rats resulted in increased pancreas weights (0.34±0.01 to 0.53±0.11), significant increases in the activities of pancreatic serum lipase (33.33±1.76 to 57.33±.76) and amylase (80.33±3.17 to 120.60±2.40) with pancreatic lesions as observed from histological studies. Administration of honey and coconut oil for 12 weeks resulted in the reduction of pancreatic serum activities of lipase (36.00±2.30 for honey, 35.33±1.76 for coconut oil) and amylase (91.33±2.40 for honey, 88.67±4.67 for oil). Pancreatic lesions were verified in all 4HAQO pancreatic tissues showed the presence of lesions ranging from dilation of ducts, pleomorphic large cells, atypical acinar cells, and necrosis. Moderate t ducts and hyperplasia were seen in 4HAQO control group. There were mild necrosis and degeneration of certain cells from rats that were administered honey and coconut oil. Coconut oil and honey show suppression of 4HAQO rats, suggesting potential curative and/or protective effects.
Quality Monitoring and Assessment of Deployed Deep Learning Models for Network AIOps

Artificial intelligence (AI) has recently attracted a lot of attention, transitioning from research labs to a wide range of successful deployments in many fields, which is particularly true for deep learning (DL) techniques. Ultimately, DL models, being software artifacts, need to be regularly maintained and updated: AIOps is the logical extension of the DevOps software development practices to AI software applied to network operation and management. In the life cycle of a DL model deployment, it is important to assess the quality of deployed models, to detect “stale” models and prioritize their update. In this article, we cover the issue in the context of network management, proposing simple but effective techniques for quality assessment of individual inference, and for overall model quality tracking over multiple inferences, that we apply to two use cases, representative of the network management and image recognition fields.
The five main influencing factors on lidar errors in complex terrain

Abstract. Light detection and ranging (notably Doppler lidar), has become a valuable technology to assess the wind resource at hub height of modern wind turbines. However, because of their measurement principle, common wind profile Doppler lidars suffer from errors at complex terrain sites. This study analyses the impact of the five main influencing factors at lidar measurement errors in complex terrain, i.e. orographic complexity, measurement height, surface roughness and forest, atmospheric stability and half-cone opening angle, in a non-dimensional, model-based parameter study. In a novel approach, the lidar error ε is split up into a part εc, caused by flow curvature at the measurement points of the lidar and a part εs, caused by the local speed-up effects between the measurement points. This approach, e.g., allows for a systematic and complete interpretation of the influence of the half-cone opening angle φ of the lidar. It also provides information about the uncertainty of simple lidar error estimations that are based on inflow and outflow angles at the measurement points. The model-based parameter study is limited to two-dimensional Gaussian hills with hill height H and hill half-width L. H/L and z/L, with z being the measurement height, are identified as the main scaling factors for the lidar error. Three flow models of different complexity are used to estimate the lidar errors. The outcome of the study provides manifold findings that enable an assessment of the applicability of these flow models. The study clearly shows that orographic complexity, roughness and forest characteristics, as well as atmospheric stability, have a significant influence on lidar error estimation. Based on the error separation approach it furthermore allows for an in-depth analysis of the influence of reduced half-cone opening angles. The choice and parameterization of flow models and the design of methods for lidar error estimation are found to be essential to achieve accurate results. The use of a RANS CFD model in conjunction with an appropriate forest model is highly recommended for lidar error estimations in complex terrain. If atmospheric stability variation at a measurement site plays a vital role, it should also be considered in the modelling. When planning a measurement campaign, an accurate estimation of the prospective lidar error should be carried out in advance to decrease measurement uncertainties and maximize the value.
Ligand-binding-site recognition

Abstract: Analysis of ligand complexation sites according to the “fuzzy oil drop” model implies a search for specific distortions in the protein’s internal hydrophobicity distribution field. A quantitative measure of these distortions enables analysts to determine the protein’s capacity for binding ligands. However, this relation is not always clear and evident in all protein–ligand complexes. While the existence of proteins in accordance with the model supports our theoretical assumptions, we must conclude that there is, in fact, more than one mechanism by which proteins are capable of binding ligands. It appears that the list of external factors that affect the distribution of internal hydrophobicity is not strictly limited to potential ligands (i.e., small molecules) but includes objects such as membranes, metal ions, and cellular organelles whose proximity deforms the protein’s hydrophobic core in specific ways.
The Effect of Philosophy Understanding on Corona Virus Diseases (COVID-19) Prevention Awareness of Physics Education Students

This research aims to answer the question of how the influence of understanding philosophy on awareness of prevention of Corona Virus Diseases (COVID-19)? The approach used in this research is quantitative with the data collection method is a survey. The respondents used in this study were 80 students at UIN STS Jambi, where they had taken philosophy courses. The data collection instrument consisted of 30 questions to identify and score the three variables. Data analysis was performed using a two-variable multiple linear regression test with the help of SPSS 25 software. Based on the description of the test results above, it can be seen that the correlation coefficient value between variables is 0.160. This shows that the ability to understand philosophy does not affect self-awareness in preventing COVID-19. The influence is only around 16%. The remaining 84% is influenced by other factors. Therefore, it can be said that understanding the concept of philosophy has a less strong influence on individual self-awareness in following government recommendations for the prevention of COVID-19. In other words, the research results show that understanding philosophy does not directly affect student awareness in the process of preventing COVID-19. Thus it can be understood that the understanding of philosophy has an indirect impact on the process. Philosophy plays a role since the design of the educational process and the educational process that has a direct impact on changing one's behavior in this context is awareness in preventing COVID-19. Keywords—understanding philosophy, awareness of COVID-19 prevention
Special Series Wild fi res intheChornobylexclusionzone — Risksandconsequences

Following the 1986 Chornobyl accident, an area approaching 5000 km surrounding the nuclear plant was abandoned, creating the Chornobyl exclusion zone (CEZ). Although this area likely contains the most radioactive terrestrial ecosystem on earth, the absence of humans and associated activities for nearly 35 years since the accident has resulted in increases in wildlife numbers. Both the Belarussian and Ukrainian components of the CEZ are now designated as nature reserves; together they form one of Europe's largest protected areas and have been described as an iconic example of rewilding. Forests and former agricultural land (now scrub) dominate the CEZ and wildfires are an annual event. In April 2020, the CEZ suffered its most widespread fires to date when greater than 800 km of the 2600 km Ukrainian portion of the CEZ was burnt. Large‐scale fires in the CEZ have implications for wildlife, as they do elsewhere, but they also pose additional radioecological and radiological protection questions. We discuss the implications of wildfires in the CEZ, considering effects on wildlife and changes in radionuclide mobility. We also demonstrate that the risk to firefighters and the wider public from the inhalation of radionuclides in smoke resulting from fires in the CEZ is likely to be low. However, further experimental and modeling work to evaluate potential doses to firefighters from inhaled radioactive particles would be valuable, not least for reassurance purposes. Integr Environ Assess Manag 2021;00:1–10 © 2021 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC).
Paper Number : U 040 A Framework for Finding ProjectedClusters in High Dimensional

Clustering problems are well known in the database literature for their use in numerous applications such as customer segmentation, classiication and trend analysis. Unfortunately, all known algorithms tend to break down in high dimensional spaces because of the inherent sparsity of the points. In such high dimensional spaces not all dimensions may be relevant to a given cluster. One way of handling this is to pick the closely correlated dimensions and nd clusters in the corresponding subspace. Traditional feature selection algorithms attempt to achieve this. The weakness of this approach is that in typical high dimensional data mining applications diierent sets of points may cluster better for diierent subsets of dimensions. The number of dimensions in each such cluster-speciic subspace may also vary. Hence, it may be impossible to nd a single small subset of dimensions for all the clusters. We therefore introduce a generalization of the clustering problem, referred to as the projected clustering problem, in which the subsets of dimensions selected are speciic to the clusters themselves. We develop an algorithmic framework for solving the projected clustering problem, and test its performance on real and synthetic data.
Decomposition of Trichloroethylene with Plasma-catalysis: A review

Abstract The aim of this paper is to give a review of the research on the decomposition of trichloroethylene (TCE), a common industrial solvent, with combined use of non-thermal plasma and heterogeneous catalysis, i.e. plasma-catalysis. This air purification technique has been investigated over the last decade in an effort to overcome the disadvantages of non-thermal plasma treatment of waste air containing volatile organic compounds (VOCs). Some examples of different plasma technologies used for plasma-catalysis are given. These include the dielectric barrier discharge, the pulsed corona discharge and the atmospheric pressure glow discharge. In a plasma-catalytic hybrid system the catalyst can either be located in the discharge region or downstream of the plasma reactor. The mechanisms that drive both configurations are briefly discussed, followed by an extended literature overview of the removal of TCE with plasma-catalysis.
University of Birmingham Towards an integrated model of supportive peer relationships in early adolescence

Supportive peer relationships (SPR) are crucial for mental and physical health. Early adolescence is an especially important period in which peer inﬂuence and school environment strongly shape psychological development and maturation of core social-emotional regulatory functions. Yet, there is no integrated evidence based model of SPR in this age group to inform future research and practice. The current meta-analysis synthetizes evidence from 364 studies into an integrated model of potential determinants of SPR in early adolescence. The model encompasses links with 93 variables referring to individual (identity, skills/strengths, affect/well-being, and behavior/health) and environmental (peer group, school, family, community, and internet/technology) potential inﬂuences on SPR based on cross-sectional correlational data. Findings suggest the central importance of identity and social–emotional skills in SPR. School environment stands out as a compelling setting for future prevention programs. Finally, we underscore an alarming gap of research on the inﬂuence of the virtual and online environment on youth’s social realm given its unquestionable importance as a globally expanding social interaction setting. Hence, we propose an integrated model that can serve as organizational framework, which may ultimately lead to the adoption of a more structured and integrated approach to understanding peer relationship processes in youth and contribute to overcoming marked fragmentation in the ﬁeld.
EFFICIENT INTENSITY MEASURES FOR THE SEISMIC ASSESSMENT OF FREE-STANDING COLUMNS AND COLONNADES

Ancient classical temples constitute common historic monuments of great archaeological value. Many of these monuments remain nowadays as free-standing columns or colonnades. This study aims to shed light on the efficiency of various seismic intensity measures of the base excitation to predict the stability of classical columns and colonnades subjected to uniaxial seismic shaking. A series of numerical analyses are performed for this purpose on representative structural systems using the finite element code ABAQUS. Two different multi-drum columns of diverse diameter, height and number of drums are investigated, including an Ionic column that has recently been restored at the Acropolis of Lindos in Rhodes and a Doric column of the Propylaea at the Acropolis of Athens. The latter column is used as a base for the investigation of the response of a colonnade that consists of three columns coupled with an architrave. The efficiency of numerical modelling is initially validated against experimental data from a series of shaking table tests that were performed on a scaled multi-drum model column. The validated numerical models are then used to evaluate the response of the actual columns and colonnade. The results of the parametric numerical analysis, in terms of the maximum displacement at the capital normalised by the base diameter are used as a representative performance criterion to identify optimal intensity measures for seismic assessment of this type of structures. The maximum spectral displacement SDmax of the base excitation was found to better describe the performance and stability of the free-standing multi-drum columns.
A STUDY TO ASSESS THE EFFECT OF PETTLEP IMAGERY TRAINING ON PENALTY FLICK PERFORMANCE WITH PERSON PRESSURE CONDITION AFTER DIFFERENT TRAINING DURATIONS ON DIFFERENT TRAINING GROUPS

To achieve the aim of the present research, a purposive sample of sixty National and InterUniversity level male Hockey players of 18-25 years in age was randomly divided into four groups. Pretest and post-test random group design was employed, groups were assigned to three experimental groups and a control group. The experimental groups along with regular hockey practice group ‘A’ received imagery training once per week (lx/wk), group ‘B’ received twice per week (2x/wk), group ‘C’ received three times per week (3x/wk) and the control group participated in regular routine practice. The experiment continued for twelve weeks. The penalty flick performance with person pressure condition was evaluated after six weeks, nine weeks and finally at twelve weeks at the end of experiment. ANCOVA was used to determine the significance of difference among mean scores of different training groups and control group after different training durations and Repeated measures analysis of variance was used to find out the significance of difference among mean scores of different training durations of different training frequency groups. Results on analysis of effect of PETTLEP imagery training with various training frequencies per week for different durations revealed that neither training frequency per week nor duration of training produced significant improvement in penalty flick performance of hockey players. As the obtained F-ratio of 1.44,1.409,0.913 and 0.186 were less than the required F-ratio 2.83 to be significant at 0.05 level
Switchable Wettability in SnO2 Nanowires and SnO2@SnO2 Heterostructures

We present here the synthesis of SnO2 nanowires SnO2@SnO2 and SnO2@SnO2@SiOx heterostructures via the chemical vapor deposition (CVD) method. Surface wettability could be modulated from superhydrophilic to superhydrophobic by changing both chemical composition and the geometrical architecture of nanoheterostructures. The random SnO2 nanowires with a contact angle of 3° presented a superhydrophilic property. The contact angle of SnO2@SnO2 heterostructures synthesized by a two-step CVD process increased to 133°. The corresponding contact angle of SnO2@SnO2@SiOx heterostructures was 155.8°. Switchable surface wettability of the SnO2@SnO2@SiOx heterostructure was observed by alternation of UV irradiation, dark storage, and O2 annealing, indicating that geometric microstructure was the major determinant in the switchable wettability from superhydrophilic to superhydrophobic. The switchable surface wettability of SnO2 nanostructures may develop the significant potential for industrial coating and self-cleaning .
RUNNING HEAD: DISTRIBUTION NEGLECT Distribution Neglect in Performance Evaluations

Five empirical studies, including both laboratory experiments and an archival investigation, provide evidence that decision makers often fail to consider variability and skew when making judgments about performance. We term this distribution neglect. Participants’ spontaneous explanations for group differences in elite achievement overwhelmingly invoked mean differences rather than group differences in variability, even when the complete distribution and summary statistics were provided (Study 1). A longitudinal examination indicates that NBA teams overweight average performance and underweight consistency of performance when deciding players’ contracts (Study 2), providing evidence that neglecting variance information leads to suboptimal judgments. In a manufacturing scenario involving monitoring assembly line workers, participants were more accurate at identifying top (high mean) performers than consistent (low variability) performers (Study 3). In a hiring simulation, decision makers were more likely to factor in variance when performance data was presented visually as a histogram (Study 4). Finally, participants’ spontaneous explanations for others’ self-assessments of ability assumed egocentric bias, when a skewed performance distribution was also a plausible contributor (Study 5). Individual differences (need for cognition) and task differences (such as style of information display) were associated with increased distribution-based reasoning in multiple studies, suggesting potential boundary conditions for further investigation. Organizational implications, and additional potential remedies for distribution neglect, are discussed.