Miracle-dz/UniFAR-FTUs huggingface dataset:
Teacher Attire and Student Impressions: A Closer Look

Our choice of clothing has a great impact on how we are perceived by others. The official dress code of the university has changed a lot. From a more formal and exquisite dress code to a range of informal styles, such as business casual and smart casual. This change raises the question of whether dress has an impact on how students develop first impressions and opinions in our campus community. This study, which took place in November and December 2022, involved 414 individuals from a heterogeneous sample who responded to an online questionnaire provided on campus. The basis of this study is the sample, which was carefully selected to represent the age and gender distribution of the university. The main objective of this study is to investigate how students' perceptions and opinions are influenced by lecturers' dress. The results show a complex relationship between what people wear and the perceptions they create. Specifically, a preference for athletic or informal clothing is associated with qualities such as flexibility and directness, while a preference for more elegant and formal clothing conveys qualities such as care and attention to detail. These findings highlight the complexity associated with our assessment and interpretation of teachers' classroom dress codes and shed light on the different facets of first impressions in a university setting.
Response of Local Tomato Varieties to Application of Poultry Manure, Cow dung and Inorganic fertilizer

Continuous application of inorganic fertilizer causes problems such as deterioration of soil structure, environmental and ground water pollution. A trial was conducted on the field to investigate the effect of poultry manure, cow dung and inorganic fertilizer on growth and yield performance of tomato. There were two (2) factors consisting of fertilizers (10t ha -1 poultry manure, 10t ha -1 cow dung and 100kg Nha -1 N.P.K fertilizer and control) as well as local tomato varieties (Hausa oval, Hausa round and Beske). The treatments were laid out using Randomized Complete Block Design (RCBD) in split plot replicated four times. Growth and yield data taken are plant height (cm), stem girth (cm) number of branches, fruit weight (kg), fruit diameter (cm) and fruit t ha -1 as well as the dry matter accumulation.Results showed that growth and yield components were significantly affected by treatments. Hausa oval variety performed better in terms of growth and yield parameters which made it the most desirable variety among the varieties used across the sampling period. At the first trial, application of N.P.K fertilizer was better than any other treatments but the growth and yield parameters were significantly comparable with those obtained with poultry manure at 10t ha -1 . However, increase in growth and yield parameters were observed with application of poultry manure at the second trial, this was followed by cow dung while the least was produced by unfertilized plants. The study showed that organic manure had better residual effects on performance of tomato with the application of poultry manure and cow dung at 10t ha -1 respectively. Keywords : Cow dung, Inorganic fertilizer, Poultry manure, tomato varieties
Effects of Supplementing Selenium-Enriched Cardamine violifolia to Laying Hens on Egg Quality and Yolk Antioxidant Capacity during Storage at 4 °C and 25 °C

Oxidative stress occurs in the process of egg storage. Antioxidants as feed additives can enhance egg quality and extend the shelf life of eggs. Selenium-enriched Cardamine violifolia (SEC) has strongly antioxidant properties. The objective of this study was to assess the effects of dietary supplementation with SEC on egg quality and the yolk antioxidant capacity of eggs stored at 4 °C and 25 °C. Four hundred fifty 65-week-old, Roman hens that were similar in laying rate (90.79 ± 1.69%) and body weight (2.19 ± 0.23 kg) were divided into 5 groups. The birds were fed diets supplemented with 0 mg/kg selenium (Se) (CON), 0.3 mg/kg Se from sodium selenite (SS), 0.3 mg/kg Se from Se-enriched yeast (SEY), 0.3 mg/kg Se for selenium-enriched Cardamine violifolia (SEC) or 0.3 mg/kg Se from Se-enriched Cardamine violifolia and 0.3 mg/kg Se from Se-enriched yeast (SEC + SEY) for 8 weeks. The eggs were collected on the 8th week and were analyzed for egg quality and oxidative stability of yolk during storage at 4 °C or 25 °C for 0, 2, 4, or 6 weeks. Dietary SEC and SEC + SEY supplementation increased the Haugh unit (HU) and albumen foam stability in eggs stored at 4 °C and 25 °C (p < 0.05). SS and SEC supplementation increased the yolk index in eggs stored at 25 °C (p < 0.05). SEC or SEC + SEY slowed down an increase in albumen pH and gel firmness in eggs stored at 4 °C and 25 °C (p < 0.05). Moreover, SEC or SEC + SEY alleviated the increase in malonaldehyde (MDA), and the decrease in total antioxidant capacity (T-AOC) level and total superoxide dismutase (T-SOD) activity in yolks stored at 4 °C and 25 °C (p < 0.05). These results indicate that SEC mitigated egg quality loss and improved the antioxidant capacity of yolks during storage. SEC supplementation would be advantageous to extend the shelf life of eggs.
Reagentless Glucose Biosensor Based on Combination of Platinum Nanostructures and Polypyrrole Layer

Two types of low-cost reagentless electrochemical glucose biosensors based on graphite rod (GR) electrodes were developed. The electrodes modified with electrochemically synthesized platinum nanostructures (PtNS), 1,10-phenanthroline-5,6-dione (PD), glucose oxidase (GOx) without and with a polypyrrole (Ppy) layer—(i) GR/PtNS/PD/GOx and (ii) GR/PtNS/PD/GOx/Ppy, respectively, were prepared and tested. Glucose biosensors based on GR/PtNS/PD/GOx and GR/PtNS/PD/GOx/Ppy electrodes were characterized by the sensitivity of 10.1 and 5.31 μA/(mM cm2), linear range (LR) up to 16.5 and 39.0 mM, limit of detection (LOD) of 0.198 and 0.561 mM, good reproducibility, and storage stability. The developed glucose biosensors based on GR/PtNS/PD/GOx/Ppy electrodes showed exceptional resistance to interfering compounds and proved to be highly efficient for the determination of glucose levels in blood serum.
Influence of Integrated Plant Nutrition System on Growth, Development and Yield of Wheat in Rice-Wheat Cropping System in Hilly Area of India

Of the 30 major cropping systems identified in India (Yadav and Prasad, 1998), rice-wheat cropping system is the most predominant in India occupying around 10.5 m ha area (Sharma 2009). Among cereals, rice and wheat are the most important crops, which account for about 60% of world’s human energy requirement. This system contributes about 75% of the nation's total food grain production, thus forms the backbone of food security (Lathwal et al., 2010). Wheat International Journal of Current Microbiology and Applied Sciences ISSN: 2319-7706 Volume 7 Number 09 (2018) Journal homepage: http://www.ijcmas. com
A Multi-Source Data Fusion Network for Wood Surface Broken Defect Segmentation

Wood surface broken defects seriously damage the structure of wooden products, these defects have to be detected and eliminated. However, current defect detection methods based on machine vision have difficulty distinguishing the interference, similar to the broken defects, such as stains and mineral lines, and can result in frequent false detections. To address this issue, a multi-source data fusion network based on U-Net is proposed for wood broken defect detection, combining image and depth data, to suppress the interference and achieve complete segmentation of the defects. To efficiently extract various semantic information of defects, an improved ResNet34 is designed to, respectively, generate multi-level features of the image and depth data, in which the depthwise separable convolution (DSC) and dilated convolution (DC) are introduced to decrease the computational expense and feature redundancy. To take full advantages of two types of data, an adaptive interacting fusion module (AIF) is designed to adaptively integrate them, thereby generating accurate feature representation of the broken defects. The experiments demonstrate that the multi-source data fusion network can effectively improve the detection accuracy of wood broken defects and reduce the false detections of interference, such as stains and mineral lines.
Complementing CO2 emission reduction by Geoengineering might
strongly enhance future welfare

Abstract. Solar Radiation Management (SRM) has been proposed as a means to reduce global warming in spite of high greenhouse gas concentrations and lower the chance of warming-induced tipping points. However, SRM may cause economic damages, and its feasibility is still uncertain. To investigate the trade-off between these gains and damages, we incorporate SRM into a stochastic-dynamic integrated assessment model and perform the first rigorous cost-benefit analysis of sulphate-based SRM under uncertainty, treating warming-induced climate tipping and SRM failure as stochastic elements. We find that SRM has the potential to greatly enhance future welfare and should therefore be taken seriously as a policy option. However, if only SRM and no CO2 abatement is used, global warming is not stabilised and will exceed 2 K. Therefore, even if successful, SRM cannot replace but only complement CO2 abatement. The optimal policy combines CO2 abatement and modest SRM and succeeds in keeping global warming below 2 K.
Relationship between Antibiotic Consumption and Resistance: A Systematic Review

Background Unreserved use of antibiotics exerted selective pressure on susceptible bacteria, resulting in the survival of resistant strains. Despite this, the relationship between antibiotic resistance (ABR) and antibiotic consumption (ABC) is rarely studied. This systematic review aims to review the relationship between ABC and ABR from 2016 to 2022. Methods Articles published over 7 years (2016–2022) were searched from December 23 to 31, 2022. The search strategy was developed by using keywords for ABC and ABR. From 3367 articles, 58 eligible articles were included in the final review. Results The pooled ABC was 948017.9 DPDs and 4108.6 DIDs where over 70% of antibiotics were from the Watch and Reserve category based on the WHO AWaRe classification. The average pooled prevalence of ABR was 38.4%. Enterococcus faecium (59.4%), A. baumannii (52.6%), and P. aeruginosa (48.6%) were the most common antibiotic-resistant bacteria. Cephalosporins (76.8%), penicillin (58.3%), and aminoglycosides (52%) were commonly involved antibiotics in ABR. The positive correlation between ABR and consumption accounted for 311 (81%). The correlation between ABR P. aeruginosa and ABC accounted for 87 (22.7%), followed by 78 (20.3%) and 77 (20.1%) for ABR E. coli and K. pneumoniae with ABCs, respectively. Consumption of carbapenems and fluoroquinolones was most commonly correlated with resistance rates of P. aeruginosa, K. pneumoniae, E. coli, and A. baumannii. Conclusion There is a positive correlation between ABC and the rate of ABR. The review also revealed a cross-resistance between the consumption of different antibiotics and ABR. Optimizing antibiotic therapy and reducing unnecessary ABC will prevent the emergence and spread of ABR. Thus, advocating the implementation of stewardship programs plays a pivotal role in containing ABR.
DDRA-Net: Dual-Channel Deep Residual Attention UPerNet for Breast Lesions Segmentation in Ultrasound Images

Automated segmentation of breast tumors in breast ultrasound images has been a challenging frontier issue. The morphological diversity, boundary ambiguity, and heterogeneity of malignant tumors in breast lesions constrain the improvement of segmentation accuracy. To address these challenges, we propose an innovative deep learning-based method, namely Dual-Channel Deep Residual Attention UPerNet (DDRA-net), for efficient and accurate segmentation of breast tumor regions. The core of DDRA-net lies in the Dual-Channel Deep Residual Attention module (DDRA), which integrates depth-wise separable convolution and Convolutional Block Attention Module (CBAM). This design aims to enhance the extraction of crucial features within the receptive field to better capture subtle details of breast lesions. Through extensive experimental evaluation, DDRA-net demonstrates remarkable performance on a publicly available breast ultrasound datasets, exhibiting higher segmentation accuracy and stability compared to contemporary mainstream deep learning methods. Importantly, it is worth emphasizing that the flexibility of this method allows easy integration with other network structures to further improve the performance and applicability of breast tumor segmentation. In the segmentation of the Breast Ultrasound Image dataset, our precision, recall, IoU, F1 score, Dice, and Hausdorff Distance achieved the following values: 95.31%, 90.79%, 88.00%, 92.39%, 95.46%, and 3.02, respectively. Compared to the original UPerNet, DDRA-net demonstrated improvements of 2.71%, 4.03%, 4.61%, 4.38%, 3.14%, and 24.5% in these six metrics on the Breast Ultrasound Image dataset.
Applicability of the Cumberland Ankle Instability Tool in Elite Volleyball Athletes: A Cross-Sectional Observational Study

Background: The ease of administration of the Cumberland Ankle Instability Tool (CAIT) could represent a methodology for periodically evaluating athletes, preventing ankle instability injuries. This study aimed to achieve three objectives: (a) to evaluate the applicability of the CAIT scale in volleyball; (b) to explore whether ankle instability presents a greater risk in lower-level volleyball categories and whether elite athletes demonstrate an ability to mitigate this risk; and (c) to identify potential predictors of ankle instability. Methods: Eighty female volleyball players participated in this cross-sectional observational study. The CAIT was administered to evaluate the athletes belonging to some teams in Series A, B, and C. Results: The Spearman’s ranks correlation coefficient showed significant correlations between CAIT items. Additionally, the Cronbach’s α showed a high internal consistency. Our results showed a significant difference between athletes who reported pain and those who did not (p < 0.001). The multiple linear regression model analysis showed that pain was a predictor of ankle instability (p < 0.001). Conclusions: Our findings suggest that the CAIT can be used to evaluate ankle stability in volleyball players. This scale could represent a valuable tool for implementing specific intervention programs to prevent ankle injuries in athletes.
The role of functional diversity in biotic resistance of non-native fishes and invertebrates in Lake Erie coastal wetlands

ii Dedication. iii Acknowledgements. iv Vita. v List of Tables. vii List of Figures. x Chapter 1: Literature review of invasion, biotic resistance, and functional diversity. 1 References. 11 Chapter 2: The role of functional diversity in biotic resistance of non-native fishes in Lake Erie coastal waters. 19 References. 39 Chapter 3The role of functional diversity of fishes and invertebrates in biotic resistance of non-native fishes in Ottawa National Wildlife Refuge. 58 References. 91 Appendix A. Native and non-native fishes found collected using fyke nets from 8 sites sampled in fall and spring 2013-2014 and their associated status, and feeding guilds (FG). 124 Appendix B. Abiotic water sampling: averages of 3 water collections collected from each site were calculated to assess seasonal and yearly fluctuations. 126 Appendix C. Invertebrate subsampling method 1 used to randomly select material to search for invertebrates for samples larger than 250-mL. 129 Appendix D. Fish species found, minnow trap mesh size they were collected in, Invader status according to GLANSIS, and associated feeding guild (FG). 130 Appendix E. Invertebrates found with Operational Taxonomic Units (OTUs), Invader status, and functional feeding group (FFG). 131
Effect of Mirror Therapy on Post-Needling Pain Following Deep Dry Needling of Myofascial Trigger Point in Lateral Elbow Pain: Prospective Controlled Pilot Trial

Background: This prospective randomized, controlled pilot trial to explore the immediate effect of adding Mirror Visual Feedback Therapy on pain sensitivity and motor performance among subjects suffering from post-needling pain diagnosed as Lateral Elbow Pain. Methods: A total of 49 participants (23 female, 26 male) were enrolled and randomly allocated to either the experimental group, which received Deep Dry Needling in the m. Brachioradialis, Ischemic Compression, Cold Spray, Stretching, and Mirror Visual Feedback Therapy (n = 25), or a control group without Mirror Visual Feedback Therapy (n = 24). Pre- and post-treatment evaluations included assessments of post-needling pain intensity, pressure pain threshold, two-point discrimination threshold, and maximum hand grip strength. Results: Intergroup analysis revealed a statistically significant reduction in post-needling pain intensity favoring the experimental group (U = 188.00, p = 0.034). Additionally, intragroup analysis showed significant improvements in post-needling pain intensity (MD = 0.400, SEM = 0.271, W = 137.00, p = 0.047) and pressure pain threshold (MD = 0.148 Kg/cm2, SEM = 0.038, W = 262.00, p < 0.001) within the experimental group following the intervention. Conclusions: These findings suggest a potential benefit of integrating Mirror Visual Feedback Therapy into treatment protocols for individuals with Lateral Elbow Pain experiencing post-needling discomfort. Further research is necessary to fully elucidate the clinical implications of these findings.
Autonomous Vehicles: Applications of Deep Reinforcement Learning

This research paper offers a concise exploration into the pivotal role played by deep reinforcement learning in propelling advancements in both perception and decision-making aspects of autonomous vehicles. Through the fusion of deep learning and reinforcement learning techniques, we delve into how these methodologies synergistically contribute to augmenting the navigational proficiency of autonomous vehicles amidst intricate and dynamically changing environments. With a focus on a streamlined presentation, this paper provides a succinct yet insightful overview of various perception algorithms utilized by autonomous vehicles, emphasizing object detection, semantic segmentation, and LiDAR-based techniques.
Fire in boreal black spruce (Picea mariana mill.) forests: respiration, temperature sensitivity, and bioavailability of soil organic matter

Boreal forests store large quantities of carbon (C) and currently act as atmospheric C sinks; however, predicted increases in temperature and fire frequency may change the boreal forest from a net C sink to a net source. This study evaluates the response of organic soil C and nitrogen (N) mineralization, and the bioavailability of C and N to burning in non-permafrost upland black spruce stands in interior Alaska. Two years after an experimental wildfire, burned soils were warmer than control soils at all depths measured, and decay of common substrates was greater in the burned than in the control soils. Burned soils had higher concentrations of total C, lignin, N, and mineral N, and lower concentrations of dissolved organic carbon (DOC) and soluble organic matter. However, apparent differences in organic matter quality did not correlate well with respiration metrics. In laboratory incubations, burned soils respired less than control soils, and this difference was entirely due to differences on the first day of the incubation. Mean Q10 values ranged from 2.1 to 2.5 and were greater in the burned soils than in the control soils.
Dietary Importance of Lycopene Against Carbon Tetrachloride Induced Hepatotoxicity in Rats

Chronic liver disease is a clinically silent condition that causes significant morbidity and mortality around the world. This study aimed to investigate the dietary importance of lycopene against Carbon Tetrachloride inducing hepatotoxicity in rats. Thirty five albino rats were divided randomly for two groups. The first group G1(7 rats), its diet was only basic diet, considering it negative control group. The remaining of rats injected with a subcutaneous of carbon tetrachloride (2ml/ kg b.w./ week) for two weeks to induce hepatic damage. After injected animals, they divided for 4 subgroups (7 rats/ once). Rats in G2 considered as positive control. Rats in G3, G4, G5 fed on the basal diet contained different levels of dried tomato and ketchup 5%, 7.5% and 10%, respectively. After eight weeks, liver and kidney functions were evaluated. Antioxidant activity was estimated, in addition to histological examination of liver tissues. The results indicated that there were significantly increasing in the levels of ALT, AST, ALP, albumin, total and direct bilirubin in G2 when compared with G1, while G3, G4 and G5 showed significant decreasing in the levels compared to positive control group. Urea nitrogen and creatinine levels in G2 showed significant increasing comparing with negative control group, the improvement were noticeable in all examined groups comparing to positive control group. Furthermore, the levels of GSH and CAT showed significant improvement in all tested groups
Optimized Fuzzy Model in Piecewise Interval for Function Approximation

- Function approximation is a technique for estimating an unknown underlying function from input-output instances or examples. Researchers have proposed different methods of function approximations, such as the neural network method, the support vector regression method, the reinforced learning method, the clustering method, the neuro-fuzzy method, etc. This paper introduces a novel data-driven function approximation scheme where the input-output data set is first segmented into multiple pieces. A Mamdani-type fuzzy submodel is constructed for each piece or portion, and the membership functions’ parameters for antecedent and consequent are optimally selected through the differential evolution algorithm. The efficacy of the suggested model is verified on three nonlinear functions, viz., a piecewise polynomial function, an exponentially decreasing sinusoidal function, and an exponentially increasing sinusoidal function. A comparative analysis is done based on the simulation results from the proposed model and the results obtained through the two state-of-the-art function approximation techniques, viz., the support vector regression model and the radial basis function network. The simulation results show that the proposed function approximator has satisfactorily approximated the three functions examined here, surpasses the two state-of-the-art techniques in approximating the two sinusoidal functions, and performs the near-best performance for the piecewise polynomial function. The proposed function approximator is expected to be applied as a new state-of-the-art method for function approximation.