Miracle-dz/UniFAR-FTUs huggingface dataset:
A COMPARISON OF INDEPENDENT, CONCURRENT SIGHTING RECORDS FROM A SHORE-BASED COUNT OF GRAY WHALES

Gray whales (Eschrichtius robustus) have been counted from shore-based observation sites for over a century (Reilly 1984). Population estimates are dependent on observers to provide accurate counts of the number of whale groups seen and the number of whales in each group. However, the accuracy of these counts of gray whales rarely has been evaluated. A study was conducted from aircraft to test the accuracy of 12 observers simultaneously estimating group sizes (Reilly et al. 1980), but only groups seen from both shore and aircraft were considered. Rugh (1984) and Rugh et al. (1990) studied observers maintaining independent, concurrent sighting records during shore-based counts of gray whales, but these were from short sample periods, 23 hours and 60 hours respectively. Magnusson et al. (1978) and Maxim et al. (1981) showed the efficiency of similar studies involving paired counts from independent observers. Few other double surveys of other species have been documented. Caughley (1974) used binomial probabilities to estimate the number of animals missed in Eltringham's (1972) map of elephant (Loxodonta africana) groups seen by separate observers in an aerial survey in eastern Africa. Estes and Jameson (1988) used simultaneous double surveys made by shore-based observers to estimate the probability of sighting sea otters (Enhydra lutris). Marsh and Sinclair (1989) found that individual observers missed >40% of dugong (Dugong dugon) groups and >80% of sea turtles (Chelonia mydas) when observers were paired in aerial surveys. They found that group size did not affect sighting rates. Graham and Bell (1989:1,014), in their review of double counts in aerial surveys of feral equids, lamented, "We are unable to suggest why so many plainly visible groups are not seen. " Others have used double sampling to compare different survey techniques. For example, Withrow (1982:7) made land-based counts to correct aerial estimates of northern sea lions (Eumetopias jubatus) on beaches in the Aleutian Islands, and Geibel and Miller (1984) compared aerial and shore-based counts of sea otters. This latter type of double sampling was examined by Cochran (1977:Chap. 12) and Eberhardt and Simmons (1987), but it is currently inapplicable to the gray whale study because of the lack of unequivocal data against which the sightings may be checked. Instead, paired observers can be tested against each other. In each of the previous gray whale studies involving double sampling (Rugh 1984, Rugh et al. 1990), large discrepancies among ob-
Insights into the structures and properties of dyes in the Fenton catalytic process for treating wastewater effluent

A notable level of apprehension exists over the adverse impacts of dye pollution on aquatic ecosystems and human well‐being. The primary objective of this research is to assess the effectiveness of Fenton catalytic reactions in degrading 14 different commercial azo dyes (both single and double) present in aqueous solutions. The investigation focused on the function of dye structures, using a combination of experimental data and examination of theoretical factors. Dye degradation process was carried out at pH 3, and the concentrations of Fe2+ (10−4 mol/L), H2O2 (2 × 10−3 mol/L), and dye (0.05 g/L). The findings revealed that dyes with a larger molecular weight were more effective at degrading (D%), with the overall degradation efficiency varying from 0% to 94%. Functional groups played an important role in degradation efficiency; for example, dyes with higher aromatic rings led to less D%, while a higher number of sulfonic, methyl, and nitro groups was responsible for better D%. Notably, the presence of OH groups in the backbone of dyes (AB 24, ABE 113, and MB 9) formed the Fe complex during the catalytic process, and the D% was minimal. On the other hand, theoretical quantum calculations such as the greater the JCLogP, highest occupied molecular orbital, and Dipole moment value, the higher the degradation efficiency. And dyes with low lowest unoccupied molecular orbital tended to have a better degradation efficiency. To some extent, UV–Vis spectral analysis was investigated to determine the degradation pathway, and the pseudo‐second‐order kinetic model fitted better in the degradation process. The overall experimental and theoretical findings suggested that dye degradation efficiency by the Fenton process is structure‐dependent.
Modified graph-based algorithm to analyze security threats in IoT

In recent years, the growing and widespread usage of Internet of Things (IoT) systems has led to the emergence of customized structures dependent on these systems. Industrial IoT (IIoT) is a subset of IoT in terms of applications and usage areas. IIoT presents many participants in various domains, such as healthcare, transportation, agriculture, and manufacturing. Besides the daily life benefits, IIoT technology provides major contributions via the Industrial Control System (ICS) and intelligent systems. The convergence of IoT and IIoT systems brings some integration and interoperability problems. In IIoT systems, devices interact with each other using information technologies (IT) and network space. However, these common usages and interoperability led to some security risks. To avoid security risks and vulnerabilities, different systems and protocols have been designed and published. Various public databases and programs identify and provide some of the security threats to make it easier for system administrators' missions. However, effective and long-term security detection mechanisms are needed. In the literature, there are numerous approaches to detecting security threats in IoT-based systems. This article presents two major contributions: First, a graph-based threat detection approach for IoT-based network systems is proposed. Threat path detection is one of the most critical steps in the security of IoT-based systems. To represent vulnerabilities, a directed acyclic graph (DAG) structure is constructed using threat weights. General threats are identified using Common Vulnerabilities and Exposures (CVE). The proposed threat pathfinding algorithm uses the depth first search (DFS) idea and discovers threat paths from the root to all leaf nodes. Therefore, all possible threat paths are detected in the threat graph. Second, threat path-reducing algorithms are proposed considering the total threat weight, hop length, and hot spot thresholds. In terms of available threat pathfinding and hot spot detecting procedures, the proposed reducing algorithms provide better running times. Therefore, all possible threat paths are founded and reduced by the constructed IoT-based DAG structure. Finally, simulation results are compared, and remarkable complexity performances are obtained.
AI Model Developed Using Machine Learning for Predicting Sperm Retrieval in Micro-TESE for Nonobstructive Azoospermia Patients

Azoospermia is a severe problem that prevents couples from having their own children through natural pregnancy. In nonobstructive azoospermia (NOA), microdissection testicular sperm extraction (micro-TESE) is required to collect sperm and, at 40%–60%, the sperm retrieval success rate is not very high. Previous studies identified no single clinical finding or investigation that could accurately predict the outcome of sperm retrieval. It would be very valuable to have a factor for predicting the possibility of sperm retrieval in patients with NOA before performing micro-TESE. We retrospectively obtained data from the medical records of 430 patients who underwent micro-TESE from 2011 to 2020. Parameters extracted were age, height, body weight, body mass index, luteal hormone, follicle-stimulating hormone, PRL, total testosterone, E2, T/E2, sperm retrieval, G-band, AZF, medical history, Rt testis, and Lt testis. Prediction One, which does not require coding, was used to create the AI prediction model for sperm retrieval. Prediction One makes the best prediction model using an artificial neural network with internal cross-validation. Prediction One also evaluates the “importance of variables” using a method based on permutation feature importance. The AUC for the AI model was 0.7246, which is acceptable. In addition, among the variables, T/E2 ratios contributed most to predicting whether sperm retrieval was possible or not. However, the difference in T/E2 between successful and unsuccessful sperm retrieval was not statistically significant. In addition, our analysis of data from 20 patients who underwent micro-TESE in 2021 found that in 85%, the actual result matched the result predicted using our novel AI model. We created an AI model for predicting sperm retrieval in patients with NOA before undergoing micro-TESE. In addition, we found that T/E2 ratios contributed most to predicting possibility of sperm retrieval in NOA using machine learning.
Underpinning sustainability paradigms: circular economy and enhanced triple bottom line

: Whilst stakeholders and policy makers in industry and academia increasingly use circular and sustainable, the terms are not clearly understood. Furthermore, the need for a switch from a current economic model (linear) to the circular one has been recognized globally by the major decision-makers. The shift from one mechanism to another has presented challenges in grasping the Circular Economy (CE) and Sustainability (S) principles: defining them, understanding the similarities and differences, and successfully applying them using Triple Bottom Line (TBL) approach. Employing systematic literature review, the aim of this paper is to clarify the ambiguities and add to clarity by exploring the concepts and the relationship of CE and S by applying TBL framework – social, economic and environmental variables. The gaps regarding relations to people and profit contribution are identified in the literature, future research priorities and new frameworks are recommended.
Exploring the antifungal potential of Allium sativum and Ocimum gratissimum against post-harvest fungal pathogens in mango fruits

<p>Post-harvest spoilage of fruits and vegetables caused by fungal pathogens is a serious challenge to fruit production in many parts of the world. The study was conducted to evaluate the sensitivity of fungal pathogens associated with post-harvest rot of mango fruits to crude extracts from two edible plants, <em>Allium sativum</em> and <em>Ocimum gratissimum</em>, in the study area. Five different fungal isolates were isolated from diseased mango fruits collected from fruit stores in the study area and identified as <em>Aspergillus</em> spp. (M<sub>1</sub>), <em>Rhizopus</em> spp. (M<sub>2</sub>), <em>Fusarium</em> spp. (M<sub>3</sub>), <em>Penicillium</em> spp. (M<sub>4</sub>), <em>Fusarium</em> spp. (M<sub>5</sub>), <em>Penicillium</em><em> spp. </em> (M<sub>6</sub>), <em>Aspergillus</em> spp. (M<sub>7</sub>), and Colletotrichum spp. (M<sub>8</sub>) using radial growth rate and morphological features of the mycelia. A constant concentration of each of the crude extracts was applied to the growth media containing the growing cultures of the fungal isolates. The radial extension of the colonies for each isolate was measured along pre-marked perpendicular axes on the base of the petri-dish after 24 h and this continued for 10–14 days. It was observed that <em>Rhizopus</em> spp. , <em>Fusarium</em> spp. , <em>Penicillium</em><em> spp</em>. , and Colletotrichum spp. had the least growth rate when treated with the extracts. </p>
Students' Mental Model Profiles on Chemical Bonding Concept Using a Two-Tier Mental Model Diagnostic Test (TDM-Two-Tier)

This study aims to analyze students' mental models on the concept of chemical bonds using a two-tier mental model diagnostic test. A test with the first tier asking the content and the second tier asking the reasons for the answers at the first tier. The test used has been developed and declared valid with a degree of reliability 0.751. This research is qualitative research with a case study design. Students' mental models are categorized into complete mental models, partial mental models, mental models with misconceptions, and mental models with inconsistencies. In the concept of chemical bonds found 17, 9, 15, and 59% of students with complete, partial, misconceptions, and inconsistencies in mental models respectively. Most students have misconceptions by stating that ionic bonds are formed through atomization and the formation of bonding electrons by reason of the sharing of electrons in ionic crystals. In addition, students understand that the process of forming covalent bonds in oxygen and fluorine occurs because of the attraction between atoms which is greater than the repulsion between bonded atoms. Among the inconsistent concepts found are students explaining the phenomenon of solubility, boiling point, and melting point based on the concept of the electron cloud.
The effect of non-audit services on audit quality

Audit quality (AQ) is value-relevant if the information is capable of making a difference in the decisions taken by various stakeholders. Therefore, the provision of non-audit services (NAS) to clients, and auditors can create economic bonding and self-review threats that compromise independence and AQ (Friedrich & Quick, 2023). The study investigates the effects of NAS on AQ in the Nigerian insurance industry. The ex-post facto research design was adopted and data were sourced from the annual reports of the 22 insurance companies listed on the Nigerian Exchange Group (NGX) between 2015 and 2020 and sampled through a filtering method. The study used descriptive statistics, correlation matrix, and binary regression techniques to test the formulated hypotheses. The study made use of a binary logistic econometric approach because the dependent variable is a dummy variable assuming the value of “1” and “0”. In agreement with the study of Pappert and Quick (2022), the regression results revealed that the provision of NAS, audit fees, and firm size significantly affect AQ in the Nigerian insurance industry, while auditor tenure had an insignificant effect on AQ. The study recommended that the provision of NAS should be strengthened and monitored to align with the list of services that auditors are not prohibited from rendering to the client.
The Roles of GRETCHEN HAGEN3 (GH3)-Dependent Auxin Conjugation in the Regulation of Plant Development and Stress Adaptation

The precise control of free auxin (indole-3-acetic acid, IAA) gradient, which is orchestrated by biosynthesis, conjugation, degradation, hydrolyzation, and transport, is critical for all aspects of plant growth and development. Of these, the GRETCHEN HAGEN 3 (GH3) acyl acid amido synthetase family, pivotal in conjugating IAA with amino acids, has garnered significant interest. Recent advances in understanding GH3-dependent IAA conjugation have positioned GH3 functional elucidation as a hot topic of research. This review aims to consolidate and discuss recent findings on (i) the enzymatic mechanisms driving GH3 activity, (ii) the influence of chemical inhibitor on GH3 function, and (iii) the transcriptional regulation of GH3 and its impact on plant development and stress response. Additionally, we explore the distinct biological functions attributed to IAA-amino acid conjugates.
Diagnostic performance of qualitative and quantitative shear wave elastography in differentiating malignant from benign breast masses, and association with the histological prognostic factors.

Background To determine the diagnostic performance of qualitative and quantitative shear wave elastography (SWE) and the optimal cutoff values of the quantitative SWE parameters in differentiating malignant from benign breast masses, and to evaluate the association between the quantitative SWE parameters and histological prognostic factors. Methods A gray scale ultrasound and SWE were prospectively performed on a total of 244 breast masses (148 benign, and 96 malignant) in 228 consecutive patients before an ultrasound-guided needle biopsy. The qualitative SWE and quantitative SWE parameters (the mean elasticity, maximum elasticity, and elasticity ratio) were measured in each mass. The diagnostic performance of SWE and the optimal cutoff values of the quantitative SWE parameters were obtained. An association analysis of the parameters and histological prognostic factors was performed. Results The malignant masses had a more heterogeneous pattern on the qualitative SWE than benign masses (P<0.001). The quantitative SWE parameters of the malignant masses were higher than those of the benign masses (P<0.001); the mean elasticity, maximum elasticity, and elasticity ratio of the benign masses were 19.73 kPa, 23.98 kPa, and 2.78, respectively; and the mean elasticity, maximum elasticity, and elasticity ratio of the malignant masses were 88.13 kPa, 98.48 kPa, and 10.64, respectively. The optimal cutoff value of the mean elasticity was 30 kPa, of the maximum elasticity was 36 kPa, and of the elasticity ratio was 4.5. The maximum elasticity had the highest AUC. Combining the three SWE parameters to differentiate between the malignant and benign masses increased the negative predictive value (NPV), which correctly downgraded 72.73% of BI-RADS category 4A masses to BI-RADS category 3. No statistically significant association was found between the quantitative SWE parameters and the tumor grading, tumor types, axillary lymph node statuses, or molecular subtypes of the breast cancers (P>0.05). Conclusions The qualitative and quantitative SWE provided good diagnostic performance in differentiating malignant and benign masses. The maximum elasticity of the quantitative SWE parameters had the best diagnostic performance. Adding the three combined quantitative SWE parameters to the BI-RADS category 4A masses potentially downgraded them to BI-RADS category 3 and avoided unnecessary biopsies. No statistically significant association was found between the quantitative SWE parameters and the histological prognostic factors.
Potential Effects of the Different Matrices to Enhance the Polyphenolic Content and Antioxidant Activity in Gluten-Free Bread

Gluten-related disorders, including celiac disease, wheat allergy, and non-celiac gluten sensitivity, have emerged as a significant phenomenon affecting people worldwide, with an estimated prevalence of nearly 5% globally. The only currently available treatment for this disease involves the exclusion of gluten from the diet, which is particularly challenging in the case of bakery products. Gluten-free bread (GFB) presents certain disadvantages when compared to traditional wheat bread, including inferior sensory attributes, technological characteristics, and lower protein and fiber content. Numerous studies have focused on strategies to improve these aspects of GFB. However, there are limited reviews regarding the content of the bioactive compounds of GFB, such as polyphenols. Polyphenols are molecules found in various foods that play a vital role in protecting the body against oxidative stress. This is particularly relevant for individuals with gluten intolerance or celiac disease, as they often experience increased oxidative stress and inflammation. Therefore, the objective of this review is to explore the use of different strategies for increasing the polyphenolic content and the antioxidant properties of GFB. Gluten-free cereals and pseudocereals are the most used matrices in GFB. Buckwheat can be a valuable matrix to enhance the nutritional profile and antioxidant properties of GFB, even more so when the whole grain is used. In the same way, the addition of various by-products can effectively increase the bioactive compounds and antioxidant activity of GFB. Furthermore, regarding the contribution of the phenolics to the bitterness, astringency, color, flavor, and odor of food, it is essential to analyze the sensory properties of these breads to ensure not only enriched in bioactive compounds, but also good consumer acceptance. In vitro studies are still in few number and are very important to execute to provide a better understanding of the bioactive compounds after their consumption.
Evaluation of contributory factors’ effects on bicycle-car crash risk at signalized intersections

Abstract Bicycle-car accidents at signalized intersections account for a considerable part of bicycle accidents. Factors that have effects on the bicycle-car crash risk at signalized intersections are not well understood. Especially, the safety effects of bicycle facilities are controversial at intersections. This paper aims to identify factors that have significant effects on bicycle-car crash risk at signalized intersections and their effect directions.The negative binomial regression model is used to model associations between the frequency of bicycle-car accidents at signalized intersections and the contributory factors, based on 6-year accident history at 140 signalized intersections in Berlin, Germany. The considered factors include the traffic volume, geometric data, and bicycle-specific and car-specific infrastructures. The factor effect coefficients are estimated by the maximum likelihood approach. The estimated coefficient of the negative binomial dispersion parameter is significant at the level of 0.001. Three factors are identified to have significant effects on the crash risk. The traffic volume of cars across intersections has negative effects on the cycling safety. Regarding bicycle facilities, the number of bicycle lanes on intersection approaches has positive safety effects, whereas the intersections with more bicycle paths is subject to a higher crash risk, though intersection modifications are applied for bicycle paths. The results support the choice of the negative binomial regression over the Poisson regression in this study. The estimated effects provide implications for the cycling safety improvement at signalized intersections.
A novel film based on a cellulose/sodium alginate/gelatin composite activated with an ethanolic fraction of Boswellia sacra oleo gum resin

Abstract Boswellia sacra and its derivatives exhibit notable bioactive properties, which have been the subject of extensive scientific research; however, their potential applications in food packaging remain largely untapped. In the current study, cellulose, sodium alginate, and gelatin composite edible films were fabricated with the addition of different concentrations (0.2% and 0.3%) of the ethanolic fraction of Boswellia sacra oleo gum resin (BSOR). The resultant films were examined for their physical, chemical, mechanical, barrier, optical, and antioxidant properties. Moreover, the films were characterized using Scanning Electron Microscopy (SEM), X‐ray diffraction (XRD), and Fourier transform infrared spectroscopy (FTIR) to study the impact of incorporating BSOR on the morphological, crystalline, and chemical properties of the films. The addition of BSOR increased the film thickness (0.026–0.08 mm), water vapor permeability (0.210–0.619 (g.mm)/(m2.h.kPa), and the intensity of the yellow color (3.01–7.20) while reducing the values of both tensile strength (6.67–1.03 MPa) and elongation at break (83.50%–48.81%). SEM and FTIR analysis confirmed the interaction between the BSOR and film‐forming components. The antioxidant properties of the edible films were significantly increased with the addition of BSOR. The comprehensive findings of the study demonstrated that BSOR possesses the potential to serve as an efficient natural antioxidant agent in the fabrication of edible films.