bluuebunny/crossref_metadata_2025_split huggingface dataset:
Cantor Diagonal Method and the Continuum Hypothesis
Authors: KUNT İBRAHİM 
Published: October 2022

Abstract
Using the relationship between the ordinal number \(\omega\) and the Cantor Diagonal Method, I study the cardinality of the digits of real numbers in a defined range. Using the results I have reached, I show the value of \(\left|\omega +1\right|\) in the ZF¬C system, and I present some conclusions regarding the Continuum Hypothesis through these results.
The effects and interrelationships of intercropping on Cotton Verticillium wilt and soil microbial communities
Authors: Zhang Yun , Yang Yuanxue , Lu Xiuyun , Wang Aiyu , Xue Chao , Zhao Ming , Zhang Jianhua 
Published: October 2022

Abstract
Background: Cotton Verticillium wilt, causing by Verticillium dahliae, has seriously affected the yield and quality of cotton. The incidence of Verticillium wilt in cotton fields has been on the rise for many years, especially after straw has been returned to the fields. Intercropping can reduce the incidence of soil borne diseases and is often used to control crop diseases, but the relationship between the effects of intercropping on microbial communities and the occurrence of plant diseases is unclear. This research explored the relationship between soil microbial community structure and Cotton Verticillium wilt in interplanting of cotton-onion, cotton-garlic, cotton-wheat and cotton monocultures. Amplicon sequencing applied to the profile of bacterial and fungal communities.
Results: The results showed that the disease index of Cotton Verticillium wilt was significantly reduced after intercropping with cotton-garlic and cotton-onion. Chao1 and Sobs indices were not significantly different in the rhizosphere soil and pre-plant soils of the four planting patterns, but the pre-plant fungal shannon index was significantly lower in the cotton-onion intercropping plot than in the other three plots. PCoA analysis showed that the soil microbial communities changed to a certain extent after intercropping, with large differences in the microbial communities under different cropping patterns. The abundance of Chaetomium was highest in the cotton-garlic intercropping before planting; the abundance of Penicillium was significantly higher in the cotton-wheat intercropping than in the other three systems.
Conclusion: Cotton-garlic and cotton-onion interplanting can control Cotton Verticillium wilt by affecting the soil microbial community. Fungi of the genera Chaetomium and Penicillium may be associated with plant disease resistance.
Study on optimal and joint allocation of water and land resources for the multiple objectives
Authors: Wang Jianwei , Qin Tianling , Lv Xizhi , Ni Yongxin , Zhang Qiufen , Ma Li 
Published: October 2022

Abstract
The mismatch of water and land resources leads to various water problem and degradation of ecological function in the basin. The existing water resources allocation and land resource allocation have different objects, basic units, allocation goals and methods, and it is difficult to achieve joint allocation on a unified platform. This paper takes the water and land resources system as the research object. The optimal allocation model of water and land resources was constructed, with the multiple objectives, from aspects of water quantity, water quality, water efficiency, ecological function and the matching degree of water and land resources. The constructed model is used to allocate water and land resources in Sihe River basin, and the results of water and land resources allocation of each configuration unit under different water supply conditions are obtained. This provides technical support for the synthetically delicacy management of water and land resources based on the land unit in the river basin.
Creating new knowledge while solving a relevant practical problem: success factors for an action research-based PhD thesis in business and management
Authors: Alfaro-Tanco José Antonio , Mediavilla Miguel , Erro-Garcés Amaya 
Published: October 2022

Abstract
This paper focuses on university–firm relationships in terms of individual interactions between researchers and practitioners. More specifically, we focus on an analysis of the main factors that influence the use of the action research (AR) methodology to achieve a successful doctoral thesis. In order to achieve this, we developed a Delphi study with 15 panelists whose common characteristic is that they defended or supervised an AR-based thesis in the field of business and management. The primary contribution of the research is the development of a reference framework that should be considered in the design of a doctoral thesis for which an AR methodology is put into practice. Four dimensions were defined: profiles of both the PhD candidate and supervisor, PhD program/university, and firm/organization. Three main conclusions were reached. First, it is crucial to have a cooperative “eye-to-eye” relationship between the university and the company. Second, the AR process must respond unequivocally to its own dichotomous nature. Third, there must be a straightforward academic process for the PhD thesis. We believe that this study may impel the development of doctoral theses based on AR methodology as a tool to potentiate collaborative university–firm relationships.
Ethnobotanical survey of medicinal wild plants in the Shouf Biosphere Reserve, Lebanon
Authors: Hani Nizar , Baydoun Safaa , Nasser Hatem , Ulian Tiziana , Arnold-Apostolides Nelly 
Published: October 2022

Abstract
Background: Medicinal plants and associated traditional knowledge play a vital role in supporting the livelihoods and resilience of indigenous communities. This ethnobotanical survey aims to identify medicinal plants used by the local communities of the Shouf Biosphere Reserve (SBR) and document the associated traditional knowledge.
Methodology: Focusgroups and personal interviews with 133 informants of community members of 22 villages of SBR were performed during 2019-2022. Informants were selected using purposive sampling techniques based on their knowledge of medicinal plants and experience in traditional herbal medicine. Interviews were conducted using a semi-structured questionnaire through field visits.
Results: Informants were equally represented by females and males, had different demographic characteristics, and the main source of knowledge was ancestral.
A total of 184 medicinal plant species belonging to 57 families were documented. The predominant families were Asteraceae (31 spp.), Lamiaceae (14 ssp.), and Rosaceae (14 spp.). Leaves (23%) were the plant part most used. Decoction (45%) was the predominant preparation method, while internal (oral) use (47%) was the most frequent administration mean. Berberis libanotica, Dittrichiaviscosa, and Daucus carota achieved the highest scores of Frequency of Citation (FC), Relative frequency of citation (RFC), Use value (UV), and Fidelity level (FL). Furthermore, the gastrointestinal tract was the most treated system.
Conclusions: Findings revealed a rich and diverse list of medicinal plants with associated traditional knowledge still actively used to treat a wide range of diseases. Future phytochemical and pharmacological studies are recommended to determine the efficacy and safety of plant species used. The management body of the SBR and all related authorities are invited to continue their conservation efforts to protect such rich biocultural heritage.
Modelling of cutter-workpiece engagement with tri-dexel approach for dynamic simulations
Authors: Dambly Valentin , Rivière-Lorphèvre Édouard , Ducobu François , Verlinden Olivier 
Published: October 2022

Abstract
In the context of Industry 4.0, the modelling of machining operations happens to be a crucial aspect of production sector. With adequate models, it is possible to predict the appearance of chatter and select optimised operational parameters. For the dynamics simulation of machine tools or robots performing 5-axis operations, modelling approaches are continuously in improvement. A robust method is proposed for the computation of the cutter-workpiece engagement (CWE) at each step of a dynamic simulation for the determination of the machining forces and the resulting machined surface. The CWE is estimated based on the interference between the workpiece, modelled with tri-dexel approach, and the tool, considered as a triangle-mesh swept volume. The relative-closest triangle algorithm is used for a robust intersection management with 5-axis trajectories. A hybrid dexel-based-analytic method is presented for accurate estimation of the uncut chip thickness. Furthermore, an approach is proposed for a simulation-based evaluation of the part resulting from dynamic simulations by comparing dexel networks with each other, allowing to assess the impact of operational parameters on the parts. The proposition is validated through experimental and virtual data with forces measurements as well as benchmark tests.
A Comparative Study of Severe Thunderstorm among Statistical and ANN Methodologies
Authors: Bhattacharya Sonia , Chakraborty(Bhattacharyya) Himadri 
Published: October 2022

Abstract

Severe Thunderstorm is the extreme weather convective feature. It causes local calamities in various ways. Proper prediction with lead time is an important factor to prevent such calamities for saving the people. Here both probabilistic and machine learning technique is applied on weather data to get proper prediction. Traditional methodologies are already there for such kind of prediction purpose. But Naïve Bayes and RBFN methodology has been introduced here with some specific weather parameters that has not done before remarkably. A comparative study has been done which are Naïve Bayes, Multilayer Perceptron (MLP), K-Nearest Neighbor (K-NN), and Radial Basis Function Network (RBFN) on weather data. All these data have been procured from Kolkata located in North-East India. The result obtained applying Radial Basis Function Network is better among three methods yielding correct prediction of 95% for severe “squall-storm” and 94% for “no storm”. Prediction can have sufficient lead time of 10- 12hours.
Investigation on the residue levels of nine frequently used pesticides in greenhouse grown tomato samples by QuEChERS extraction using GC-MS and HPLC analysis in Hamedan province, I. R. Iran
Authors: Morowati Mohssen , Nikan Jafar 
Published: October 2022

Abstract
Suitable conditions bring about high population of pests or diseases in green-houses and therefore, frequent applications of pesticides occur in this production system which causes public anxiety about pesticide residue in green-house grown crops such as tomato. The present report is the result of an investigation performed on pesticide residue level measurements in green-house grown tomato in Hamadan province. In this study, 43 tomato samples were taken from the green-houses across the province and the residue levels of nine pesticides in each sample were measured. The results indicated that 95.4% of the samples were completely free of all measured insecticides. In 4.6% of the samples the residue of Chlorpyrifos was detected of which the residue level of only one sample (2.3%) was higher than the Maximum residue limit (MRL) for this pesticide in tomato (MRL = 0.1 ppm).
Network pharmacology to explore the mechanism of scutellarin in the treatment of brain ischemia and experimental verification of JAK2/STAT3 signaling pathway
Authors: Jia Qiu-Ye , Chen Hao‑Lun , Qi Zhi , Zhang Xiao‑Li‑Na , Zheng Li-Yang , Liu Teng-Teng , Yuan Yun , Yang Li , Wu Chun‑Yun 
Published: October 2022

Abstract
Objective
This study elucidated the neuroprotective mechanisms of scutellarin in microglia and astrocytes during the progression of neuropathology in cerebral ischemia.
Methods
Network pharmacology was first used to filtrate the core targets and pathways. Arising from this, JAK2/STAT3 signaling pathway was specifically identified and experimentally verified. Expression of JAK2/STAT3 signaling related proteins in TNC-1 astrocytes subjected to different treatments with BV-2 microglia conditioned medium (CM) was then analyzed by western blot and immunofluorescence staining. Along with the above, expression of the various biomarkers was also evaluated in astrocytes given pretreatment with AG490, the JAK2/STAT3 signaling inhibitor. In tandem, middle cerebral artery occlusion (MCAO) in rats was performed in different experimental groups to detect the expression of the above biomarkers in the cerebral astrocytes.
Results
Network pharmacology suggests that JAK2/STAT3 signaling pathway is one of the mechanisms by which scutellarin can mitigate the cerebral ischemia damage. In TNC-1 astrocytes, p-JAK2 and p-STAT3 expression was significantly up-regulated in microglia CM group. Scutellarin promoted the up-regulation of various markers, and of note, AG490 neutralized the effect of scutellarin. In vivo at 1, 3, and 7d after MCAO, p-JAK2 and p-STAT3 expression was significantly increased. Consistent with in vitro results, the rise in expression was augmented by scutellarin.
Conclusion
It is concluded from this study that scutellarin exerts its neuroprotective effects via activated microglia by activating the astrocyte JAK2/STAT3 signaling pathway. This has given the herbal compound a firm experimental basis for its clinical application.
The effect of environmental estrogens exposure on oxidative stress and dyslipidemia, and their impact on insulin sensitivity
Authors: Riiffee Jessica N. J. , Wade Madison , Sine Tyler , Griffith Christopher , Benite-Ribeiro Sandra , Haney Andrea , Santos Julia Matzenbacher dos 
Published: October 2022

Abstract
Bisphenol A and S (BPA and BPS), chemicals used in food packaging, have been closely associated with insulin resistance. However, the mechanism by which BPA and BPS induces type 2 diabetes is debatable. The aim of this study was to investigate if oxidative stress mediates BPA and BPS’s effect on lipid profiles and glucose uptake via insulin and aerobic exercise. Normal weight and overweight/obese subjects participated in 2 separate testing days. On both days, blood glucose was measured before 50 g of maltodextrin consumption and following 30-, 60-, and 75-minutes. On the “Exercising” testing day, subjects ran for 30-minutes at 70% of maximal heart rate; while on the “Resting” day, they remained seated. Urinary BPA, BPS, 8-isoprostane (an oxidative stress marker), creatinine, lipid profile, body fat percentage and physical fitness were measured. The exercise condition produced a decrease in blood glucose during the 30-60-minute protocol interval within normal and overweight/obese subjects when compared to the resting day. Blood glucose of both experimental days was negatively associated with body fat (r=-0.58) only. Urinary BPA and BPS were positively associated with oxidative stress (r = 0.62 and 0.82, respectively). BPA and oxidative stress were negatively associated with physical fitness (r=-45 and − 0,5, respectively), while BPS and oxidative stress were associated with increased triglycerides (r = 0.47 and 0.49, respectively). Oxidative stress mediates the effect of BPA and BPS on risk factors related to T2D development. Thus, modulating oxidative stress could be a valuable strategy to attenuate the effect of bisphenols in the human body.
Walking and cycling infrastructure priorities: Qualitative testing of a Best-Worst Scaling experiment
Authors: Albahlal Fahad , Haggar Paul , Potoglou Dimitris 
Published: October 2022

Abstract
The built environment plays an important role on individuals’ propensity to walk and cycle and local authorities increasingly invest financial resources towards their development. Organisations managing the built environment have developed auditing tools as guidelines to inspect routes and identify improvements to support active travel. Using several auditing tools, this study developed 21 walking and 25 cycling investment-relevant factors that were embedded into two choice-based survey instruments focusing on walking and cycling, respectively. The study aims to internally validate a preference-based elicitation approach known as Best-Worst Scaling (BWS) aimed to capture pedestrian and cyclist preferences. Preferences directly translate into investment priorities aimed at increasing the rates of walking and cycling. As part of a survey instrument, these experiments will help obtain a ranking (preference) order of the most and least important factors that are likely to encourage people to walk and cycle on a common scale. We report findings on the internal validity of the BWS choice tasks as these were examined via a series of cognitive interviews with 20 participants (10 participants for each experiment). In both sets of interviews, four themes emerged regarding how the participants approached the BWS task and six themes related to the understanding of the factors. The study findings provide insights on how participants perceive BWS experiments, which can improve our large-scale BWS survey and similar studies. Furthermore, the study aims to produce an internally consistent BWS instrument that any local authority can use to determine which walking and cycling infrastructure investments to prioritise.
Application of CNN-SCN in early diagnosis of Alzheimer's disease
Authors: TONG Yinsheng , Li Zuoyong , Huang Hui , Gao Libin , Xu Minghai , Hu Zhongyi 
Published: October 2022

Abstract
Background: The early and effective diagnosis of Alzheimer's disease(AD) and mild cognitive impairment(MCI) has received increasing attention in recent years.There are many machine learning and deep learning methods that are widely used in neural image analysis, among which structural magnetic resonance images play an important role in early diagnosis and intervention for patients with Alzheimer's disease and mild cognitive impairment as a data pattern, and many studies have constructed many network models based on structural magnetic resonance images, but most of the existing studies do not pay enough attention to the spatial structure information in structural magnetic resonance images, and do not go deeper to explore the potential connection between spatial slices and slices,thus making the network models less accurate, poor generalization ability and other problems.We believe that the lesion areas are highly correlated with other areas,and there is a certain relationship between spatial context slices.To explore deeper the connection between spatial context slices and solve the above problems,this research is designed to develop a new deep learning method to effectively detect or predict AD by digging into the deeper spatial contextual structural information.
Results: In this paper, we design a spatial context network based on 3D convolutional neural network to learn the multi-level structural features of brain MRI images for AD classification.In addition, this paper designs a new deep learning framework to adapt spatial contextual association networks for early diagnosis of Alzheimer's disease. The experimental results show that the model has good stability, accuracy and generalization ability.Our experimental results showed an accuracy of 92.6% in the AD/CN group, 74.9% in the AD/MCI group, and 76.3% in the MCI/CN group, and several experiments showed that the model has excellent generalization ability.
Conclusions: From the comparison of a large number of experimental results, it can be seen that the spatial contextual domain association network can effectively mine the potential information of spatial contextual structural features. The network has better results for the cases that need to go for spatial structure contextual association features.
Comparative Analysis of Steel Buildings With and Without Bracings in Nepal
Authors: Suwal Rajan , Dahal Peshal , Shrestha Prabesh 
Published: October 2022

Abstract
The past few years has seen a remarkable increase in the construction of steel framed buildings in Nepal. This has provided a much-needed architectural relief to urban centers full of RC buildings. The main reasons for this current proclivity towards steel buildings can be attributed to the faster time of erection of steel buildings, its light weight resulting in easier handling and cheaper transportation, and lower material cost. However, because of its flexible nature, an unbraced steel building will have higher storey displacement when compared to the RC buildings. For mid-rise and high-rise buildings, the steel frames need to be equipped with braces to keep the storey drifts and displacements within acceptable limits. This will result in a stiffer building and hence result in increased base shears and bending moments. This change in base shears and storey drifts along with the building’s fundamental time period may not be similar for different positions of braces despite the use of similar bracing sections. This paper aims to find such differences, if any, to aid designers in selecting optimum position for braces while designing steel framed buildings.
Who suffered the income loss in India during the COVID-19 lockdown?
Authors: Das Amarendra , Das Bibhunandini , Gual Laxmikanta 
Published: October 2022

Abstract
The worldwide spread COVID 19 Pandemic has severely impacted the lives and livelihoods of all sections of the society. Due to the nationwide lockdown during the first wave, a record high level of unemployment was witnessed. In this context, we have tried to answer who suffered the income loss in India during the first phase of COVID-19 lockdown? Did the low-income households suffer more income loss than the high-income households? Did the households that had COVID-19 infection suffer more income loss? Did rural households suffer more income loss than urban households? Did the households residing in the red zone suffer more income loss than others? We observe that a relatively more significant proportion of low-income households suffered income loss than high-income households. A higher percentage of households reporting job loss suffered the income loss. We did not find any significant difference between the income loss of households residing in the red zone and other zones and rural and urban areas. Similarly, education of the households, household size, and COVID infection did not make a significant difference to the income loss of the households.
JEL Codes: E66, E24, E29
Effect of Site Specific Soil Characteristics on the Nonlinear Ground Response Analysis
Authors: CİVELEKLER Ebru , Afacan Kamil Bekir 
Published: October 2022

Abstract
Damages occurring during earthquakes may vary depending on the ground conditions in which the earthquake waves pass, the magnitude of the earthquake, the focal depth of the shaking and as well as the structural characteristics. Regional seismicity, ground movement and behavior of local soil conditions are important in earthquake-resistant building designs. Local site conditions consists of the layering, bedrock depth, dynamic and topographic characteristics of soil alter the the bedrock waves through the soil profile during an earthquake. The change occurs in terms of amplitude, frequency and the time where peak happens during the wave propagation. This initiates a big difference between the surface and bedrock motion. The behavior of the soil under cyclic loads resulting from seismic action is non-linear. The aim of this study is to demonstrate the effects of strong ground motion by taking into account the nonlinear behavior of the soil layers. In addition, in this study, the results obtained from the equivalent linear and non-linear methods were compared, taking into account the results of the equivalent linear analysis conducted before for the same boreholes. The results of the study showed that the characteristics of soil layers and strong ground motion significantly affect the field response analysis and generally larger spectral parameters have been obtained with the equivalent linear method.