bluuebunny/crossref_metadata_2025_split huggingface dataset:
Managing corporate business travel policy: A quantitative approach using machine learning
Authors: Zarate-Carbajal Jose-Mario , Ruiz-Cruz Riemann , Sanchez-Torres Juan Diego 
Published: October 2022

Abstract

There is a constant conflict in global corporations between satisfying the business needs and complying with the travel policy to avoid paying over-priced fares. This article reviews the nature of business travel, discusses its main characteristics, and the complexity for management in defining the policy. A travel policy must be feasible to comply with and contribute to optimizing the budget. Each company requires a different policy according to business needs; a manufacturing company with planned trips requires a different policy than a consulting firm with unpredictable trips. We adapted the machine-learning algorithm of regressive decision trees to include the characteristics of business travel policy; our algorithm self-adjusts to each company's data. We test our results using travel data from a company and simulating different scenarios. Our findings support management with a quantitative method to determine the optimal travel policy.
JEL Classification: M10 , M19 , C610 , C630
Impacts of Changes in Land Use and Coverage on the Ibicuí River Basin
Authors: Leal Desirreé Cristine Pena Vieira , Adam Katiúcia do Nascimento , Hüffner Anelise Nardi , Fernandes Lindemberg Lima , Sena Manoel José dos Santos 
Published: October 2022

Abstract
The need to manage water resources and the way they behave in the face of changes in land use are essential for managing a watershed. In this context, a large basin modeling tool was applied to simulate the flow regime of the Ibicuí River basin considering two land use scenarios. The results were used to analyze the changes in the maximum and minimum annual and monthly average flows. The greatest change in land use was the forest coverage reduction associated to agriculture land use. As a result, an increase in the average monthly flows and in the reference flow Q90 was verified. In some sub-basins, a significant modification in the reference Q90 flow and maximum flow was verified. The Mann Whitney test showed that the results were accurate. The results indicated that changes in forest coverage and land use have an impact in the flow regime in the Ibicuí Watershed. The procedure used in this research can be applied to simulate future scenarios of land use and its impacts in the sub-basin´s flow rates.
Superpixel Driven Unsupervised Deep Image Super-resolution
Authors: Yang Jun , Zhang Chao , Xu Li , Luo Bing 
Published: October 2022

Abstract
Most of the existing deep learning-based image super-resolution methods require a large number of datasets or ground truth. However, these methods are not suitable for the restoration of real image with different domains. Recently, Deep Image Prior (DIP) based on single-image explores image prior and uses network structure as implicit image prior to recover images, but it ignores the explicit prior information of the actual image itself. The addition of image prior can effectively alleviate the ill-posed problem in the image restoration model. Therefore, in this paper, we propose an unsupervised deep image super-resolution (SR) method that based on segmentation driven. Intuitively, clear image has a clearer segmentation boundary. It will drive deep neural networks (DNN) to obtain higher performance SR image when forcing the restored image to have clear boundary. In order to make energy flow into DIP better, we use the fully convolutional networks-based (FCN-based) superpixel method, and we use back propagation to inject the gradient generated by segmentation entropy energy into DIP to obtain lower energy optimization parameters. Experiments show that the image generated by our method has clearer boundary and better performance than that generated by DIP on Set5, Set14 and BSD100.
Channel Splitting-and-Merging Connection in Neural Networks
Authors: Zhu Meng , Min Weidong , Han Qing , Zhan Guowei , Fu Qiyan , Li Jiahao 
Published: October 2022

Abstract
Neural networks have achieved success in both computer vision and natural language processing. The existing state-of-the-art neural networks dedicate to increase model complexity for improving performance. However, this causes two problems. One is that these neural networks cannot be deployed in computationally limited platforms. The other is that these neural networks cannot meet real-time requirements for large resolution input. To alleviate the two problems, we propose a novel skip connection method called channel splitting-and-merging (CSM) connection, which is aimed to directly replace the residual connection method in neural networks while reducing parameters and running latency. By dissecting the channel shuffle connection method, it is found that channel splitting and channel merging operations efficiently reduce model complexity. Therefore, we introduce these two operations into the residual mapping for reducing model complexity. A range of tasks show that replacing the residual connection method with our CSM connection method effectively reduces parameters and FLOPs at a little cost of losing performance. The experimental results show that our CSM connection outperforms the channel shuffle connection method while utilizing less inferring time and equal number of parameters.
The relationship between headache- attributed disability and lost productivity. 3. Attack frequency is the dominating variable
Authors: Husøy Andreas , Katsarava Zaza , Steiner Timothy J 
Published: October 2022

Abstract
Background
In an earlier paper, we examined the relationship between headache-attributed disability, measured as proportion of time in ictal state (pTIS), and lost productivity. In a linear model, we found positive and significant associations with lost paid worktime, lost household worktime and total lost productivity (paid + household), but with high variance, which was increased when headache intensity was introduced as a factor. We speculated that analyses based on headache frequency alone as the independent variable, eliminating both the subjectivity of intensity estimates and the uncertainties of duration, might show stronger associations.
Methods
Focusing on migraine, we used individual participant data (IPD) from 16 countries surveyed either in population-based studies or in the Eurolight project. These data included frequency (headache days/month), usual attack duration (hours), usual headache intensity (“not bad”, “quite bad”, “very bad”) and lost productivity from paid and household work according to enquiries using the Headache-Attributed Lost Time (HALT) questionnaire. We used multiple linear regressions, calculating regression equations along with unstandardized and standardized regression coefficients. We made line and bar charts to visualize relationships.
Results
There was no collinearity between the independent variables. Both frequency and intensity were highly significant predictors of lost productivity in all multiple linear regressions, with linear relationships in both genders between frequency and lost productivity from both paid and household work. Visualizations showed that relationships between intensity and lost productivity were more or less linear in both genders, while the impact of duration varied little across the range of 2–24 hours. The standardized regression coefficients demonstrated that frequency was a much better predictor of lost productivity from paid work than intensity or duration.
Conclusion
In the relationship between migraine-attributed impairment (symptom burden) and lost productivity, frequency (migraine days/month) is the dominating variable – more important than headache intensity and far more important than episode duration. This has major implications for current practice in headache care and for health policy and health-resource investment. Preventative drugs, grossly underutilized in current practice, offer a high prospect of economic benefit (cost-saving), but new preventative drugs are needed with better efficacy and/or tolerability.
The Effect of Cybercrime on Financial Institutions: A Case Study of Mumuadu Rural Bank, Osino in the Fanteakwa District - Eastern Region, Ghana
Authors: Ghann Patricia , Owiredu Joseph , laryea Samuel Afotey 
Published: October 2022

Abstract
Crimes committed via the internet and other electronic media are a growing threat and an important subject to most organizations. This is because most organizations rely on the internet to provide services to customers. Thus, the use of the inter-networked system of communication in organizations such as the banks poses challenges to both customers and organizations on daily basis. This study analyses cybercrime activities and their effects on Financial Institutions; a case study of Mumuadu Rural Bank Limited, Osino in the Fanteakwa District - Eastern Region. The study was guided by three objectives and used a mixed-method (both qualitative and quantitative) approach in data collection. The total estimated sample size was 30 staff out of a population of thirty – two (32). A questionnaire was used to obtain information from 29 respondents who were randomly selected from the population while an interview was used to solicit further details from the bank’s General Manager who was purposively selected. The findings revealed that cybercrime and information security breaches have reached an alarming proportion with negative consequences on financial Industries. As a result, the bank has different insurance accounts set aside to protect customers against losses that may arise from cybercrime attacks or other related losses that may affect customers. It also emerged that young people in the district mostly indulge in cybercrime activities with the motive of living a luxurious life due to economic hardship attributed to unemployment, and lack of strong policies or legislation. Furthermore, the study also recorded a high rate of respondents who cited a loss of customer confidence due to cybercrime which has led to the loss of lives of customers and a reduction of revenue target of the bank as part of the effects of cybercrime on the bank. Additionally, the research identified some knowledge gaps and consequently recommended that cyber insurance policies be available and also be strengthened to help financial institutions compensate those who may be victims of a cybercrime attack. Furthermore, the paper suggests that organizations be constantly updated by the Security Agencies on the emerging techniques that are deployed by cybercriminals.
Effect of Nano Urea on Growth and Yield of Potato in Lower Gangetic Planes of West Bengal
Authors: Dutta Debashis 
Published: October 2022

Abstract
In today’s world it is the need of the hour to adopt new technology to sustain the production of future. Nano technology is gaining popularity for its efficiency over various applied field of science. In agriculture the nano materials have a huge impact on efficiency of fertilizer pesticides etc. As it requires in very less quantity and has a negligible residual effect the environment is safe with the innovation of Nano fertilizer. Keeping this view into account an experimental Trial at farmer’s field was carried out at Berui village in Hooghly District of West Bengal during the winter (rabi) season of 2019 – 20 under the supervision of Berui Cooperative, KVK-Hooghly, BCKV and IFFCO with nano-Urea, nano-Zn and nano-Cu using RBD design with 10 treatments and 3 replications. Experimental results revealed that highest tuber yield was obtained in T-7 (50% N+100% P & K+ 2 spray of nano-Urea), and that was followed by T-10 (50% N + 100% P & K + 50% Zn + 1 spray each of Nano-Urea, Zn and Cu) and T-8 (100% N-P-K + 50% Zn + 2 spray of Nano-Zn). The performance of nano fertilizers, Nano- Urea, was quite promising and economically viable as compared to 100% recommended dose with commercial fertilizers (RDF).
Deep Residual Learning with Attention Mechanism for Breast Cancer Classification
Authors: Toa Chean Khim , Elsayed Mahmoud , Sim Kok Swee 
Published: October 2022

Abstract
Invasive Ductal Carcinoma (IDC) is a common form of breast cancer that can be found in women. In traditional medical practice, physicians have to manually test and classify the areas which they suspect to be cancerous. However, the literature strongly shows that that the process manual segmentation done by the medical practitioners, is neither time-efficient nor accurate as it depends on their subjective judgment. The model called Residual Attention Neural Network Breast Cancer Classification (RANNBCC) is introduced in this paper to help medical practitioners in the cancer diagnostic process. RANNBCC utilizes Residual Neural Network (ResNet) as an expert-supportive method to help medical practitioners in cancer diagnosis. The implementation of RANN-BCC can support the classification of Whole Slide Imaging (WSI) into non-IDC and IDC without prior information about the presence of a cancerous lesion. The result of classification shows that the RANN-BCC model achieved 92.45% accuracy, 0.98 recall, 0.91 precision, and 0.94 F-score which outperform other models such as CNN, AlexNet, Residual Neural Network 34 (ResNet34), and Feed Forward Neural Network. The developed RANN-BCC model aims to help medical experts classify IDC and non-IDC of breast cancer by learning the feature content of medical images.
Bioaccumulation of trace elements in vegetables grown in various anthropogenic conditions
Authors: Kaledin Anatoly , Stepanova Marina 
Published: October 2022

Hazardous compounds accumulate in plants and animals as a result of anthropogenic impact. Trace elements, such as heavy metals, move up in the system of snow – soil – water – plant – animal. When contaminants accumulate in plants that serve as animal feed, they eventually accumulate in the animals that consume the feed because heavy metals usually enter living organisms via digestive tract, i.e., with food.
In 2003–2021, we studied fodder plants grown and harvested by urban zoological organizations, e.g., zoos, nature corners, etc. This research covered the Central Federal District represented by the cities of Moscow, Ivanovo, Yaroslavl, and Uglich. The empirical part of the study relied on a combination of modern ecological, biochemical, and statistical methods. A KVANT-2AT atomic absorption spectrometer was used to define the trace elements and their quantities.
Broccoli proved to be the most resistant feed vegetable to all the toxic elements in this study. Kohlrabi, sweet potato, and dill had low content of lead and cadmium, while garlic was highly resistant to cadmium and arsenic. Spinach, fennel, potatoes, beets, and bell peppers, which were used as fodder in metropolis conditions, exceeded the maximal permissible concentration of heavy metals. The samples obtained from the Moscow Zoo contained by 1.98 times more zinc, by 1.06 times more copper, and by 89.47 times more lead than average. The samples from Ivanovo accumulated the greatest extent of iron, which exceeded the average level by 3.26 times. The vegetables from Uglich and Ivanovo had the lowest concentration of zinc, which was by 67.86 and 62.70% below the average, respectively. The samples from Yaroslavl contained by 33.08% less copper. In 2003–2021, feed vegetables grown in the Central Federal District had an average increase in zinc, copper, and lead by 1.13, 1.45, and 2.80 times, respectively. The level of iron stayed almost the same throughout 2018–2021, while that of arsenic gradually decreased in concentration. The accumulation level of zinc, copper, iron, and arsenic in feed vegetables appeared to depend on the concentration of their water-soluble metal forms in the soil.
Therefore, forage agriculture in urban areas requires constant chemical and toxicological tests to prevent contaminated feed from entering animal diet.
Novel construction of the catalyst from red mud by the pyrolysis reduction of glucose for the peroxymonosulfate-induced degradation of m-cresol
Authors: Chen Hongliang , Li Longjiang , Zhang Yutao 
Published: October 2022

Abstract
Red mud of low cost is regarded as a promising alternative to heterogeneous catalysts for activating peroxymonosulfate (PMS) to degrade m-cresol. Improper valence states of metal oxides and coated active substances in red mud greatly hampered its wide application. To solve this problem, the modified red mud (WRMG/700) was prepared by the pyrolysis reduction of glucose in N2 atmosphere. X-ray diffraction (XRD), scanning electron microscopy (SEM) and X-ray photoelectron spectrum (XPS) analysis confirmed the production of Fe3O4, MnO and NiO in red mud and their gathering on the surface of particles. WRMG/700 exhibited the excellent performance toward PMS activation for the m-cresol degradation with 99.02% degradation efficiency and a pH-independent catalytic activity between initial pH 3–8. The removal efficiency of COD increased with the reaction time under the optimized degradation conditions. The free radical scavenging experiments and electron paramagnetic resonance (EPR) test confirmed 1O2 played a dominant role during m-cresol degradation in the WRMG/700/PMS system, implying m-cresol degradation was a non-radical oxidation process. Accordingly, the possible reaction mechanism was proposed. WRMG/700 retained its activation performance even after five recycles. This study showed a low cost and simple operation process for m-cresol elimination.
Optimization of constructed wetlands on purifying black-odorous water and their potential purification mechanism
Authors: Chen Chun-xing , Yang Feng-juan , Deng Yang-yang , A Dan 
Published: October 2022

Abstract
Black-odorous water has become a common and widespread problem in recent decades. In this study, nine constructed wetlands (CWs) with different flow types, filters, plants, and hydraulic loadings were designed according to an orthogonal array (L9 (34), and were used for the purification of black-odorous water in summer and winter. The results showed that CWs are regarded as effective to purify black-odorous water in both seasons. Microbial degradation is the major removal pathway of pollutants in CWs during summer, while the joint effect of biodegradation and adsorption is the main treatment route during winter. Flow type and hydraulic loading appear to be the most important factors impacting the purification performance of CWs, by changing the redox condition of systems and retention time of contaminants, respectively. ‘Vertical flow-zeolite filter-high loading’ is proposed as the best parameter selection for CWs on the purification of black-odorous water: among them, CWs with vertical flow have better oxygen transport capacity that is conductive to aerobic processes of pollutants, zeolite substrates may adsorb more nitrogen via ion exchange, higher hydraulic loadings can extend the contact time between contaminants and filters, and regulate the water temperature for microbial activity.
Long Non-coding RNA LINC00473 Promotes Breast Cancer Progression
via miR-424-5p/CCNE1 Pathway
Authors: Zhang Chao , Yang Ting 
Published: October 2022

Background:
There has been a large increase in the incidence of breast cancer (BC) among
women. LINC00473 is a cancer-related lncRNA, participating in the progression of many cancers, but
its role in the progression of BC awaits more elaboration.

Methods:
Quantitative real-time polymerase chain reaction (qRT-PCR) was used to quantify
LINC00473, miR-424-5p, and cyclin E1 (CCNE1) mRNA expression levels in BC tissues and cells.
Cell counting kit-8 (CCK-8) assay was employed to detect the cell viability; the cell migration and
invasion abilities were evaluated by the Transwell assay. Western blot and immunohistochemistry
(IHC) were adopted to study CCNE1 protein expression; dual-luciferase reporter assay was performed
to clarify the targeting relationships among LINC00473, miR-424-5p, and CCNE1.

Results:
LINC00473 expression was elevated in BC tissues and cell lines, which was associated with
lymph node metastasis and higher clinical stage of the patients with BC. LINC00473 proved to be a
molecular sponge for miR-424-5p; LINC00473 knockdown impeded the growth, migration, invasion,
and epithelial-mesenchymal transition of BC cells, while these effects were abolished by miR-424-5p
inhibitors; miR-424-5p targeted CCNE1 to restrain its expression. LINC00473 positively regulated
CCNE1 expression, and CCNE1 restoration counteracted the effects induced by LINC00473
knockdown in BC cells.

Conclusion:
LINC00473 facilitates the progression of BC through miR-424-5p/CCNE1 axis.
Toxicological Advancements in Cocaine Detection: A Review
Authors: Patanè Federico Giuseppe , Maria Maglitto Andreana Nicoletta , Esposito Massimiliano , Cocimano Giuseppe , Di Nunno Nunzio , Salerno Monica , Sessa Francesco 
Published: October 2022

Abstract:
Cocaine, also known as methyl benzoylecgonine, is one of the most used
drugs of abuse and one of the oldest; however, there has been a recent increase in the consumption
of this substance. This trend has once again caught the attention of the scientific
community. We discuss the current knowledge about this drug, focusing our attention
on the forensic approach. Despite the fact that the cut-off of positivity to cocaine in drug
tests is quite high, most current tests are able to detect much lower concentrations and
could improve forensic sciences in both post-mortem investigations and in people screening.
Immunological assays possessing substantial cross-reactivity to cocaine are particularly
useful for screening oral fluid, hair, and post-mortem blood, where significant concentrations
of the drug can be found. Liquid chromatography has now supplanted the previous
techniques because it is very sensitive and specific and allows samples to be analyzed
in a shorter time with only minimal sample preparation. Recent studies have focused
on increased sensitivity, reduced processing times, and cheaper analysis.
A Deep Dive in the Involvement of the Cerebellum in Epilepsy: A Neuroanatomical and Cellular Approach
Authors: Rubio Carmen , Moreno Wilhelm , Ochoa Ernesto , Uribe Eric 
Published: October 2022

Objective:The purpose of this article is to describe the state-of-art of neuroanatomical and cellular aspects of the cerebellum in epilepsy.Background:Over the years, cerebellum epileptogenesis has been widely studied. There is growing evidence linking the cerebellum with this pathology by several other structures involved: mainly the limbic system, thalamus, cerebral cortex, red nucleus, and reticular formation. As a result, these anatomical and cellular changes in the cerebellum might trigger the genesis and propagation of seizures.Discussion:We herewith outline the cerebellum's deep nuclei physiological pathways, responsible for seizure spread via ion channels and neurotransmitter dysfunction. Additionally, we describe the shifts in seizures produced after cell death, gene expression, and protein interaction with their respective molecular and anatomical pathways.Conclusion:Finally, we highlight the role played by the cerebellum in seizure propagation to the brain and how it can be counteracted in some subtypes of drug-resistant epilepsy.