bluuebunny/crossref_metadata_2025_split huggingface dataset:
Suicidality and Non-Fatal Self-Injury Behaviors Among Epileptic Patients in Neurology Clinic at Zewditu Memorial Hospital and Amanuel Mental Specialized Hospital, Addis Ababa, Ethiopia, a Cross-Sectional Study
Authors: Anbessie Mohammed N. , Gebrehanna Ewnet , Zewde Yared Z. , Ayele Biniyam A. 
Published: November 2022

Abstract

Background: - Suicidality /suicidal ideation and plan/ and non-fatal self-harm behaviors are more frequent among People living with Epilepsy (PWE) than the general population. The increased risk of suicidality and non-fatal self-harm behaviors and associated factors among people with Epilepsy varies across sociodemographic and disease-related factors as well as comorbid psychiatric conditions. The study aimed to determine the magnitude of suicidality and non-suicidal self-injury behaviors and identify its associated factors among People with Epilepsy seeking medical care at Amanuel Mental Specialized Hospital and Zewditu Memorial Hospital, Addis Ababa, Ethiopia 2021.
Methods: - Facility-based cross-sectional study was conducted on randomly selected 345 epileptic patients that attended the outpatient neurology treatment service at Amanuel Mental Specialized Hospital and Zewditu Memorial Hospital. The study was conducted from 15 December 2020 to 15 February 2021. The WHO composite international diagnostic interview (CIDI) was used to assess suicidality, depression, and epilepsy-related factors. Association between outcome variables and selected independent variables was tested using a logistic regression model.
Result: - The magnitude of suicidal ideation, plan, and non-fatal self-injury behavior among people living with epilepsy were 21.2, 18.3, and 11.9% respectively. Living alone, Poor social support, and comorbid depression were significantly associated with suicidal ideation, plan, and nonfatal self-injurious behavior. Those who were taking 2 or more Anti-Epileptic Drugs also showed statistical association with suicidal ideation (AOR 0.45, 95% CI= .21, .97; p=0.041) and suicidal plan (AOR 0.36, 95% CI= .162, .815; p=0.014) respectively.
Conclusion - The prevalence of suicidal ideation, and non-fatal self-injurious behavior among people with epilepsy was high among Ethiopian epileptic patients in a hospital setting. Routine screening and proper intervention for comorbid depression as well as avoiding polytherapy might prevent suicidality and non-fatal self-injurious behavior, A strong social support also helped in preventing suicide as well as improving quality of life.
Relationships of perception of health risks by use of pesticides: A Man-Environment look.
Authors: Silverio Astrid Merino , Cunha Maristela Casé Costa , de Andrade Wbaneide Martins , Simplício Luane dos Santos 
Published: November 2022

Abstract
The use of agricultural pesticides is increasingly associated with public health problems and negative impacts on the environment, in addition to the lack of protective actions developed by Brazilian environmental agencies. Our objective in this study was to analyze the relationships in the process that lead to the perception of risk of damage to human health by the use of pesticides in the riverine farming communities of the São Francisco Valley, in Brazilian northeast. We carried out a qualitative literature review, using the Constructivist Grounded Theory applied to the review of published scientific articles. The elements in the perceptive process found were: 1) the environment; 2) conditioning factors; 3) the perception of the human body; 4) the memory; 5) socio-cognitive processing; 6) automatic response; 7) the decision process and 8) the behavior. Each of those elements and its relationships guide where the causes of an inadequate perception to resolve them.
Challenges and Approaches when Realizing Online Surface Inspection Systems with Deep Learning Algorithms
Authors: STEPHANI Henrike , WEIBEL Thomas , RÖSCH Ronald , MOGHISEH Ali 
Published: November 2022

Abstract
Using deep learning in complex online surface inspection systems is challenging due to different framework conditions. First, time restrictions in production are usually fixed in terms of clock rate and response time. Furthermore, these methods need a lot of data, while typically the data situation is thin in the beginning as well as continuously unbalanced: defects occur rarely and thereby providing few example data for learning, while the desired detection rate is 100%. Another important issue is that although defect catalogues exist, they often change, especially when automatic inspection is applied for the first time. This is due to imaging systems usually being able to detect more defects than visual-manual inspection, therefore production, management, and quality assurance usually reiterate their prior defect catalogues. However, data driven methods depend heavily on consistent annotation. Therefore, respective parties must be made aware of this issue on the one hand, on the other hand, annotation and reannotation must be easy and useable by non-experts. Related is the issue of parametrization and traceability. Both are not inherent to neural networks but must be provided to some level to help building trust in machine learning methods. In this paper, we present a quality inspection system that uses deep neural networks for defect detection under real production conditions in wood manufacturing. We will address how we systematically deal with the above issues both in terms of process and algorithm.
Range margin reduction in carbon ion therapy: potential benefits of using radioactive ion beams
Authors: Sokol Olga , Cella Laura , Boscolo Daria , Horst Felix , Oliviero Caterina , Pacelli Roberto , Palma Giuseppe , Simoni Micol , Conson Manuel , Caroprese Mara , Weber Ulrich , Graeff Christian , Parodi Katia , Durante Marco 
Published: November 2022

Abstract
Sharp dose gradients and high biological effectiveness make heavy ions such as 12C an ideal tool to treat deep-seated tumors, however, at the same time, sensitive to errors in the range prediction. Tumor safety margins mitigate these uncertainties, but during the irradiation they lead to unavoidable damage to the surrounding healthy tissue. To fully exploit the Bragg peak benefits, a large effort is put into establishing precise range verification methods. Despite positron emission tomography being widely in use for this purpose in 12C therapy, the low count rates, biological washout, and broad activity distribution still limit its precision. Instead, radioactive beams used directly for treatment would yield an improved signal and a closer match with the dose fall-off, potentially enabling precise in vivo beam range monitoring. We have performed a treatment planning study to estimate the possible impact of the reduced range uncertainties, enabled by radioactive 11C ions treatments, on sparing critical organs in tumor proximity. Compared to 12C treatments, (i) annihilation maps for 11C ions can reflect sub- millimeter shifts in dose distributions in the patient, (ii) outcomes of treatment planning with 11C significantly improve and (iii) less severe toxicities for serial and parallel critical organs can be expected.
Preconditioning with interleukin-1 alpha is required for the neuroprotective properties of mesenchymal stem cells after ischaemic stroke in mice
Authors: Wong Raymond , Smith Craig , Allan Stuart , Pinteaux Emmanuel 
Published: November 2022

Abstract
Mesenchymal stem cells (MSCs) pre-conditioning with interleukin-1 alpha (IL-1ɑ) drives MSCs toward a potent anti-inflammatory and pro-trophic phenotype. The aim of this study was to assess the therapeutic potential of IL-1ɑ preconditioning of MSCs, administered intra-arterially (a clinically relevant approach in the setting of thrombectomy) after experimental cerebral ischaemia in mice. Focal ischaemic stroke was induced by filament occlusion of the middle cerebral artery in mice. After 3 h from start of occlusion, animals were treated with vehicle, 9.1x104 non-conditioned or IL-1ɑ preconditioned MSCs by intra-arterial administration. Animals were allowed to recover for 3 days or 14 days post-stroke and lesion volume and functional outcomes were evaluated. To assess reperfusion cerebral blood flow was measured at 1.5 h after treatment using laser speckle imaging in a separate cohort of animals. Preconditioned MSCs reduced lesion volume and neurological deficits compared to vehicle by 67%, while non-conditioned MSCs had no effect, at 3 days post-stroke. A separate cohort of animals recovered to 14 days post-stroke also showed reduced infarct volume at 48 h (assessed by MRI) when treated with preconditioned MSCs, along with lower neurological deficits at 14 days and better weight recovery compared to vehicle treated mice. Cerebral blood flow was increased by preconditioned MSCs compared to vehicle by 32%. Preconditioning MSCs with IL-1α increases their neuroprotective capability and improves functional recovery after delayed intra-arterial administration in a mouse model of focal cerebral ischaemia. With increasing use of thrombectomy the adjunct use of preconditioned MSCs therefore represents a highly relevant therapy to improve outcomes in ischaemic stroke.
Nairobi Fly Dermatitis outbreak Investigation in Bodite town AdministrationWolaita Zone, Southern Ethiopia, April, 2018
Authors: Gunta Mesay , woldetensai Abate , Hailu Mesay , Sugerman David , Bekele Haile , Shibeshi Behailu 
Published: November 2022

Abstract
Background: Nairobi fly dermatitis is unusual form of contact dermatitis caused by pederine, ahemolymph fluid released when the insects are crushed against the skin. Patients often present with a sudden onset burning sensation and cutaneous pain. The insects are belonging to the genus Paederus. These insects are found worldwide, although the concentration is higher in tropical and subtropical areas. In Ethiopia, more particularly in Wolaita, Nairobi fly dermatitis is uncommon previously. Hence, we aimed to describe the clinical characteristics and identify risk factors prone to the disease.
Methods: We conducted unmatched case-control study (ratio 1:2) with 45 cases and 90 controls from April 5 to 14, 2018 in Ade charake Village, Southern Ethiopia. Cases were patients who had a history of linear dermatitis, kissing/mirror image/ lesions, multiple vesiculo-pustular lesion, extensive pustules, blistering and papulo-pustular lesions over face, neck, arms, shoulders, axillaries region, lower limbs, chest, upper limbs or any other area of the body in Ade Charake Village in the study period. Controls were asymptomatic individuals selected randomly from the households or neighbors during the outbreak period. The investigators initially developed a clinical-epidemiological questionnaire to obtain data from cases as well as controls. Basic descriptive summary including attack rate, in addition to bivariate and multivariable logistic regression was computed. The odds ratio was computed at 95% CI with a P-value <=0.05 to ascertain the association.
Results: Among 45 cases, 60 %( 27/45) were females. The commonly affected age groups were between 8-15 years 31% (14/45). The frequently appearing clinical manifestation was Erythmato-vesicular lesions 40% (18/45) and most patients 71% (32/45) presented with a complain of burning sensation followed by pruritus 62% (28/45).We found that use of light during sleep (AOR=8.5,95% CI, 1.033-64.8), disposing wastes near vicinity(AOR=5.44, 95% CI 2.094,14.1250) and proximity of dense vegetations or fruit in the vicinity (AOR=7,95% CI, 1.143-43.78) were risk factors to develop Nairobi fly dermatitis.
Conclusion: We found that Nairobi fly dermatitis predominantly affects females while sleeping with light on and disposing of wastes near vicinity. The presence vegetation’s and/or fruits in the neighborhood found to be the risk factors for Nairobi fly dermatitis.
Toward Reduced CO2 Emissions from Vehicles: Onboard Capture and Storage System Using Metal-Organic Frameworks
Authors: Pezzella Giuseppe , Bhatt Prashant M. , AlHaji Abdulhadi , Ramirez Adrian , Grande Carlos A. , Gascon Jorge , Eddaoudi Mohamed , Sarathy S. Mani 
Published: November 2022

Abstract
The transportation sector is among the largest contributors to carbon dioxide (CO2) emissions and demands immediate action. Although electrification is a promising technology to decarbonize light-duty vehicles, it has limited potential when applied to heavy trucks due to their longer travel distances and weight constraints. Hence, possible mitigation pathways must be identified to lower trucks’ carbon footprint. In this work, we propose an onboard post-combustion capture and storage system on heavy-duty freight vehicles using two state-of-the-art metal-organic frameworks (MOFs) with high CO2 selectivity and high-storage-capacity, respectively. We selected KAUST-7 as the capturing material because of its high stability and selectivity toward CO2 even in humid conditions; while Al-soc-MOF-1 as a CO2 storing material for its high gravimetric and volumetric CO2 uptake between 10 and 50 bar. Our solution aimed to reduce heavy-duty vehicle CO2 emissions by at least 50% and achieve above 95% CO2 purity at the storage point. First, we measured and modeled KAUST-7’s thermodynamic and kinetic properties, then we simulated and optimized the process conditions for the carbon capture system in response to dynamic engine behavior. Additionally, we minimized the capture and storage mass, offering as result innovative methods to mitigate carbon emissions in the heavy-duty freight industry.
Detecting long-term effects of mining-induced ground deformation on plant patterns in semi-arid areas using a cellular automata model
Authors: Mi Jiaxin , Zhang Shaoliang , Hou Huping , Hua Yifei , Yang Yongjun , Ding Zhongyi 
Published: November 2022

Abstract
Contexts
Mining-induced ground deformation has various effects on different plant communities. However, little is known about the effects of ground deformation on plant patterns after spontaneous succession, and there is currently no quantitative approach to the detection of these long-term effects.
Objectives
A plant community succession model (PCSM) based on cellular automate was developed, and the 30-year plant succession within a subsidence area in the Yungang mining area in China under mining and non-mining scenarios, as well as under two sets of initial conditions (plant-covered and bare), were simulated and compared.
Methods
The normalized mean square error (NMSE) was applied to test the accuracy of the PCSM and to reveal the effects of ground deformation at the patch scale, which was 0.06–0.59 for simulated and observed plant patterns. Six landscape indicators (contagion index (CONTAG), patch cohesion index (COHESION), landscape division (DIVISION), Shannon’s diversity index (SHDI), Shannon’s evenness index (SHEI), and aggregation index (AI)) were calculated for the mining and non-mining scenarios and compared to reveal the effects at the landscape scale.
Results
The results show that the DIVISION, SHDI, and SHEI were significantly higher in the mining scenario than in the non-mining scenario under plant-covered conditions; while the DIVISION was greater for the mining scenario than for the non-mining scenario, indicating that the ground deformation resulted in a loose, separated, and mixed plant pattern. The dynamics of the plant coverages and patterns in the two scenarios reflect the negative and positive effects of ground deformation on the tree and shrub communities, respectively. In terms of the shrub and tree communities, the NMSEs fluctuated at a high level under bare conditions, especially at the patch scale of 10 × 10 m, for which it was maintained at >0.5.
Conclusion
Overall, the mining-induced ground deformation chronically influenced the plant succession by limiting tree communities and promoting shrub communities, and it led to a heterogenous plant pattern. The results of this research provide a reference for detecting the long-term effects of mining-induced ground deformation on plant patterns, and they also provide insights into the effects of underground mining on different plant communities.
Expression of programmed cell death 1 on neuroblastoma cells in TH-MYCN transgenic mice
Authors: Takeuchi Yuta , Inoue Seiichiro , Odaka Akio 
Published: November 2022

Abstract
Background
Immunotherapy may improve the poor prognosis of high-risk neuroblastoma. Programmed cell death 1 (PD-1) is expressed in several cancers. The tyrosine hydroxylase MYCN (TH-MYCN) transgenic mouse model is widely used in neuroblastoma research, but detailed information on its immunological background is lacking. Therefore, we studied the immunological tumor microenvironment and tumor cell surface antigen expression in homozygote and hemizygote mice and effects of antibody therapy against PD-1.
Methods
CD4, CD8, CD11b, and CD11c expression in immune cells from retroperitoneal lymph nodes and spleen was analyzed by flowcytometry. Tumor cell surface antigen expression was confirmed, and data from homozygote and hemizygote mice were compared. Effects of anti-PD-1 antibody were evaluated.
Results
CD4-, CD8-, CD11b-, and CD11c-positive cells were not significantly different in homozygote and hemizygote mice, and CD11b- and CD11c-positive cells were identified in the tumor microenvironment in both. Tumor cells expressed PD-1, and anti-PD-1 antibody had anti-tumor effects and significantly reduced the percentage of living tumor cells in cultures after 2 hours.
Conclusion
The immunological background is similar in homozygote and hemizygote TH-MYCN transgenic mice, and both have PD-1–positive tumor cells. Anti-PD-1 antibody suppresses tumor growth. This mouse model may be a useful for studying immunotherapy of neuroblastoma.
Underground Lightning - A Possible Earthquake Occurrence Mechanism and Early Warning Application
Authors: jianfeng Su , hai Chen 
Published: November 2022

Abstract
Through the comparative and analysis of the positive anomaly characteristics of atmospheric electric field before lightning and terrestrial electric field before earthquake, this paper proposes that one of the mechanisms of earthquake generation is underground lightning, that is, huge underground electrical energy accumulates and releases instantaneously, and electrical energy is converted into mechanical energy instantaneously, causing the rupture of the solid structure of the underground lithosphere to form an earthquake. Based on this mechanism, the feasible methods of earthquake early warning are explored.
Approximation of Elasticity Modulus of Groundnut Shell Ash Based Self-Consolidating High-Performance Concrete (SCHPC) Using Artificial Neural Network (ANN)
Authors: Buari T. A , Adeleke J. S. , Olutoge F. A. , Ayinnuola G. M. , Dahunsi B. I.O. 
Published: November 2022

Abstract
The focus of this study is the prediction of Elasticity Modulus (ME) of Self-Consolidating high-performance concrete (SCHPC) incorporated with Groundnut Shell Ash (GSA) with Artificial Neural Networks (ANN). The present research utilized GSA as a SCM in the development of SCHPC with GSA (0, 10, 20, 30 and 40%) to produce concrete (SCHPC0, SCHPC10, SCHPC20, SCHPC30 and SCHPC40) and a designed concrete mix of 41 N/mm2 was employed in accordance with ACI and EFNARC guidelines. The compressive strength, tensile strength, Elasticity Modulus and microstructure densifications of SCHPC were the major parameters measured. The Elasticity Modulus was modelled with curing age, percentage substitution of GSA, tensile strength and compressive strength as input while output layer has only one neuron which represents modulus rupture as the target value, in this case, the Modulus Elasticity of GSA Blended SCHPC. Adequacy of adopted models was determined using coefficient of determination (R2) and Mean Square Error (MSE). phase transformation and microstructural analysis of SCHPC showed microstructure densification with an improved interface obtained from SCHPC10 and SCHPC20.The adopted model (back propagation 4-8-4-1) adequately predicted the EM properties of SCHPC (R2: 0.67–0.96; MSE: 0.28–4.81).
A Critical Study Based on Achievement between Public and Private Secondary Schools in Tehsil Lal Qilla District Dir Lower, Khyber Pakhtunkhwa, Pakistan
Authors: Hussain Altaf 
Published: November 2022

Abstract
The present study was conducted to compare the achievement based performance of the public and private secondary schools on different variables such as leader’s leadership styles, management practices and physical facilities provided in these schools. Two public and two private secondary schools were selected as case study from Tehsil Lal Qilla on the basis of convenience and accessibility. The stakeholder’s views approach was adopted for case study. The secondary school principals, teachers, students of 9th and 10th classes and their parents were identified as stakeholders of these schools. Interview protocol for each stakeholder, observation and document analysis were used as instruments of data collection. In this way interviews were conducted for these cases including interviews from public and private secondary schools. The school management/leadership, practices of heads, implementation of departmental policies, teaching learning environment and discipline in schools, lesson planning, available facilities, co-curricular activities and future developmental plans etc. were explored in different interview protocols from each stakeholder. Data was analyzed by using qualitative analysis methods. It was found that, the public schools have better facilities, spacious buildings, highly qualified staff and people oriented management styles as compared to private schools. The heads and teachers of private schools desired to shift in public schools. It is recommended that Government should bound the private sector to provide infrastructure and facilities to the students similar to the public schools.
Comparison of two statistical methods to identify groups in a student satisfaction survey
Authors: Álvarez-Vaz Ramón , Vernazza Elena 
Published: November 2022

Abstract
This work studies the main characteristics of the construction of Student Satisfaction in the undergraduate courses of the Facultad de Ciencias Económicas y de Administra ción from Universidad de la República, Uruguay, by using and comparing two multivariate data analysis techniques: Cluster Analysis and Latent Classes Analysis. Data used for the implementation presented in this work originate from a survey applied on a sample of undergraduate students in 2009. This questionnaire is structured in sets of questions: the first set contains variables which allow characterize students sociodemographically. On the other hand, variables from the ECSI (European Customer Satisfaction Index) model which shall be used to characterize Student Satisfaction are presented. The 6 observed/manifest variables considered as input for the construction and characterization of Student Satisfaction are: student - expectations (E) when they begin studying in the institution, the image (I) they have of the institution, the quality of education received (CSA) and of services provided (CSF), the personal needs and desires with regards to College (ND), and the perceived value (VP). On the one hand, results presented arise from considering that there is an actual hidden/latent variable referred to Student Satisfaction and that this variable is defined from the interaction of the 6 manifest variables, by 4 latent classes. On the other hand, with reference to clusters, it is proposed to group students into 3 groups based on the analysis of results arising from clustering using Ward’s method. Additionally, the comparison of results obtained using both techniques is presented.