bluuebunny/crossref_metadata_2025_split huggingface dataset:
Adult education and entrepreneurship: getting young adults involved
Authors: Biney Isaac Kofi 
Published: March 2023

AbstractThis paper reflects on adult education and the fostering of an entrepreneurial mindset. It solicits roles adult education, especially the non-formal education (NFE), could play in fostering entrepreneurial mindset of young adults. It examines short-to-medium, and long-term plans of young adults in nurturing growth and enterprising mindsets through involvement in NFE endeavours. It probes into entrepreneurial opportunities and challenges in the communities that young adults could recognise and create enterprises for themselves. This is a narrative case study which purposively selected, as the unit of analysis, an adult learner who was operating a micro-enterprise and pursuing a degree programme at Accra Learning Centre. An in-depth telephone interview was conducted to garner stories and experiences young adult have had innovating with an entrepreneurial mindset. Thematic, analytical, narrative and interpretivist approaches were adapted in presenting the results. The participant had a good experience in his start up, he learned lessons, and worked hard to grow his micro-enterprises. The savings culture he built allowed him to cope with difficulties posed by Covid-19 pandemic to his micro-enterprises. Governments and stakeholders in entrepreneurship should via policy, advisory and financial support motivate young adults to invest in entrepreneurship and create sustainable jobs for themselves.
A crowdsourcing database for the copy-number variation of the Spanish population
Authors: López-López Daniel , Roldán Gema , Fernández-Rueda Jose L. , Bostelmann Gerrit , Carmona Rosario , Aquino Virginia , Perez-Florido Javier , Ortuño Francisco , Pita Guillermo , Núñez-Torres Rocío , González-Neira Anna ,   CSVS Crowdsourcing Group, Alonso Angel , Salgado-Garrido Josefa , Pasalodos-Sanchez Sara , Ayuso Carmen , Minguez Pablo , Avila-Fernandez Almudena , Corton Marta , Artuch Rafael , Borrego Salud , Antiñolo Guillermo , Carracedo Angel , Amigo Jorge , Castaño Luis Antonio , Tejada Isabel , Delmiro Aitor , Espinos Carmina , Grinberg Daniel , Guillén Encarnación , Lapunzina Pablo , Lopez-Escámez Jose Antonio , Gallego-Martinez Alvaro , Martí Ramón , Rovira Eulalia , Millán José Mª , Moreno Miguel Angel , Morin Matías , Moreno-Galdó Antonio , Fernández-Cancio Mónica , Morte Beatriz , Mulero Victoriano , García Diana , Nunes Virginia , Palau Francesc , Perez Belén , Jurado Luis Pérez , Perona Rosario , Pujol Aurora , Ramos Feliciano , Lopez Esther , Ribes Antonia , Rosell Jordi , Surrallés Jordi , Peña-Chilet María , Dopazo Joaquin 
Published: March 2023

Abstract
Background
Despite being a very common type of genetic variation, the distribution of copy-number variations (CNVs) in the population is still poorly understood. The knowledge of the genetic variability, especially at the level of the local population, is a critical factor for distinguishing pathogenic from non-pathogenic variation in the discovery of new disease variants.

Results
Here, we present the SPAnish Copy Number Alterations Collaborative Server (SPACNACS), which currently contains copy number variation profiles obtained from more than 400 genomes and exomes of unrelated Spanish individuals. By means of a collaborative crowdsourcing effort whole genome and whole exome sequencing data, produced by local genomic projects and for other purposes, is continuously collected. Once checked both, the Spanish ancestry and the lack of kinship with other individuals in the SPACNACS, the CNVs are inferred for these sequences and they are used to populate the database. A web interface allows querying the database with different filters that include ICD10 upper categories. This allows discarding samples from the disease under study and obtaining pseudo-control CNV profiles from the local population. We also show here additional studies on the local impact of CNVs in some phenotypes and on pharmacogenomic variants. SPACNACS can be accessed at: http://csvs.clinbioinfosspa.es/spacnacs/.

Conclusion
SPACNACS facilitates disease gene discovery by providing detailed information of the local variability of the population and exemplifies how to reuse genomic data produced for other purposes to build a local reference database.
Non-pharmaceutical interventions for COVID-19 reduced the incidence of infectious diseases: a controlled interrupted time-series study
Authors: Zhang Wenyi , Wu Yao , Wen Bo , Zhang Yongming , Wang Yong , Yin Wenwu , Sun Shanhua , Wei Xianyu , Sun Hailong , Zhang Zhijie , Li Shanshan , Guo Yuming 
Published: March 2023

AbstractBackgroundNon-pharmaceutical interventions (NPIs) have been implemented worldwide to suppress the spread of coronavirus disease 2019 (COVID-19). However, few studies have evaluated the effect of NPIs on other infectious diseases and none has assessed the avoided disease burden associated with NPIs. We aimed to assess the effect of NPIs on the incidence of infectious diseases during the COVID-19 pandemic in 2020 and evaluate the health economic benefits related to the reduction in the incidence of infectious diseases.MethodsData on 10 notifiable infectious diseases across China during 2010–2020 were extracted from the China Information System for Disease Control and Prevention. A two-stage controlled interrupted time-series design with a quasi-Poisson regression model was used to examine the impact of NPIs on the incidence of infectious diseases. The analysis was first performed at the provincial-level administrative divisions (PLADs) level in China, then the PLAD-specific estimates were pooled using a random-effect meta-analysis.ResultsA total of 61,393,737 cases of 10 infectious diseases were identified. The implementation of NPIs was associated with 5.13 million (95% confidence interval [CI] 3.45‒7.42) avoided cases and USD 1.77 billion (95%CI 1.18‒2.57) avoided hospital expenditures in 2020. There were 4.52 million (95%CI 3.00‒6.63) avoided cases for children and adolescents, corresponding to 88.2% of total avoided cases. The top leading cause of avoided burden attributable to NPIs was influenza [avoided percentage (AP): 89.3%; 95%CI 84.5‒92.6]. Socioeconomic status and population density were effect modifiers.ConclusionsNPIs for COVID-19 could effectively control the prevalence of infectious diseases, with patterns of risk varying by socioeconomic status. These findings have important implications for informing targeted strategies to prevent infectious diseases.
Neurofibromatosis type 1-dependent alterations in mouse microglia function are not cell-intrinsic
Authors: Logiacco Francesca , Grzegorzek Laura Cathleen , Cordell Elizabeth C. , Popp Oliver , Mertins Philipp , Gutmann David H. , Kettenmann Helmut , Semtner Marcus 
Published: March 2023

AbstractWe previously discovered a sex-by-genotype defect in microglia function using a heterozygous germline knockout mouse model of Neurofibromatosis type 1 (Nf1 ± mice), in which only microglia from male Nf1 ± mice exhibited defects in purinergic signaling. Herein, we leveraged an unbiased proteomic approach to demonstrate that male, but not female, heterozygous Nf1 ± microglia exhibit differences in protein expression, which largely reflect pathways involved in cytoskeletal organization. In keeping with these predicted defects in cytoskeletal function, only male Nf1 ± microglia had reduced process arborization and surveillance capacity. To determine whether these microglial defects were cell autonomous or reflected adaptive responses to Nf1 heterozygosity in other cells in the brain, we generated conditional microglia Nf1-mutant knockout mice by intercrossing Nf1flox/flox with Cx3cr1-CreER mice (Nf1flox/wt; Cx3cr1-CreER mice, Nf1MG ± mice). Surprisingly, neither male nor female Nf1MG ± mouse microglia had impaired process arborization or surveillance capacity. In contrast, when Nf1 heterozygosity was generated in neurons, astrocytes and oligodendrocytes by intercrossing Nf1flox/flox with hGFAP-Cre mice (Nf1flox/wt; hGFAP-Cre mice, Nf1GFAP ± mice), the microglia defects found in Nf1 ± mice were recapitulated. Collectively, these data reveal that Nf1 ± sexually dimorphic microglia abnormalities are likely not cell-intrinsic properties, but rather reflect a response to Nf1 heterozygosity in other brain cells.
Effect of glycerol triglycidyl ether on the dimensional stability and flexibility of photographic gelatine films
Authors: Liu Jiaojiao , Yang Junchang , Li Yuhu , Hu Daodao , Chen Ran 
Published: March 2023

Abstract
The gelatine emulsions used in historical photographs can shrink and become brittle under alternating dry–wet environmental conditions, which would result in curling and fracture of the gelatin paper photographs, thereby degrading their quality and threatening the long-term inheritance of such cultural heritage. To improve the stability and flexibility of gelatine films under dry–wet cycling, glycerol triglycidyl ether (GPE) was employed as a synergistic crosslinking and plasticising agent. The plasticising effect of GPE on the dimensional stability and flexibility of gelatine films in alternating dry–wet environments was firstly studied. Gelatine films with different contents of GPE were prepared and their dimensional changes during dry–wet cycling were investigated. The results indicate that GPE greatly enhances the dimensional stability of the films during cycling. By analysing the swelling behaviour, molecular structure, mechanical strength, fracture cross-sections, and other properties of the gelatine–GPE films, it was confirmed that the addition of GPE greatly reduces the moisture absorption and swelling of gelatine and improves its moisture stability. Furthermore, benefiting from GPE as a crosslinking agent, the mechanical strength and flexibility of the gelatine films were both enhanced. In this study, the modification of gelatin film by GPE provides experimental evidence for the subsequent research on the application of restoration and conservation for the gelatin paper photographs.
Demonstration of p-type stack-channel ternary logic device using scalable DNTT patterning process
Authors: Lee Yongsu , Kwon Heejin , Kim Seung-Mo , Lee Ho-In , Kim Kiyung , Lee Hae-Won , Kim So-Young , Hwang Hyeon Jun , Lee Byoung Hun 
Published: March 2023

AbstractA p-type ternary logic device with a stack-channel structure is demonstrated using an organic p-type semiconductor, dinaphtho[2,3-b:2',3'-f]thieno[3,2-b]thiophene (DNTT). A photolithography-based patterning process is developed to fabricate scaled electronic devices with complex organic semiconductor channel structures. Two layers of thin DNTT with a separation layer are fabricated via the low-temperature deposition process, and for the first time, p-type ternary logic switching characteristics exhibiting zero differential conductance in the intermediate current state are demonstrated. The stability of the DNTT stack-channel ternary logic switch device is confirmed by implementing a resistive-load ternary logic inverter circuit.
Acceptance and hesitancy to receive COVID-19 vaccine among university students in Egypt: a nationwide survey
Authors: Tharwat Samar , Saad Ahmed Mohammed , Nassar Mohammed Kamal , Nassar Dalia Kamal 
Published: March 2023

Abstract
Background
The public's willingness to be vaccinated will determine the success of the COVID-19 vaccination program. The aim of this study was to identify acceptance and hesitancy to receive COVID-19 vaccine among university students in Egypt, assess their level of knowledge about COVID-19 vaccine and identify factors that influence their intention towards COVID-19 vaccination.

Methods
A standardized and self-administered questionnaire was distributed among university students allover Egypt. The questionnaire included sociodemographic data, intention to receive COVID-19 vaccine, knowledge and beliefs about it and status of COVID-19 vaccination. Logistic regression analysis was used to determine factors associated with COVID-19 vaccine acceptancy.

Results
A total of 1071 of university students were involved, with a mean age of 20.51 years (SD = 1.66) and 68.2% were females. COVID-19 vaccination acceptability rate was 69.0% while hesitancy was 20.8% and resistancy was 10.2%. Median knowledge score of 4 out of 8 (IQR = 8). The main motivation for vaccine acceptance was fear of being infected (53.6%) and desire to get back to normal life (51.0%) while the main barriers against getting vaccinated were being afraid of serious side effects. Univariate regression analysis revealed an increasing likelihood of vaccine acceptancy associated with an active lifestyle (OR 1.35, 95% CI 1.04–1.75, p = 0.025), a high knowledge score (OR 1.53, 95% CI 1.42–1.66, p < 0.001), and positive vaccine beliefs.

Conclusion
There is a high rate of acceptability of COVID-19 vaccination among university students. Vaccine acceptability is associated with an active lifestyle, a high knowledge score and positive vaccine beliefs. Educational campaigns and efforts aiming to raise awareness about safety and efficacy of COVID-19 vaccines need to be directed to this important population.
Patient and public involvement in research: a review of practical resources for young investigators
Authors: Arumugam Ashokan , Phillips Lawrence Rick , Moore Ann , Kumaran Senthil D. , Sampath Kesava Kovanur , Migliorini Filippo , Maffulli Nicola , Ranganadhababu Bathri Narayanan , Hegazy Fatma , Botto-van Bemden Angie 
Published: March 2023

AbstractPatient and public involvement (PPI) in every aspect of research will add valuable insights from patients’ experiences, help to explore barriers and facilitators to their compliance/adherence to assessment and treatment methods, bring meaningful outcomes that could meet their expectations, needs and preferences, reduce health care costs, and improve dissemination of research findings. It is essential to ensure competence of the research team by capacity building with available resources on PPI. This review summarizes practical resources for PPI in various stages of research projects—conception, co-creation, design (including qualitative or mixed methods), execution, implementation, feedback, authorship, acknowledgement and remuneration of patient research partners, and dissemination and communication of research findings with PPI. We have briefly summarized the recommendations and checklists, amongst others, for PPI in rheumatic and musculoskeletal research (e.g. the European Alliance of Associations for Rheumatology (EULAR) recommendations, the Core Outcome Measures in Effectiveness Trials (COMET) checklist and the Guidance for Reporting Involvement of Patients and the Public (GRIPP) checklist). Various tools that could be used to facilitate participation, communication and co-creation of research projects with PPI are highlighted in the review. We shed light on the opportunities and challenges for young investigators involving PPI in their research projects, and have summarized various resources that could be used to enhance PPI in various phases/aspects of research. A summary of web links to various tools and resources for PPI in various stages of research is provided in Additional file 1.
Origanum majorana L. extract alleviates dexamethasone-induced hepatotoxicity, oxidative stress and pathological alterations in vivo
Authors: Abou- Seif Howida Sayed , Hozayen Walaa Gamal 
Published: March 2023

AbstractBackgroundOriganum majorana(O. majorana) is one of the most widely used herbs in Egypt due to its antioxidant, anti-inflammatory, anti-genotoxic, antimutagenic, anticoagulant and beneficial properties. Our study's main goal is to determine how wellO. majoranaleaf extract can reduce hepatotoxicity and oxidative stress produced by dexamethasone (DXM). Thirty female rats were divided into three groups of ten. Animals in group1 received distilled water daily for eight weeks and served as control. Those in group 2 exposed subcutaneously to 0.1 mg/kg body weight of DXM three times per week for eight weeks and served as the toxic group, while those in group 3 were treated daily and orally with 100 mg/kg ofO. majoranaaqueous extract + 0.1 mg/kg of DXM three times per week for eight weeks and served as treated group.ResultsDue to DXM treatment, the activities of liver function markers were significantly elevated (P < 0.0001), whereasO. majoranapretreated animals improved or reduced the elevated liver function enzyme activities. Dexamethasone administration considerably enhancing oxidative stress which rose (P < 0.0001) MDA concentration and attenuated the antioxidant defense system by decreasing the activities of GST, GSP, GSR, and CAT significantly in liver homogenate when compared to control animals. The results further demonstrated that pretreatment withO. majoranaboosted the antioxidant defenses against the damaging effects of DXM.ConclusionIt can be said that dexamethasone exposure induced- hepatotoxicity and oxidative stress in rats that repaired byO. majoranaaqueous extract which had the ability to reduce the impact of hepatic damage. To evaluate the health benefits and safety ofO. majoranain individuals, more clinical research is needed.Graphical abstract
Android malware category detection using a novel feature vector-based machine learning model
Authors: Manzil Hashida Haidros Rahima , Manohar Naik S. 
Published: March 2023

AbstractMalware attacks on the Android platform are rapidly increasing due to the high consumer adoption of Android smartphones. Advanced technologies have motivated cyber-criminals to actively create and disseminate a wide range of malware on Android smartphones. The researchers have conducted numerous studies on the detection of Android malware, but the majority of the works are based on the detection of generic Android malware. The detection based on malware categories will provide more insights about the malicious patterns of the malware. Therefore, this paper presents a detection solution for different Android malware categories, including adware, banking, SMS malware, and riskware. In this paper, a novel Huffman encoding-based feature vector generation technique is proposed. The experiments have proved that this novel approach significantly improves the efficiency of the detection model. This method makes use of system call frequencies as features to extract malware’s dynamic behavior patterns. The proposed model was evaluated using machine learning and deep learning methods. The results show that the proposed model with the Random Forest classifier outperforms some existing methodologies with a detection accuracy of 98.70%.
Artificial intelligence-based traffic flow prediction: a comprehensive review
Authors: Sayed Sayed A. , Abdel-Hamid Yasser , Hefny Hesham Ahmed 
Published: March 2023

AbstractThe expansion of the Internet of Things has resulted in new creative solutions, such as smart cities, that have made our lives more productive, convenient, and intelligent. The core of smart cities is the Intelligent Transportation System (ITS) which has been integrated into several smart city applications that improve transportation and mobility. ITS aims to resolve many traffic issues, such as traffic congestion issues. Recently, new traffic flow prediction models and frameworks have been rapidly developed in tandem with the introduction of artificial intelligence approaches to improve the accuracy of traffic flow prediction. Traffic forecasting is a crucial duty in the transportation industry. It can significantly affect the design of road constructions and projects in addition to its importance for route planning and traffic rules. Furthermore, traffic congestion is a critical issue in urban areas and overcrowded cities. Therefore, it must be accurately evaluated and forecasted. Hence, a reliable and efficient method for predicting traffic is essential. The main objectives of this study are: First, present a comprehensive review of the most popular machine learning and deep learning techniques applied in traffic prediction. Second, identifying inherent obstacles to applying machine learning and deep learning in the domain of traffic prediction.
Angiomatous antrochoanal polyp: a rare entity of choanal polyps
Authors: Ali Alhussien Awad , Sayed Ramadan Hashem , Dahy Khaled Gamal 
Published: March 2023

Abstract
Introduction
Angiomatous polyp is a benign, non-neoplastic variant of antrochoanal polyp that is extremely uncommon.

Objectives
Reviewing the prevalence, clinical characteristics, preoperative assessment, histology, and treatment of angiomatous antrochoanal polyps.

Methods
All patients presented with antrochoanal polyps accompanied by epistaxis during the period from 2012 to 2022 were included in the study. Based on a detailed history, clinical examination, findings of nasal endoscopy, radiological examination (CT scan nose and paranasal sinuses), and intraoperative data. A histopathological examination for the polyp biopsy specimens was done for all patients presented with epistaxis.

Results
Over 10 years, among 94 patients with lesions that met the diagnostic criteria for antrochoanal polyp, 16 patients (17%) presented with recurrent ipsilateral epistaxis. All lesions were unilateral, 9 on the right side and 7 on the left side, with no affection of the contralateral sinonasal cavity. Clinical, radiological, and histopathological examinations showed a picture suggestive of an angiomatous antrochoanal polyp. Endoscopic sinus surgery under general anesthesia was performed and no recurrence was detected in the patients with angiomatous antrochoanal polyps.

Conclusion
It seems that epistaxis exclusively occurs in the angiomatous variety of the antrochoanal polyp. This polyp is not only a variation of the common antrochoanal polyp but rather a unique variety. The identification of the distinctive physical characteristics of an angiomatous antrochoanal polyp will aid in avoiding the incorrect diagnosis of a vascular tumor and the need for unnecessary surgery.
Newborn Time - improved newborn care based on video and artificial intelligence - study protocol
Authors: Engan Kjersti , Meinich-Bache Øyvind , Brunner Sara , Myklebust Helge , Rong Chunming , García-Torres Jorge , Ersdal Hege L. , Johannessen Anders , Pike Hanne Markhus , Rettedal Siren 
Published: March 2023

Abstract
Background
Approximately 3-8% of all newborns do not breathe spontaneously at birth, and require time critical resuscitation. Resuscitation guidelines are mostly based on best practice, and more research on newborn resucitation is highly sought for.

Methods
The NewbornTime project will develop artificial intelligence (AI) based solutions for activity recognition during newborn resuscitations based on both visible light spectrum videos and infrared spectrum (thermal) videos. In addition, time-of-birth detection will be developed using thermal videos from the delivery rooms. Deep Neural Network models will be developed, focusing on methods for limited supervision and solutions adapting to on-site environments. A timeline description of the video analysis output enables objective analysis of resuscitation events. The project further aims to use machine learning to find patterns in large amount of such timeline data to better understand how newborn resuscitation treatment is given and how it can be improved. The automatic video analysis and timeline generation will be developed for on-site usage, allowing for data-driven simulation and clinical debrief for health-care providers, and paving the way for automated real-time feedback. This brings added value to the medical staff, mothers and newborns, and society at large.

Discussion
The project is a interdisciplinary collaboration, combining AI, image processing, blockchain and cloud technology, with medical expertise, which will lead to increased competences and capacities in these various fields.

Trial registration
ISRCTNregistry, number ISRCTN12236970