bluuebunny/crossref_metadata_2025_split huggingface dataset:
Assessment of interrelationships between cognitive performance, symptomatic manifestation and social functioning in the acute and clinical stability phase of schizophrenia: Insights from a network analysis
Authors: Misiak Błażej , Piotrowski Patryk , Samochowiec Jerzy 
Published: July 2023

Abstract
Background: It has been shown that various aspects of clinical manifestation of schizophrenia are strongly related to social functioning. However, it remains unknown as to whether similar factors predict social functioning at various stages of psychosis. Therefore, the present study aimed to compare the effects of interconnections between various domains of psychopathology and neurocognition on social functioning in people during acute phase of psychosis and those during remission of positive and disorganization symptoms using a network analysis.
Methods: Two independent samples of individuals with schizophrenia spectrum disorders were enrolled (n = 208). Clinical assessment covered the levels of functioning, positive, negative and depressive symptoms. Cognition was recorded using the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS).
Results: Both networks did not differ significantly on the majority of network comparison tests, except of significantly higher strength centrality of negative symptoms in participants during clinical stability. In both networks, the majority of centrality metrics had the highest values for the RBANS attention score that is a sum of scores from two tasks (digit span and coding). In both networks, social functioning was directly connected to positive, negative and depressive symptoms as well as the RBANS scores of attention and language.
Conclusions: Findings from the present study indicate the central role of cognitive deficits, especially those related to attention, processing speed, and working memory in shaping functional impairments regardless of schizophrenia phase. Therapeutic interventions that aim to improve functional capacity need to target these domains of neurocognitive performance.
Bridging Data Gaps for 1D-2D Flood Modeling in Northeast Central Morocco: Insights from Statistics of Extremes and Estimation Methods
Authors: Okacha Abdelmonaim , Salhi Adil , Bouchouou Mounir , Fattasse Hamid 
Published: July 2023

Abstract
Floodplains are both a blessing and a curse. They offer fertile soil and water but pose a risk of flooding and habitat loss, particularly in semi-arid regions such as Northeast Central Morocco. Flood modeling is critical for mitigating flood impacts and improving disaster management strategies. However, data scarcity poses significant challenges in accurately simulating floods. This article discusses three knowledge gaps in flood risk management: (i) evaluating flood flow estimation methods, (ii) improving flood modeling accuracy, and (iii) updating plans to mitigate flood risks. This study addresses this challenge by using a two-step approach to fill hydrological data gaps and enhance flood modeling. The first step uses frequency analysis to predict extreme rainfall events. The second step compares the Gradex technique and empirical analysis of flood flows. These techniques consider rainfall-flow relationships, flood flow return time, and concentration time. By integrating 1D and 2D flood models and analyzing rainfall and topographic data, the study aimed to improve flood predictions and address challenges arising from limited data availability. It was revealed that the estimated flow for the 100-year return in the Nekor plain is 1,338.75 m3/s. This would result in extensive flooding, affecting an area of 2,017 Ha. The flooding would likely inundate farmlands, villages, and infrastructure, causing widespread damage and disruption. These findings have practical implications for decision-makers, planners, and researchers involved in hydraulic modeling and urban planning.
Influence of window opening on cyclic behavior of precast infill wall with sliding joints
Authors: Huang Weiyuan , Chen Qiming , Zhang Chao , Wongso Santosa , Zhang Shaohua , Deng Xuesong , Liang Zhicheng 
Published: July 2023

Abstract
In engineering practice, creating window openings in partition infill walls is a common requirement for infilled frames. However, the intervention of infill walls may interrupt the desired cyclic behavior of the infilled frame, and worst yet, the inevitable window opening might further aggravate such negative interaction. To protect the openings from the detrimental multiple diagonal struts mechanism of the traditional infill wall with a window opening under lateral loadings, this research presents a novel infill wall system with a window opening for semi-rigid steel frames. Three half scaled specimens are subjected to quasi-static cycle tests: a bare steel frame, a steel frame infilled with a traditional infill wall with a window opening, and a precast infill wall with a window opening and sliding joints in a steel frame. Experimental results show that the proposed infill system with a window opening can release adverse crack development or opening deformation of the window opening by mitigating the detrimental multiple diagonal struts effect in conventional infill walls with window openings under lateral loadings. In this way, the developed infilled frame exhibits similar cyclic behavior to the designed bare steel frame with higher energy dissipation capacity. Furthermore, parametric analysis results reveal that the friction factor of the sliding joints has a significant effect on enhancing the bearing capacity of the proposed infill system, while the change of opening sizes and locations of the window opening has negligible impact on the cyclic behavior of the developed infill system.
An unpremeditated complication of COVID-19 and mucormycosis: a case report, brief review, and warning for tunnel vision
Authors: Mehdinezhad Hamed , Ahangar Reza Mohseni , Azizi Mohammad Golparvar , Ghasemian Mohammad , Pirzaman Ali Tavakoli 
Published: July 2023

Abstract
Over the course of the Coronavirus disease 2019 (COVID-19) pandemic, numerous complications have been documented. In this report, we have detailed an unexpected complication of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection that occurred in a 73-year-old female patient who was simultaneously afflicted with mucormycosis and another unanticipated problem. Due to the lack of recovery of the patient after receiving mucormycosis treatment and continued fever, cough and hemoptysis, bronchoscopy was performed for her. During bronchoscopy, we encountered a foreign body that was the cause of the patient's fever, cough, and hemoptysis. Rigid bronchoscopy was performed and a foreign body (2.7 x 1.2 cm) was removed from the left main bronchus. Although research has showed fewer cases of pediatric Foreign Body Aspiration (FBA) during lockdown periods, there is not enough evidence about FBA risk in elderly patients with comorbidities. Finally, in the treatment of cases of COVID-19 infections co-infected with opportunistic fungal and maybe even bacterial infections, we should not look at the patient through a tunnel vision and consider all possible scenarios for the patient.
OTLD：A four-stages visual system for perception of autonomous vehicles
Authors: Xue Qingfeng , Wang Xinyu , Tu Gepeng , Wu Jing 
Published: July 2023

Abstract
With the development of autonomous vehicle, it has become a challenging problem that reducing cost under the condition of ensuring perception performance. The sensors such as lidars have greatly increased the production cost of autonomous vehicles while camera is much cheaper. So in this manuscript we develop OTLD (O-object detection, T-multiple object tracking, L-lane detection, D-distance estimation), a complete four-stages visual system to solve environmental perception of autonomous vehicles. And it consists of four functions including object detection, tracking, lane detection and distance estimation. You Only Look Once version-4 (YOLOv4), Simple Online and Real- time Tracking (SORT), Ultra-Fast Lane Detection (UFLD) and iteration method of Perspective-n-Point (PnP) are respectively selected as the solutions of four tasks and their superiorities on the aspects of accuracy and real-time performance are verified in our application scenario. Through fitting lane lines and sorting traffic targets by lane and distance, the 4 stages of OTLD works collaboratively and we encapsulate them into a graphical user interface (GUI) to establish a new system of environmental perception. The final integration OTLD runs at 25FPS in the form of C++ program on GTX1660 GPU and Inter Corei5-9400F CPU, which meets the real-time requirement. And it could realize all the functions that have been mentioned about environmental perception even by using a single monocular camera. For automotive industry, OTLD provides algorithmic reference for other vision projects of autonomous vehicle.
Bacterial Colonization in a Neonatal Intensive Care Unit
Authors: Gonçalves Carolina , Garcia Catarina , Aliyeva Elzara , Ferreira Marta , Barroso Maria 
Published: July 2023

Abstract
Objective: Analyze the multi-drug resistant bacteria (MDRB) colonization rate and its associated risk factors, as well as the subsequent development of infection.
Study Design: Retrospective review of all newborns admitted to a level III NICU, between November 2018 and November 2019 (n=294). Rectal and nasal swabs were performed upon admission and weekly until discharge for detection of MDRB.
Results: The MDRB colonization rate was 28.2%. Colonization with MDRB was associated with mothers’ admission at least 1 week prior to delivery, infants’ lower gestational age and birth weight, antibiotic therapy upon admission, mechanical ventilation, central line and longer hospitalization. Colonization with a MDRB was an important risk factor for subsequent infection (31.3% of colonized-infants developed late-onset sepsis vs. 5.2% of non-colonized ones).
Conclusions: Early detection of colonized patients through screening with subsequent implementation of strict contact
Mating type revulsion and dynamic genetic diversity of Phytophthora infestans during 2010–2021 in yunnan, China
Authors: Tang Wei , Li JianMei , Liang JingSi , Tan Chen , Wang MengLin , Hao DaHai , Li Zhou , Zou WanJun , Liu Jing , Wang Hongyang , Li Canhui 
Published: July 2023

Abstract
Potato late blight caused by Phytophthora infestans is the most severe problem in the Yunnan Province. To understand the population dynamics of P. infestans in Yunnan during 2010–2020, 357 isolates were collected from Dali and Kunming, purified, and analyzed for the mating type, mitochondrial DNA (mtDNA) haplotype, metalaxyl resistance, pathotype, and simple sequence repeat (SSR) DNA fingerprints. The A1 mating type was dominant before 2012, but since 2012, the A2, A1A2 and self-fertile types became dominant and fewer A1 isolates were obtained over the years. Among the 357 isolates, only two were IIa mtDNA haplotypes and the rest were Ia mtDNA haplotypes. Pathogenicity assays using R1-R11 gene carried hosts revealed 67 pathotypes among all test isolates. SSR analysis identified 242 multi locus genotypes(MLGs), combined principal component analysis indicated that populations in 2010, 2011 and 2012 predominantly adopted asexual life cycles, but from 2013 to 2021, limited sexual reproduction likely occurred. UPGMA analysis indicated that five test isolates collected from Dali and Kunming from 2013 to 2015 but not in other years represented the EU_13_A2 lineage. Our results support the hypothesis that clonal reproduction, combined with host selection and limited sexual reproduction, underlies the dynamic genetic diversity of P. infestans in Yunnan.
Analysis of novel biomarkers and immune cell alterations in sepsis based on single-cell sequencing and machine learning algorithms
Authors: Tao Linfeng , Zhu Yue , Liu Jun , Li Chao , Pan Yiyuan 
Published: July 2023

Abstract
We aim to investigate the changes of the immune milieu during sepsis and screen out novel biomarkers with favor diagnostic value using single-cell sequencing and machine learning algorithms. Two gene-chip datasets (GSE28750 and GSE95233) and two single-cell sequencing datasets (GSE167363 and GSE195965) were obtained from the GEO database. We used “limma” package in R software to screen out differentially expressed genes (DEGs) in GSE28750 dataset. Then, 10 key genes mostly associated with sepsis were screened out using the random forest algorithm, including SNX3, NAIP, MMP8, EVL, TRBC1, BCL11B, FAIM3, ABLIM1, SIRPG, and CD7. Results of ROC curves showed that these genes also have favor diagnostic value. Moreover, the diagnostic values of biomarkers were also validated in GSE95233 dataset. The immunological microenvironment of sepsis was analyzed using CIBERSORT algorithm, and the relationship between biomarkers and immune cells was identified by “Spearman” method. We also carried out single-cell sequencing analysis on GSE167363 dataset and found that septic T cells differentiated later than normal T cells, and expression of TRBC1 was gradually downregulated over T cell developmental trajectories. Meanwhile, through combing single-cell sequencing analysis and WGCNA analysis, we found that monocytes were upregulated and functionally activated, whereas T cells exhibited significant apoptosis and loss of function both in patients with sepsis and mouse sepsis models.
A constitutive model based on internal variable method for the microstructure simulation of four-layer structure formed by the superplastic forming/diffusion bonding process
Authors: Wu Dipeng , Wu Yong , Fan Ronglei , Qiu Jiayang , Chen Minghe 
Published: July 2023

Abstract
This study set out to realize the prediction of microstructure evolution and mechanical properties of the titanium alloy four-layer structure formed by the superplastic forming/diffusion bonding (SPF/DB) process. The flow behavior and the microstructure evolution of TC31 alloy were studied by the high-temperature experiments. A physically-based constitutive model was established and applied in the superplastic forming process of the four-layer structure. The TC31 titanium alloy four-layer structure was fabricated to verify the accuracy of the constitutive model. The results showed that the main reason for the increase in material stress and the decrease in elongation was the growth of grains. The TC31 four-layer structure was soundly fabricated by SPF/DB process, and the maximum damage value of the structure was located at the sidewall area with a value of 0.16. The compression strength of the structure was 19.0MPa, and the compression failure mode of the four-layer structure was the cracking of the bonding area. The experimental results were similar to the simulation results, which demonstrated that the finite element simulation with the internal variable model could accurately predict the shape, the thickness distribution and the damage distribution of the four-layer structure during the SPF process.
Robust Segmentation Model Based on Triplet Criterion for Images with Intensity Inhomogeneity
Authors: Ullah Inam , Khan Muhammad Salim , Ali Haider , Shah Zahir 
Published: July 2023

Abstract
Intensity inhomogeneity poses a significant obstacle in the process of image segmentation, particularly when employing region-based level set methodologies. This challenge becomes particularly pronounced when dealing with images that exhibit varying intensity values between the background and foreground objects. To mitigate this issue, a novel approach has been introduced, which leverages both global and local statistical information to enhance the accuracy of segmentation outcomes. The proposed model comprises three key components: a regularisation term, a local term, and a global term. The regularisation term facilitates the attainment of smooth and coherent segmented regions, while the local term detects areas of intensity variation by utilizing location-specific statistical data. The global term takes into account the overall intensity characteristics of the image, enabling the differentiation of items with dissimilar intensities. The effectiveness of the proposed model has been meticulously evaluated through comprehensive experimentation, which has demonstrated superior accuracy and efficacy when compared to existing models. These results serve to affirm the efficacy of the methodology and underscore its capacity to effectively address the challenges arising from non-uniform intensity distribution in image segmentation tasks.
DeepRNAScanner: Deep Learning-Based Discovery of Regulatory miRNA Sequences in Lung Cancer
Authors: Akram Adeel , Iqbal Muhammad Shahid , Rehman Saeed Ur 
Published: July 2023

Abstract
Lung cancer remains a formidable and life-threatening disease worldwide. Recent advancements in machine learning and artificial intelligence have led to the discovery of several significant miRNAs in lung cancer research, offering potential solutions to critical issues. In this study, we introduce miRES, a novel method that employs extreme learning machines, support vector machines, and deep learning techniques to identify lung cancer-associated miRNAs. Our approach tackles the inherent two-class classification problem using machine learning and deep learning algorithms. By leveraging the miRES method, we uncover detailed information about miRNA sequences and discern their regulatory functions, including up- and down-regulation. Through comparative analysis with other machine learning and deep learning methods, we demonstrate that miRES surpasses performance metrics such as sensitivity, specificity, and accuracy. Specifically, miRES achieve an impressive 83.34% sensitivity (Sn), 78.55% specificity (Sp), 0.73 F1 score, and 0.4882 Matthews correlation coefficient (MCC). Furthermore, our proposed method outperforms various deep learning methods, including CNN, ResNet101, ResNet152, VGG16, VGG19, AlexNet, and GoogleNet, in classifying miRNA sequences, attaining a K-10 value of 96.25%. Overall, miRES offers a powerful and effective approach for identifying and characterizing lung cancer miRNA sequences, leveraging the strengths of machine learning and deep learning techniques. This research contributes to the growing body of knowledge aimed at combating lung cancer and improving patient outcomes.
Helping Clinicians Conceptualise Behavioural Insomnia in Children: Development of the Kids Insomnia Problems Scale (KIPS)
Authors: Donovan Caroline L. , Uhlmann Laura , Shiels Amy 
Published: July 2023

Abstract
This paper outlines the development and psychometric evaluation of the Kids Insomnia Problems Scale (KIPS), an instrument intended to assess factors underpinning child behavioural insomnia. Study 1 comprised an exploratory factor analysis (EFA; n = 328 parents of children aged 3–12 years), with items found to load highly onto 6 factors; Sleep Maintenance Problems, Co-Sleeping Behaviours, Bedtime Routines, Bedtime Resistance, Bedtime Worries and Bedtime Fears. Study 2 comprised a confirmatory factor analysis (CFA) and tests of convergent validity (n = 313), with results confirming the factor structure and providing evidence for convergent validity through correlations in expected directions between KIPS scores and other sleep, anxiety and behaviour measures. Study 3 tested the test-retest reliability of the KIPS (n = 53), and found support for the temporal stability of the KIPS over a 2-week period. Overall, the results provide strong preliminary evidence for the validity of the KIPS total score and its subscales, although the Bedtime Routines subscale may be less useful.
Influence of language barrier and cultural background in Hepatitis B disease knowledge in a Chinese community of Spain.
Authors: Pocurull Anna , Tapias Laura , Wang Tao , Morata Maria Jose , Miralpeix Anna , Collazos Cristina , Mariño Zoe , Lens Sabela , Forns Xavier 
Published: July 2023

Abstract
Background
Hepatitis B infection is prevalent in patients of Asian origin. Due to language barriers and cultural differences, it is not always straightforward to evaluate disease knowledge in the liver clinics. We aimed to assess the current awareness on HBV (Hepatits B virus) infection and its mechanisms of transmission in HBV-infected Chinese patients and their household contacts.
Methods
HBV-infected Chinese patients and their household contacts were interviewed by a nurse (Chinese or native) about their knowledge on hepatitis B transmission mechanisms, use of preventive measures and vaccination status. Non-Chinese HBV-infected patients were defined as a control group.
Results
A total of 182 patients and 398 relatives/household contacts participated in the study. Eighty-five (48%) patients and 240 (60%) of household contacts were from China. Language barrier was documented in 80% of Chinese patients and 44% of their household contacts. Knowledge on parenteral and sexual HBV transmission was high (90%) in both groups of patients. However, Chinese patients were significantly more aware of vertical transmission (94% vs 68%, p < 0.01) and were more forewarned in the use of parenteral transmission measures (93% vs 74%; p < 0.01). No differences in preventive sexual measures were detected. Despite being less knowledgeable on horizontal and sexual HBV transmission compared to controls (86% vs 96% for parenteral; 81% vs 95% for sexual, p < 0.01),Chinese household contacts used preventive measures more frequently (79% vs 65% for horizontal transmission, p < 0.01). Vaccination coverage was lower in Chinese (78%) compared to control (86%) household contacts although the difference did not reach statistical significance.
Conclusions
Despite relevant language barriers, Chinese HBV-infected patients are well informed on the mechanisms of HBV transmission, particularly on the vertical route. Cultural differences may explain a higher use of preventive measures among the Chinese population. HBV vaccination of household contacts should be reinforced in both groups of individuals.
Did the Cold War Produce Development Clusters in Africa?
Authors: Dower Paul Castañeda , Gokmen Gunes , Breton Michel Le , Weber Shlomo 
Published: July 2023

Abstract
We examine the lasting impact of Cold War alignment on African economic development. Faced with the empirical challenge of ambiguous and interdependent international alliances during the Cold War, we introduce a non-cooperative game of social interactions to determine blocs. Employing computational methods for non-convex optimization, we solve for the unique equilibrium two-bloc partition. The partition predicts UN General Assembly voting patterns in Africa during the Cold War but not after, and is uncorrelated with pre-Cold War outcomes. Surprisingly, average incomes in these two groups of countries are similar today. Yet, the alignment does affect the shape of development. Western-aligned countries have greater financial development, inequality, and democracy than Eastern-aligned ones, reflecting the Cold War’s ideological divide.
JEL codes: C62, C72, F54, F55, N47, O19, O57.