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COVID-19-related stress, anxiety and vaccine hesitancy among healthcare workers in a tertiary hospital in South-Western Nigeria

Dielectric function and thermo-optic coefficients of silicon-doped GaN substrates at elevated temperature from 298 K to 873 K in the UV-Vis-NIR spectrum

Abstract Understanding the thermal influence on gallium nitride (GaN) single crystal substrates is critical for the advancement of GaN-based optoelectronic devices. In this study, we comprehensively characterized the thermal effects on the optical properties of silicon-doped GaN substrates using spectroscopic ellipsometry over a broad wavelength range from 250 nm to 1600 nm. The dielectric function of GaN was determined at temperatures ranging from 298 K to 873 K, demonstrating consistent temperature-dependent behavior. The exciton transitions were precisely characterized and modeled using the empirical Varshni expression. Moreover, we report, for the first time, the thermo-optic coefficients across the wide spectrum, parameterized using a Sellmeier model. This work significantly expand the GaN optical properties database beyond thin films and provide essential insights for the design and optimization of next-generation GaN-based optoelectronic devices.

An efficient medical data encryption scheme using selective shuffling and inter-intra pixel diffusion IoT-enabled secure E-healthcare framework

Bundle sheath cell-dependent chloroplast movement in mesophyll cells of C4 plants analyzed using live leaf-section imaging

Correction: Impact of COVID-19 on gynecologic and obstetrical services at two large health systems

Uncovering the genetic basis of milk production traits in Mexican Holstein cattle based on individual markers and genomic windows

The objective of this study was to evaluate the proportion of genetic variance explained by single nucleotide polymorphism markers, individually or clustered in 1, 2, and 5 Mb windows, for milk yield, fat yield, protein yield, fat content, protein content, and somatic cell score in Mexican Holstein cattle. The analysis included data from 640,746 lactation records of 358,857 cows born between 1979 and 2019, distributed in 353 herds in 18 states of Mexico. The analysis included genotypic data on 7,713 cows and 577 sires, with information on 88,911 markers previously imputed and filtered by quality control. Genomic scans via the single-step genomic best linear unbiased prediction method were performed using BLUPF90 software. A total of 162 markers were significantly associated (p<0.01) with the phenotypic traits evaluated, and the SNP markers were distributed across chromosomes 1, 3, 5, 6, 10, 12, 14, 16, 18, 20, 22, and 29. When the size of the genomic windows was increased from 1 to 5 Mb, a greater proportion of genetic variance was explained by the SNPs within the window, and a greater number of windows explained more than 1% of the genetic variance. The most significant regions were associated with two or more phenotypic traits, such as one region on chromosome 14 that harbors the DGAT1, EXOSC4, PPP1R16A, and FOXH1 genes, which affect all the traits under study. In general, the utilization of genomic windows resulted in a greater proportion of genetic variance explained by milk production traits.

Clinical efficacy of different methods for treatment of granulomatous lobular mastitis: A systematic review and network meta-analysis

Objective This network meta-analysis aims to evaluate the recurrence rates of various treatment options for granulomatous lobular mastitis. Methods We systematically searched and identified eligible studies in PubMed, EMBASE, Cochrane Library, and Web of Science databases until September 30, 2023. Original studies reporting the recurrence rates of various treatments were included. Subsequently, literature screening, data extraction, and network meta-analysis were conducted. This study was registered with PROSPERO (registration number CRD 42023434773). Results Nineteen articles involving 1,095 patients were included in this study. The network meta-analysis revealed that several treatment combinations reduced the recurrence rate compared to observation: Surgery + Local steroid injection + Systemic steroids therapy (OR: 0.23, 95% CI 0.01 to 4.53), Local steroid injection (OR: 0.34, 95% CI 0.02 to 6.81), Surgery + Systemic steroids therapy (OR: 0.36, 95% CI 0.02 to 5.29), Surgery + Traditional Chinese Medicine (OR: 0.33, 95% CI 0.01 to 9.11), Systemic steroids therapy + MTX (OR: 0.62, 95% CI 0.01 to 34.59), and Systemic steroids therapy + drainage (OR: 0.76, 95% CI 0.05 to 10.67). Among these, Surgery + Local steroid injection + Systemic steroids therapy demonstrated superior efficacy. The surface under cumulative ranking curve (SUCRA) values were highest for Surgery + Local steroid injection + Systemic steroids therapy (0.85), followed by Local steroid injection (0.78) and Surgery + Systemic steroids therapy (0.77). Conclusions Steroid-based combination therapy may be the first choice for IGM patients, with a comprehensive strategy of local and systemic steroids combined with surgery having the best effect on IGM.

Development of clinical decision support for patients older than 65 years with fall-related TBI using artificial intelligence modeling

Background Older persons comprise most traumatic brain injury (TBI)-related hospitalizations and deaths and are particularly susceptible to fall-induced TBIs. The combination of increased frailty and susceptibility to clinical decline creates a significant ongoing challenge in the management of geriatric TBI. As the population ages and co-existing medical conditions complexify, so does the need to improve the quality of care for this population. Utilizing early hospital admission variables, this study will create and validate a multinomial decision tree that predicts the discharge disposition of older patients with fall-related TBI. Methods From the National Trauma Data Bank, we retrospectively analyzed 11,977 older patients with a fall-related TBI (2017–2021). Clinical variables included Glasgow Coma Scale (GCS) score, intracranial pressure monitor use, venous thromboembolism (VTE) prophylaxis, and initial vital signs. Outcomes included hospital discharge disposition re-categorized into home, care facility, or deceased. Data were split into two sets, where 80% developed a decision tree, and 20% tested predictive performance. We employed a conditional inference tree algorithm with bootstrap (B = 100) and grid search options to grow the decision tree and measure discrimination ability using the area under the curve (AUC) and calibration plots. Results Our decision tree used seven admission variables to predict the discharge disposition of older TBI patients. Significant non-modifiable variables included total GCS and injury severity scores, while VTE prophylaxis type was the most important interventional variable. Patients who did not receive VTE prophylaxis treatment had a higher probability of death. The predictive performance of the tree in terms of AUC value (95% confidence intervals) in the training cohort for death, care, and home were 0.66 (0.65–0.67), 0.75 (0.73–0.76), and 0.77 (0.76–0.79), respectively. In the test cohort, the values were 0.64 (0.62–0.67), 0.75 (0.72–0.77), and 0.77 (0.73–0.79). Conclusions We have developed and internally validated a multinomial decision tree to predict the discharge destination of older patients with TBI. This tree could serve as a decision support tool for caregivers to manage older patients better and inform decision-making. However, the tree must be externally validated using prospective data to ascertain its predictive and clinical importance.

Parental mediation and the use of social networks: A systematic review

Social networks are used daily by almost all adolescents and young people. They are used extensively, and their positive aspects are well-known, but they present multiple risks. Parents’ mediation (PM) in their children’s use of social networks (SNs) to prevent numerous problems has been recently researched. This systematic review analyzed works published since 2012 about online PM strategies concerning the use of SNs by children/adolescents aged between 9 and 18 years old. Following the PRISMA protocol, this review was submitted to Prospero (ID: CRD42022345033), five electronic databases were examined (WOS, SCOPUS, ERIC, ProQuest Psychology, and PubMed), and to assess the risk of bias the ROBIS tool was used. 32 papers were selected. The results indicate that PM strategies (especially the restrictive strategies over the enabling ones) effectively reduce the time spent on SNs and their associated risks. However, it is unclear whether one type of strategy is more effective or whether a combination of the different strategies, depending on the problem to be addressed, is most effective. Finally, no studies have been found that have analyzed the relationship between PM strategies and the benefits associated with the use of SNs. Possible lines of action for future programs and research are proposed.

Correction: The mediating role of psychological resilience on the negative effect of pain in patients with rheumatoid arthritis: a cross-sectional study

Investigation of customized total knee implant with articular cartilage under loading conditions using finite element analysis

Knee osteoarthritis (KOA) is a degenerative joint disease predominantly affecting the elderly and is often managed through knee replacement surgeries. West Asians, who frequently engage in activities involving bending and kneeling during their prayers, tend to exhibit distinct bone anatomy compared to the Caucasian population. This research posits that patient-specific, customized knee implants with articular cartilages may lead to reduced post-surgical discomfort and a better implant fit compared to conventional standard implants. This study presents a novel concept and approach for the development of a customized total knee implant with articular cartilages, specifically tailored to simulate loading conditions using finite element analysis (FEA) for the Saudi Arabian population. The research analyses patient-specific customized knee implants with articular cartilages under both pre- and post-implant conditions using a finite element model (FEM). Computed tomography (CT) images of patients were utilized to create a solid model, which was then analysed under various constraints and conditions. The meshing process employed tetrahedral elements, converging with 76,197 nodes and 43,009 elements. The analysis was conducted under different body weights, specifically 75–80 kg and 100–105 kg. Two sets of force and moment were applied: the first with a force of 1000 N and a moment of 1.5 N-m, and the second with a force of 750 N and a moment of 0.8 N-m. The results indicated a 5% reduction in stress with implants designed for a 100 kg body weight, along with a significant reduction in ligament strain when compared to conventional knee joint stresses. This study offers a promising pathway toward reducing post-surgical discomfort. The proposed innovative solution has the potential to revolutionize total knee implant technology, offering enhanced functionality and improved patient outcomes for the Saudi Arabian population.

The impact of polypharmacy on health outcomes in the aged: A retrospective cohort study

Objectives To estimate the prevalence of polypharmacy among community-dwelling adults in the UK and determine its association with mortality, hospitalization, adverse drug reactions and falls at one and five years. To also determine the effect of polypharmacy on the outcomes in different patient groups. Methods A retrospective cohort study was carried out using 1000 patients aged 75 years and above from the Clinical Practice Research Datalink. The study periods for the one- and five-years analysis were January 2010-December 2010 and January 2010-December 2014 respectively. Sociodemographic and clinical variables were retrieved using medical and product codes. Polypharmacy was defined as the use of five or more medicines. The association between polypharmacy and mortality, falls, adverse drug reactions, or hospitalization was determined using cox regression analysis while confounding for age, sex, Charlson’s comorbidity index, potentially inappropriate medicines, hospitalization prior to study, and falls prior to study. Subgroup analysis was used to determine the effect of polypharmacy on the outcomes for different patient groups. Key findings 977 people were reviewed. 36% were male and the mean age was 83 years. The prevalence of polypharmacy was 47%. Adjusted hazard ratios with their 95% confidence intervals for association between polypharmacy and outcomes at five years were: mortality 1.60 (1.30–2.00), hospitalization 1.49 (1.30–1.70), falls 1.49 (0.90–2.40) and adverse drug reactions 0.97 (0.50–1.80). The results for the one-year analysis were mortality 2.37 (1.40–3.90), hospitalization 2.47 (1.40–4.30), and falls 0.37 (0.03–4.00). Conclusion Polypharmacy was found to be a risk factor for mortality and hospitalization. The risk increased with an increase in age, potentially inappropriate medicines and comorbidities.

Human-environment interaction during the Holocene in Eastern South America: Rapid climate changes and population dynamics

About 15 years ago, we suggested that the low frequency of archaeological sites dating from the mid-Holocene in several regions of Lowland South America (which was then called the “Archaic Gap”) was due to an increase in the magnitude of dry periods related to the mid-Holocene hypsithermal. Since then, data regarding paleoenvironmental reconstructions for this vast area, coupled with an increase in the archaeological knowledge, allow us to reassess the idea of the “Archaic Gap” and redefine both the spatial extent of the phenomenon and its possible causes. Our present analysis aims to present a broader picture of the relations between humans and the environment in Eastern South America since the Late Pleistocene. The obtained results suggest that the extent of the areas that were somewhat depopulated during the mid-Holocene is larger than previously thought; not only Central Brazil, but parts of the Amazon and the Pantanal (close to the Bolivian border) seem to show the same pattern. However, as expected when larger datasets are available, it is possible to perceive oscillations in the archaeological signal that suggest reoccupation of some areas. Although we maintain that the main reasons underlying these patterns are related to climate, they are most probably related to an increase in climatic variability, and not necessarily to an increase in dryness. These observations are of interest to the current debate about the effects of the global warming on human populations.

Multi-level high utility-itemset hiding

Privacy is as a critical issue in the age of data. Organizations and corporations who publicly share their data always have a major concern that their sensitive information may be leaked or extracted by rivals or attackers using data miners. High-utility itemset mining (HUIM) is an extension to frequent itemset mining (FIM) which deals with business data in the form of transaction databases, data that is also in danger of being stolen. To deal with this, a number of privacy-preserving data mining (PPDM) techniques have been introduced. An important topic in PPDM in the recent years is privacy-preserving utility mining (PPUM). The goal of PPUM is to protect the sensitive information, such as sensitive high-utility itemsets, in transaction databases, and make them undiscoverable for data mining techniques. However, available PPUM methods do not consider the generalization of items in databases (categories, classes, groups, etc.). These algorithms only consider the items at a specialized level, leaving the item combinations at a higher level vulnerable to attacks. The insights gained from higher abstraction levels are somewhat more valuable than those from lower levels since they contain the outlines of the data. To address this issue, this work suggests two PPUM algorithms, namely MLHProtector and FMLHProtector, to operate at all abstraction levels in a transaction database to protect them from data mining algorithms. Empirical experiments showed that both algorithms successfully protect the itemsets from being compromised by attackers.

Does the digital transformation of enterprises affect capital mismatch? evidence from Chinese listed firms

In this study, based on the data of the Chinese listed firms, the effect of digital transformation on capital mismatch was examined. And the potential mechanism was also further discussed. It was found that digital transformation can significantly suppress capital mismatch, especially for non-state-owned enterprises, mature enterprises, and regions with high marketization and financial technology level. In addition, management capability and information environment are potential influencing mechanisms of digital transformation to suppress capital mismatch. These findings have important implications for revealing the relationship between enterprise digital transformation and capital mismatch, provides new ideas for improving the efficiency of capital allocation, and also provides important insights for enterprises to accelerate digital transformation and promote the high-quality development of enterprises.

Transition of clinical biomarker status from childhood into adolescence–A prospective study in children from eight European countries

Purpose Understanding factors influencing clinical biomarkers is important for the prevention of chronic disease. This study aimed to estimate transitions of biomarker status from childhood to adolescence and to identify determinants of biomarker status in early life in a prospective children cohort. Subjects and methods Our sample comprised 1295 children participating in the baseline (2007/08) and second follow-up examination (2013/14) of the multi-center IDEFICS (Identification and prevention of Dietary- and lifestyle-induced health EFfects In Children and infantS)/I.Family study. Clinical blood biomarkers including glycated hemoglobin A1c (HbA1c), high-density lipoprotein cholesterol (HDL-cholesterol), triglycerides, C-reactive protein (CRP), interleukin 6, ferritin, leptin and insulin-like growth factor 1 (IGF-1) were repeatedly measured in 2007/2008 (age range: 3.0 to <10.0 years) and in 2013/2014. Latent transition analysis was used to estimate biomarker statuses and transition probabilities; determinants of biomarker status were estimated using mixed-effects models. Results Four distinct biomarker statuses were identified: (1) “normal” (all biomarkers low/medium; except HDL-cholesterol; reference), (2) “low leptin/IGF-1/HbA1c”, (3) “dyslipidemia/high leptin” and (4) “inflammation”. Children classified as “low leptin/IGF-1/HbA1c” at baseline were most likely to stay in this status (89.8%) or to change to the “normal” status (10%) during follow-up. Compared to “normal” children, children classified as “low leptin/IGF-1/HbA1c” were less likely to have a family history of diabetes (0.26 [0.08;0.86]; odds ratio (OR) and 95% confidence interval) or hypertension (0.53 [0.29;0.99]) and the children (0.32 [0.27;0.38]) as well as their mothers (0.93 [0.88;0.98]) had a lower BMI. Children from families with low/medium education had a 55% [9%-119%] higher risk of being in the “dyslipidemia/high leptin” and 49% [1%-121%] higher risk of being in the “inflammation” status as compared to children in the “normal” status. Membership in a sports club reduced the latter risks by 28% [2%-47%] and 40% [17%-56%], respectively. Conclusions European children showed distinct phenotypes for the investigated biomarkers. Especially parental characteristics like a family history of diabetes or hypertension, a high maternal BMI, or low/medium education were associated with unfavorable biomarker status in children.

A matching method for elderly care service personnel with multiple types of service expectations

With the rapid growth of the global aging population, the problem of providing for the elderly has become increasingly prominent. As a new model of providing for the elderly in China, home-based care has attracted more and more attention from all walks of life. The research on how to realize reasonable and effective matching between elderly care service personnel and the elderly under the home care model deserves attention and has important practical significance. In this paper, a matching method for elderly care service personnel considering multi-type service expectations is proposed. This approach involves first obtaining the actual values of the expectation indexes for each other, as well as the expectation requirements of the elderly and the service personnel. Next, we compute the satisfaction of the elderly and the service personnel for each other based on the elastic service expectation type, and finally, we make a decision about whom to choose based on the inelastic service expectation indexes. On this basis, the situation is considered that there are sufficient and insufficient elderly care service personnel, the two-sided matching models are constructed, respectively, and the optimal matching results are obtained by solving the models. Finally, an example is given to illustrate the feasibility and effectiveness of the proposed method.

Comparing P300 flashing paradigms in online typing with language models

The P300 Speller is a brain-computer interface system that allows victims of motor neuron diseases to regain the ability to communicate by typing characters into a computer by thought. Since the system has a relatively slow typing speed, different stimulus presentation paradigms have been proposed designed to allow users to input information faster by reducing the number of required stimuli or increase signal fidelity. This study compares the typing speeds of the Row-Column, Checkerboard, and Combinatorial Paradigms to examine how their performance compares in online and offline settings. When the different flashing patterns were tested in conjunction with other established optimization techniques such as language models and dynamic stopping, they did not make a significant impact on P300 speller performance. This result could indicate that further performance improvements on the system lie beyond optimizing flashing patterns.

Innovative strategies for pollution assessment in Northern Bangladesh: Mapping pollution areas and tracing metal(loid)s sources in various soil types

This study assessed the risks of soil pollution by heavy metals in Chilmari Upazila, northern Bangladesh, using the static environmental resilience (Pi) model of soil. Geostatistical modeling and self-organizing maps (SOM) identified pollution areas and spatial patterns, while a positive matrix factorization (PMF) model revealed pollution sources. The results showed that the average concentrations of Cr, Pb and As were well above background levels. Agricultural and industrial soils were mainly contaminated with Cr, Pb and As according to the Nemerow Pollution Index (NPI), Ecological Risk (ER) and Pi Index. Over 70% of the sites were contaminated with Pb and Cr, while co-contamination was particularly high. A one-way ANOVA showed significant correlations between Pb, Cu and Zn levels and human activities. The PMF analysis revealed that industrial effluents, agrochemicals and lithogenic sources were the main contributors to soil contamination with 16%, 41% and 43%, respectively. The SOM analysis revealed three distinct spatial patterns (Pb-Zn, Cr-Cu-Ni and Co-Mn-As), which are consistent with the PMF results. These results emphasize the need for stringent measures to reduce industrial emissions and remediate soil contamination in order to improve soil quality and food security.

Detection of opening motion characteristics in DC circuit breakers based on machine vision

A circuit breaker is a crucial component in power systems, and its operation is essential for evaluating its interruption performance. However, electromagnetic interference often affects sensor accuracy. To address this issue, this paper investigates a non-contact measurement technique for assessing the motion characteristics of circuit breakers. A motion detection method based on Franklin moments is proposed. A synchronous image acquisition platform was established using high-speed cameras to capture the motion of 252kV circuit breakers. The captured images are preprocessed, with coarse edges extracted using the Laplacian algorithm. Franklin moment convolution calculations are then applied to determine sub-pixel coordinates of the image edges based on these coarse edges. By analyzing the frame-to-frame variations of these sub-pixel coordinates, the opening motion characteristics of the circuit breaker are extracted. This method can detect the vibration parameters and bouncing phenomenon of circuit breaker motion machine in millisecond level, and the accuracy is 0.01 mm. These findings offer valuable insights for future research on circuit breaker performance.