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The rolling bearing is a critical part of rotating machinery and its condition determines the performance of industrial equipment; it is necessary to detect rolling bearing faults as early as possible. The traditional methods of fault diagnosis are not efficient and are time-consuming. With the help of deep learning, the convolution neural network (CNN) plays a huge role in the data-driven methods of bearing fault diagnosis. However, the vibration signal is non-stationary, contains high noise, and is one-dimensional, which is difficult to analyze directly by the CNN model. Considering the multi-domain learning as an advantage of deep learning, this paper proposes a novel rolling bearing fault diagnosis approach using an improved one-dimensional (1D) and two-dimensional (2D) convolution neural network (CNN) of two-domain information learning. The constructed fault diagnosis model combining 1D and 2D CNN extracts the fault features from the two-domain information of bearing fault samples. The padding and dropout technology are utilized to fully extract features from the raw data and reduce over-fitting. To prove the validity of the proposed method, this paper performs two tests with two bearing datasets, the Case Western Reserve University (CWRU) bearing dataset and the Dalian University of Technology (DUT) vibration laboratory dataset. The experimental results show that our proposed method achieves high recognition accuracy of rolling bearing fault states via two-domain learning of monitoring data, and there is no manual experience necessary. Vibration data under strong noise were also used to test the method, and the results show the superiority and robustness of the proposed method. [ABSTRACT FROM AUTHOR]

The Dubair-Shang granitoids are the major intrusive bodies in Besham group and are exposed along the Karakoram Highway in Besham and lower Kohistan districts. A variety of these granitoid rocks have been investigated in terms of their petrographic features and physico-mechanical properties. The studied rocks are classified into four different textural varieties including Dubair mylonitized (DM), Dubair coarse grained (DCG), Shang coarse grained (SCG) and Shang foliated (SF) granitoids based on field observations and petrographic features. Petrographically quartz, potash feldspar, plagioclase and biotite are the essential minerals present in all varieties in varying amount. Beside these hornblende, chlorite, epidote, ore mineral(s) and sphene are also present in the accessory amount. As a part of the present investigation some of the mechanical and physical properties including uniaxial compressive strength (UCS), uniaxial tensile strength (UTS), specific gravity, water absorption, total porosity, and Los Angeles abrasion were also determined. The combined approach of petrographic features with the physico-mechanical investigation revealed that the textural characteristics and mineralogy have a significant influence on the physico-mechanical properties of the studied rocks. It is determined that modal percentage of minerals, degree of alteration, recrystallization, grain size and shape, types of grain boundary contacts have significant effect on characteristics of these granitoids. Based on strength tests studied rocks fall in category of moderately strong to strong. The values of specific gravity, porosity, water absorption and Los Angeles are within the range permissible for their use as constructional materials except SF. Based on physico-mechanical properties and petrographic examination Dubair-Shang granitoids could be used as aggregate for the construction of road, railway tracks, embankment, and canals. Theses rocks could also be used as sills, lentils, and roofing but should not be used for load bearing masonry like bridges, tunnels, buildings, dams etc. [ABSTRACT FROM AUTHOR]

Purpose: Smoking is a major public health issue, and its effect on cardiovascular outcomes is well established. This study evaluates the impact of donor smoking on heart transplant (HT) outcomes. Methods: HT recipients between January 1, 2005, and December 31, 2016, with known donor smoking status were queried from the International Society of Heart and Lung Transplantation (ISHLT) registry. The primary outcome was all‐cause mortality, and secondary endpoints were graft failure, acute rejection, and cardiac allograft vasculopathy. We utilized propensity‐score matching to identify cohorts of recipients with and without a history of donor smoking. Hazard ratios for post‐transplant outcomes for the matched sample were estimated from separate Cox proportional hazard models. Results: Of 26 390 patients in the cohort, 18.9% had history of donor smoking. Donors with history of smoking were older, predominantly male and had higher incidence of diabetes, hypertension, cocaine use, and "high‐risk" status. In propensity‐matched analysis, recipients with a history of donor smoking had increased risk of death (HR 1.11, 95% CI 1.03‐1.20) and higher risk of graft failure (HR 1.11, 95% CI 1.03‐1.20). Conclusion: Donor smoking was associated with increased mortality and higher incidence of graft failure following HT. Consideration of donor smoking history is warranted while evaluating donor hearts. [ABSTRACT FROM AUTHOR]

Aim: Platelet function is intricately linked to the pathophysiology of critical Illness, and some studies have shown that antiplatelet therapy (APT) may decrease mortality and incidence of acute respiratory distress syndrome (ARDS) in these patients. Our objective was to understand the efficacy of APT by conducting a meta-analysis.Materials and Methods: We conducted a meta-analysis using PubMed, Central, Embase, The Cochrane Central Register, the ClinicalTrials.gov Website, and Google Scholar. Studies were included if they investigated critically ill patients receiving antiplatelet therapy and mentioned the outcomes being studied (mortality, duration of hospitalization, ARDS, and need for mechanical ventilation).Results: We found that there was a significant reduction in all-cause mortality in patients on APT compared to control (odds ratio [OR]: 0.83; 95% confidence interval [CI]: 0.70-0.97). Both the incidence of acute lung injury/ARDS (OR: 0.67; 95% CI: 0.57-0.78) and need for mechanical ventilation (OR: 0.74; 95% CI: 0.60-0.91) were lower in the antiplatelet group. No significant difference in duration of hospitalization was observed between the two groups (standardized mean difference: -0.02; 95% CI: -0.11-0.07).Conclusion: Our meta-analysis suggests that critically ill patients who are on APT have an improved survival, decreased incidence of ARDS, and decreased need for mechanical ventilation. [ABSTRACT FROM AUTHOR]

The Industrial Internet of things (IIoT) is the main driving force behind smart manufacturing, industrial automation, and industry 4.0. Conversely, industrial IoT as the evolving technological paradigm is also becoming a compelling target for cyber adversaries. Particularly, advanced persistent threats (APT) and especially botnets are the foremost promising and potential attacks that may throw the complete industrial IoT network into chaos. IIoT-enabled botnets are highly scalable, technologically diverse, and highly resilient to classical and conventional detection mechanisms. Subsequently, we propose a deep learning (DL)-enabled novel hybrid architecture that can efficiently and timely tackle distributed, multivariant, lethal botnet attacks in industrial IoT. The proposed approach is thoroughly evaluated on a current state-of-the-art, publicly available dataset using standard performance evaluation metrics. Moreover, our proposed technique has been precisely verified with our constructed hybrid DL-enabled architectures and current benchmark DL algorithms. Our devised mechanism shows promising results in terms of high detection accuracy with a trivial trade-off in speed efficiency, assuring the proposed scheme as an optimal and legitimate cyber defense in prevalent IIoTs. Besides, we have cross-validated our results to show utterly unbiased performance. [ABSTRACT FROM AUTHOR]

Introduction: Hip fracture incidence is rising globally, making it crucial to understand the demographic factors that influence their occurrence for targeted healthcare interventions. This study focuses on examining the determinants of hip fracture incidence, particularly socioeconomic status, body mass index (BMI), and gender., Methods: The study utilised data from 570 patients recorded in the 2023 National Hip Fracture Database Audit tool. Socioeconomic status was assessed through the Index of Multiple Deprivation (IMD), based on patient postcodes. The analysis aimed to explore correlations between socioeconomic status, BMI, gender, and the incidence and types of hip fractures., Results: The findings indicate that the majority of hip fractures occurred in individuals from the lowest socioeconomic deciles, with a statistically significant correlation (p < 0.05) between lower socioeconomic status and higher fracture incidence. Gender-specific disparities were observed, with males experiencing fractures at younger ages and presenting with different fracture types compared to females. Additionally, lower BMI was significantly associated with a higher likelihood of certain fracture types (p < 0.05)., Conclusions: The study highlights the substantial influence of socioeconomic status, gender, and BMI on hip fracture incidence and typology. These results indicate the need for targeted prevention strategies and health policies aimed at mitigating hip fracture risks in socioeconomically disadvantaged populations. Understanding these factors can enable healthcare providers to allocate resources and interventions more effectively, reducing the incidence and impact of hip fractures in deprived areas., Competing Interests: Human subjects: Consent was obtained or waived by all participants in this study. University Hospital of South Manchester-Wythenshawe Hospital issued approval S33N. Animal subjects: All authors have confirmed that this study did not involve animal subjects or tissue. Conflicts of interest: In compliance with the ICMJE uniform disclosure form, all authors declare the following: Payment/services info: All authors have declared that no financial support was received from any organization for the submitted work. Financial relationships: All authors have declared that they have no financial relationships at present or within the previous three years with any organizations that might have an interest in the submitted work. Other relationships: All authors have declared that there are no other relationships or activities that could appear to have influenced the submitted work., (Copyright © 2024, Hussain et al.)

Introduction A clear picture of the prevalence of Fanconi anemia is not known due to limited studies and research of the subject. This study will detect the frequency of positive chromosomal breakage in pediatric aplastic patients and provide the evidence-based guidelines which help in consideration of appropriate treatment and awareness to the society. Methods A total of 104 aplastic anemia patients were recruited of age <18 years whose samples were tested for chromosomal breakage with mitomycin C (MMC). History of consanguinity between parents were documented for all the patients referred to us. Result Out of 104 diagnosed aplastic anemia patients, 35 (33.7%) patients were found to be Fanconi positive. Mean age of all hypoplastic patients for aplastic anemia and Fanconi anemia was 10.7 ± 4.5 and 10.6 ± 3.5, respectively. Male preponderance was found to be higher (64, 61.5%) as compared to females (40, 38.5%) in aplastic patients. The male to female ratio was observed as 2.5:1 in Fanconi patients while 1.3:1 in non-Fanconi aplastic patients. Parental consanguinity was observed in 33 (94.2%) with Fanconi anemia. Conclusion Fanconi anemia accounts for significant number of patients with hypoplastic bone marrow, therefore consanguineous marriages should be avoided through mass education in Pakistan., Competing Interests: The authors have declared that no competing interests exist., (Copyright © 2020, Siddiqui et al.)