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Natural plant based fibres are being increasingly used in sustainable fibre reinforced composite applications in order to meet the demand of using environmentally friendly materials for composites. Fibre metal laminates (FMLs) are used in aerospace, automobile, marine and civil engineering applications, due to their excellent mechanical behaviors compared to traditional metals and their alloys. This study describes a novel fabrication of jute fibre reinforced aluminum metal laminates, using different jute fibre architectures (plain and twill fabric structures), wherein jute fibres were used in the skins and aluminum in the core layers. Jute fibres and aluminum sheets were chemically treated to enhance the compatibility and interfacial bonding at fibre-metals-matrix interfaces. FMLs were manufactured by hot pressing technique, after the application of wet lay-up process for the resin impregnation and they were further tested under tensile, flexural and impact loading conditions. While comparing results, the twill architecture showed improved tensile and flexural properties compared to plain fabric based FMLs. Chemical treatments on twill jute fibres and metal sheets further exceptionally enhanced the flexural properties (151 MPa flexural strength and 21.3 GPa modulus and they were increased by 186.5 % and 722.7 % respectively compared to the untreated jute fibre counterparts) of the laminates due to a significant improvement in the adhesion between the jute fibre and aluminum sheet after alkali treatment applied. Therefore, with these enhanced properties, jute based FML laminates can be used as sustainable composite materials in many structural applications.

Background: The detection of lung nodules at their early stages may significantly enhance the survival rate and prevent progression to severe disability caused by advanced lung cancer, but it often requires manual and laborious efforts for radiologists, with limited success. To alleviate it, we propose a Multi-View Soft Attention-Based Convolutional Neural Network (MVSA-CNN) model for multi-class lung nodular classifications in three stages (benign, primary, and metastatic). Methods: Initially, patches from each nodule are extracted into three different views, each fed to our model to classify the malignancy. A dataset, namely the Lung Image Database Consortium Image Database Resource Initiative (LIDC-IDRI), is used for training and testing. The 10-fold cross-validation approach was used on the database to assess the model's performance. Results: The experimental results suggest that MVSA-CNN outperforms other competing methods with 97.10% accuracy, 96.31% sensitivity, and 97.45% specificity. Conclusions: We hope the highly predictive performance of MVSA-CNN in lung nodule classification from lung Computed Tomography (CT) scans may facilitate more reliable diagnosis, thereby improving outcomes for individuals with disabilities who may experience disparities in healthcare access and quality. [ABSTRACT FROM AUTHOR]

Jute fibre reinforced composites (JFRCs) are facing challenges to composite manufacturers due to the high cost of dry fibre preforming and inferior fibre performance compared to other commonly used natural plant fibres such as flax, sisal, hemp, and kenaf. Therefore, long fibre architecture jute fibre preforms often cannot fulfil the performance requirement of the composites. Using shorter length of jute fibres and then transform them into dry preforming sheet can ideally be used in manufacturing intricate composite products with low processing cost and high fibre reinforcing effect. On the other hand, short jute fibres suffer with extremely low fibre content and hence, they are difficult to use in making complex shape composite structures. In this work, a highly individualised and chemically treated (alkali) short jute fibre preforms with increased fibre contents were developed with the help of compression moulding. Composites were fabricated by impregnating the dry fibre preforms with epoxy resin by wet layup technique and cured in the hot press. These composites were found to have significantly higher mechanical properties when compared to traditional randomly orientated short jute fibre composites; showing the tensile strength ⁓93 MPa and flexural strength ⁓190 MPa for these composites, are the highest than any other natural short fibre composites reported so far in the literature. It was found that the extent of the improvement of mechanical properties of these composites, is related with the content of fibre in the composites, chemical modification of fibre ensuring higher bonding between the fibre and matrix. This work highlights new insights into high performance short jute fibres. If short jute fibres can be transformed into highly packed dry fibre preform, then it can be used in many semi-structural and structural composite applications.

Autism Spectrum Disorder (ASD) is a chronic condition characterised by impairments in social interaction and communication. Early detection of ASD is desired, and there exists a demand for the development of diagnostic aids to facilitate this. A lightweight Involutional Neural Network (INN) architecture has been developed to diagnose ASD. The model follows a simpler architectural design and has less number of parameters than the state‐of‐the‐art (SOTA) image classification models, requiring lower computational resources. The proposed model is trained to detect ASD from eye‐tracking scanpath (SP), heatmap (HM), and fixation map (FM) images. Monte Carlo Dropout has been applied to the model to perform an uncertainty analysis and ensure the effectiveness of the output provided by the proposed INN model. The model has been trained and evaluated using two publicly accessible datasets. From the experiment, it is seen that the model has achieved 98.12% accuracy, 96.83% accuracy, and 97.61% accuracy on SP, FM, and HM, respectively, which outperforms the current SOTA image classification models and other existing works conducted on this topic. [ABSTRACT FROM AUTHOR]

In this study, Mn3O4 nanoparticle was synthesized using Mn(CH3COO)2 and bloom gelatin as template of weight ratio 1:1 for the application in aqueous rechargeable zinc ion battery (ARZIB). The preparation of Mn3O4 was confirmed by FTIR, Raman spectra, FESEM, EDX, and XRD. Solid-state UV-Vis spectroscopic technique was used to identify its low optical band gap (2.75 eV) which indicated its semiconductor property. With additives, prepared Mn3O4 was used as cathode material, thereby CR-2032 coin cell of ARZIB was fabricated. The coin cell delivered a high specific discharge capacity of 219.33 mAh/g at 100 mA/g current density with columbic efficiency of 98.09%. It also showed excellent capacity retention, 92.69% and 64.84% after 200 and 1000 charge-discharge cycles, respectively. To check the effect of gelatin, Mn3O4 nanoparticles were further synthesized keeping the raw material constant and changing the amount of gelatin from zero to three fold. XRD was used to characterize the further prepared Mn3O4 and similar CR-2032 coin cells were fabricated and tested by cyclic voltammetry and battery charging-discharging profile. Results showed gelatin plays significant role in the surface morphology of Mn3O4 nanoparticle as well as the zinc ion storage capacity. The work offers a facile and cost-effective approach for preparing cathode material of ARZIBs. [ABSTRACT FROM AUTHOR]

In this study, a simple calcination route was adopted to prepare hausmannite Mn3O4 nanoparticles using rice powder as soft bio-template. Prepared Mn3O4 was characterized by Fourier Transform Infra-Red Spectroscopy (FTIR), Field Emission Scanning Electron Microscopy (FESEM), Energy Dispersive X-ray microanalysis (EDX), Powder X-Ray Diffraction (XRD), Transmission Electron Microscopy (TEM), Brunauer-Emmett-Teller (BET) and Solid state UV-Vis spectroscopic techniques. Mn-O stretching in tetrahedral site was confirmed by FTIR and Raman spectra. % of Mn and O content supported Mn3O4 formation. The crystallinity and grain size was found to be 68.76% and 16.43 nm, respectively; tetragonal crystal system was also cleared by XRD. TEM clarified the planes of crystal formed which supported the XRD results and BET demonstrated mesoporous nature of prepared Mn3O4 having low pore volume. Low optical band gap of 3.24 eV of prepared Mn3O4 nanoparticles indicated semiconductor property and was used as cathode material to fabricate CR-2032 coin cell of Aqueous Rechargeable Zinc Ion Battery (ARZIB). A reversible cyclic voltammogram (CV) showed good zinc ion storage performance. Low cell resistance was confirmed by Electrochemical Impedance Spectroscopy (EIS). The coin cell delivered high specific discharge capacity of 240.75 mAhg-1 at 0.1 Ag-1 current density. The coulombic efficiency was found to be 99.98%. It also delivered excellent capacity retention 94.45% and 64.81% after 300 and 1000 charge-discharge cycles, respectively. This work offers a facile and cost effective approach for preparing cathode material of ARZIBs. [ABSTRACT FROM AUTHOR]

Introduction: A wide range of study designs have been utilized in evaluations of home telemonitoring and these studies have produced conflicting outcomes over the years. While some of the research has shown that telemonitoring is beneficial in reducing all-cause mortality, hospital admission, length of stay in hospital and emergency room visits, other studies have not shown such benefits. This study, therefore, aims to examine several home telemonitoring study designs and the influence of study design on study outcomes. Method: Articles were obtained by searching PubMed database with the term heart failure combined with the following terms: telemonitoring, telehealth, home monitoring, and remote monitoring. Searches were limited to randomized controlled trial conducted between year January 1, 2000 and February 6, 2021. The characteristics of the study designs and study outcomes were extracted and analyzed. Result: Our review of 34 randomized controlled trials of heart failure telemonitoring did not show any significant influence of study design on reduction in number of hospitalizations and/or decrease in mortality. Studies that were done outside North America (USA and Canada) and studies that selected patients at high risk of re-hospitalization were more likely to result in decreased hospitalization and/or mortality, though this was not statistically significant. All the studies that met our inclusion criteria were from high-income countries and only one study enrolled patients at high risk of re-hospitalization. Conclusion: There is a need for more studies to understand why telemonitoring studies in Europe were more likely to reduce hospital admission and mortality compared to those in North America. There is also a need for more studies on the effect of telemonitoring in patients at high risk of hospital readmission. [ABSTRACT FROM AUTHOR]

In this report, natural dyes extracted from three different, black-colored fruits were used as photosensitizers for the construction of dye-sensitized solar cells (DSSCs). The natural dyes were extracted from the dark-colored peels of jamun (also known as Indian black plum), black plum, and blackberry fruit. These natural dyes contain polyphenolic compounds—most prominently anthocyanins—which interact strongly with titanium dioxide (TiO2) semiconductors and accordingly enhance the efficiency of DSSCs. The natural dyes extracted from the various fruits were characterized utilizing UV-Vis and fluorescence spectroscopy. The interaction between the dyes and TiO2 was monitored with FTIR and Raman spectroscopy. The fabricated DSSCs were characterized via current–voltage measurements and electrochemical impedance analysis. DSSCs fabricated with jamun produced the highest efficiency of 1.09% with a short-circuit current of 7.84 mA/cm2, an open-circuit voltage of 0.45 V, and a fill factor of 0.31. The efficiencies of the DSSCs from black plum and blackberry were 0.55% and 0.38%, respectively. The flow of charge occurring at the interfaces between the natural dye and the TiO2 layers were investigated using electrochemical impedance spectroscopy (EIS). To the best of our knowledge, this study is the first to directly compare three distinct types of black DSSCs. Computation analysis was also carried out utilizing SCAPS-1D software (version 3.3.07), which revealed how the type of defects in the devices impacts their performance. [ABSTRACT FROM AUTHOR]

Open in new tab Download slide OBJECTIVES The aim of this study was to develop a method to quantify the peel force in an in vitro model simulating repair of ascending aortic dissections with tissue glue (Bioglue). METHODS This study adapted an adhesive T-Peel test for the determination of the peel strength of adhesives by measuring the peeling force of a T-shaped bonded tissue. Measurements were performed on iatrogenic dissected ascending porcine aorta, which has been repaired with Bioglue using different pressure levels. Four conditions were tested: zero sample pressure according to the manufacturer's recommendation (n  = 10), low (504 Pa; n  = 11), moderate pressure (1711 Pa; n  = 24) and pressure applied by a round shaped vascular 'Borst clamp' (1764 Pa; n  = 23). Non-parametric one-way analysis of variance was applied for statistical significance. RESULTS The median peel force (lower quartile, upper quartile) of aortic samples increased depending on the applied pressure: [no pressure 0.030 N/mm (0.016, 0.057), low pressure 0.040 N/mm (0.032, 0.070) and moderate pressure 0.214 N/mm (0.050, 0.304)]. Samples pressurized with the Borst clamp reached 0.078 N/mm (0.046, 0.152), which was comparable to the peel force of the unpeeled controls [0.107 N/mm (0.087, 0.124)]. Compared to samples without pressure, Bioglue with the application of the Borst clamp (P  = 0.021) and with moderate pressure (P  = 0.0007) performed significantly better. CONCLUSIONS The novel T-Peel test offers an attractive method to test tissue glues in defined in vitro environments. Bioglue peel force increased with pressure on the aortic sample in contrast to low or no pressure as per the manufacturer's recommendation. Modifying current recommended use may aid in increasing effectiveness of this approach. [ABSTRACT FROM AUTHOR]

This study examined how major U.S. newspapers differentiated themselves from social networking website Facebook through their coverage of misinformation and conspiracy theories. A combination of qualitative and computational analysis of newspaper articles (N = 441) published between 2008 and 2021 revealed five major themes. Facebook was often portrayed as a vehicle for dissemination of conspiracies and misinformation. The computational analysis revealed major events, topics, and actors that generated newspaper articles regarding Facebook's role in spreading misinformation. [ABSTRACT FROM AUTHOR]

The Internet of Medical Things (IoMT) has become an attractive playground to cybercriminals because of its market worth and rapid growth. These devices have limited computational capabilities, which ensure minimum power absorption. Moreover, the manufacturers use simplified architecture to offer a competitive price in the market. As a result, IoMTs cannot employ advanced security algorithms to defend against cyber-attacks. IoMT has become easy prey for cybercriminals due to its access to valuable data and the rapidly expanding market, as well as being comparatively easier to exploit.As a result, the intrusion rate in IoMT is experiencing a surge. This paper proposes a novel Intrusion Detection System (IDS), namely SafetyMed, combining Convolutional Neural Networks (CNN) and Long Short-Term Memory (LSTM) networks to defend against intrusion from sequential and grid data. SafetyMed is the first IDS that protects IoMT devices from malicious image data and sequential network traffic. This innovative IDS ensures an optimized detection rate by trade-off between False Positive Rate (FPR) and Detection Rate (DR). It detects intrusions with an average accuracy of 97.63% with average precision and recall, and has an F1-score of 98.47%, 97%, and 97.73%, respectively. In summary, SafetyMed has the potential to revolutionize many vulnerable sectors (e.g., medical) by ensuring maximum protection against IoMT intrusion. [ABSTRACT FROM AUTHOR]

Alzheimer's disease has become a major concern in the healthcare domain as it is growing rapidly. Much research has been conducted to detect it from MRI images through various deep learning approaches.However, the problems of the availability of medical data and preserving the privacy of patients still exists. To mitigate this issue in Alzheimer's disease detection, we implement the federated approach, which is found to be more efficient, robust, and consistent compared with the conventional approach. For this, we need deep excavation on various orientations of MRI images and transfer learning architectures. Then, we utilize two publicly available datasets (OASIS and ADNI) and design various cases to evaluate the performance of the federated approach. The federated approach achieves better accuracy and sensitivity compared with the conventional approaches in most of the cases. Moreover, the robustness of the proposed approach is also found to be better than the conventional approach. In our federated approach, MobileNet, a low-cost transfer learning architecture, achieves the highest 95.24%, 81.94%, and 83.97% accuracy in the OASIS, ADNI, and merged (ADNI + OASIS) test sets, which is much higher than the achieved performance in the conventional approach. Furthermore, in the proposed approach, only the weights of the model are shared, which keeps the original MRI images in their respective hospital or institutions, preserving privacy in the healthcare domain. [ABSTRACT FROM AUTHOR]

Regular monitoring of hemipteran hopper species (including psyllids) associated with small-fruited acid lime trees (Citrus aurantifolia L.) was conducted for four years using motorized insect suction to determine the possible vectors of witches’- broom disease of lime (WBDL). The study was done in two phases: monitoring was done in Habra village, Wilayat Wadi AlMaawal (Batinah region) for one year from June 2000 to May 2001; then monitoring was done in Maharah village, Wilayat AlMusannah (Batinah region), for a period of three years from May 2001 to April 2004. Twelve species of cicadellid leafhoppers and one delpahacid planthopper species were collected, while no psyllids were found. Hishimonus phycitis (Distant) (Cicadellidae) was the most abundant hopper (78.4 % of collected individuals). Next in abundance were Toya sp. (Delphacidae), Circulifera haematiceps? and a deltocephalin leafhopper, respectively constituting 10.4, 3.8 and 2.4 % of the total catches of the four years. Nine other species made up 5% of the total collection: Exitianus nanus (Distant), Cicadulina sp. (either chinai (Ghauri) or storeyi (China)), Emposca distinguenda (Paoli), Amrasca biguttula (Ishihara), Deltocephalus (Recilia) pruthii (Metcalf), Neolimnus aegyptiacus (Mutsumura) and three undetermined species (one Deltocephalinae, one Typhlocybinae and one undeterminable to subfamily). Catches of H. phycitis were highest from November to March and lowest from May to September. There was a significant linear relationship between number of H. phycitis and maximum and mininmum temperature. Relative humidity was not significantly correlated to number of H. phycitis. In Maharah, young lime trees were free from WBDL but the disease incidence increased with age. H. phycitis is the best candidate vector of WBDL. The potential of Toya sp., Circulifera haematiceps? and an undetermined deltocephalin as candidate vectors is discussed. Finally, it is suggested that regular sprayings of acid lime trees with effective systemic insecticides during November to March each year can greatly reduce the vector population and can prevent or delay the spread of the disease to a great extent.

This exploratory study examined PolitiFact fact-checks (N=18,446) published between 2008 and 2020 to understand the extent to which the largest political fact-checking network in the United States utilizes traditional media routines in finding check-worthy claims and gathering information to verify claims. An automated content analysis revealed that PolitiFact relies more on routine channels of news production to find check-worthy claims than non-routine channels. The results also show that non-elite sources account for a negligible portion of PolitiFact sources, but the organization uses more non-traditional channels to find sources. [ABSTRACT FROM AUTHOR]