The severity of dry eye symptoms and risk factors among university students in Saudi Arabia: a cross-sectional study.

Dry eye syndrome (DES) is a tear film disorder caused by increased tear evaporation or decreased production. The heavy workload on the eye and the increased usage of digital screens may decrease blink frequency, leading to an increased evaporation rate and an upsurge in the incidence and severity of DES. This study aims to assess the severity of DES symptoms and the risk factors among university students. A cross-sectional study was conducted at Umm AlQura University to evaluate the severity of DES among students and explore its potential association with digital screen use. Validated questionnaires were used to assess the severity of DES and digital screen usage. The study included 457 participants, of which 13% had symptoms suggestive of severe DES. Furthermore, multiple risk factors had a significant association with the severity of DES, including gender, use of monitor filters, monitor and room brightness, and smoking habits. DES symptoms were prevalent among university students, particularly female students. Although there was no significant association with the duration of screen usage and collage distribution. Other factors however, such as the usage of screen monitors and the brightness of both the monitor and the room, were significantly associated with the severity of DES symptoms.

Cardiotoxicity in Cancer Patients: The Prevalence, Risk Factors, and Cardioprotective Measures in a Cancer Centre in Saudi Arabia.

BACKGROUND: Chemotherapy-related cardiotoxicity can exhibit several patterns of functional, structural, and vascular complications. This study aims to identify the patterns and the factors associated with cardiotoxicity in cancer patients. METHOD: A retrospective cross-sectional analysis of 96 adult cancer patients undergoing anticancer therapy was investigated at King Khalid Hospital in Najran, Saudi Arabia, from May 2022 to April 2023. The data on patient and cancer characteristics, treatment, and outcomes were collected and analyzed. Factors associated with cardiotoxicity were investigated through univariate analyses using odds ratio (OR) and 95% confidence interval (CI). RESULTS:  Among the 96 cancer patients in the study, cardiotoxicity occurred in 12 individuals (12.5%). The mean age was 57.0 ± 13.3 years (range: 32-81 years), with 32 (33.3%) being above 65 years. The most common comorbidities were diabetes (n=48; 50%), followed by hypertension (n=32; 33.3%), and dyslipidemia (n=20; 20.8%). The most common cancers were gastrointestinal cancer (n=32; 33.3%), followed by breast cancer (n=22; 22.9%) and lymphoma (n=14; 14.6%). Females were disproportionately affected (64.6%), with 57.3% of them in the metastatic stage. The majority of patients (90.6%) had normal ejection fraction before chemotherapy initiation. In univariate analysis, current smoking (OR: 7.00; 95%CI: 1.94-25.25, p= 0.003), history of percutaneous cardiac intervention (OR: 40.24; 95%CI: 1.80-896.26, p= 0.019), diabetes (OR: 6.05; 95%CI: 1.24-29.32, p= 0.025), renal failure (OR: 8.20; 95%CI: 0.91-74.88, p= 0.046), dyslipidemia (OR: 5.00; 95 CI: 1.38-18.32, p=0.012), anthracycline use (OR: 18.33; 95%CI: 4.36-126.55, p <0.001), trastuzumab use (OR: 25.00; 95%CI: 6.25-129.86, p < 0.001), and increased chemotherapy cycles number (> 10 cycles) (OR: 73.00; 95%CI: 8.56- 622.36, p < 0.001) were associated with cardiotoxicity. Additionally, beta-blocker use was associated with lower rates of cardiotoxicity (OR: 0.17; 95%CI: 0.036-0.84, p= 0.029). CONCLUSIONS: The incidence of cardiotoxicity among cancer patients treated with chemotherapy is modest, difficult to predict, and independent of baseline cardiac systolic functions. Factors associated with cardiotoxicity include smoking, history of percutaneous cardiac intervention, diabetes, renal failure, dyslipidemia, anthracycline or trastuzumab use, and increased chemotherapy cycle numbers. A combination of various anticancer drugs and chemotherapy may dramatically raise the risk of cardiotoxicity in cancer patients. As a result, patients receiving high-risk cardiotoxic drugs should be monitored with caution to avoid drug-related cardiotoxicity. Furthermore, proactive treatment techniques aiming at reducing the possible cardiotoxic effects of anticancer therapy are critical.

Mechanical Recycling of Carbon Fiber-Reinforced Polymer in a Circular Economy.

This review thoroughly investigates the mechanical recycling of carbon fiber-reinforced polymer composites (CFRPCs), a critical area for sustainable material management. With CFRPC widely used in high-performance areas like aerospace, transportation, and energy, developing effective recycling methods is essential for tackling environmental and economic issues. Mechanical recycling stands out for its low energy consumption and minimal environmental impact. This paper reviews current mechanical recycling techniques, highlighting their benefits in terms of energy efficiency and material recovery, but also points out their challenges, such as the degradation of mechanical properties due to fiber damage and difficulties in achieving strong interfacial adhesion in recycled composites. A novel part of this review is the use of finite element analysis (FEA) to predict the behavior of recycled CFRPCs, showing the potential of recycled fibers to preserve structural integrity and performance. This review also emphasizes the need for more research to develop standardized mechanical recycling protocols for CFRPCs that enhance material properties, optimize recycling processes, and assess environmental impacts thoroughly. By combining experimental and numerical studies, this review identifies knowledge gaps and suggests future research directions. It aims to advance the development of sustainable, efficient, and economically viable CFRPC recycling methods. The insights from this review could significantly benefit the circular economy by reducing waste and enabling the reuse of valuable carbon fibers in new composite materials.

A Survey on Industrial Internet of Things Security: Requirements, Attacks, AI-Based Solutions, and Edge Computing Opportunities.

The Industrial Internet of Things (IIoT) paradigm is a key research area derived from the Internet of Things (IoT). The emergence of IIoT has enabled a revolution in manufacturing and production, through the employment of various embedded sensing devices connected by an IoT network, along with a collection of enabling technologies, such as artificial intelligence (AI) and edge/fog computing. One of the unrivaled characteristics of IIoT is the inter-connectivity provided to industries; however, this characteristic might open the door for cyber-criminals to launch various attacks. In fact, one of the major challenges hindering the prevalent adoption of the IIoT paradigm is IoT security. Inevitably, there has been an inevitable increase in research proposals over the last decade to overcome these security concerns. To obtain an overview of this research area, conducting a literature survey of the published research is necessary, eliciting the various security requirements and their considerations. This paper provides a literature survey of IIoT security, focused on the period from 2017 to 2023. We identify IIoT security threats and classify them into three categories, based on the IIoT layer they exploit to launch these attacks. Additionally, we characterize the security requirements that these attacks violate. Finally, we highlight how emerging technologies, such as AI and edge/fog computing, can be adopted to address security concerns and enhance IIoT security.

Fabrication of a Biomass-Derived Activated Carbon-Based Anode for High-Performance Li-Ion Batteries.

Porous carbons are highly attractive and demanding materials which could be prepared using biomass waste; thus, they are promising for enhanced electrochemical capacitive performance in capacitors and cycling efficiency in Li-ion batteries. Herein, biomass (rice husk)-derived activated carbon was synthesized via a facile chemical route and used as anode materials for Li-ion batteries. Various characterization techniques were used to study the structural and morphological properties of the prepared activated carbon. The prepared activated carbon possessed a carbon structure with a certain degree of amorphousness. The morphology of the activated carbon was of spherical shape with a particle size of ~40-90 nm. Raman studies revealed the characteristic peaks of carbon present in the prepared activated carbon. The electrochemical studies evaluated for the fabricated coin cell with the activated carbon anode showed that the cell delivered a discharge capacity of ~321 mAhg-1 at a current density of 100 mAg-1 for the first cycle, and maintained a capacity of ~253 mAhg-1 for 400 cycles. The capacity retention was found to be higher (~81%) with 92.3% coulombic efficiency even after 400 cycles, which showed excellent cyclic reversibility and stability compared to commercial activated carbon. These results allow the waste biomass-derived anode to overcome the problem of cyclic stability and capacity performance. This study provides an insight for the fabrication of anodes from the rice husk which can be redirected into creating valuable renewable energy storage devices in the future, and the product could be a socially and ethically acceptable product.

Influence of Carbon Micro- and Nano-Fillers on the Viscoelastic Properties of Polyethylene Terephthalate.

In this research study, three carbon fillers of varying dimensionality in the form of graphite (3D), graphite nano-platelets (2D), and multiwall carbon nanotubes (1D) were incorporated into a matrix of poly (ethylene terephthalate), forming carbon-reinforced polymer composites. Melt compounding was followed by compression moulding and then a quenching process for some of the samples to inhibit crystallization. The samples were analysed using dynamic mechanical thermal analysis (DMTA) and scanning electron microscopy (SEM), considering the dimensionality and loading of the carbon fillers. The dynamic mechanical analysis revealed a similar decline of storage moduli for all composites during the glassy to rubbery transition. However, storage moduli values at room temperature increased with higher loading of nano-fillers but only to a certain level; followed by a reduction attributed to the formation of agglomerates of nanotubes and/or rolled up of nano-platelets, as observed by SEM. Much greater reinforcement was observed for the carbon nanotubes compared to the graphite and or the graphite nano-platelets. The quenched PET samples showed significant changes in their dynamic mechanical properties due to both filler addition and to cold crystallization during the DMTA heating cycle. The magnitude of changes due to filler dimensionality was found to follow the order: 1D > 2D > 3D, this carbon filler with lower dimensionality have a more significant effect on the viscoelastic properties of polymer composite materials.

Experimental and Theoretical Analysis of Mechanical Properties of Graphite/Polyethylene Terephthalate Nanocomposites.

In this work, graphite nanoplatelets (GNP) were incorporated into poly (ethylene terephthalate) (PET) matrix to prepare PET-GNP nanocomposites using a melt compounding followed by compression moulding and then quenching process. Both static and dynamic mechanical properties of these quenched materials were characterized as a function of GNP contents using dynamic mechanical thermal analysis (DMTA) and tensile machine, respectively. The results demonstrated that the addition of GNP improved the stiffness of PET significantly. Additionally, the maximum increase in the storage modulus of 72% at 6 wt.% GNP. The incorporation of GNP beyond 6 wt.% into PET decreases the storage moduli, but they remain higher than pure PET. The observed reduction could be due to agglomeration, resulting in poorer dispersion and distribution of higher levels of GNP into the PET matrix. In contrast to the results for moduli, tensile strength and elongations at break reduce with increasing the GNP content. For example, tensile strength reduced from ∼46 MPa (neat PET) to ∼39 MPa (-15%) for the nanocomposites containing 2 wt.% GNP. This reduction is accompanied by a decline in elongation at break from ∼6.3 (neat PET) to ∼3.4 (-46%) for the same nanocomposites. Such reductions are followed by a gradual decrease in upon further addition of GNP. These reductions indicate that increasing GNP loadings, results in brittleness in nanocomposites. In addition, it was found that quenched PET and composite samples were not fully crystallized after processing and therefore (cold) crystallized during the first heating cycle DMTA, as indicated by a rise in storage moduli above the glass transition temperature during the DMTA first heat. Furthermore, mathematical models based on non-linear theories are developed to capture the experimental data. For this, a set of mechanical stress-strain data is used for model parameters' identification. Another set of data is used for the model validation that demonstrates good agreements with the experimental study.

Performance of Nanocomposites of a Phase Change Material Formed by the Dispersion of MWCNT/TiO2 for Thermal Energy Storage Applications.

Thermal energy storage technology is an important topic, as it enables renewable energy technology to be available 24/7 and under different weather conditions. Phase changing materials (PCM) are key players in thermal energy storage, being the most economic among those available with adjustable thermal properties. Paraffin wax (PW) is one of the best materials used in industrial processes to enhance thermal storage. However, the low thermal conductivity of PW prevents its thermal application. In this study, we successfully modified PW based on multi-walled carbon nanotubes (MWCNT) with different concentrations of TiO2-3, 5 and 7 wt.%. The morphology of PCM and its relationship with the chemical structure and stability were characterized using scanning electron microscopy (SEM), Fourier transform infrared (FTIR) and Thermogravimetric analysis (TGA). As a result, the composites achieved a highest latent heat enthalpy of 176 J/g, in addition to enhanced thermal stability after 15 thermal cycles, and reliability, with a slight change in latent heat observed when using a differential scanning calorimeter (DSC). The thermal conductivity of the composites could significantly be enhanced by 100%. Compared to pure paraffin, the PCM composites developed in this study exhibited an excellent preference for thermal energy storage and possessed low cost, high reliability, and phase change properties.

Intelligent Medical IoT-Enabled Automated Microscopic Image Diagnosis of Acute Blood Cancers.

Blood cancer, or leukemia, has a negative impact on the blood and/or bone marrow of children and adults. Acute lymphocytic leukemia (ALL) and acute myeloid leukemia (AML) are two sub-types of acute leukemia. The Internet of Medical Things (IoMT) and artificial intelligence have allowed for the development of advanced technologies to assist in recently introduced medical procedures. Hence, in this paper, we propose a new intelligent IoMT framework for the automated classification of acute leukemias using microscopic blood images. The workflow of our proposed framework includes three main stages, as follows. First, blood samples are collected by wireless digital microscopy and sent to a cloud server. Second, the cloud server carries out automatic identification of the blood conditions-either leukemias or healthy-utilizing our developed generative adversarial network (GAN) classifier. Finally, the classification results are sent to a hematologist for medical approval. The developed GAN classifier was successfully evaluated on two public data sets: ALL-IDB and ASH image bank. It achieved the best accuracy scores of 98.67% for binary classification (ALL or healthy) and 95.5% for multi-class classification (ALL, AML, and normal blood cells), when compared with existing state-of-the-art methods. The results of this study demonstrate the feasibility of our proposed IoMT framework for automated diagnosis of acute leukemia tests. Clinical realization of this blood diagnosis system is our future work.

Genetic diversity of wild rodents and detection of Coxiella burnetii, the causative agent of Q fever, in Saudi Arabia.

Throughout history, wildlife has been regarded as a major source of infectious diseases. Rodentia, the most speciose order of mammals, whose members are recognised hosts of more than 60 zoonotic diseases, represent a potential threat to human health. Recently, epidemiological data from Saudi Arabia indicated an actual growth in the number of emerging and/or re-emerging cases of several zoonoses. However, there is a lack of studies focusing on the molecular taxonomy of rodents and the pathogens they may harbour in this region. In this study, the first molecular characterisation of six rodent taxa in this region is provided, based on partial Cyt B and 16S genes. The data confirm the spread of rodent-associated C. burnetii strains in Jazan, southwestern Saudi Arabia. The PCR targeting IS111, the multi-copy transposase gene, revealed 17.5% (36/205) positive samples, whereas the second nested PCR, targeting the single-copy Com1 gene, revealed 16.6% (34/205) positive samples. Phylogenetic and network analyses indicated the presence of four haplotypes of C. burnetii within the studied localities. One major haplotype (H-2) was observed in all rodent species and from 18 localities. The infection rates of C. burnetii among studied species, localities and habitats were not significantly different (>0.05). Our results facilitate the assessment of the health risk associated with rodents and the development of strategies to control the increasing impacts of Q fever.

Enhancing the Performance of a Metal-Free Self-Supported Carbon Felt-Based Supercapacitor with Facile Two-Step Electrochemical Activation.

Carbon felt (CF) is an inexpensive carbon-based material that is highly conductive and features extraordinary inherent surface area. Using such a metal-free, low-cost material for energy storage applications can benefit their practical implementation; however, only limited success has been achieved using metal-free CF for supercapacitor electrodes. This work thoroughly studies a cost-effective and simple method for activating metal-free self-supported carbon felt. As-received CF samples were first chemically modified with an acidic mixture, then put through a time optimization two-step electrochemical treatment in inorganic salts. The initial oxidative exfoliation process enhances the fiber's surface area and ultimately introduced oxygen functional groups to the surface, whereas the subsequent reduction process substantially improved the conductivity. We achieved a 205-fold enhancement of capacitance over the as-received CF, with a maximum specific capacitance of 205 Fg-1, while using a charging current density of 23 mAg-1. Additionally, we obtained a remarkable capacitance retention of 78% upon increasing the charging current from 0.4 to 1 Ag-1. Finally, the cyclic stability reached 87% capacitance retention after 2500 cycles. These results demonstrate the potential utility of electrochemically activated CF electrodes in supercapacitor devices.

Improved Support Vector Machine Enabled Radial Basis Function and Linear Variants for Remote Sensing Image Classification.

Remote sensing technologies have been widely used in the contexts of land cover and land use. The image classification algorithms used in remote sensing are of paramount importance since the reliability of the result from remote sensing depends heavily on the classification accuracy. Parametric classifiers based on traditional statistics have successfully been used in remote sensing classification, but the accuracy is greatly impacted and rather constrained by the statistical distribution of the sensing data. To eliminate those constraints, new variants of support vector machine (SVM) are introduced. In this paper, we propose and implement land use classification based on improved SVM-enabled radial basis function (RBF) and SVM-Linear for image sensing. The proposed variants are applied for the cross-validation to determine how the optimization of parameters can affect the accuracy. The accuracy assessment includes both training and test sets, addressing the problems of overfitting and underfitting. Furthermore, it is not trivial to determine the generalization problem merely based on a training dataset. Thus, the improved SVM-RBF and SVM-Linear also demonstrate the outstanding generalization performance. The proposed SVM-RBF and SVM-Linear variants have been compared with the traditional algorithms (Maximum Likelihood Classifier (MLC) and Minimum Distance Classifier (MDC)), which are highly compatible with remote sensing images. Furthermore, the MLC and MDC are mathematically modeled and characterized with new features. Also, we compared the proposed improved SVM-RBF and SVM-Linear with the current state-of-the-art algorithms. Based on the results, it is confirmed that proposed variants have higher overall accuracy, reliability, and fault-tolerance than traditional as well as latest state-of-the-art algorithms.

Improving water oxidation performance by implementing heterointerfaces between ceria and metal-oxide nanoparticles.

The main technical challenge for the electrolytic production of hydrogen via water splitting lies in realizing a very stable material that effectively oxidizes water under low overpotential (η). Of all materials, metal oxides hold the greatest promise due to their inherited chemical stability in aqueous solutions; however, electrolytic effectiveness in water oxidation reactions (OERs) is limited to precious metals. In this study, we designed metal oxide/metal oxide (MO/MO) nanoparticle heterointerfaces to offer more active sites and enhance the overall performance of the OER. To demonstrate this improvement, we synthesized and characterized CeO2/Co3O4, CeO2/CuO, and CeO2/NiO nanoparticles. In these structures, onset potential and photoactivity were significantly improved relative to a single MO. A cathodic shift of onset potential as high as ~0.4 or 0.3 V was recorded for CeO2/Co3O4 relative to CeO2 or Co3O4, respectively. This improvement was further investigated using density functional theory calculations, upon which adsorption preferability and reaction free energy at the CeO2/Co3O4 heterointerface were found to play significant roles in OER enhancement.

Binder-Free Electrode Based on ZnO Nanorods Directly Grown on Aluminum Substrate for High Performance Supercapacitors.

Herein, for the first time, the growth of ZnO nanorods directly on aluminum (Al) substrate via a low temperature (80 °C) wet chemical method, and used as binder-free electrode for supercapacitors were reported. XRD pattern and HRTEM images showed that high crystalline nanorods grown on Al substrate with c-axis orientation. Morphological studies revealed that the nanorods possessed well defined hexagon phase with length and diameter of ~2 µm and 100-180 nm, respectively. Raman spectrum of ZnO nanorods showed that the characteristic E2H mode corresponds to the vibration associated with the oxygen atoms of ZnO. The optical properties of ZnO nanorods studied using Room-temperature PL spectra revealed a near-band-edge (NBE) peak at ~388 nm emission and deep level (DLE) at ~507 nm. Electrochemical measurements showed that ZnO nanorods on Al substrate exhibited remarkably enhanced performance as electrode for supercapacitors with a value of specific capacitance of 394 F g-1 measured with scan rate of 20 mV s-1. This unique nanorods structures also exhibited excellent stability of >98% capacitance retention for 1000 cycles that were measured at 1A g-1. The presented easy and cost-effective method might open up the possibility for the mass production of binder-free electrodes for efficient electrochemical energy storage devices.

Near-Infrared Colloidal Quantum Dots for Efficient and Durable Photoelectrochemical Solar-Driven Hydrogen Production.

A new hybrid photoelectrochemical photoanode is developed to generate H2 from water. The anode is composed of a TiO2 mesoporous frame functionalized by colloidal core@shell quantum dots (QDs) followed by CdS and ZnS capping layers. Saturated photocurrent density as high as 11.2 mA cm-2 in a solar-cell-driven photoelectrochemical system using near-infrared QDs is obtained.

A Monolithically Integrated Gallium Nitride Nanowire/Silicon Solar Cell Photocathode for Selective Carbon Dioxide Reduction to Methane.

A gallium nitride nanowire/silicon solar cell photocathode for the photoreduction of carbon dioxide (CO2 ) is demonstrated. Such a monolithically integrated nanowire/solar cell photocathode offers several unique advantages, including the absorption of a large part of the solar spectrum and highly efficient carrier extraction. With the incorporation of copper as the co-catalyst, the devices exhibit a Faradaic efficiency of about 19 % for the 8e(-) photoreduction to CH4 at -1.4 V vs Ag/AgCl, a value that is more than thirty times higher than that for the 2e(-) reduced CO (ca. 0.6 %).

A New MAC Address Spoofing Detection Technique Based on Random Forests.

Media access control (MAC) addresses in wireless networks can be trivially spoofed using off-the-shelf devices. The aim of this research is to detect MAC address spoofing in wireless networks using a hard-to-spoof measurement that is correlated to the location of the wireless device, namely the received signal strength (RSS). We developed a passive solution that does not require modification for standards or protocols. The solution was tested in a live test-bed (i.e., a wireless local area network with the aid of two air monitors acting as sensors) and achieved 99.77%, 93.16% and 88.38% accuracy when the attacker is 8-13 m, 4-8 m and less than 4 m away from the victim device, respectively. We implemented three previous methods on the same test-bed and found that our solution outperforms existing solutions. Our solution is based on an ensemble method known as random forests.

Epitaxial Bi2 FeCrO6 Multiferroic Thin Film as a New Visible Light Absorbing Photocathode Material.

Ferroelectric materials have been studied increasingly for solar energy conversion technologies due to the efficient charge separation driven by the polarization induced internal electric field. However, their insufficient conversion efficiency is still a major challenge. Here, a photocathode material of epitaxial double perovskite Bi(2) FeCrO(6) multiferroic thin film is reported with a suitable conduction band position and small bandgap (1.9-2.1 eV), for visible-light-driven reduction of water to hydrogen. Photoelectrochemical measurements show that the highest photocurrent density up to -1.02 mA cm(-2) at a potential of -0.97 V versus reversible hydrogen electrode is obtained in p-type Bi(2) FeCrO(6) thin film photocathode grown on SrTiO(3) substrate under AM 1.5G simulated sunlight. In addition, a twofold enhancement of photocurrent density is obtained after negatively poling the Bi(2) FeCrO(6) thin film, as a result of modulation of the band structure by suitable control of the internal electric field gradient originating from the ferroelectric polarization in the Bi(2) FeCrO(6) films. The findings validate the use of multiferroic Bi(2) FeCrO(6) thin films as photocathode materials, and also prove that the manipulation of internal fields through polarization in ferroelectric materials is a promising strategy for the design of improved photoelectrodes and smart devices for solar energy conversion.

High efficiency solar-to-hydrogen conversion on a monolithically integrated InGaN/GaN/Si adaptive tunnel junction photocathode.

H2 generation under sunlight offers great potential for a sustainable fuel production system. To achieve high efficiency solar-to-hydrogen conversion, multijunction photoelectrodes have been commonly employed to absorb a large portion of the solar spectrum and to provide energetic charge carriers for water splitting. However, the design and performance of such tandem devices has been fundamentally limited by the current matching between various absorbing layers. Here, by exploiting the lateral carrier extraction scheme of one-dimensional nanowire structures, we have demonstrated that a dual absorber photocathode, consisting of p-InGaN/tunnel junction/n-GaN nanowire arrays and a Si solar cell wafer, can operate efficiently without the strict current matching requirement. The monolithically integrated photocathode exhibits an applied bias photon-to-current efficiency of 8.7% at a potential of 0.33 V versus normal hydrogen electrode and nearly unity Faradaic efficiency for H2 generation. Such an adaptive multijunction architecture can surpass the design and performance restrictions of conventional tandem photoelectrodes.