Dataset on the Mediterranean soils from the coastal region of the Lattakia governorate, Syria

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Effect of pre-harvest application of salicylic acid, potassium silicate, and calcium chloride, on storability and quality attributes of table grape

Pre-harvest application of potassium silicate, calcium chloride and salicylic acid as spraying treatments is a promising strategy for the management of fruit quality and exhibits a high potential in controlling post-harvest losses of horticultural crops. The aim of this study was to investigate the storability of ‘ARAA18’ cultivar after some pre-harvest treatments that were applied during two consecutive growing seasons. The ‘ARRA 18’ table grape variety is one of the ‘ARRA’ group varieties that have been recently introduced to Egypt. Treatments were applied as foliar sprays at three different stages during the growing season before harvest. The plants were sprayed with potassium silicate (K2SiO3), salicylic acid, and calcium chloride, while untreated vine trees sprayed with water served as control. Mature clusters were harvested, then placed in carton containers and stored in cold storage at 0±1 °C to study the storability of ‘ARRA18’. Records of physical and chemical quality parameters were taken at 7-day intervals. All treatments reduced weight loss, berry softening and decay incidence comparing to control under storage conditions. K2SiO3 generally showed the highest significant effect compared to other treatments and control. Hence, the use of (K2SiO3) at both applied concentrations and (SA) at 100 ppm, significantly proved to be the most effective treatments in keeping the overall quality of stored grapes

Structural, Magnetic and Electrical Properties of Co-Doped Barium Monoferrite BaFe2O4

Cobalt-substituted barium monoferrite with theformula BaCoxFe2-xO4 (x = 0.0 – 0.4, step 0.1) has been preparedthrough the sol-gel autocombustion method. Phase purity forprepared samples sintered at 700 and 1050 ̊C was analyzed byX-ray diffraction (XRD) patterns that indicated the formationof the typical orthorhombic phase for the samples. Fouriertransforminfrared (FTIR) spectroscopy was used to investigatethe effect of cobalt doping on the vibrational modes of thestudied samples. Scherrer and Williamson-Hall formulae wereused to define the microstrian and the crystallite size being inthe range of 44.1 to 59.7 nm, which was further confirmed withtransmission electron microscopy (TEM) images. Magneticcharacteristics including magnetic saturation and coercivitywere obtained from hysteresis loops traced using vibratingsample magnetometry (VSM). Magnetic properties werecorrelated with the composition of the prepared samples.Finally, dielectric measurements were operated to furtherconfirm the structural and magnetic analysis

Heart patient health monitoring system using invasive and non-invasive measurement

The abnormal heart conduction, known as arrhythmia, can contribute to cardiac diseases that carry the risk of fatal consequences. Healthcare professionals typically use electrocardiogram (ECG) signals and certain preliminary tests to identify abnormal patterns in a patient’s cardiac activity. To assess the overall cardiac health condition, cardiac specialists monitor these activities separately. This procedure may be arduous and time-intensive, potentially impacting the patient’s well-being. This study automates and introduces a novel solution for predicting the cardiac health conditions, specifically identifying cardiac morbidity and arrhythmia in patients by using invasive and non-invasive measurements. The experimental analyses conducted in medical studies entail extremely sensitive data and any partial or biased diagnoses in this field are deemed unacceptable. Therefore, this research aims to introduce a new concept of determining the uncertainty level of machine learning algorithms using information entropy. To assess the effectiveness of machine learning algorithms information entropy can be considered as a unique performance evaluator of the machine learning algorithm which is not selected previously any studies within the realm of bio-computational research. This experiment was conducted on arrhythmia and heart disease datasets collected from Massachusetts Institute of Technology-Berth Israel Hospital-arrhythmia (DB-1) and Cleveland Heart Disease (DB-2), respectively. Our framework consists of four significant steps: 1) Data acquisition, 2) Feature preprocessing approach, 3) Implementation of learning algorithms, and 4) Information Entropy. The results demonstrate the average performance in terms of accuracy achieved by the classification algorithms: Neural Network (NN) achieved 99.74%, K-Nearest Neighbor (KNN) 98.98%, Support Vector Machine (SVM) 99.37%, Random Forest (RF) 99.76 % and Naïve Bayes (NB) 98.66% respectively. We believe that this study paves the way for further research, offering a framework for identifying cardiac health conditions through machine learning techniques

High SARS CoV2 antibody-prevalence among health care workers with variable exposure to COVID-19 patients: A cross-sectional university hospital study.

Background: During the COVID-19 pandemic, the pattern of medical services changed to minimize transmission to health care workers (HCWs) or hospitalized patients. Despite the care of COVID-19 patients in a special ward, new cases are accidentally discovered. This study aimed at determining the antibody seroprevalence among asymptomatic HCWs and the associated risks. Methods: The study involved 190 participants, including physicians, nurses, technicians, and administrative staff. All were inquired for sociodemographic, specialty, previous isolation, and previous infection, and their blood was tested for SARS-CoV2 antibody. Results: Of 190 HCWs; 72,1% were females, the mean age was 32.6±7.9 years, 10.5% were smokers, and 15.8% reported co-morbid illness. SARS CoV2 antibodies were found in 68 (35.8%); being IgG, IgM and both IgM and IgG in 47 (69.1%), 10 (14.7%) and 11 (16.2%) participants respectively. The prevalence was higher (47.6%) among HCWs of the COVID unit, [OR=1.7 (95% CI: 0.69-4.3)] and HCWs with previous COVID-19, OR:1.61 (95% CI:0.88-2.94). The prevalence was significantly lower among smokers (p=0.049), OR:0.29 (95% CI:0.08-1.01), and significantly higher in HCWs who recalled cough (p=0.036) OR: 1.97 (95% CI: 1.05-3.69). The likelihood of antibody seropositivity increased in technicians [OR:2.02 (95% CI: 0.92-4.44)], followed by physicians [OR:1.7 (95% CI: 0.7-4.33)] while the odds ratio was low among nurses [OR:0.58 (95% CI: 0.32-1.07). Conclusion: A considerable proportion of antibody positive HCWs had evidence of past SARS CoV2. Provision of adequate personal protective equipment and periodic screening of HCWs are urgently needed to lessen the transmission within the health care settings

Clear Aligner Therapy Concerns: Addressing Discrepancies Between Digitally Anticipated Outcomes and Clinical Ground Realities

Expeditious strides in the fields of biomaterials, computer-aided design, and manufacturing have catapulted clear aligner therapy (CAT) to become a comprehensive orthodontic treatment modality. The efficiency of achieving planned tooth movement with clear aligners is a significant consideration while setting up the final treatment goals, as well as calculating treatment times and costs based on the available evidence. Contemporary research outcomes confirm that one of the most commonly reported clinical concerns with CAT is the discrepancy between the prescribed outcome in the digital treatment plan and the clinically achieved outcome from a given series of aligners. Inaccurate prediction of tooth movements may not only lead to a prolonged duration of aligner treatment with an additional need for refinement strategies; but it may also cause other concerns, such as patient burnout and increased potential for relapse. The authors of this paper have elucidated some of the critical elements that may help address this discrepancy between digitally prescribed and clinical outcomes based on an evidence-based approach with regard to the predictability and accuracy of CAT. A strong diagnostic acumen, judicious case selection, solid biomechanical understanding of various types of orthodontic tooth movements, a research framework that keeps pace with technological and material developments and provides evidence-based knowledge of the limitations of CAT; and above all, the ability of the clinician to continually innovate as per different clinical scenarios, all contribute to attaining treatment predictability, efficacy, and efficiency with CAT

Arbitration in Islamic banking: Exploring legal and practical implications for dispute resolution

Dispute resolution in Islamic banking presents unique legal and procedural challenges due to the dual requirement of compliance with national laws and Islamic Sharia principles. This study aims to evaluate the legal and practical effectiveness of arbitration in resolving Islamic banking disputes, particularly in terms of efficiency, compliance with Sharia, and institutional trust. A qualitative approach was employed, based on semi-structured interviews with 12 domain experts, including Islamic banking professionals, arbitrators, legal advisors, and Sharia scholars, each with 10–25 years of experience in relevant fields.The findings indicate that 83% of respondents (10 out of 12) believe arbitration is more efficient than litigation in Islamic banking disputes, particularly in terms of speed and confidentiality. 75% of participants identified the lack of codified Sharia-compliant arbitration frameworks as a major limitation to broader adoption. Meanwhile, 67% emphasized the absence of a unified Sharia Supervisory Board as a critical institutional gap affecting arbitration legitimacy. Furthermore, 58% of experts pointed to weak trust in arbitration outcomes among financial institutions as the key reason arbitration clauses are often excluded from contracts.Despite these barriers, 92% of respondents agreed that arbitration has high potential to resolve Islamic banking disputes effectively if institutional and legislative reforms are implemented. The study recommends establishing standardized arbitration protocols, enhancing regulatory oversight, and developing Sharia-aligned legal infrastructure.These insights contribute to the broader discourse on Islamic finance governance and offer practical recommendations for policymakers, arbitration centers, and financial institutions seeking to enhance dispute resolution mechanisms in line with Sharia principles. AcknowledgmentThe authors are thankful to the Deanship of Graduate Studies and Scientific Research at the University of Bisha for supporting this work through the Fast-Track Research Support Program