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The catastrophic environmental, life and monetary losses concomitant to the hazardous cargo accidents have remained a matter of critical concern for the maritime transportation officials. The factors that instigate these accidents while dealing with hazardous cargo in a port environment requires rigorous analysis and evaluation, which still remains in its infancy. In accord to these prevailing issues, this study focusses on the assessment of multifactor risks associated with the dealing of hazardous cargos inside a port. The methodology adopted is the amalgamation of expert judgment and literature review for the identification of factors and developing their causal relationship, while Bayesian Network (BN) for the inference, which was based on 348 past accident reports from the year 1990 to 2018. The results indicate that under normal circumstances, the probability of an accident with considerable consequences is 59.8, where human and management were found to be the highest contributing factors. Setting evidence at the environment and pollution accident to occur, the incidence probability of the “management” is raised by 7.06%. A sensitivity analysis was conducted to determine the most critical factors for the hazardous cargo accident. This study reveals that in order to evade the hazardous cargo accidents and curtail severity of the consequences, the port authorities, concerned government departments and other related institutions should pay specific attention to the qualification, training and attitude of the involved workforce. Moreover, the development and implementation of stringent safety protocols was also revealed to have critical prominence. This study holds practical vitality for enhancing safety and mitigating risks associated to hazardous cargo dealing in a port.

Biodegradable natural polymers have been investigated extensively as the best choice for encapsulation and delivery of drugs. The research has attracted remarkable attention in the pharmaceutical industry. The shortcomings of conventional dosage systems, along with modified and targeted drug delivery methods, are addressed by using polymers with improved bioavailability, biocompatibility, and lower toxicity. Therefore, nanomedicines are now considered to be an innovative type of medication. This review critically examines the use of natural biodegradable polymers and their drug delivery systems for local or targeted and controlled/sustained drug release against fatal diseases.

This research work investigates some theoretical and semi-analytical results for the mathematical model of tuberculosis disease via derivative due to Caputo and Fabrizio. The concerned derivative involves exponential kernel and very recently it has been adapted for various applied problems. The required results are established by using some fixed point approach of Krasnoselskii and Banach. Further, by the use of iterative tools of Adomian decomposition and Laplace, the semi-analytical results are studied. Some graphical results are given with discussion.

The effect of deformation temperature on tensile behavior of Inconel 718 alloy has been studied by a self-developed in-situ high-temperature tensile stage inside a scanning electron microscopy at a temperature range from room temperature (RT) to 750 °C. The dynamic microstructure evolution and mechanical properties at different temperatures were performed and compared by the uniaxial tensile tests. The in-situ test results showed that the mechanical properties and fracture mechanisms of Inconel 718 alloy were sensitive to deformation temperatures. From RT to 650 °C, the yield stress and ultimate tensile strength decrease slightly and the tensile ductility is comparable. While up to 750 °C, the yield stress and ultimate tensile strength decrease significantly, the elongation and reduction of cross section also showed a significant decrease from RT to 750 °C. It was found that at RT and 650 °C, tensile cracks tended to initiate around the carbide particles and the triple junctions of grain boundaries, also propagated transgranularly; at 750 °C, the cracks initiated at grain boundaries and propagated intergranularly. In fact, with the increase in deformation temperature, the fracture mechanism transformed from the ductile transgranular fracture to the brittle intergranular fracture.

Shipbuilding is a complex and large-scale operation involving many intermediate products (blocks) and the frequent transfer of blocks among workshops and stockyards. The reasonable use of methods to complete the transfer scheduling of intermediate products is of great importance. In this paper, the blocks and the flat transporters are the research objects. Based on organizing the various logistical processes for blocks and the circulation process in the shipyard, we established a model that takes the task time window and other factors as constraints, and minimizes the sum of delay time and no-load time of flat transporters while satisfying the punctuality of scheduling tasks. Three conclusions are reached: (1)The flat transporter utilization rate is inversely related to the value of the objective function. The smaller the value of the objective function, the more the usage rate of a particular one (2) loading is the biggest obstacle to the overall working time of flat transporters, and a simple optimization model cannot solve this problem; and (3) based on the optimization model, the load efficiency of flat transporters can be improved, and the delivery time can be reduced.

Awareness about negative externalities generated by conventional farming is gaining momentum with consumers around the world, opting for alternatively, namely organically, produced food products. Information about consumers’ awareness is an essential element for farmers and marketing agencies to successfully plan production that can capture a greater market share. This study discusses effective factors influencing consumers’ awareness about the benefits of organic food in the United Arab Emirates. Sample data and ordinary least square (OLS) regression techniques are applied to delineate factors influencing consumers’ awareness about organic food. The results from this regression analysis highlight the importance of specific socioeconomic determinants that change awareness about organic food products in United Arab Emirates (UAE) households. This study finds that awareness about organic food is influenced more effective factors such as gender, nationality, and education as well as income, occupation and age. These research findings apply to other economies and societies that have an increasing per capita spending on organic food, but also where people are highly sensitive to information provided about organic food. Therefore, these results are important to these research beneficiaries including food marketing planners, researchers, and agricultural and food policy makers.

pH responsive hydrogels have gained much attraction in biomedical fields. We have formulated ternary hydrogel films as a new carrier of drug. Polyelectrolyte complex of chitosan/guar gum/polyvinyl pyrrolidone cross-linked via sodium tripolyphosphate was developed by solution casting method. Fourier transform infrared spectroscopy, scanning electron microscopy and thermogravimetric analysis were conducted to examine the interactions between the polymeric chains, surface morphology and thermal stability, respectively. The swelling tests resulted that the swelling was reduced with the increase in the concentration of crosslinker due to the more entangled arrangement and less availability of pores in hydrogels. Ciprofloxacin hydrochloride was used as a model drug and its release in simulated gastric fluid, simulated intestinal fluid and phosphate buffer saline solution was studied. pH responsive behaviour of the hydrogels have subjected these hydrogels for drug release applications.

The Hindu Kush Himalaya region is experiencing rapid climate change with adverse impacts in multiple sectors. To put recent climatic changes into a long-term context, here we reconstructed the region’s climate history using tree-ring width chronologies of climate-sensitive Cedrus deodara and Pinus gerardiana . Growth-climate analysis reveals that the species tree-growth is primarily limited by moisture stress during or preceding the growing season, as indicated by a positive relationship between the chronology and precipitation and scPDSI, and a negative one with temperature. We have reconstructed 635 years (1384–2018 CE) of February–June precipitation using a robust climate reconstruction model that explains about 53% variance of the measured precipitation data. Our reconstruction shows several dry and wet episodes over the reconstruction period along with an increase in extreme precipitation events during recent centuries or years. Long, very wet periods were observed during the following years: 1392–1393, 1430–1433, 1456–1461, 1523–1526, 1685–1690, 1715–1719, 1744–1748, 1763–1767, 1803–1806, 1843–1846, 1850–1855, 1874–1876, 1885–1887, 1907–1909, 1921–1925, 1939–1944, and 1990–1992, while long dry periods were observed during the following years: 1398–1399, 1464–1472, 1480–1484, 1645–1649, 1724–1727, 1782–1786, 1810–1814, 1831–1835, 1879–1881, 1912–1918, 1981–1986, 1998–2003, and 2016–2018 CE. We found predominantly short-term periodicity cycles of 2.0, 2.2, 2.3, 2.4, 2.6–2.7, 2.9, 3.3, 4.8, 8.1–8.3, and 9.4–9.6 years in our reconstruction. Spatial correlation analyses reveal that our reconstruction is an effective representation of the precipitation variability in the westerly climate-dominated areas of Pakistan and adjacent regions. In addition to the influence of regional circulation systems like western disturbances, we found possible teleconnections between the precipitation variability in northern Pakistan and broader-scale climate modes or phases like AMO and ENSO. The study also highlights the prospects of tree-ring application to explore linkages between western disturbance, increasing intensity and frequency of extreme climate events, and analysis of long-term atmospheric circulation over the western Himalayan region.

Background: Thyroid hormones regulate energy homeostasis, lipid/glucose metabolism, and protein turnover. Chronic Hepatitis C Virus (HCV) infection is highly associated with autoimmune hypothyroidism, which may have profound metabolic implications. This study evaluates thyroid dysfunction and anti-thyroid peroxidase (anti-TPO) autoimmunity in HCV patients and explores its potential metabolic implications in a high-prevalence region. Methods: In this comparative cross-sectional study adhering to STROBE guidelines, we enrolled 100 PCR-confirmed chronic HCV patients and 100 age/gender-matched controls from District Peshawar, Pakistan. Serum TSH, fT3, fT4, and anti-TPO antibodies were quantified. Multivariable logistic regression, adjusted for age, gender, and viral load, was used to compute adjusted odds ratios (aOR) with 95% confidence intervals (CI). Results: Thyroid dysfunction affected 41% of HCV patients vs. 12% of controls (aOR 5.2, 95% CI 2.8–9.6, p < 0.001), predominantly hypothyroidism (29% overall; 18% overt, 11% subclinical). Anti-TPO positivity was 38% in HCV vs. 8% in controls (aOR 6.7, 95% CI 3.1–14.5, p < 0.001). Anti-TPO titers correlated positively with TSH (r = +0.62, p < 0.001) and inversely with fT3/fT4. Subgroup analysis showed higher dysfunction in patients aged ≥40 years (52% vs. 28%, p = 0.012) and viral load ≥ 106 IU/mL (48% vs. 32%, p = 0.041). We hypothesize that these findings may have significant metabolic implications, including impaired mitochondrial β-oxidation and insulin resistance. Conclusions: HCV infection is strongly associated with autoimmune hypothyroidism, which may amplify cardiometabolic risk. The paper has not explicitly identified metabolic parameters, including lipid profiles, indices of insulin resistance, and metabolomic signatures, and, therefore, any metabolic inferences are speculative and based on established thyroid and HCV pathophysiology. Routine thyroid screening pre- and post-DAA therapy is recommended, alongside metabolomic profiling to validate these proposed metabolic pathways.

Human gait identification is a biometric technique that permits recognizing an individual from a long distance focusing on numerous features such as movement, time, and clothing. This approach in particular is highly useful in video surveillance scenarios, where biometric systems allow people to be easily recognized without intruding on their privacy. In the domain of computer vision, one of the essential and most difficult tasks is tracking a person across multiple camera views, specifically, recognizing the similar person in diverse scenes. However, the accuracy of the gait identification system is significantly affected by covariate factors, such as different view angles, clothing, walking speeds, occlusion, and low-lighting conditions. Previous studies have often overlooked the influence of these factors, leaving a gap in the comprehensive understanding of gait recognition systems. This paper provides a comprehensive review of the most effective gait recognition methods, assessing their performance across various image source databases while highlighting the limitations of existing datasets. Additionally, it explores the influence of key covariate factors, such as viewing angle, clothing, and environmental conditions, on model performance. The paper also compares traditional gait recognition methods with advanced deep learning techniques, offering theoretical insights into the impact of covariates and addressing real-world application challenges. The contrasts and discussions presented provide valuable insights for developing a robust and improved gait-based identification framework for future advancements.