Violations of basic rights of prisoners in conventional and Islamic law: theory and practice

In prisons, the convicted are most often unattended by the authority and therefore they become victim to abuses and maltreatment. Their basic rights as humans are being violated in most of the prisons. Although there have been a lot of laws and regulations upholding the rights of prisoners prevalent in the international community, it seems ineffective in protecting their rights in real life. This paper examines the problems of the prisoners in general and discloses the issue of human rights violation of prisoners. The paper particularly exposes problems in the prisons such as sexual abuse, mental and physical torturing, illegal enforcement of prison labour, overcrowding, poor education and health care initiations. With approaching the issues of the prisoners from a human rights perspective, the paper also explores the issues from an Islamic law viewpoint and attempts to provide a conceptual frame work of solutions. A critical and descriptive analytical approach is employed in this study

Soil Quality Variation under Different Land Use Types in Haramosh Valley, Gilgit, Pakistan

Soil quality is a fundamental component of environmental quality and impact of land use is also a keydetrimental factor in today’s rapid urbanization era. The study aims to evaluate the effects of different land-use type on selected soil quality indicators. Sixty soil samples were collected from various land use types, i.e, pasture, forest and agriculture from a depth of 0-15cm. Analysis of variance (ANOVA) showed that the land use type significantly affected the soil’s physical and chemical properties. The moisture content was significantly higher (p<0.001) in the pasture (41.7%) than the forest (26.2%) and lowest in agricultural land (14.4%). The soil pH was significantly higher or slightly alkaline for agriculture (7.8), while for pasture (6.5) and forest (6.1), it was found to be slightly acidic. Electric conductivity (EC) and bulk density (BD) did not vary significantly with land use type, but the EC followed the decreasing order: forest (203.7μS/cm) < pasture (235μS/cm) < agriculture (328.7μS/cm). The soil organic matter (SOM) and soil organic carbon (SOC) significantly (p<0.05) differed with land use type and found in the order: forest (3.0%, 1.3 %) > pasture land (2.9%, 1.2%) > arable land (2.5%, 1.1%). NO3-N, available P and exchangeable K did not vary significantly across land use types. However, mean values were higher for agriculture (10.2mg/kg, 4.5mg/kg, 66mg/kg) than forest (10mg/kg,3.5mg/kg, 60mg/kg) and pasture (9.8mg/kg, 4.3, 60.2mg/kg). Alpine soils are good ecological indicators because of vulnerability to environmental change, therefore, regular monitoring of soil properties along with carbon stocks is essential to maintain soil health, enhance agricultural productivity and sustain agroecosystems

An effective deep learning approach for the classification of Bacteriosis in peach leave

Bacteriosis is one of the most prevalent and deadly infections that affect peach crops globally. Timely detection of Bacteriosis disease is essential for lowering pesticide use and preventing crop loss. It takes time and effort to distinguish and detect Bacteriosis or a short hole in a peach leaf. In this paper, we proposed a novel LightWeight (WLNet) Convolutional Neural Network (CNN) model based on Visual Geometry Group (VGG-19) for detecting and classifying images into Bacteriosis and healthy images. Profound knowledge of the proposed model is utilized to detect Bacteriosis in peach leaf images. First, a dataset is developed which consists of 10000 images: 4500 are Bacteriosis and 5500 are healthy images. Second, images are preprocessed using different steps to prepare them for the identification of Bacteriosis and healthy leaves. These preprocessing steps include image resizing, noise removal, image enhancement, background removal, and augmentation techniques, which enhance the performance of leaves classification and help to achieve a decent result. Finally, the proposed LWNet model is trained for leaf classification. The proposed model is compared with four different CNN models: LeNet, Alexnet, VGG-16, and the simple VGG-19 model. The proposed model obtains an accuracy of 99%, which is higher than LeNet, Alexnet, VGG-16, and the simple VGG-19 model. The achieved results indicate that the proposed model is more effective for the detection of Bacteriosis in peach leaf images, in comparison with the existing models

Investigation on rheological properties of water-based novel ternary hybrid nanofluids using experimental and Taguchi method

This study presents the rheological behavior of water-based GO-TiO2 -Ag and rGO-TiO2 -Ag ternary-hybrid nanofluids. The impact of nanoparticles’ volumetric concentration and temperature on the rheological properties were studied. All experiments were performed under temperatures ranging from 25 to 50 ◦C in the solid volume concentration range of 0.5–0.00005%. The data optimization technique was adopted using the Taguchi method. The types of nanomaterials, concentration, temperature, and shear rate were chosen to optimize the viscosity and shear stress. The effect of shear stress, angular sweep, frequency sweep, and damping factor ratio is plotted. The experimental results demonstrated that the rheological properties of the ternary hybrid nanofluid depend on the ternary hybrid nanofluid’s temperature. The viscosity of ternary hybrid nanofluids (THNf) change by 40% for GO-TiO2 -Ag and 33% for rGO-TiO2 -Ag when temperature and shear rates are increased. All the ternary hybrid nanofluids demonstrated non-Newtonian behavior at lower concentrations and higher shear stress, suggesting a potential influence of nanoparticle aggregation on the viscosity. The dynamic viscosity of ternary hybrid nanofluid increased with enhancing solid particles’ volume concentration and temperature

Impact of opioid-free analgesia on pain severity and patient satisfaction after discharge from surgery: multispecialty, prospective cohort study in 25 countries

Background: Balancing opioid stewardship and the need for adequate analgesia following discharge after surgery is challenging. This study aimed to compare the outcomes for patients discharged with opioid versus opioid-free analgesia after common surgical procedures.Methods: This international, multicentre, prospective cohort study collected data from patients undergoing common acute and elective general surgical, urological, gynaecological, and orthopaedic procedures. The primary outcomes were patient-reported time in severe pain measured on a numerical analogue scale from 0 to 100% and patient-reported satisfaction with pain relief during the first week following discharge. Data were collected by in-hospital chart review and patient telephone interview 1 week after discharge.Results: The study recruited 4273 patients from 144 centres in 25 countries; 1311 patients (30.7%) were prescribed opioid analgesia at discharge. Patients reported being in severe pain for 10 (i.q.r. 1-30)% of the first week after discharge and rated satisfaction with analgesia as 90 (i.q.r. 80-100) of 100. After adjustment for confounders, opioid analgesia on discharge was independently associated with increased pain severity (risk ratio 1.52, 95% c.i. 1.31 to 1.76; P < 0.001) and re-presentation to healthcare providers owing to side-effects of medication (OR 2.38, 95% c.i. 1.36 to 4.17; P = 0.004), but not with satisfaction with analgesia (beta coefficient 0.92, 95% c.i. -1.52 to 3.36; P = 0.468) compared with opioid-free analgesia. Although opioid prescribing varied greatly between high-income and low- and middle-income countries, patient-reported outcomes did not.Conclusion: Opioid analgesia prescription on surgical discharge is associated with a higher risk of re-presentation owing to side-effects of medication and increased patient-reported pain, but not with changes in patient-reported satisfaction. Opioid-free discharge analgesia should be adopted routinely

Family-centered rounds in Pakistani pediatric intensive care settings: non-randomized pre- and post-study design

Background: Involvement of family in bedside rounds is one strategy to implement family-centered care to help families get clear information about their child, and be actively involved in decision-making about care. However in developing countries such as Pakistan, daily bedside rounds include the physician, residents, medical students and a nurse/technician. Parents are not currently a part of these rounds. Objective: To assess whether family-centered rounds improve parents’ and health care professionals’ satisfaction, decrease patient length of stay, and improve time utilization when compared to traditional practice rounds in a population with a low literacy rate, socioeconomic status, and different cultural values and beliefs. Design: A non-randomized before–after study design. Setting: A private hospital in Karachi, Pakistan. Participants: A convenience sample of 82 parents, whose children were hospitalized for a minimum of 48 h, and 25 health care professionals able to attend two consecutive rounds. Methods: During the before phase, traditional bedside rounds were practiced; and during after phase, family-centered rounds were practiced. Parents and health care professionals completed a questionnaire on the second day of rounds. An observational form facilitated data collection on length of stay and time utilization during. Results: Parents’ ratings during the family-centered rounds were significantly higher for some parental satisfaction items: evidence of team work (p = 0.007), use of simple language during the rounds (p = 0.002), feeling of inclusion in discussion at rounds (p = 0.03), decision making (p = 0.01), and preference for family-centered rounds (p = Conclusion: Parents were satisfied with both forms of rounds; however, they appeared to have a greater preference for family-centered rounds than health care professionals. Family-centered rounds were a resource for Pakistani parents, enabling direct communication with the medical team without impacting on the time required to complete rounds. Family-centered rounds may improve quality of care such as decreasing length of stay or preventing critical incidents

Synthesis and Characterization of Novel Ternary-Hybrid Nanoparticles as Thermal Additives

The performance of water as a heat transfer medium in numerous applications is limited by its effective thermal conductivity. To improve the thermal conductivity of water, herein, we report the development and thermophysical characterization of novel metal-metal-oxide-carbon-based ternary-hybrid nanoparticles (THNp) GO-TiO2-Ag and rGO-TiO2-Ag. The results indicate that the graphene oxide- and reduced graphene oxide-based ternary-hybrid nanoparticles dispersed in water enhance the base fluid (H2O) thermal conductivity by 66% and 83%, respectively, even at very low concentrations. Mechanisms contributing to this significant enhancement are discussed. The experimental thermal conductivity is plotted against the existing empirical hybrid thermal conductivity correlations. We found that those correlations are not suitable for the metal-metal-oxide-carbon combinations, calling for new thermal conductivity models. Furthermore, the rheological measurements of the nanofluids display non-Newtonian behavior, and the viscosity reduces with the increase in temperature. Such behavior is possibly due to the non-uniform shapes of the ternary-hybrid nanoparticles