A Comparison of Sperm Motility Between Fertile and Infertile Males

Background: To determine the sperm motility of proven fertile males and compare this with that of infertile males. Methods: The study design was cross-sectional comparative and was carried out at Islamic International Medical College Rawalpindi and its attached Railway hospital and Islamabad Clinic Serving Infertile Couples Islamabad, from June 2005 to July 2006. Fifty healthy fertile males were selected and their sperm motility was determined with the latest Makler’s chamber, while another 50 infertile males were recruited as controls. The sampling technique used was convenience non-probability. Inclusion criterion for proven fertile males was pregnancy achieved within one year of marriage with successful coituses. In case of infertile males it was failure to achieve pregnancy without the use of assisted reproductive techniques, with no infertility factors in the female partner. The semen samples were obtained at the laboratory after 3 to 4 days of sexual abstinence with clear written and oral instructions given to the subjects before the collection of the sample. Results: The infertile group was found to be statistically older than the proven fertile group i.e. (36.60 versus 31.32 years). Proven fertile group showed significantly higher motility (60.32 ± 10.80%) and progressive motility (14.32 ± 8.31%) than the infertile male group. Conclusion: Sperm motility is useful in in-vivo situation to find males having a greater possibility of infertility problem. More studies with a larger sample size are required to establish a cut-off value in the local population

Improving Growth and Productivity of Oleiferous Brassicas under Changing Environment: Significance of Nitrogen and Sulphur Nutrition, and Underlying Mechanisms

Mineral nutrients are the integral part of the agricultural systems. Among important plant nutrients, nitrogen (N) and sulphur (S) are known essential elements for growth, development, and various physiological functions in plants. Oleiferous brassicas (rapeseed and mustard) require higher amounts of S in addition to N for optimum growth and yield. Therefore, balancing S-N fertilization, optimization of nutrient replenishment, minimization of nutrient losses to the environment, and the concept of coordination in action between S and N could be a significant strategy for improvement of growth and productivity of oleiferous brassicas. Additionally, positive interaction between S and N has been reported to be beneficial for various aspects of oilseed brassicas. The current paper updates readers on the significance of N and S for the improvement of plant growth, development, and productivity in detail. In addition, S-N nutrition-mediated control of major plant antioxidant defense system components involved in the removal and/or metabolism of stress-induced/generated reactive oxygen species in plants (hence, the control of plant growth, development, and productivity) has been overviewed

EXAMINING THE EFFECT OF ETHICAL LEADERSHIP ON GREEN WORK OUTCOMES: A MODERATED MEDIATION ANALYSIS

The current study examines the direct effect of ethical leadership (EL) on employee green commitment (EGC) and the indirect effect on employee green innovative work behavior (EGIWB). It also tested the moderating effect of employee green knowledge (EGK) in the relationship between EL and EGC. Data were collected from 359 employees working in the manufacturing sector of Pakistan. Time lagged and conveniences sampling technique was adopted. The statistical results showed that EL was positively related to EGC. EGC enhances the EGIWB. Moreover, results showed that EGK moderates the relationship between EL and EGC. Such that employees having high green knowledge have more inclination towards green commitment. The results also showed that EL enhances EGIWB via EGC. Moderated mediation results also showed that EGK strengthens the indirect relationship between EL and EGIWB. Result depicted that employee having high green knowledge shows more green innovative work behavior via increased green commitment. The study brings important practical implications for top and middle managers and addresses their concerns about green practices and green innovations in their firms

Potassium-induced alleviation of salinity stress in Brassica campestris L.

Salinity is an important abiotic factor that adversely affects major agricultural soils of the world and hence limits crop productivity. An optimum mineral-nutrient status of plants plays critical role in determining plant tolerance to various stresses. A pot experiment was conducted on mustard (Brassica campestris L.) to study the protective role of added potassium (K, 40 mg kg-1 soil) against salinity-stress (0, 40 and 80 mM NaCl)-induced changes in plant growth, photosynthetic traits, ion accumulation, oxidative stress, enzymatic antioxidants and non-enzymatic antioxidants at 30 days after sowing. Increasing NaCl levels decreased the growth, photosynthetic traits and the leaf ascorbate and glutathione content but increased the leaf ion accumulation and oxidative stress, and the activity of antioxidant enzymes. In contrast, K-nutrition improved plant growth, photosynthetic traits, activity of antioxidant enzymes and the ascorbate and glutathione content, and reduced ion accumulation and oxidative stress traits in the leaves, more appreciably at 40 mM than at 80 mM NaCl. The study illustrates the physiological and biochemical basis of K-nutrition-induced NaCl tolerance in mustard as a means to achieving increased crop productivity in a sustainable way.Authors are grateful to Hamdard National Foundation (HNF), New Delhi, India for financial assistance for the work. Authors sincerely thank to Dr. Ali Qadar of Central Soil Salinity Research Institute (CSSRI), ICAR, Karnal, Haryana (India) for his valuable critical comments on the second version of this manuscript, and colleagues and staffs at Department of Botany, Hamdard University, New Delhi, for their kind support and encouragements.publishe

The cientificWorldJOURNAL Review Article Improving Growth and Productivity of Oleiferous Brassicas under Changing Environment: Significance of Nitrogen and Sulphur Nutrition, and Underlying Mechanisms

Mineral nutrients are the integral part of the agricultural systems. Among important plant nutrients, nitrogen (N) and sulphur (S) are known essential elements for growth, development, and various physiological functions in plants. Oleiferous brassicas (rapeseed and mustard) require higher amounts of S in addition to N for optimum growth and yield. Therefore, balancing S-N fertilization, optimization of nutrient replenishment, minimization of nutrient losses to the environment, and the concept of coordination in action between S and N could be a significant strategy for improvement of growth and productivity of oleiferous brassicas. Additionally, positive interaction between S and N has been reported to be beneficial for various aspects of oilseed brassicas. The current paper updates readers on the significance of N and S for the improvement of plant growth, development, and productivity in detail. In addition, S-N nutrition-mediated control of major plant antioxidant defense system components involved in the removal and/or metabolism of stress-induced/generated reactive oxygen species in plants (hence, the control of plant growth, development, and productivity) has been overviewed

Protection of growth and photosynthesis of Brassica juncea genotype with dual type sulfur transport system against sulfur deprivation by coordinate changes in the activities of sulfur metabolism enzymes and cysteine and glutathione production

Mustard (Brassica juncea L. Czern and Coss.) cvs. Pusa Jai Kisan (with low-affinity S transporter (LAT) system) and Pusa Bold (with dual, low- and high-affinity transporters (LAT + HAT) system) were supplied with 0 or 1 mM S in hydroponics culture, and the coordinate changes in growth traits (plant dry weight and leaf area), photosynthetic traits (photosynthetic rate, intercellular CO2, F v/F m, and chlorophyll content), activities of key enzymes of sulfur metabolism, such as ATP-sulfurylase (ATP-S), serine acetyltransferase (SAT), and glutathione reductase (GR), and the contents of cysteine (Cys) and glutathione (GSH) were studied in 30 days after sowing. The results showed that cv. Pusa Jai Kisan was more sensitive to S deprivation than cv. Pusa Bold. In cv. Pusa Jai Kisan, S deprivation resulted in a stronger decrease of plant growth and photosynthetic traits, Cys and GSH contents, and a notable decline in activity of ATP-S. S deprivation up-regulated GR activity to a greater extent in cv. Pusa Bold. In contrast, despite the activity of SAT, an enzyme involved in the final step of Cys biosynthesis, was increased in cv. Pusa Jai Kisan stronger than in cv. Pusa Bold under S-deprivation, it could not be translated into the increase in Cys and, thus, GSH contents and a consequent improvement in growth and photosynthesis. The study demonstrated that cv. Pusa Bold (with LAT + HAT) can be a promising cultivar for activation of Cys and/or GSH biosyntheses and increased plant tolerance to S-deprivation conditions.NAA is grateful to Council of Scientific and Industrial Research (CSIR-EMR), India, for providing fellowship in the form of Research Associateship (9/112(0401)2K8-EMR-I).publishe

Privacy-aware relationship semantics–based XACML access control model for electronic health records in hybrid cloud

State-of-the-art progress in cloud computing encouraged the healthcare organizations to outsource the management of electronic health records to cloud service providers using hybrid cloud. A hybrid cloud is an infrastructure consisting of a private cloud (managed by the organization) and a public cloud (managed by the cloud service provider). The use of hybrid cloud enables electronic health records to be exchanged between medical institutions and supports multipurpose usage of electronic health records. Along with the benefits, cloud-based electronic health records also raise the problems of security and privacy specifically in terms of electronic health records access. A comprehensive and exploratory analysis of privacy-preserving solutions revealed that most current systems do not support fine-grained access control or consider additional factors such as privacy preservation and relationship semantics. In this article, we investigated the need of a privacy-aware fine-grained access control model for the hybrid cloud. We propose a privacy-aware relationship semantics–based XACML access control model that performs hybrid relationship and attribute-based access control using extensible access control markup language. The proposed approach supports fine-grained relation-based access control with state-of-the-art privacy mechanism named Anatomy for enhanced multipurpose electronic health records usage. The proposed (privacy-aware relationship semantics–based XACML access control model) model provides and maintains an efficient privacy versus utility trade-off. We formally verify the proposed model (privacy-aware relationship semantics–based XACML access control model) and implemented to check its effectiveness in terms of privacy-aware electronic health records access and multipurpose utilization. Experimental results show that in the proposed (privacy-aware relationship semantics–based XACML access control model) model, access policies based on relationships and electronic health records anonymization can perform well in terms of access policy response time and space storage

Thermal-aware resource allocation in earliest deadline first using fluid scheduling

Thermal issues in microprocessors have become a major design constraint because of their adverse effects on the reliability, performance and cost of the system. This article proposes an improvement in earliest deadline first, a uni-processor scheduling algorithm, without compromising its optimality in order to reduce the thermal peaks and variations. This is done by introducing a factor of fairness to earliest deadline first algorithm, which introduces idle intervals during execution and allows uniform distribution of workload over the time. The technique notably lowers the number of context switches when compare with the previous thermal-aware scheduling algorithm based on the same amount of fairness. Although, the algorithm is proposed for uni-processor environment, it is also applicable to partitioned scheduling in multi-processor environment, which primarily converts the multi-processor scheduling problem to a set of uni-processor scheduling problem and thereafter uses a uni-processor scheduling technique for scheduling. The simulation results show that the proposed approach reduces up to 5% of the temperature peaks and variations in a uni-processor environment while reduces up to 7% and 6% of the temperature spatial gradient and the average temperature in multi-processor environment, respectively

On the Feature Selection Methods and Reject Option Classifiers for Robust Cancer Prediction

Cancer is the second leading cause of mortality across the globe. Approximately 9.6 million people are estimated to have died due to cancer disease in 2019. Accurate and early prediction of cancer can assist healthcare professionals to devise timely therapeutic innervations to control sufferings and the risk of mortality. Generally, a machine learning (ML) based predictive system in healthcare uses data (genetic profile or clinical parameters) and learning algorithms to predict target values for cancer detection. However, optimization of predictive accuracy is an important endeavor for accurate decision making. Reject Option (RO) classifiers have been used to improve the predictive accuracy of classifiers for cancer like complex problems. In a gene profile all of the features are not important and should be shaved off. ML offers different techniques with their own methodology for feature selection (FS) and the classification results are dependent on the datasets each having its own distribution and features. Therefore, both FS methods and ML algorithms with RO need to be considered for robust classification. The main objective of this study is to optimize three parameters (learning algorithm, FS method and rejection rate) for robust cancer prediction rather than considering two traditional parameters (learning algorithm and rejection rate). The analysis of different FS methods (including t-Test, Las Vegas Filter (LVF), Relief, and Information Gain (IG)) and RO classifiers on different rejection thresholds is performed to investigate the robust predictability of cancer. The three cancer datasets (Colon cancer, Leukemia and Breast cancer) were reduced using different FS methods and each of them were used to analyze the predictability of cancer using different RO classifiers. The results reveal that for each dataset predictive accuracies of RO classifiers were different for different FS methods. The findings based on proposed scheme indicate that, the ML algorithms along with their dependence on suitable FS methods need to be taken into consideration for accurate prediction

Porous and highly responsive polymeric fabricated nanometrices for solubility enhancement of acyclovir; characterization and toxicological evaluation

Solubility is one of the major factors which affects several therapeutic mioeties in terms of their therapeutic efficacy. In the current study, we presented a porous and amorphous nanometrices system for the enhancement of the solubility of acyclovir. The polymeric network was fabricated by crosslinking polyethylene glycol-6000, polycaprolactone, and β-cyclodextrin with methacrylic acid by optimizing free radical polymerization technique using methylene bisacrylamide as a crosslinking agent. The formulated nanometrices were then characterized by zetasizer, FTIR, PXRD, Scanning electron microscopy, Thermogravimetric analysis, swelling, sol-gel fraction, drug loading, stability, solubility, and in-vitro dissolution analysis. Since the formulated system has to be administered orally, therefore to determine the in-vivo biocompatibility, nanometrices were administered orally to experimental animals. SEM images provided a rough and porous structure while PXRD showed an amorphous diffractogram of the unloaded and loaded nanometrices. Moreover, the particle size of the optimum loaded formulation was 25 nm higher than unloaded nanometrices due to the repulsion of the loaded drug. A significant loading of the drug with enhanced solubility and dissolution profiles was observed for the poorly soluble drug. The dissolution profile was quite satisfactory as compared to the marketed brand of drug which depicted that the solubility of the drug has been enhanced. Toxicity study conducted on rabbits confirmed the biocompatibility of the nanometrices. The systematic method of preparation, enhanced solubility and high dissolution profile of the formulated nanometrices may be proved as a promising technique to enhance the solubility of poorly aqueous soluble therapeutic agents