Effect of cadmium chloride and ascorbic acid exposure on the vital organs of freshwater Cyprinid, Labeo rohita

The present study was carried out to evaluate the impact of sub lethal concentrations of heavy metal, cadmium chloride (CdCl2.H2O), ascorbic acid (vitamin C) and their combination on Labeo rohita. The effect was investigated on the basis of histopathological examinations of control and experimental groups exposed to heavy metal. The acute semi statistical toxicity test for L. rohita revealed 96 h LC50 value 22.92 mg L-1 for cadmium chloride (CdCl2.H2O). 215 fingerlings of L. rohita were exposed to three different experimental conditions for 96 h: 11.46 mg L-1 CdCl2.H2O, or 450 mg Kg-1 ascorbic acid or combination of both these doses. No alterations were observed in gill sections upon comparison between treated and untreated groups. Congestion in sinusoids, fatty change, an increase in Kupffer cells and intrahepatic lymphocytes was observed in CdCl2.H2O treated group. In kidney sections of heavy metal treated group, degeneration of the glomerular tissue, occlusion in tubular lumen and necrosis were observed. Similar changes but in less severe form, as described above, were observed in the fish exposed to combination of CdCl2.H2O and ascorbic indicating that ascorbic acid do detoxify the effect of heavy metal to some extant. Our results indicate that cadmium chloride (CdCl2.H2O), if present in fresh water bodies, may act as strong toxic agent for L. rohita.Keywords: Labeo rohita, cadmium chloride (CdCl2.H2O), ascorbic acid, histopatholog

Prognostic Factors for Decompressive Hemicraniectomy in Severe Traumatic Brain Injury Patients with Traumatic Mass Lesions: A Prospective Experience from a Developing Country

Objective:  To evaluate the prognostic factors affecting functional clinical outcomes in severe traumatic brain injury patients with traumatic mass lesions undergoing decompressive hemicraniectomy (DHC). Materials and Methods:  A prospective cohort of 85 patients of severe traumatic brain injury patients with traumatic mass lesions underwent a unilateral decompressive hemicraniectomy. Functional outcomes were assessed using the Glasgow Outcome Score at 28 days, 3 months, and 6 months. Bivariate analysis (chi-squared) was used to identify parameters that resulted in poor outcomes and multiple regression was used to identify independent factors predicting poor outcomes. Results:  85 patients were recruited. Functional outcomes were dichotomised as favourable (Glasgow Outcome Score of 4 – 5) and poor (Glasgow Outcome Score 1-3) and evaluated at 28 days, 3 and 6 months. A total of 59 patients expired (69.4%). Bivariate analysis revealed GCS 3 – 5 at presentation (P = 0.002), midline shift greater than 7.5mm (P < 0.001), the volume of the mass lesion more than 40ml (P = 0.006) resulted in a poor outcome. Age dichotomised to less than or more than 50 years bordered statistical significance (P = 0.063). Only GCS at presentation and midline shift were independent factors that predicted poor outcomes when controlling for covariates.  Conclusion:  Decompressive hemicraniectomy can be a lifesaving intervention in managing severe traumatic brain injury patients with traumatic mass lesions. However, its use needs to be employed judiciously.&nbsp

Acute kidney injury in lymphoma: a single centre experience

Background. Acute kidney injury (AKI) is a common but least studied complication of lymphoma. Objective. To determine the frequency and predictors of AKI in lymphoma and to study the impact of AKI on hospital stay and mortality. Methods. Retrospective review of medical records of hospitalized lymphoma patients aged ≥14 years between January 2008 and December 2011 was done. Results. Out of 365 patients, AKI was present in 31.8% (116/365). Multivariate logistic regression analysis showed that independent predictors for AKI included sepsis (odds ratio (OR) 3.76; 95% CI 1.83-7.72), aminoglycosides (OR 4.75; 95% CI 1.15-19.52), diuretics (OR 2.96; 95% CI 1.31-6.69), tumor lysis syndrome (OR 3.85; 95% CI 1.54-9.59), and R-CVP regimen (OR 4.70; 95% CI 1.20-18.36). AKI stages 2 and 3 was associated with increased hospital stay (OR 2.01; 95% CI 1.19-3.40). Conclusion. AKI was significantly associated with sepsis, aminoglycoside, diuretics, presence of tumor lysis syndrome, and use of R-CVP regimen. Presence of AKIN (Acute Kidney Injury Network) stages 2 and 3 AKI had increased hospital stay. AKI was also associated with increased mortality

Secondary School Teachers’ Journey from Self-Efficacy to Collective Efficacy

Education is perceived as a powerful agency, which instrument in bringing about the desired changes in the social, economic and cultural life of any nation. The whole process of education is shaped and molded by the human personality called the teacher. Teaching is a challenging profession and only those teachers can shoulder the heavy responsibilities of nation building, who are adequately prepared and have sound professional attitude. Self-efficacy is belief of teachers about their own potential, skills, pedagogy, developing learning school environment while living within the limited resources. And when it turns to expectations of other stakeholders like principal, students, society as a collective capability of a group of teachers to influence student achievement is refers as collective teachers-efficacy. This study aimed at to highlight the relation and changing paradigms from teachers’ self-efficacy to collective-efficacy. To achieve the set aim, survey research technique was adopted. Southern Punjab was the population of the study and target was selected by adopting multistage random sampling technique. Equal opportunity was given to both genders. Total sample of the study was 480 (principals were 30, teachers 150, and students 300). Three different research tool were developed out of which first research tool was for knowing the teachers’ self-efficacy as Teachers’ Sense of Efficacy Scale (TSES) which was developed by Tschannen-Moran and Woolfolk Hoy in 2001. Second research tool was of knowing the Collective Efficacy Scale (CE-Scale) developed by Goddard and Woolfolk Hoy (2004). Third research tool was Omnibus T-Scale (OTS) developed by Hoy in 2002. The analysis of the collected data was done by using Statistical Package for Social Sciences (SPSS) software version 21. Findings of the study shows that secondary school teachers are fully confident regarding their skills, competencies, pedagogy and ready to face the challenges. At the same time, their principals have shown strong trust on their teachers, but students’ opinion was different from the principals

Mathematica: Teaching Learning Process at Secondary School Level in Punjab

Technology becomes an integral part of academia. Computer or technology is rooted out from Mathematics. When it is said that 21st century is the century of technology, then how the field of education is remained away from technology. Modern science labs are technology oriented and in such a way the subject of Mathematics is also shifted on technology. Mathematics is not an integral part of daily routine life as well as playing a key role in the progress of science and technology. In the teaching learning process, technology-based teaching is the modern mode of teaching. Keeping in mind the same scenario, current study was conducted to highlight the concept of Mathematica (Mathematics and Information Technology) in the teaching learning process at secondary school level in Punjab province. Study aimed at to observe the technology role on the mathematics’ teaching at secondary school level. The study was quantitative by nature and descriptive approach was adopted. Self-developed questionnaire was applied as a research tool to get the data from the target sample through survey technique. Total targeted sample was 60 teachers who are teaching Mathematics at secondary school level and their 200 students. Findings of the study revealed that technology usage in the teaching learning process of mathematics enhance the understanding of the mathematical concepts many times

A Machine Learning-Based Anomaly Prediction Service for Software-Defined Networks

Software-defined networking (SDN) has gained tremendous growth and can be exploited in different network scenarios, from data centers to wide-area 5G networks. It shifts control logic from the devices to a centralized entity (programmable controller) for efficient traffic monitoring and flow management. A software-based controller enforces rules and policies on the requests sent by forwarding elements; however, it cannot detect anomalous patterns in the network traffic. Due to this, the controller may install the flow rules against the anomalies, reducing the overall network performance. These anomalies may indicate threats to the network and decrease its performance and security. Machine learning (ML) approaches can identify such traffic flow patterns and predict the systems’ impending threats. We propose an ML-based service to predict traffic anomalies for software-defined networks in this work. We first create a large dataset for network traffic by modeling a programmable data center with a signature-based intrusion-detection system. The feature vectors are pre-processed and are constructed against each flow request by the forwarding element. Then, we input the feature vector of each request to a machine learning classifier for training to predict anomalies. Finally, we use the holdout cross-validation technique to evaluate the proposed approach. The evaluation results specify that the proposed approach is highly accurate. In contrast to baseline approaches (random prediction and zero rule), the performance improvement of the proposed approach in average accuracy, precision, recall, and f-measure is (54.14%, 65.30%, 81.63%, and 73.70%) and (4.61%, 11.13%, 9.45%, and 10.29%), respectively