Effect of Feed Cycling on Specific Growth Rate, Condition Factor, Body Composition And Rna/Dna Ratio Of Cirrhinus mrigala.

A randomly selected 60 samples of Cirrhinus mrigala, fingerling sized, were collected from Qadria fish hatchery and farm, Matital road, Multan. Fish were divided into three groups namely, control, 5 and 10 days cyclic feeding group. Specific growth rate (% g day-1), condition factor (K), body composition andRNA/DNA ratio of individual specimen and of each group were calculated. It was found that there was highly significant effect of feed cycling on specific growth rate (P0.05) suggesting a compensatory growth which was independent of length of starvation. Feed cycling had marked effect (

Cross-layer MAC/routing protocol for reliable communication in Internet of Health Things

Internet of Health Things (IoHT) involves intelligent, low-powered, and miniaturized sensors nodes that measure physiological signals and report them to sink nodes over wireless links. IoHTs have a myriad of applications in e-health and personal health monitoring. Because of the data’s sensitivity measured by the nodes and power-constraints of the sensor nodes, reliability and energy-efficiency play a critical role in communication in IoHT. Reliability is degraded by the increase in packets’ loss due to inefficient MAC, routing protocols, environmental interference, and body shadowing. Simultaneously, inefficient node selection for routing may cause the depletion of critical nodes’ energy resources. Recent advancements in cross-layer protocol optimizations have proven their efficiency for packet-based Internet. In this article, we propose a MAC/Routing-based Cross-layer protocol for reliable communication while preserving the sensor nodes’ energy resource in IoHT. The proposed mechanism employs a timer-based strategy for relay node selection. The timer-based approach incorporates the metrics for residual energy and received signal strength indicator to preserve the vital underlying resources of critical sensors in IoHT. The proposed approach is also extended for multiple sensor networks, where sensor in vicinity are coordinating and cooperating for data forwarding. The performance of the proposed technique is evaluated for metrics like Packet Loss Probability, End-To-End delay, and energy used per data packet. Extensive simulation results show that the proposed technique improves the reliability and energy-efficiency compared to the Simple Opportunistic Routing protocol

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

Barriers and perceptions regarding code status discussion with families of critically ill patients in a tertiary care hospital of a developing country: A cross-sectional study

Background: In Asian societies including Pakistan, a complex background of illiteracy, different familial dynamics, lack of patient’s autonomy, religious beliefs, and financial constraints give new dimensions to code status discussion. Barriers faced by physicians during code status discussion in these societies are largely unknown.Aim: To determine the barriers and perceptions in discussion of code status by physicians.Design: Questionnaire-based cross-sectional study.Setting and participants: This study was conducted in the Department of Medicine of The Aga Khan University Hospital, Karachi, Pakistan. A total of 134 physicians who had discussed at least five code statuses in their lifetime were included.Results: A total of 77 (57.4%) physicians responded. Family-related barriers were found to be the most common barriers. They include family denial (74.0%), level of education of family (66.2%), and conflict between individual family members (66.2%). Regarding personal barriers, lack of knowledge regarding prognosis (44.1%), personal discomfort in discussing death (29.8%), and fear of legal consequences (28.5%) were the top most barriers. In hospital-related barriers, time constraint (57.1%), lack of hospital administration support (48.0%), and suboptimal nursing care after do not resuscitate (48.0%) were the most frequent. There were significant differences among opinions of trainees when compared to those of attending physicians.Conclusion: Family-related barriers are the most frequent roadblocks in the end-of-life care discussions for physicians in Pakistan. Strengthening communication skills of physicians and family education are the potential strategies to improve end-of-life care. Large multi-center studies are needed to better understand the barriers of code status discussion in developing countries

Variable parameters for a single exponential model of photovoltaic modules in crystalline-silicon

The correct approximation of parallel resistance (Rp) and series resistance (Rs) poses a major challenge for the single diode model of the photovoltaic module (PV). The bottleneck behind the limited accuracy of the model is the static estimation of resistive parameters. This means that Rp and Rs, once estimated, usually remain constant for the entire operating range of the same weather condition, as well as for other conditions. Another contributing factor is the availability of only standard test condition (STC) data in the manufacturer’s datasheet. This paper proposes a single-diode model with dynamic relations of Rp and Rs. The relations not only vary the resistive parameters for constant/distinct weather conditions but also provide a non-iterative solution. Initially, appropriate software is used to extract the data of current-voltage (I-V) curves from the manufacturer’s datasheet. By using these raw data and simple statistical concepts, the relations for Rp and Rs are designed. Finally, it is proved through root mean square error (RMSE) analysis that the proposed model holds a one-tenth advantage over numerous recently proposed models. Simultaneously, it is low complex, iteration-free (0 to voltage in maximum power point Vmpp range), and requires less computation time to trace the I-V curve

Ordering of droplets and light scattering in polymer dispersed liquid crystal films

We study the effects of droplet ordering in initial optical transmittance through polymer dispersed liquid crystal (PDLC) films prepared in the presence of an electrical field. The experimental data are interpreted by using a theoretical approach to light scattering in PDLC films that explicitly relates optical transmittance and the order parameters characterizing both the orientational structures inside bipolar droplets and orientational distribution of the droplets. The theory relies on the Rayleigh-Gans approximation and uses the Percus-Yevick approximation to take into account the effects due to droplet positional correlations.Comment: revtex4, 18 pages, 8 figure

Evaluation of allelopathic potential of some selected medicinal species

Laboratory trials were made to evaluate the allelopathic potential of selected medicinal species. The aqueous extracts bioassay on two test plants (wheat and pea) was carried out through filter paper method. Toxicity and non toxicity was assessed by recording their effects on germination and percentage growth of radicle and plumule of test plants. The trials were replicated three times in Randomized Complete Split Block Design. The data was analyzed by using software SPSS v II. The results suggested that Sonchus asper and Melilotus officinalis stimulate the growth of wheat (Triticum aestivum) up to 150% of plumule and 40% of radicle. These species had significantly enhanced effect on the percentage growth of test plant. The inhibitory effect was more on the wheat, by aqueous extractions of Sisymbrium irio, Cannabis sativus and Oxalis corniculata. The growth of wheat was more enhanced in the aqueous extractions of Gallium aperine and Ageratum conizoides, almost 150% of radicle. But the most inhibitory and retarded effect was observed in case of S. irio, O. corniculata, Rumex dentatus and Parthenium hysterophorus.Key words: Allelopathy, medicinal species, filter paper