The study of fluctuation of large pelagic stock (yellowfin tuna, skipjack tuna, longtail tuna, Narrow-barred Spanish mackerel) in order to optimum exploitation in the Persian Gulf & Oman sea

The study of fluctuation of large pelagic stock (yellowfin tuna, skipjack tuna, longtail tuna, Narrow-barred Spanish mackerel ) in order to optimum exploitation in the Persian Gulf & Oman sea This study was carried out from 2005-07 in order to acquire some biological characteristics and population dynamic parameters for stock management and responsible fisheries. Thunnus albacares (yellowfin tuna), katsuwonus pelamis (skipjack tuna), Thunnus tonggol (longtail tuna) and scomberomorus commerson (Narrow- barred Spanish mackerel) were sampled. In total, length frequency of 9345 specimens of yellowfin tuna were analyzed. Size range was 37-172 cm. Teleost fishes were the most dominant prey species observed in this study (42%), Occurrence of Potunus Pelagicus was found to be the second (28%).Sthenoteuthis oualaniensis (22%), Natosquilla (5%) and octopus (3%) also were identified in the gut content of the yellowfin tuna. Length of maturity (50%) of yellow fin tuna was estimated 77.2 cm and spawning season was started from May. 8443 specimens of skipjack with size range of 32-90 cm were sampled. 48% of food items were teleost fishes. Squid and shrimp were also identified. Spawning season was begun from June. Growth parameters & fishing mortalities of yellow fin tuna and skipjack tuna were also estimated. Size range if longtail tuna was from 26-125cm Length infinity was estimated 132.3 cm with growth parameter of 0.35 per year. In total 10451 specimens of narrow- barred Spanish mackerel were sampled. Size range was from 20-164 cm. Teleost fishes were the most dominant prey species observed in the study (91.3%). Crustaceans (0.6%) and Indian squid (0.2%) also were identified in the specimens. Length maturity (50%) was estimated 83.6cm

Growth performance and age composition of Salmo trutta caspius in Iranian part of Caspian Sea

The aim of this project is to study the growth and age structure in the Caspian trout, comparison with other coldwater species and check the trend of these parameters in recent years. This study was conducted during 2013 till 2015. Totally, 43 specimens for back calculation and 101 specimens for biometrical study of the Caspian trout have been caught in two month period. Biometric parameters such as length, weight and age of the fish were recorded. Base on Back calculation method in 1393, the average length of fish at ages 1, 2 and 3 years old were 18.98 ± 3.5, 30.5 ± 7.24 and 41.7 ± 9.1 cm. So these age groups are under the adult age and don’t approaching to near the beach and rivers for spawning behavior. Therefore, these length groups cannot be observed in catch composition. The result showed, the mean of gonad weight in this fish was about 11 percent of total weight and number of eggs per gram of gonad calculated about 10.8 numbers. Minimum age and maximum age of this species determined 4 years and 7 years (mean = 5.6) and the most frequency allocated to 5 age group and the frequency of 6 and 7 years has been remarkable. The average length of salmon was 69.2 ± 6.2 cm (minimum 57 and maximum 81 cm) and the average weight was measured 3323 ± 677 g (2400 to 5600 g) in the catch composition. Growth parameters such as k, L_∞ and ø’ was measured 0.18, 104 cm and 3.289 respectively. The amount of b for relation length and weight was 2.9 which imply negative allometry. L_∞ and growth coefficient (K) on the Caspian trout were acceptable range, that it shows good growth the fish in the sea water. Most of the fishes were catched from Cheshmehkileh River. As at present Shilat uses just the broods of the Tonekaboon region for restocking of this species, we recommend using the broods of the western region separately for rehabilitation of the stocks of this region

Biomass estimation of demersal resources in the Persian Gulf and Oman Sea by swept area method

Regarding to monitor of demersal resources in the Persian Gulf and Oman Sea, and also biomass and CPUA estimation of them, ten research cruises were carried out by using R/V Ferdows-1 equipped with bottom trawl, covering the area from 49º 00´ E in the west (north-west Persian Gulf) to 61º 25´ E in the east (borderline with Pakistan) from 2012 to 2014 The study area was stratified into 17 strata (A to Q) of which 10 strata (A to J) were in the Persian Gulf and 7 strata (K to Q) were in the Oman Sea, covering the depths of 10-50 m in the Persian Gulf and 10-100 m in the Oman Sea. A total of 316 stations were randomly selected and the biomass and CPUA were estimated by swept area method during this three years period, the strat A and B weren’t covered. The comparison between two regions indicated that the percentage of density of demersal fishes in the Persian Gulf during years 2012, 2013 and 2014 were 1.0, 1.4 and 1.6 times more than the Oman Sea and totally 50-60% of total biomass was found for the Persian Gulf. Also a comparison among 17 strata the highest biomass was found for K region (Sirik to Jask) in the Oman Sea in 2012 & 2014; and C region (Genaveh to Bordkhoon) in 2013 in the Persian Gulf. The same comparison was done for CPUA of commercial, non-commercial and total in both water bodies and it was found that in years 2012 to 2014 the region K (Sirik to Jask) in the Oman Sea and Stratum Q (Bersi to Gwatr) had the highest value of CPUA. On the contrary, the stratum M (Biahi to Galak estuary) showed the lowest value of biomass for both commercial and non-commercial fishes. With review the mean CPUA in different depth layers for years 2012, 2013 and 2014, it was concluded that in the Oman Sea with increasing the depth, the mean CPUA is decreased and the lowest CPUA belongs to depths of 30-50 m The comparison between commercial and non-commercial groups in both ecosystems, it concluded that the density of commercial species were higher than non-commercial ones; and for years 2009, 2010 and 2011 the commercial species consist of 63.4, 65.0 and 59.7 % of total biomass. In all years the Persian Gulf indicated higher values than the Oman Sea. The most abundant fishes were Rays, Ribbon fishes, Carangids, Grunts, Japanese threadfin bream, Lizardfish and Barracuda for both Persian Gulf and Oman Sea

An Automatic Clustering Technique for Query Plan Recommendation

Source Code of NSGA-II Optimized Density-based Clustering (NODC

An efficient automated incremental density-based algorithm for clustering and classification

Data clustering divides the datasets into different groups. Incremental Density-Based Spatial Clustering of Applications with Noise (DBSCAN) is a famous density-based clustering technique able to find the clusters of variable sizes and shapes. The quality of incremental DBSCAN results has been influenced by two input parameters: MinPts (Minimum Points) and Eps (Epsilon). Therefore, the parameter setting is one of the major problems of incremental DBSCAN. In the present article, an improved incremental DBSCAN accorded to Non-dominated Sorting Genetic Algorithm II (NSGA-II) has been presented to address the issue. The proposed algorithm adjusts the two parameters (MinPts and Eps) of the incremental DBSCAN via the iteration and the fitness functions to enhance the clustering precision. Moreover, our proposed method introduces suitable fitness functions for both labeled and unlabeled datasets. We have also improved the efficiency of the proposed hybrid algorithm by parallelization of the optimization process. The evaluation of the introduced method has been done through some textual and numerical datasets with different shapes, sizes, and dimensions. According to the experimental results, the proposed algorithm provides better results than Multi-Objective Particle Swarm Optimization (MOPSO) based incremental DBSCAN and a few well-known techniques, particularly regarding the shape and balanced datasets. Also, good speed-up can be reached with a parallel model compared with the serial version of the algorithm. © 2020 Elsevier B.V

Apelin�13 protects against memory impairment and neuronal loss, Induced by Scopolamine in male rats

The present study aimed to evaluate the effects of Apelin�13 on scopolamine�induced memory impairment in rats. Forty male rats were divided into five groups of eight. The control group received no intervention; the scopolamine group underwent stereotaxic surgery and received 3 mg/kg intraperitoneal scopolamine. The treatment groups additionally received 1.25, 2.5 and 5 µg apelin�13 in right lateral ventricles for 7 days. All rats (except the control group) were tested for the passive avoidance reaction, 24 h after the last drug injection. For histological analysis, hippocampal sections were stained with cresyl violet; synaptogenesis biochemical markers were determined by immunoblotting. Apelin�13 alleviated scopolamine�induced passive avoidance memory impairment and neuronal loss in the rats� hippocampus (P<0.001). The reduction observed in mean concentrations of hippocampal synaptic proteins (including neurexin1, neuroligin, and postsynaptic density protein 95) in scopolamine�treated animals was attenuated by apelin�13 treatment. The results demonstrated that apelin�13 can protect against passive avoidance memory deficiency, and neuronal loss, induced by scopolamine in male rats. Further experimental and clinical studies are required to confirm its therapeutic potential in neurodegenerative diseases. © 2021, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature

Using shapes of COVID-19 positive patient-specific trajectories for mortality prediction

Machine learning can be used to identify relevant trajectory shape features for improved predictive risk modeling, which can help inform decisions for individualized patient management in intensive care during COVID-19 outbreaks. We present explainable random forests to dynamically predict next day mortality risk in COVID -19 positive and negative patients admitted to the Mount Sinai Health System between March 1st and June 8th, 2020 using patient time-series data of vitals, blood and other laboratory measurements from the previous 7 days. Three different models were assessed by using time series with: 1) most recent patient measurements, 2) summary statistics of trajectories (min/max/median/first/last/count), and 3) coefficients of fitted cubic splines to trajectories. AUROC and AUPRC with cross-validation were used to compare models. We found that the second and third models performed statistically significantly better than the first model. Model interpretations are provided at patient-specific level to inform resource allocation and patient care

BEHRTDAY: dynamic mortality risk prediction using time-variant COVID-19 patient specific trajectories

Incorporating repeated measurements of vitals and laboratory measurements can improve mortality risk-prediction and identify key risk factors in individualized treatment of COVID-19 hospitalized patients. In this observational study, demographic and laboratory data of all admitted patients to 5 hospitals of Mount Sinai Health System, New York, with COVID-19 positive tests between March 1st and June 8th, 2020, were extracted from electronic medical records and compared between survivors and non-survivors. Next day mortality risk of patients was assessed using a transformer-based model BEHRTDAY fitted to patient time series data of vital signs, blood and other laboratory measurements given the entire patients’ hospital stay. The study population includes 3699 COVID-19 positive (57% male, median age: 67) patients. This model had a very high average precision score (0.96) and area under receiver operator curve (0.92) for next-day mortality prediction given entire patients’ trajectories, and through masking, it learnt each variable’s context

An interactive web-based application for Comprehensive Analysis of RNAi-screen Data

RNAi screens are widely used in functional genomics. Although the screen data can be susceptible to a number of experimental biases, many of these can be corrected by computational analysis. For this purpose, here we have developed a web-based platform for integrated analysis and visualization of RNAi screen data named CARD (for Comprehensive Analysis of RNAi Data; available at https://card.niaid.nih.gov). CARD allows the user to seamlessly carry out sequential steps in a rigorous data analysis workflow, including normalization, off-target analysis, integration of gene expression data, optimal thresholds for hit selection and network/pathway analysis. To evaluate the utility of CARD, we describe analysis of three genome-scale siRNA screens and demonstrate: (i) a significant increase both in selection of subsequently validated hits and in rejection of false positives, (ii) an increased overlap of hits from independent screens of the same biology and (iii) insight to microRNA (miRNA) activity based on siRNA seed enrichment

Contraceptive content shared on social media: an analysis of Twitter

Abstract Background Information on social media may affect peoples’ contraceptive decision making. We performed an exploratory analysis of contraceptive content on Twitter (recently renamed X), a popular social media platform. Methods We selected a random subset of 1% of publicly available, English-language tweets related to reversible, prescription contraceptive methods posted between January 2014 and December 2019. We oversampled tweets for the contraceptive patch to ensure at least 200 tweets per method. To create the codebook, we identified common themes specific to tweet content topics, tweet sources, and tweets soliciting information or providing advice. All posts were coded by two team members, and differences were adjudicated by a third reviewer. Descriptive analyses were reported with accompanying qualitative findings. Results During the study period, 457,369 tweets about reversible contraceptive methods were published, with a random sample of 4,434 tweets used for final analysis. Tweets most frequently discussed contraceptive method decision-making (26.7%) and side effects (20.5%), particularly for long-acting reversible contraceptive methods and the depot medroxyprogesterone acetate shot. Tweets about logistics of use or adherence were common for short-acting reversible contraceptives. Tweets were frequently posted by contraceptive consumers (50.6%). A small proportion of tweets explicitly requested information (6.2%) or provided advice (4.2%). Conclusions Clinicians should be aware that individuals are exposed to information through Twitter that may affect contraceptive perceptions and decision making, particularly regarding long-acting reversible contraceptives. Social media is a valuable source for studying contraceptive beliefs missing in traditional health research and may be used by professionals to disseminate accurate contraceptive information