Scorpions of Sri Lanka (Arachnida: Scorpiones). Part III. \u3cem\u3eHeterometrus yaleensis\u3c/em\u3e sp. n. (Scorpionidae)

Heterometrus yaleensis sp. n. from Sri Lanka, Southern Province, Yale National Park is described and compared with other species of the genus. The presence of a unique dorsointernal carina on the pedipalp chela distinguishes H. yaleensis sp. n. from all other Heterometrus species. Additional information is provided on the taxonomy and distribution of the genus Heterometrus in Sri Lanka, fully complemented with color photos of specimens of both sexes of the new species, as well as of their habitat. In addition to external morphology and hemispermatophore, we also describe the karyotype of H. yaleensis sp. n. (2n=99)

DISTRIBUTION OF SNAKES IN HANTANA RANGE AND PERADENIYA UNIVERSITY PARK

Sri Lanka is blessed with a diverse serpentine fauna, and the island harbours 93 snakespecies in 46 genera and 26 families.Seven major habitat types namely Grasslands, Natural forest patches, Streams and waterways, PinUS plantations, Riverine forests, Agricultural lands, and managed landscape inthe Hantana range and Peradeniya University Park were surveyed for six months fromNovember 2001 to April 2002. Day and night-time survey was carried out to locate snakesand to record their microhabitats. Species identification was done in the field andphotographs of snakes were taken whenever necessary .Twenty snake species (25'1'0 of the total: including six endemics were recorded from theseven sites during the survey. Highest number of species (l6) was recorded from thegrasslands. Agricultural lands, Riverine forests and Natural forest held the second highestnumber of species with nine and eight respectively. The number of species in the grasslandrepresents 30%. of the total number present in the country.Hantana Range and the University land are subjected to severe degradation due to humanactivities. The natural forests have. reduced to a greater extent due to the illegal felling, andthe grasslands and Pinus plantations arc subjected to annual fires. Therefore, the mostsnake species found in the grasslands are heavily threatened Study and planningprograms should be initiated to conserve the diverse habitats types in the area to protectand conserve the diverse snake fauna of the area.

Dietary soy and meat proteins induce distinct physiological and gene expression changes in rats

This study reports on a comprehensive comparison of the effects of soy and meat proteins given at the recommended level on physiological markers of metabolic syndrome and the hepatic transcriptome. Male rats were fed semi-synthetic diets for 1 wk that differed only regarding protein source, with casein serving as reference. Body weight gain and adipose tissue mass were significantly reduced by soy but not meat proteins. The insulin resistance index was improved by soy, and to a lesser extent by meat proteins. Liver triacylglycerol contents were reduced by both protein sources, which coincided with increased plasma triacylglycerol concentrations. Both soy and meat proteins changed plasma amino acid patterns. The expression of 1571 and 1369 genes were altered by soy and meat proteins respectively. Functional classification revealed that lipid, energy and amino acid metabolic pathways, as well as insulin signaling pathways were regulated differently by soy and meat proteins. Several transcriptional regulators, including NFE2L2, ATF4, Srebf1 and Rictor were identified as potential key upstream regulators. These results suggest that soy and meat proteins induce distinct physiological and gene expression responses in rats and provide novel evidence and suggestions for the health effects of different protein sources in human diets

White rice, brown rice and the risk of type 2 diabetes: a systematic review and meta-analysis

Objective Intake of white rice has been associated with elevated risk for type 2 diabetes (T2D), while studies on brown rice are conflicting. To inform dietary guidance, we synthesised the evidence on white rice and brown rice with T2D risk. Design Systematic review and meta-analysis. Data sources PubMed, EMBASE and Cochrane databases were searched through November 2021. Eligibility criteria Prospective cohort studies of white and brown rice intake on T2D risk (≥1 year), and randomised controlled trials (RCTs) comparing brown rice with white rice on cardiometabolic risk factors (≥2 weeks). Data extraction and synthesis Data were extracted by the primary reviewer and two additional reviewers. Meta-analyses were conducted using random-effects models and reporting followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Risk of bias was assessed using the Newcastle Ottawa Scale for prospective cohort studies and the Cochrane Risk of Bias Tool for RCTs. Strength of the meta-evidence was assessed using NutriGrade. Results Nineteen articles were included: 8 cohort studies providing 18 estimates (white rice: 15 estimates, 25 956 cases, n=5 77 426; brown rice: 3 estimates, 10 507 cases, n=1 97 228) and 11 RCTs (n=1034). In cohort studies, white rice was associated with higher risk of T2D (pooled RR, 1.16; 95% CI: 1.02 to 1.32) comparing extreme categories. At intakes above ~300 g/day, a dose–response was observed (each 158 g/day serving was associated with 13% (11%–15%) higher risk of T2D). Intake of brown rice was associated with lower risk of T2D (pooled RR, 0.89; 95% CI: 0.81 to 0.97) comparing extreme categories. Each 50 g/day serving of brown rice was associated with 13% (6%–20%) lower risk of T2D. Cohort studies were considered to be of good or fair quality. RCTs showed an increase in high-density lipoprotein-cholesterol (0.06 mmol/L; 0.00 to 0.11 mmol/L) in the brown compared with white rice group. No other significant differences in risk factors were observed. The majority of RCTs were found to have some concern for risk of bias. Overall strength of the meta-evidence was moderate for cohort studies and moderate and low for RCTs. Conclusion Intake of white rice was associated with higher risk of T2D, while intake of brown rice was associated with lower risk. Findings from substitution trials on cardiometabolic risk factors were inconsistent

A limited-size ensemble of homogeneous CNN/LSTMs for high-performance word classification

The strength of long short-term memory neural networks (LSTMs) that have been applied is more located in handling sequences of variable length than in handling geometric variability of the image patterns. In this paper, an end-to-end convolutional LSTM neural network is used to handle both geometric variation and sequence variability. The best results for LSTMs are often based on large-scale training of an ensemble of network instances. We show that high performances can be reached on a common benchmark set by using proper data augmentation for just five such networks using a proper coding scheme and a proper voting scheme. The networks have similar architectures (convolutional neural network (CNN): five layers, bidirectional LSTM (BiLSTM): three layers followed by a connectionist temporal classification (CTC) processing step). The approach assumes differently scaled input images and different feature map sizes. Three datasets are used: the standard benchmark RIMES dataset (French); a historical handwritten dataset KdK (Dutch); the standard benchmark George Washington (GW) dataset (English). Final performance obtained for the word-recognition test of RIMES was 96.6%, a clear improvement over other state-of-the-art approaches which did not use a pre-trained network. On the KdK and GW datasets, our approach also shows good results. The proposed approach is deployed in the Monk search engine for historical-handwriting collections