Natural Windbreaks Sustain Bird Diversity in a Tea- Dominated Landscape

Windbreaks often form networks of forest habitats that improve connectivity and thus conserve biodiversity, but little is known of such effects in the tropics. We determined bird species richness and community composition in windbreaks composed of remnant native vegetation amongst tea plantations (natural windbreaks), and compared it with the surrounding primary forests. Fifty-one, ten-minute point counts were conducted in each habitat type over three days. Despite the limited sampling period, our bird inventories in both natural windbreaks and primary forests were nearly complete, as indicated by bootstrap true richness estimator. Bird species richness and abundance between primary forests and windbreaks were similar, however a difference in bird community composition was observed. Abundances of important functional groups such as frugivores and insectivores did not vary between habitat types but nectarivores were more abundant in windbreaks, potentially as a result of the use of windbreaks as traveling routes, foraging and nesting sites. This preliminary study suggests that natural windbreaks may be important habitats for the persistence of bird species in a production landscape. However, a better understanding of the required physical and compositional characteristics for windbreaks to sustain bird communities is needed for effective conservation management

Variations in host genes encoding adhesion molecules and susceptibility to falciparum malaria in India

<p>Abstract</p> <p>Background</p> <p>Host adhesion molecules play a significant role in the pathogenesis of <it>Plasmodium falciparum </it>malaria and changes in their structure or levels in individuals can influence the outcome of infection. The aim of this study was to investigate the association of SNPs of three adhesion molecule genes, <it>ICAM1</it>, <it>PECAM1 </it>and <it>CD36</it>, with severity of falciparum malaria in a malaria-endemic and a non-endemic region of India.</p> <p>Methods</p> <p>The frequency distribution of seven selected SNPs of <it>ICAM1</it>, <it>PECAM1 </it>and <it>CD36 </it>was determined in 552 individuals drawn from 24 populations across India. SNP-disease association was analysed in a case-control study format. Genotyping of the population panel was performed by Sequenom mass spectroscopy and patient/control samples were genotyped by SNaPshot method. Haplotypes and linkage disequilibrium (LD) plots were generated using PHASE and Haploview, respectively. Odds-ratio (OR) for risk assessment was estimated using EpiInfo™ version 3.4.</p> <p>Results</p> <p>Association of the ICAM1 rs5498 (exon 6) G allele and the CD36 exon 1a A allele with increased risk of severe malaria was observed (severe versus control, OR = 1.91 and 2.66, P = 0.02 and 0.0012, respectively). The CD36 rs1334512 (-53) T allele as well as the TT genotype associated with protection from severe disease (severe versus control, TT versus GG, OR = 0.37, P = 0.004). Interestingly, a SNP of the <it>PECAM1 </it>gene (rs668, exon 3, C/G) with low minor allele frequency in populations of the endemic region compared to the non-endemic region exhibited differential association with disease in these regions; the G allele was a risk factor for malaria in the endemic region, but exhibited significant association with protection from disease in the non-endemic region.</p> <p>Conclusion</p> <p>The data highlights the significance of variations in the <it>ICAM1</it>, <it>PECAM1 </it>and <it>CD36 </it>genes in the manifestation of falciparum malaria in India. The <it>PECAM1 </it>exon 3 SNP exhibits altered association with disease in the endemic and non-endemic region.</p

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe

Responsive supply chain: modeling and simulation

Unexpected occurrence like natural calamity, abruptly change in customer demands, upgradation of technologies, necessity of compatible suppliers etc. is the most challenging issues even for efficient global supply chain management. Therefore, modeling of responsive supply chain is an emerging technology for sustaining any firm/industry in future competitive environment. In this paper, an attempt has been made to not only analyze the performance of efficient supply chain management but also how to improve the performance of existing supply chain with the objective of developing a modeling of responsive supply chain management. The complexity of the model is also highlighted with the help of numerical example. This paper also explores the possibility to mathematical modeling of the responsive supply chain which will be an emerging topic for researchers and practitioners. The modeling of responsive supply chain can be employed as a competitive strategy for e-commerce, green supply chain, and compatible supplier selection problem. The another salient feature of this paper is that a distinct comparative literature review of the lean, agile, efficient, and responsive supply chain management has been presented

Leveraging AI and Blockchain for Privacy Preservation and Security in Fog Computing

INTRODUCTION: Cloud computing\u27s offshoot, fog computing, moves crucial data storage, processing, and networking capabilities closer to the people who need them. There are certain advantages, such improved efficiency and lower latency, but there are also some major privacy and security concerns. For these reasons, this article presents a new paradigm for fog computing that makes use of blockchain and Artificial Intelligence (AI). OBJECTIVES: The main goal of this research is to create and assess a thorough framework for fog computing that incorporates AI and blockchain technology. With an emphasis on protecting the privacy and integrity of data transactions and streamlining the management of massive amounts of data, this project seeks to improve the security and privacy of Industrial Internet of Things (IIoT) systems that are cloud-based. METHODS: Social network analysis methods are utilised in this study. The efficiency and accuracy of data processing in fog computing are guaranteed by the application of artificial intelligence, most especially Support Vector Machine (SVM), due to its resilience in classification and regression tasks. The network\u27s security and reliability are enhanced by incorporating blockchain technology, which creates a decentralised system that is tamper resistant. To make users\u27 data more private, zero-knowledge proof techniques are used to confirm ownership of data without actually disclosing it. RESULTS: When applied to fog computing data, the suggested approach achieves a remarkable classification accuracy of 99.8 percent. While the consensus decision-making process of the blockchain guarantees trustworthy and secure operations, the support vector machine (SVM) efficiently handles massive data analyses. Even in delicate situations, the zero-knowledge proof techniques manage to keep data private. When these technologies are integrated into the fog computing ecosystem, the chances of data breaches and illegal access are greatly reduced. CONCLUSION: Fog computing, which combines AI with blockchain, offers a powerful answer to the privacy and security issues with cloud centric IIoT systems. Combining SVM with AI makes data processing more efficient, while blockchain\u27s decentralised and immutable properties make it a strong security measure. Additional security for user privacy is provided via zero-knowledge proofs. Improving the privacy and security of fog computing networks has never been easier than with this novel method

Extreme Haemodilution to Haemoglobin of 1.2 gm.dl-1 due to Severe Blood Loss in Liver Transplantation

We report a case of a 50-year-old man, a known case of hepatitis C virus cirrhosis, who was presented for cadaveric orthotopic liver transplantation. There was severe intraoperative haemorrhage requiring massive transfusion of blood and blood products. During anhepatic phase the supply of our blood bank got exhausted. So we had to replace the ongoing blood loss with volume-expanders for approximately one hour. Patient tolerated haemodilution intraoperatively to the extent of haemoglobin 1.2 g.dl. -

Correlation of the stature with arch and chord dimensions in young subjects using carrea's index- An anthropometric study

Background: Forensic identifications have utilized the height or stature of an individual in their field. Teeth and dentition can act as reliable tools to estimate the stature in cases where the only skull is presented as evidence. The Carrea's index assesses the stature in a subject from the lower anterior teeth dimensions. Aim: The present study was aimed to judge the reliability of Carrea's index in Indian subjects. Materials and Methods: From 80 subjects who were undergraduate students, plaster models were made and each was assessed individually making 160 hemiarches. These hemiarches were divided based on the teeth alignment into normal, diastema, and crowded forms. This was followed by measurement with a vernier caliper into chord and arch. Results: In both genders, the difference seen was statistically significant between dental arch types concerning various alignments with 95.23% and 83.75% success for males and females in normal dentition and 92.30% and 85.71% in crowded dentition. Also, a significant difference was seen for the type of arch with P ≤ 0.001 and 0.003, respectively. Lesser success was seen for spacing in both the genders and arches. Conclusion: The present study concludes that Carrea's index is a dependable and efficient tool for estimating height in subjects having arches with crowded and normal dentition which is functional for both the gender on the left and right side of the dental arches. However, in hemiarches with diastema, this method is not reliable

Effect of Varying Levels of Boron and Sulphur on Yields and Nutrient Uptake of Linseed (Linum usitatissimum L.) Grown in a Mollisol

A greenhouse experiment was conducted to study the effect of effect of varying levels of boron and sulphur on yield and nutrient uptake of linseed (Linum usitatissimum L.) grown in a Mollisol. The experiment was conducted under factorial completely randomized design with three replications and consisted of six levels of each of boron (0, 0.5, 1.0, 1.5, 2.0 mg kg−1soil and two foliar sprays of 0.2% boron) and sulphur (0, 10, 20, 30, 40 and 60 mg kg−1soil). The different doses of sulphur and boron and their interaction had significant effect on seed and stover yields, B and S concentrations and uptake by linseed crop indicating a differential requirement of boron and sulphur by the crop.&nbsp; The highest seed yield was recorded under the combined application of 2 mg B kg−1 soil and 60 mg S kg−1 soil

Non-metric multidimensional scaling (NMDS) ordination of the bird assemblages in primary forests (solid triangles) and windbreaks (asterisk).

<p>Points are census sites. The ordination diagram is for visualisation only; all tests of treatment effects are conducted using <i>mvabund</i> (see text for statistical details).</p