Photon multiplicity measurements at forward rapidity in the ALICE experiment at CERN

We present the first preliminary results on photon multiplicity measurements at LHC at forward pseudorapidity (2.3 \textless $\eta$ \textless 3.9) in proton-proton ($pp$) collisions at $\sqrt{s}$ = 7 TeV. The multiplicity distribution is found to be reasonably well explained by a double Negative Binomial Distribution (NBD). The average photon multiplicity increases logarithmically with $\sqrt{s}$. It is found that none of the models we used (PYTHIA6D6T, PHOJET, and HERWIG) could explain the data.Comment: 4 pages, 6 figure

Toxigenic molds on fish feeds-1: impact of climatic change

The present communication is a survey report carried out to assess the incidence of toxic mycoflora on seven types of agriculture products/by products incorporated during fish culture as supplementary dietary items. Samples were obtained from various sources at Darbhanga, Madhubani and Samashtipur districts during summer, winter and monsoon months. Out of the total 1774 samples, only 894 appeared to be fresh visually reflecting average incidence of contamination around 46.6%. However, the apparently fresh samples, when subjected to culture, 26.9% of them were found to be contaminated. Thus, degree of fungal spoilage in feed ingredients in parts of north Bihar appears to be significantly high (73.5%). The present study illustrates the facts with special reference to Aspergillus flavus, A. parasiticus (elaborating aflatoxins) A. ochraceous, Penicilium viradicatuin (elaborating ochratoxins) and A. versicolor (elaborating sterigmatocystin). The other strains already known for their toxigenic potentials that appeared on the present substrates included A. niger, A. fumigatus, A. candidus, P. islandicum, Rhizopus spp. and Mucur spp. Studies indicate that the prevalent climatic factors like temperature and relative humidity facilitate a congenial condition almost all through the year and in particular during summer and monsoon months. But water content of the substrates is a vital factor that further accelerates the pace of mycobial spoilage. A thorough sun-drying of the agricultural commodities before prolonged storage to bring water content below the "low risk limit" may significantly reduce the incidence of molds

Optimization of Complex Water Supply Network

AbstractThe Millennium drought created critical water shortages throughout Australia and particularly in South East Queensland (SEQ). In response to this the bulk water network was significantly enhanced resulting in large infrastructure augmentations consisting of cross regional pipelines, a desalination plant and a purified recycled water plant. Given that SEQ can transition from drought to flood and vice versa in a short period of time it is a fine balance to operate the new more complicated asset base economically whilst maintaining sufficient supply security. With rising energy prices and the increasing cost of living pressures, there is an immediate need to better understand what optimal grid operation looks like and this is currently being investigated by the Seqwater Decision Support System (DSS).Till now, a network such as the SEQ water grid with its variety of water supply sources of varying reliabilities and complexity of the network has been operated in a relatively manual manner using manual heuristics. Given the number of factors which need to be considered when making decisions about which parts of the network to activate at any one time and the limitations of the human mind to resolve these, means that sub optimal results are frequently generated.The development of a DSS using optimization techniques can help determine the most efficient mode of delivery of water taking into account the operating costs of the various assets within the network, amongst a range of other constraints. This paper goes into detail the application of the optimization technology to the SEQ Water grid

Varieties and mulching influence on weed growth in wheat under Indo- Gangetic plain of India

Weeds are one of the primary factors responsible for reducing wheat yield. Despite, herbicides’ being one of the important components of weed management programme in India, but it was not adopted by resource poor farmers. Keeping these facts in view, a field experiment was carried out at Agricultural research farm, Institute of Agricultural sciences, Banaras Hindu University during the rabi (winter) season of the year 2012-13 to scrutinize the influence of ‘mulching’ and ‘varieties’ on weed control potential as well as growth and yield of wheat. The treatments comprised of five wheat varieties (C-306, K-8027, K-0307, DBW-39 and HD-2888) and four mulching treatments (No-mulch, paddy straw 6t/ha, maize straw 6t/ha, and saw dust 6t/ha). Surface application of paddy straw mulch 6t/ha considerably reduced the density and biomass of broad leafed weeds and grasses and showed higher weed control efficiency over other treatments like maize straw 6t/ha, saw dust 6t/ha and no-mulch. Varieties DBW-39 and K-0307 was highly effective in smothering of the weeds and produced higher dry matter accumulation, leaf area index, number of grain/earhead, biological yield and harvest index of wheat

A NARRATIVE REVIEW OF PRECISION MEDICINE, ARTIFICIAL INTELLIGENCE, AND THE FUTURE OF PERSONALIZED CARE: REVOLUTIONIZING HEALTHCARE.

Background The merging of AI and precision medicine is a paradigm change in healthcare. Precision medicine uses patient-specific traits to adapt medical interventions, while AI improves decision-making with advanced computational approaches. This convergence considers genetic and nongenomic characteristics, patient symptoms, clinical history, and lifestyle to address precision medicine difficulties. Objective This narrative review explores the potential of AI in advancing precision medicine. It examines the synergy between AI and precision medicine, emphasizing their combined capacity to enable individualized diagnosis and prognosis for patients with unique healthcare requirements or atypical responses to treatments. Summary of Narrative Review Recent literature underscores the promise of AI in precision medicine through translational research. AI's computational power allows it to analyze vast datasets, identify patterns, and generate valuable insights. By integrating genomic and nongenomic determinants with clinical and lifestyle data, AI enhances the accuracy and effectiveness of diagnosis and prognosis. This review delves into the transformative potential of this convergence, highlighting its applications in healthcare decision-making and patient care. Implications for Future Research Future research should focus on further developing AI-driven precision medicine tools and platforms. Investigating the real-world clinical impact of AI-driven precision medicine is essential, along with evaluating the scalability, ethical considerations, and regulatory frameworks for its implementation. Additionally, exploring AI's potential in optimizing treatment plans, drug discovery, and healthcare resource allocation is a crucial avenue for future research. Clinical Practice and Policy Development The amalgamation of AI and precision medicine offers healthcare professionals augmented intelligence, empowering them to make more informed decisions tailored to individual patient needs. This has the potential to improve treatment outcomes, reduce adverse effects, and enhance patient care. Policymakers and healthcare institutions should consider investing in AI-driven precision medicine initiatives and establishing guidelines for data privacy, ethics, and patient consent to ensure its responsible and ethical implementation

Electronic Warfare Simulation-based on Service Oriented Architecture

The realisation of service oriented architecture (SOA) is embodied in the accomplishments of various simulation applicable functions in the form of service encapsulation and the interconnection and interoperation of services. In this paper, an electronic warfare (EW) simulation is structured to SOA and achieved the effect of dynamic sharing and reusability. As a proof of concept, a radar electronic support (ES) simulator, which intercepts and classifies radar signals is designed and explained in this paper.Defence Science Journal, 2012, 62(4), pp.219-222, DOI:http://dx.doi.org/10.14429/dsj.62.92

Preliminary observations on the availability of Tor tor (Hamilton) fry in the River Narmada near Hoshangabad, Madhya Pradesh

Collection of mahseer (Tor tor) fry during December to January from three centres of the river Narmada near Hoshangabad, (Joshipur ghat, Dungerwada ghat and Kherra ghat) using a special type of fry collection net is described. The physical features and physico-chemical conditions of the collection sites are also dealt with

Work and Time analysis for rendering terms in a thesaurus derived from a faceted classification schedule : a case study with Lathe Production

Describes the various steps involved in rendering a standard term. Identifies the difference in the role of the term occuring in a faceted classification schedule. Analyses the work involved in the conversion, and the time required for each of the steps

Assessment of atmospheric aerosols from two reanalysis products over Australia

Assessments of atmospheric aerosols from reanalysis are important for understanding uncertainty in model simulations, and ultimately predictions, such as for solar power or air quality forecasts and assessments. This study intercompares total aerosol optical depth (AOD) and dust AOD (DAOD) from two global reanalyses datasets, the European Centre for Medium-Range Weather Forecasts (ECMWF) Monitoring Atmospheric Composition and Climate (MACC) and the NASA Modern-Era Retrospective Analysis for Research-2 (MERRA-2). These are evaluated against AeroSpan (Aerosol characterisation via Sun photometry: Australian Network) ground observations which forms part of the Aerosol Robotic Network (AERONET) over the Australian continent for the 2002–2012 period. During dust storms, AeroSpan/AERONET AOD measurements were missing due to cloud screening. To overcome validation limitations in sun photometry for dust events, a nephelometer's scattering coefficient is qualitatively compared against reanalysis of DAOD at a key dust storm activation site, Tinga Tingana in South Australia (~200 km east of Lake Eyre). A specific extreme event that occurred in 2009 originating from the Lake Eyre basin, a major dust source covering one-sixth of Australia, was studied. The results show that MERRA-2 reanalysis overestimates monthly total AOD twice as much compared to AeroSpan/AERONET ground observations but seems better correlated against AeroSpan/AERONET than ECMWF/MACC. Mean data of MERRA-2 time series over 10 years provide lower DAOD values and lower dust aerosol estimates than ECMWF/MACC reanalysis (over the Lake Eyre basin with spatial averaging). Specifically at Tinga Tingana, the correlation from MERRA-2 (0.45 correlation) and ECMWF/MACC (0.43 correlation) against AeroSpan/AERONET's AOD were similar. Between MERRA-2 and ECMWF/MACC decade long daily gridded DAOD, the correlation coefficient was high at 0.73, again indicating similarity between the datasets. MERRA-2 total AOD correlation is significantly higher (by 0.26) against AeroSpan/AERONET than ECMWF/MACC. MERRA-2 also provides higher AOD values in extreme cases which may correspond to dust storms. During dust storms, a hybrid strategy using nephelometers and hourly reanalysis from MERRA-2 is able to identify dust storms better than AeroSpan/AERONET. Overall, this work can enable and inform better aerosol data assimilation into forecast models such as for solar energy, agriculture or air quality over Australia

Ectopic expression of alkaline phosphatase in proximal tubular brush border membrane of human renal cell carcinoma

AbstractThe present study was conducted to find out any alteration in the expression and activity of alkaline phosphatase in the brush border membrane (BBM) from renal cell carcinoma (RCC) in comparison to normal renal BBM. The specific activity of alkaline phosphatase was drastically reduced in homogenate as well as BBM from RCC kidney when compared to ALP activity in BBM of normal kidney. Kinetic studies revealed that diminished activity of alkaline phosphatase in BBM isolated from RCC was fraternized with decrease in maximal velocity (Vmax) and increase in affinity constant (Km) of the enzyme. SDS-PAGE studies showed that the BBM proteins having molecular weights ranging from 95 to 170 kDa were poorly expressed in RCC BBM in relative to normal kidney BBM. Incubation of SDS-PAGE gel with BCIP/NBT dye clearly showed that the expression of ALP in tumor renal BBM was markedly reduced as compared to normal kidney. Further, Western blot analysis using anti-alkaline phosphatase antibody also confirmed the reduced expression of ALP in tumor renal BBM. Lipid composition in reference to phospholipids, glycolipids and cholesterol in tumor renal BBM was altered to that of normal renal BBM, indicating alteration in membrane fluidity of tumor renal BBM