Grain storage at farm and warehouses level

Grain storage is very important because the quality of flour obtained from grain will be found in the finished products’ quality. Grains must be stored in well established conditions regarding temperature, humidity, airflow, trying to avoid the risk of being attacked by rodents and insects. If these conditions are not complied with, some qualitative deficits of the grains - such as mould at pH, infestation, fermentation etc. - may appear. The storage methods are those responsible for maintaining a good quality of the grains

Enhancement of Learning Style in Kolej Poly-Tech MARA (KPTM) via Mobile EEF Learning System (MEEFLS)

Mobile communication provides access to the outside world without borders everywhere and at any time. The learning method that related to mobile communication technology is known as mobile learning (M-learning). It is a method that communicates learning materials with mobile device technology. The purpose of this method is to increase the interest in learning among students and assist them in obtaining learning materials at Kolej Poly-Tech MARA (KPTM) in order to improve the student's performance in their study and to encourage educators to diversify the teaching practices. This paper discusses the student's awareness for enhancement of learning style using mobile technologies and their readiness to apply the elements of mobile learning in learning to improve performance and interest in learning among students. An application called Mobile EEF Learning System (MEEFLS) has been developed as a tool to be used as a pilot test in KPTM

Enhancement of Learning Style in Kolej Poly-Tech MARA (KPTM) via Mobile EEF Learning System (MEEFLS)

Mobile communication provides access to the outside world without borders everywhere and at any time. The learning method that related to mobile communication technology is known as mobile learning (M-learning). It is a method that communicates learning materials with mobile device technology. The purpose of this method is to increase the interest in learning among students and assist them in obtaining learning materials at Kolej Poly-Tech MARA (KPTM) in order to improve the student's performance in their study and to encourage educators to diversify the teaching practices. This paper discusses the student's awareness for enhancement of learning style using mobile technologies and their readiness to apply the elements of mobile learning in learning to improve performance and interest in learning among students. An application called Mobile EEF Learning System (MEEFLS) has been developed as a tool to be used as a pilot test in KPTM

Improving water productivity, reducing poverty and enhancing equity in mixed crop-livestock systems in the Indo-Gangetic Basin: CPWF project report 68

Farming systems / Mixed farming / Water productivity / Feed production / Livestock / Energy consumption / Gender / Poverty / River basins / Case studies / India / Indo-Gangetic Basin / West Bengal / Haryana / Uttar Pradesh

Measurements of heterotypic associations between cluster of differentiation CD74 and CD44 in human breast cancer-derived cells

Interactions between pairs of membrane-bound receptors can enhance tumour development with implications for targeted therapies for cancer. Here we demonstrate clear heterotypic interaction between cluster of differentiation (CD) 74 and CD44, which might act in synergy and hence contribute to breast cancer progression. CD74, a type II transmembrane glycoprotein, is a chaperone for MHC class II biosynthesis and a receptor for the macrophage migration inhibitory factor (MIF). CD44 is the receptor for hyaluronic acid and is a type II transmembrane protein. Interactions between CD74, MIF and the intra-cytoplasmic domain of CD44 result in activation of ERK1/2, leading to increased cell proliferation and decreased apoptosis. The level of CD44 in the breast tumor cell lines CAMA-1, MDA-MB-231, MDA-MB-435 and the immortalized normal luminal cell line 226LDM was higher than that of CD74. It was also observed that CD74 and CD44 exhibit significant variation in expression levels across the cells. CD74 and CD44 were observed to accumulate in cytoplasmic compartments, suggesting they associate with each other to facilitate tumour growth and metastasis. Use of a novel and validated colocalisation and image processing approach, coupled with co-immunoprecipitation, confirmed that CD74 and CD44 physically interact, suggesting a possible role in breast tumour growth. This is the first time that CD74 and CD44 colocalization has been quantified in breast cancer cells using a non-invasive validated bioimaging procedure. Measuring the co-expression levels of CD74 and CD44 could potentially be used as a 'biomarker signature' to monitor different stages of breast cancer

Pregnane steroidogenesis is altered by HIV-1 Tat and morphine: Physiological allopregnanolone is protective against neurotoxic and psychomotor effects

Pregnane steroids, particularly allopregnanolone (AlloP), are neuroprotective in response to central insult. While unexplored in vivo, AlloP may confer protection against the neurological dysfunction associated with human immunodeficiency virus type 1 (HIV-1). The HIV-1 regulatory protein, trans-activator of transcription (Tat), is neurotoxic and its expression in mice increases anxiety-like behavior; an effect that can be ameliorated by progesterone, but not when 5α-reduction is blocked. Given that Tat\u27s neurotoxic effects involve mitochondrial dysfunction and can be worsened with opioid exposure, we hypothesized that Tat and/or combined morphine would perturb steroidogenesis in mice, promoting neuronal death, and that exogenous AlloP would rescue these effects. Like other models of neural injury, conditionally inducing HIV-1 Tat in transgenic mice significantly increased the central synthesis of pregnenolone and progesterone\u27s 5α-reduced metabolites, including AlloP, while decreasing central deoxycorticosterone (independent of changes in plasma). Morphine significantly increased brain and plasma concentrations of several steroids (including progesterone, deoxycorticosterone, corticosterone, and their metabolites) likely via activation of the hypothalamic-pituitary-adrenal stress axis. Tat, but not morphine, caused glucocorticoid resistance in primary splenocytes. In neurons, Tat depolarized mitochondrial membrane potential and increased cell death. Physiological concentrations of AlloP (0.1, 1, or 10 nM) reversed these effects. High-concentration AlloP (100 nM) was neurotoxic in combination with morphine. Tat induction in transgenic mice potentiated the psychomotor effects of acute morphine, while exogenous AlloP (1.0 mg/kg, but not 0.5 mg/kg) was ameliorative. Data demonstrate that steroidogenesis is altered by HIV-1 Tat or morphine and that physiological AlloP attenuates resulting neurotoxic and psychomotor effects

DREAM4: Combining Genetic and Dynamic Information to Identify Biological Networks and Dynamical Models

Current technologies have lead to the availability of multiple genomic data types in sufficient quantity and quality to serve as a basis for automatic global network inference. Accordingly, there are currently a large variety of network inference methods that learn regulatory networks to varying degrees of detail. These methods have different strengths and weaknesses and thus can be complementary. However, combining different methods in a mutually reinforcing manner remains a challenge.We investigate how three scalable methods can be combined into a useful network inference pipeline. The first is a novel t-test-based method that relies on a comprehensive steady-state knock-out dataset to rank regulatory interactions. The remaining two are previously published mutual information and ordinary differential equation based methods (tlCLR and Inferelator 1.0, respectively) that use both time-series and steady-state data to rank regulatory interactions; the latter has the added advantage of also inferring dynamic models of gene regulation which can be used to predict the system's response to new perturbations.Our t-test based method proved powerful at ranking regulatory interactions, tying for first out of methods in the DREAM4 100-gene in-silico network inference challenge. We demonstrate complementarity between this method and the two methods that take advantage of time-series data by combining the three into a pipeline whose ability to rank regulatory interactions is markedly improved compared to either method alone. Moreover, the pipeline is able to accurately predict the response of the system to new conditions (in this case new double knock-out genetic perturbations). Our evaluation of the performance of multiple methods for network inference suggests avenues for future methods development and provides simple considerations for genomic experimental design. Our code is publicly available at http://err.bio.nyu.edu/inferelator/

Modelling and analysis of influenza A (H1N1) on networks

Network modelling is a useful tool for studying the transmission of H1N1 in China, capturing the main features of the spread of H1N1. The paper calculates the basic reproduction number and studies the effects of various immunization schemes. The final size relation is derived for the network epidemic model. While a uniform, mass-immunization strategy helps control the prevalence, a targeted immunization strategy focusing on specific groups with given connectivity may better control an epidemic

Journal Staff

We present the first measurements of the differential cross section d sigma/dp(T)(gamma) for the production of an isolated photon in association with at least two b-quark jets. The measurements consider photons with rapidities vertical bar y(gamma)vertical bar < 1.0 and transverse momenta 30 < p(T)(gamma) < 200 GeV. The b-quark jets are required to have p(T)(jet) > 15 GeVand vertical bar y(jet)vertical bar < 1.5. The ratio of differential production cross sections for gamma + 2 b-jets to gamma + b-jet as a function of p(T)(gamma) is also presented. The results are based on the proton-antiproton collision data at root s = 1.96 TeV collected with the D0 detector at the Fermilab Tevatron Collider. The measured cross sections and their ratios are compared to the next- to- leading order perturbative QCD calculations as well as predictions based on the k(T)- factorization approach and those from the sherpa and pythia Monte Carlo event generators

Precise measurement of the top quark mass in the dilepton channel at D0

We measure the top quark mass (mt) in ppbar collisions at a center of mass energy of 1.96 TeV using dilepton ttbar->W+bW-bbar->l+nubl-nubarbbar events, where l denotes an electron, a muon, or a tau that decays leptonically. The data correspond to an integrated luminosity of 5.4 fb-1 collected with the D0 detector at the Fermilab Tevatron Collider. We obtain mt = 174.0 +- 1.8(stat) +- 2.4(syst) GeV, which is in agreement with the current world average mt = 173.3 +- 1.1 GeV. This is currently the most precise measurement of mt in the dilepton channel.Comment: 7 pages, 4 figure