Smart Dairy Cattle Farming and In-Heat Detection through the Internet of Things (IoT)

The Internet of Things (IoT) technology has been being revolutionized in various aspects of agriculture around the world ever since. Its application has already found its success in some countries. On the contrary, this technology has yet to find its substantial breakthrough in the Philippines. This study shows the application of IoT in improving the detection efficiency of standing-heat behaviors of cows through automated detection using Pan-tilt-zoom cameras and a Python-driven Web Application. The dimensions of the barn were measured, and the Cameras' Field of Views (FOVs) were pre-calculated for the strategic positions of the cameras atop of the cowshed. The program detects the cows and any estrus events through the surveillance cameras. The results will be sent to the cloud server to display on the web application for analysis. The web app can allow updates on cow information, inseminations, pregnancy, and calving records, estimate travel time from the user's geolocation to the farm, provide live monitoring and remote camera accessibility and control through the cameras and deliver reliable cross-platform push-notification and call alerts on the user's device(s) whenever an estrus event is detected. Based on the results, the program performed satisfactorily at 50% detection efficiency

How protective is cervical cancer screening against cervical cancer mortality in developing countries? The Colombian case

<p>Abstract</p> <p>Background</p> <p>Cervical cancer is one of the top causes of cancer morbidity and mortality in Colombia despite the existence of a national preventive program. Screening coverage with cervical cytology does not explain the lack of success of the program in reducing incidence and mortality rates by cervical cancer. To address this problem an ecological analysis, at department level, was carried out in Colombia to assess the relationship between cervical screening characteristics and cervical cancer mortality rates.</p> <p>Methods</p> <p>Mortality rates by cervical cancer were estimated at the department level for the period 2000-2005. Levels of mortality rates were compared to cervical screening coverage and other characteristics of the program. A Poisson regression was used to estimate the effect of different dimensions of program performance on mortality by cervical cancer.</p> <p>Results</p> <p>Screening coverage ranged from 28.7% to 65.6% by department but increases on this variable were not related to decreases in mortality rates. A significant reduction in mortality was found in departments where a higher proportion of women looked for medical advice when abnormal findings were reported in Pap smears. Geographic areas where a higher proportion of women lack health insurance had higher rates of mortality by cervical cancer.</p> <p>Conclusions</p> <p>These results suggest that coverage is not adequate to prevent mortality due to cervical cancer if women with abnormal results are not provided with adequate follow up and treatment. The role of different dimensions of health care such as insurance coverage, quality of care, and barriers for accessing health care needs to be evaluated and addressed in future studies.</p

Amygdala inputs to prefrontal cortex guide behavior amid conflicting cues of reward and punishment

Orchestrating appropriate behavioral responses in the face of competing signals that predict either rewards or threats in the environment is crucial for survival. The basolateral nucleus of the amygdala (BLA) and prelimbic (PL) medial prefrontal cortex have been implicated in reward-seeking and fear-related responses, but how information flows between these reciprocally connected structures to coordinate behavior is unknown. We recorded neuronal activity from the BLA and PL while rats performed a task wherein competing shock- and sucrose-predictive cues were simultaneously presented. The correlated firing primarily displayed a BLA→PL directionality during the shock-associated cue. Furthermore, BLA neurons optogenetically identified as projecting to PL more accurately predicted behavioral responses during competition than unidentified BLA neurons. Finally photostimulation of the BLA→PL projection increased freezing, whereas both chemogenetic and optogenetic inhibition reduced freezing. Therefore, the BLA→PL circuit is critical in governing the selection of behavioral responses in the face of competing signals.National Institutes of Health (U.S.) (Award 1R25-MH092912-01)National Institute of Mental Health (U.S.) (Grant R01- MH102441-01)National Institutes of Health (U.S.) (Award DP2- DK-102256-01

fabH deletion increases DHA productionin Escherichia coli expressing Pfa genes

Background: Some marine bacteria, such as Moritella marina, produce the nutraceutical docosahexaenoic acid (DHA) thanks to a specific enzymatic complex called Pfa synthase. Escherichia coli heterologously expressing the pfa gene cluster from M. marina also produces DHA. The aim of this study was to find genetic or metabolic conditions to increase DHA production in E. coli. Results: First, we analysed the effect of the antibiotic cerulenin, showing that DHA production increased twofold. Then, we tested a series of single gene knockout mutations affecting fatty acid biosynthesis, in order to optimize the synthesis of DHA. The most effective mutant, fabH, showed a threefold increase compared to wild type strain. The combination of cerulenin inhibition and fabH deletion rendered a 6.5-fold improvement compared to control strain. Both strategies seem to have the same mechanism of action, in which fatty acid synthesis via the canonical pathway (fab pathway) is affected in its first catalytic step, which allows the substrates to be used by the heterologous pathway to synthesize DHA. Conclusions: DHA-producing E. coli strain that carries a fabH gene deletion boosts DHA production by tuning down the competing canonical biosynthesis pathway. Our approach can be used for optimization of DHA production in different organisms.Funding: The work in the FdlC and GM laboratories was financed by the Spanish Ministry of Economy, Industry and Competitiveness Grant BFU2014-55534-C2

Depression and physical activity in a sample of nigerian adolescents: levels, relationships and predictors

<p>Abstract</p> <p>Background</p> <p>Physical inactivity is related to many morbidities but the evidence of its link with depression in adolescents needs further investigation in view of the existing conflicting reports.</p> <p>Methods</p> <p>The data for this cross-sectional study were collected from 1,100 Nigerian adolescents aged 12-17 years. Depressive symptomatology and physical activity were assessed using the Children's Depression Inventory (CDI) and the Physical Activity Questionnaire-Adolescent version (PAQ-A) respectively. Independent t tests, Pearson's Moment Correlation and Multi-level logistic regression analyses for individual and school area influences were carried out on the data at p < 0.05.</p> <p>Results</p> <p>The mean age of the participants was 15.20 ± 1.435 years. The prevalence of mild to moderate depression was 23.8%, definite depression was 5.7% and low physical activity was 53.8%. More severe depressive symptoms were linked with lower levels of physical activity (r = -0.82, p < 0.001) and moderate physical activity was linked with reduced risk of depressive symptoms (OR = 0.42, 95% CI = 0.29-0.71). The odds of having depressive symptoms were higher in older adolescents (OR = 2.16, 95% CI = 1.81-3.44) and in females (OR = 2.92, 95% CI = 1.82-3.54). Females had a higher risk of low physical activity than male adolescents (OR = 2.91, 95% CI = 1.51-4.26). Being in Senior Secondary class three was a significant predictor of depressive symptoms (OR = 3.4, 95% CI = 2.55-4.37) and low physical activity.</p> <p>Conclusions</p> <p>A sizable burden of depression and low physical activity existed among the studied adolescents and these were linked to both individual and school factors. Future studies should examine the effects of physical activity among clinical samples of adolescents with depression.</p

TRY plant trait database - enhanced coverage and open access

Plant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

Performance of CMS muon reconstruction in pp collision events at sqrt(s) = 7 TeV

The performance of muon reconstruction, identification, and triggering in CMS has been studied using 40 inverse picobarns of data collected in pp collisions at sqrt(s) = 7 TeV at the LHC in 2010. A few benchmark sets of selection criteria covering a wide range of physics analysis needs have been examined. For all considered selections, the efficiency to reconstruct and identify a muon with a transverse momentum pT larger than a few GeV is above 95% over the whole region of pseudorapidity covered by the CMS muon system, abs(eta) < 2.4, while the probability to misidentify a hadron as a muon is well below 1%. The efficiency to trigger on single muons with pT above a few GeV is higher than 90% over the full eta range, and typically substantially better. The overall momentum scale is measured to a precision of 0.2% with muons from Z decays. The transverse momentum resolution varies from 1% to 6% depending on pseudorapidity for muons with pT below 100 GeV and, using cosmic rays, it is shown to be better than 10% in the central region up to pT = 1 TeV. Observed distributions of all quantities are well reproduced by the Monte Carlo simulation.Comment: Replaced with published version. Added journal reference and DO

Azimuthal anisotropy of charged particles at high transverse momenta in PbPb collisions at sqrt(s[NN]) = 2.76 TeV

The azimuthal anisotropy of charged particles in PbPb collisions at nucleon-nucleon center-of-mass energy of 2.76 TeV is measured with the CMS detector at the LHC over an extended transverse momentum (pt) range up to approximately 60 GeV. The data cover both the low-pt region associated with hydrodynamic flow phenomena and the high-pt region where the anisotropies may reflect the path-length dependence of parton energy loss in the created medium. The anisotropy parameter (v2) of the particles is extracted by correlating charged tracks with respect to the event-plane reconstructed by using the energy deposited in forward-angle calorimeters. For the six bins of collision centrality studied, spanning the range of 0-60% most-central events, the observed v2 values are found to first increase with pt, reaching a maximum around pt = 3 GeV, and then to gradually decrease to almost zero, with the decline persisting up to at least pt = 40 GeV over the full centrality range measured.Comment: Replaced with published version. Added journal reference and DO