EDUKASI PEMANFAATAN ENERGI SURYA KAWASAN AGRO EKOWISATA ORGANIK, MULYAHARJA BOGOR

Ketersediaan dan kebutuhan energi memiliki peran yang sangat penting bagi Pengelola Agro Ekowisata Organik (AEWO) di Mulyaharja, Bogor karena merupakan salah satu sumber konflik kepentingan di bidang pertanian dan pariwisata. Salah satu komponen daya tarik wisata adalah aktivitas pertanian ramah lingkungan yang harus dikomunikasikan, karena berkontribusi pada wisata. Permasalahan yang dihadapi mitra pengelola AEWO adalah Kebutuhan Daya Listrik (KDL) yang harus berbagi antara aktivitas pariwisata dan pertanian. Kondisi KDL untuk aktivitas pertanian sering dikalahkan ketika KDL yang menunjang wisata (lampu-lampu penerangan di warung-warung untuk menyediakan makanan dan minuman bagi para wisatawan) dinilai lebih prioritas. Keberlanjutan AEWO tidak dapat dipisahkan dari aktivitas pertanian itu sendiri. Edukasi pemanfaatan energi surya bertujuan untuk mengurangi konflik KDL bersama dengan kebijakan operasional per jam yang optimal untuk penggunaan listrik secara adil, terbuka, dan transparan. Tahapan pelaksanaan kegiatan pengabdian pada masyarakat adalah: (1) Diskusi tim pengabdi dengan pihak mitra (pengelola AEWO dan petani organik); (2) Observasi lokasi; (3) Diskusi pelaksanaan; (4) Sosialisasi dan pendampingan keterampilan penciptaan prototip dengan pemanfaatan energi surya, serta evaluasi melalui pre-test dan post-test. Hasil kegiatan mampu meningkatkan pemahaman penggunaan energi surya bagi pengelola wisata dan petani. Keberhasilan program ini diharapkan mampu meningkatkan pendapatan AEWO yang dapat direplikasi ke desa wisata lainnya

Application of Artificial Intelligence in Modern Ecology for Detecting Plant Pests and Animal Diseases

Climate change could lead to an increase in diseases in plants and animals. Plant pathogens have caused devastating production losses, such as in tropical countries. The development of algorithms that match the accuracy of plant and animal disease detection in predicting the toxicity of substances has continued through a massive database. Data and information from 10,000 substances from more than 800,000 animal tests have been carried out to generate the algorithms. Plant and animal disease detection using artificial intelligent in the modern ecological era is important and needed. Diseases in animals are still found in several Ruminant-Slaughterhouses. The purpose of the study is to identify the leverage attributes for using of Artificial Intelligent (AI) in detecting plant pests and animal diseases. The use of Multidimensional Scaling (MDS) produces a leverage attribute for the use of AI in detecting plant pests and animal diseases. The results showed that leverage attributes found were: Prediction of the presence of proteins structures produced by pathogens with a Root Mean Square (RMS) value of 4.5123; and Plant and Animal Disease Data will be opened with an RMS value of 4.2555. The findings of this study in the real world are to produce the development of smart agricultural applications in detecting plant pests and animal diseases as an early warning system. In addition, the application is also useful for eco-tourism managers who have a natural close relationship with plants and animals, so that ecological security in the modern ecological era, can be better maintained

UFPRSheffield: Contrasting Rule-based and Support Vector Machine Approaches to Time Expression Identification in Clinical TempEval

We present two approaches to time expression identification, as entered in to SemEval2015 Task 6, Clinical TempEval. The first is a comprehensive rule-based approach that favoured recall, and which achieved the best recall for time expression identification in Clinical TempEval. The second is an SVM-based system built using readily available components, which was able to achieve a competitive F1 in a short development time. We discuss how the two approaches perform relative to each other, and how characteristics of the corpus affect the suitability of different approaches and their outcomes

Concentration-dependent diffusivity and anomalous diffusion: A magnetic resonance imaging study of water ingress in porous zeolite

Magnetic resonance imaging is employed to study water ingress in fine zeolite powders compacted by high pressure. The experimental conditions are chosen such that the applicability of Boltzmann's transformation of the one-dimensional diffusion equation is approximately satisfied. The measured moisture profiles indicate subdiffusive behavior with a spatiotemporal scaling variable eta=x/t(gamma/2) (0 <gamma < 1). A time-fractional diffusion equation model of anomalous diffusion is adopted to analyze the data, and an expression that yields the moisture dependence of the generalized diffusivity is derived and applied to our measured profiles. In spite of the differences between systems exhibiting different values of gamma a striking similarity in the moisture dependence of the diffusivity is apparent. This suggests that the model addresses the underlying physical processes involved in water transport.731

A recessive genetic model and runs of homozygosity in major depressive disorder

Genome-wide association studies (GWASs) of major depressive disorder (MDD) have yet to identify variants that surpass the threshold for genome-wide significance. A recent study reported that runs of homozygosity (ROH) are associated with schizophrenia, reflecting a novel genetic risk factor resulting from increased parental relatedness and recessive genetic effects. Here, we explore the possibility of such a recessive model in MDD. In a sample of 9,238 cases and 9,521 controls reported in a recent mega-analysis of 9 GWAS we perform an analysis of ROH and common variants under a recessive model. Since evidence for association with ROH could reflect a recessive mode of action at loci, we also conducted a genome-wide association analyses under a recessive model. The genome-wide association analysis using a recessive model found no significant associations. Our analysis of ROH suggested that there was significant heterogeneity of effect across studies in effect (P=0.001), and it was associated with genotyping platform and country of origin. The results of the ROH analysis show that differences across studies can lead to conflicting systematic genome-wide differences between cases and controls that are unaccounted for by traditional covariates. They highlight the sensitivity of the ROH method to spurious associations, and the need to carefully control for potential confounds in such analyses. We found no strong evidence for a recessive model underlying MDD

Cross-national variations in reported discrimination among people treated for major depression worldwide : the ASPEN/INDIGO international study

No study has so far explored differences in discrimination reported by people with major depressive disorder (MDD) across countries and cultures. To (a) compare reported discrimination across different countries, and (b) explore the relative weight of individual and contextual factors in explaining levels of reported discrimination in people with MDD. Cross-sectional multisite international survey (34 countries worldwide) of 1082 people with MDD. Experienced and anticipated discrimination were assessed by the Discrimination and Stigma Scale (DISC). Countries were classified according to their rating on the Human Development Index (HDI). Multilevel negative binomial and Poisson models were used. People living in ‘very high HDI’ countries reported higher discrimination than those in ‘medium/low HDI’ countries. Variation in reported discrimination across countries was only partially explained by individual-level variables. The contribution of country-level variables was significant for anticipated discrimination only. Contextual factors play an important role in anticipated discrimination. Country-specific interventions should be implemented to prevent discrimination towards people with MDD

Numerical comparison of the closing dynamics of a new trileaflet and a bileaflet mechanical aortic heart valve

[[abstract]]The closing velocity of the leaflets of mechanical heart valves is excessively rapid and can cause the cavitation phenomenon. Cavitation bubbles collapse and produce high pressure which then damages red blood cells and platelets. The closure mechanism of the trileaflet valve uses the vortices in the aortic sinus to help close the leaflets, which differs from that of the monoleaflet or bileaflet mechanical heart valves which mainly depends on the reverse flow. We used the commercial software program Fluent to run numerical simulations of the St. Jude Medical bileaflet valve and a new trileaflet mechanical heart valve. The results of these numerical simulations were validated with flow field experiments. The closing velocity of the trileaflet valve was clearly slower than that of the St. Jude Medical bileaflet valve, which would effectively reduce the occurrence of cavitation. The findings of this study are expected to advance the development of the trileaflet valve.[[incitationindex]]SCI[[booktype]]電子版[[booktype]]紙