Trauma, Grief and the Social Model: Practice Guidelines for Working with Adults with Intellectual Disabilities in the Wake of Disasters

Formulating personal needs assessments and plans for self-protection have been the recent focus of disaster preparedness manuals for individuals with intellectual disabilities and their caregivers. Interventions to address the minimization of psychological ill effects of trauma and grief in the aftermath of disasters for this population, however, remain largely unexplored. In the wake of such events, persons with intellectual disabilities require trained mental health professionals to assist them in identifying and coping with trauma exposure and its associated, often sudden losses. Intervention should be based on the unique needs of this population within the context of disaster and each individual's cognitive strengths and capacities. Coupled with reviews of research and practice in the area of disaster mental health, the social model of disability served as a foundation for the formulation of best practice guidelines for tertiary interventions with adults with intellectual disabilities. The guidelines suggest approaches that will enable professionals to identify and minimize acute and chronic responses to disasters as well as foster resilience and enhance the valuable contributions of adults with intellectual disabilities in disaster-affected communities

Implikasi Perjanjian Asean-korea Free Trade Area (Akfta) Terhadap Ekspor Minyak Dan Gas Brunei Darussalam Ke Korea Selatan Tahun 2007 – 2011

This research is an International relations research in economy politic studies which describes about the implications of ASEAN – KOREA FREE TRADE AREA (AKFTA) agreement on exports of oil and gas from Brunei Darussalam to South Korea in 2007 – 2011. The establishment of the ASEAN-Korea Free Trade Area (AKFTA) are to strengthen and develop economies, markets and investments in cooperation between ASEAN and Korean member countries which characterized by gradual liberalization and promote the market of transparent, liberal goods and services and provide facilities for investation.This is qualitative research which used descriptive methods, and collecting datas from some resources like books, journals, official publications and relevant websites. This paper used the neo – liberalism perspective and Free Trade Theory by David Ricardo which known as "comparative advantages" (comparative advantages). The object of this research is the export and import relationship between Brunei Darussalam and South Korea.The results of this research shows that ASEAN – KOREA FREE TRADE AREA (AKFTA) which creates agreements in various sectors like trade, economy, and politics. Including export and production, trade contracts, Free Trade, and the influence of AKFTA on the hegemony of Japan and the People\u27s Republic of China in ASEAN that involving Brunei Darussalam and South Korea in 2007 – 2011

Measuring Slowness in Old Age: Times to Perform Moberg Picking-Up and Walking Speed Tests.

Slowness is a marker of frailty captured by the Fried phenotype by a walking speed test which, for health or logistical reasons, is sometimes difficult to perform. The Moberg picking-up test (MPUT) is another timed functional test. It measures hand motor activity and might represent an alternative to assess slowness when the walking speed cannot be evaluated. This study aimed to evaluate the relationship between MPUT and walking speed. Cross-sectional. In total, 2748 individuals aged 66 to 83 years who participated in the latest examination (2015-2017) of the population-based Lausanne cohort 65+ and completed both tests. Walking speed (time to walk 20 meters at usual pace) and MPUT (time to pick up 12 objects) were compared using scatter graphs. Multivariate regression models further investigated the relationship between MPUT and walking times with adjustment for height, grip strength, body mass index, and Mini-Mental State Examination. All analyses were stratified by sex. MPUT and walking times were moderately, positively correlated in men (r = 0.38, P < .001) and in women (r = 0.38, P < .001). Higher grip strength and Mini-Mental State Examination performances were correlated to shorter MPUT and walking times. Men and women slower at the MPUT were also significantly slower at the walking speed test when adjusting for height (P < .001) as well as in fully adjusted models (P < .001). These preliminary results point to a positive association between MPUT and walking speed independent of muscle strength and cognition. Further research is needed to investigate the capacity of MPUT to predict adverse health outcomes before considering this test as an alternative measure of slowness in the assessment of frailty

Mining livestock genome datasets for an unconventional characterization of animal DNA viromes

Whole genome sequencing (WGS) datasets, usually generated for the investigation of the individual animal genome, can be used for additional mining of the fraction of sequencing reads that remains unmapped to the respective reference genome. A significant proportion of these reads contains viral DNA derived from viruses that infected the sequenced animals. In this study, we mined more than 480 billion sequencing reads derived from 1471 WGS datasets produced from cattle, pigs, chickens and rabbits. We identified 367 different viruses among which 14, 11, 12 and 1 might specifically infect the cattle, pig, chicken and rabbit, respectively. Some of them are ubiquitous, avirulent, highly or potentially damaging for both livestock and humans. Retrieved viral DNA information provided a first unconventional and opportunistic landscape of the livestock viromes that could be useful to understand the distribution of some viruses with potential deleterious impacts on the animal food production systems

How many Observations are Enough? Knowledge Distillation for Trajectory Forecasting

Accurate prediction of future human positions is an essential task for modern video-surveillance systems. Current state-of-the-art models usually rely on a "history" of past tracked locations (e.g., 3 to 5 seconds) to predict a plausible sequence of future locations (e.g., up to the next 5 seconds). We feel that this common schema neglects critical traits of realistic applications: as the collection of input trajectories involves machine perception (i.e., detection and tracking), incorrect detection and fragmentation errors may accumulate in crowded scenes, leading to tracking drifts. On this account, the model would be fed with corrupted and noisy input data, thus fatally affecting its prediction performance.In this regard, we focus on delivering accurate predictions when only few input observations are used, thus potentially lowering the risks associated with automatic perception. To this end, we conceive a novel distillation strategy that allows a knowledge transfer from a teacher network to a student one, the latter fed with fewer observations (just two ones). We show that a properly defined teacher supervision allows a student network to perform comparably to state-of-the-art approaches that demand more observations. Besides, extensive experiments on common trajectory forecasting datasets highlight that our student network better generalizes to unseen scenarios

Population genomic structures and signatures of selection define the genetic uniqueness of several fancy and meat rabbit breeds

Following the recent domestication process of the European rabbit (Oryctolagus cuniculus), many different breeds and lines, distinguished primarily by exterior traits such as coat colour, fur structure and body size and shape, have been constituted. In this study, we genotyped, with a high-density single-nucleotide polymorphism panel, a total of 645 rabbits from 10 fancy breeds (Belgian Hare, Champagne d'Argent, Checkered Giant, Coloured Dwarf, Dwarf Lop, Ermine, Giant Grey, Giant White, Rex and Rhinelander) and three meat breeds (Italian White, Italian Spotted and Italian Silver). ADMIXTURE analysis indicated that breeds with similar phenotypic traits (e.g. coat colour and body size) shared common ancestries. Signatures of selection using two haplotype-based approaches (iHS and XP-EHH), combined with the results obtained with other methods previously reported that we applied to the same breeds, we identified a total of 5079 independent genomic regions with some signatures of selection, covering about 1777 Mb of the rabbit genome. These regions consistently encompassed many genes involved in pigmentation processes (ASIP, EDNRA, EDNRB, KIT, KITLG, MITF, OCA2, TYR and TYRP1), coat structure (LIPH) and body size, including two major genes (LCORL and HMGA2) among many others. This study revealed novel genomic regions under signatures of selection and further demonstrated that population structures and signatures of selection, left into the genome of these rabbit breeds, may contribute to understanding the genetic events that led to their constitution and the complex genetic mechanisms determining the broad phenotypic variability present in these untapped rabbit genetic resources

Survey on Vision-based Path Prediction

Path prediction is a fundamental task for estimating how pedestrians or vehicles are going to move in a scene. Because path prediction as a task of computer vision uses video as input, various information used for prediction, such as the environment surrounding the target and the internal state of the target, need to be estimated from the video in addition to predicting paths. Many prediction approaches that include understanding the environment and the internal state have been proposed. In this survey, we systematically summarize methods of path prediction that take video as input and and extract features from the video. Moreover, we introduce datasets used to evaluate path prediction methods quantitatively.Comment: DAPI 201

Single-marker and haplotype-based genome-wide association studies for the number of teats in two heavy pig breeds

The number of teats is a reproductive-related trait of great economic relevance as it affects the mothering ability of the sows and thus the number of properly weaned piglets. Moreover, genetic improvement of this trait is fundamental to parallelly help the selection for increased litter size. We present the results of single-marker and haplotypes-based genome-wide association studies for the number of teats in two large cohorts of heavy pig breeds (Italian Large White and Italian Landrace) including 3990 animals genotyped with the 70K GGP Porcine BeadChip and other 1927 animals genotyped with the Illumina PorcineSNP60 BeadChip. In the Italian Large White population, genome scans identified three genome regions (SSC7, SSC10, and SSC12) that confirmed the involvement of the VRTN gene (as we previously reported) and highlighted additional loci known to affect teat counts, including the FRMD4A and HOXB1 gene regions. A different picture emerged in the Italian Landrace population, with a total of 12 genome regions in eight chromosomes (SSC3, SSC6, SSC8, SSC11, SSC13, SSC14, SSC15, and SSC16) mainly detected via the haplotype-based genome scan. The most relevant QTL was close to the ARL4C gene on SSC15. Markers in the VRTN gene region were not significant in the Italian Landrace breed. The use of both single-marker and haplotype-based genome-wide association analyses can be helpful to exploit and dissect the genome of the pigs of different populations. Overall, the obtained results supported the polygenic nature of the investigated trait and better elucidated its genetic architecture in Italian heavy pigs

CAR-Net: Clairvoyant Attentive Recurrent Network

We present an interpretable framework for path prediction that leverages dependencies between agents' behaviors and their spatial navigation environment. We exploit two sources of information: the past motion trajectory of the agent of interest and a wide top-view image of the navigation scene. We propose a Clairvoyant Attentive Recurrent Network (CAR-Net) that learns where to look in a large image of the scene when solving the path prediction task. Our method can attend to any area, or combination of areas, within the raw image (e.g., road intersections) when predicting the trajectory of the agent. This allows us to visualize fine-grained semantic elements of navigation scenes that influence the prediction of trajectories. To study the impact of space on agents' trajectories, we build a new dataset made of top-view images of hundreds of scenes (Formula One racing tracks) where agents' behaviors are heavily influenced by known areas in the images (e.g., upcoming turns). CAR-Net successfully attends to these salient regions. Additionally, CAR-Net reaches state-of-the-art accuracy on the standard trajectory forecasting benchmark, Stanford Drone Dataset (SDD). Finally, we show CAR-Net's ability to generalize to unseen scenes.Comment: The 2nd and 3rd authors contributed equall