Dinamika Peran Indonesia Di Arf : Upaya Menyelaraskan Kepentingan Nasional Dengan Tekanan Stuktur Internasional

This study examines the driven factors of Indonesian involvement and developments in the ARF (ASEAN Regional Forum) by applying neo-classical realism perspective. The driven factors are both the external factors such as International structure, and internal ones such as political economic situation, regime interests, and leadership role that are giving impact to Indonesia's foreign policy implementations. The involvement of Indonesia in ARF is primarily influenced by a changing structure of International politics and security in Asia Pacific. In order to ensure the stability of the country that has been integrated into ASEAN, Indonesia is actively involved in the ARF. While, Indonesia's active participation in the multilateral forum is generally to show its role as a leading country in Southeast Asia, and try to balancing powers structure in the region through ASEAN. Thus, to understanding the driven factors of Indonesia's involvement in ARF are correspondence with neoclassical realism theory, which states that country's behavior in the International system needs to be interpreted by variables such as International structure and domestic factors

Characteristic Regularisation for Super-Resolving Face Images

Existing facial image super-resolution (SR) methods focus mostly on improving "artificially down-sampled" lowresolution (LR) imagery. Such SR models, although strong at handling artificial LR images, often suffer from significant performance drop on genuine LR test data. Previous unsupervised domain adaptation (UDA) methods address this issue by training a model using unpaired genuine LR and HR data as well as cycle consistency loss formulation. However, this renders the model overstretched with two tasks: consistifying the visual characteristics and enhancing the image resolution. Importantly, this makes the end-to-end model training ineffective due to the difficulty of back-propagating gradients through two concatenated CNNs. To solve this problem, we formulate a method that joins the advantages of conventional SR and UDA models. Specifically, we separate and control the optimisations for characteristics consistifying and image super-resolving by introducing Characteristic Regularisation (CR) between them. This task split makes the model training more effective and computationally tractable. Extensive evaluations demonstrate the performance superiority of our method over state-of-the-art SR and UDA models on both genuine and artificial LR facial imagery data

Symbolic Side-Channel Analysis for Probabilistic Programs

In this paper we describe symbolic side-channel analysis techniques for detecting and quantifying information leakage, given in terms of Shannon and Min Entropy. Measuring the precise leakage is challenging due to the randomness and noise often present in program executions and side-channel observations. We account for this noise by introducing additional (symbolic) program inputs which are interpreted probabilistically, using symbolic execution with parameterized model counting. We also explore an approximate sampling approach for increased scalability. In contrast to typical Monte Carlo techniques, our approach works by sampling symbolic paths, representing multiple concrete paths, and uses pruning to accelerate computation and guarantee convergence to the optimal results. The key novelty of our approach is to provide bounds on the leakage that are provably under- and over-approximating the real leakage. We implemented the techniques in the Symbolic PathFinder tool and we demonstrate them on Java programs

Unsupervised Person Re-identification by Soft Multilabel Learning

Although unsupervised person re-identification (RE-ID) has drawn increasing research attentions due to its potential to address the scalability problem of supervised RE-ID models, it is very challenging to learn discriminative information in the absence of pairwise labels across disjoint camera views. To overcome this problem, we propose a deep model for the soft multilabel learning for unsupervised RE-ID. The idea is to learn a soft multilabel (real-valued label likelihood vector) for each unlabeled person by comparing (and representing) the unlabeled person with a set of known reference persons from an auxiliary domain. We propose the soft multilabel-guided hard negative mining to learn a discriminative embedding for the unlabeled target domain by exploring the similarity consistency of the visual features and the soft multilabels of unlabeled target pairs. Since most target pairs are cross-view pairs, we develop the cross-view consistent soft multilabel learning to achieve the learning goal that the soft multilabels are consistently good across different camera views. To enable effecient soft multilabel learning, we introduce the reference agent learning to represent each reference person by a reference agent in a joint embedding. We evaluate our unified deep model on Market-1501 and DukeMTMC-reID. Our model outperforms the state-of-the-art unsupervised RE-ID methods by clear margins. Code is available at https://github.com/KovenYu/MAR.Comment: CVPR19, ora

Response dynamics of phosphorelays suggest their potential utility in cell signalling

Phosphorelays are extended two-component signalling systems found in diverse bacteria, lower eukaryotes and plants. Only few of these systems are characterized, and we still lack a full understanding of their signalling abilities. Here, we aim to achieve a global understanding of phosphorelay signalling and its dynamical properties. We develop a generic model, allowing us to systematically analyse response dynamics under different assumptions. Using this model, we find that the steady-state concentration of phosphorylated protein at the final layer of a phosphorelay is a linearly increasing, but eventually saturating function of the input. In contrast, the intermediate layers can display ultrasensitivity. We find that such ultrasensitivity is a direct result of the phosphorelay biochemistry; shuttling of a single phosphate group from the first to the last layer. The response dynamics of the phosphorelay results in tolerance of cross-talk, especially when it occurs as cross-deactivation. Further, it leads to a high signal-to-noise ratio for the final layer. We find that a relay length of four, which is most commonly observed, acts as a saturating point for these dynamic properties. These findings suggest that phosphorelays could act as a mechanism to reduce noise and effects of cross-talk on the final layer of the relay and enforce its input–response relation to be linear. In addition, our analysis suggests that middle layers of phosphorelays could embed thresholds. We discuss the consequence of these findings in relation to why cells might use phosphorelays along with enzymatic kinase cascades

The UK joint specialist societies guideline on the diagnosis and management of acute meningitis and meningococcal sepsis in immunocompetent adults.

Bacterial meningitis and meningococcal sepsis are rare conditions with high case fatality rates. Early recognition and prompt treatment saves lives. In 1999 the British Infection Society produced a consensus statement for the management of immunocompetent adults with meningitis and meningococcal sepsis. Since 1999 there have been many changes. We therefore set out to produce revised guidelines which provide a standardised evidence-based approach to the management of acute community acquired meningitis and meningococcal sepsis in adults. A working party consisting of infectious diseases physicians, neurologists, acute physicians, intensivists, microbiologists, public health experts and patient group representatives was formed. Key questions were identified and the literature reviewed. All recommendations were graded and agreed upon by the working party. The guidelines, which for the first time include viral meningitis, are written in accordance with the AGREE 2 tool and recommendations graded according to the GRADE system. Main changes from the original statement include the indications for pre-hospital antibiotics, timing of the lumbar puncture and the indications for neuroimaging. The list of investigations has been updated and more emphasis is placed on molecular diagnosis. Approaches to both antibiotic and steroid therapy have been revised. Several recommendations have been given regarding the follow-up of patients

Genome-wide association study identifies RNF123 locus as associated with chronic widespread musculoskeletal pain

BACKGROUND AND OBJECTIVES: Chronic widespread musculoskeletal pain (CWP) is a symptom of fibromyalgia and a complex trait with poorly understood pathogenesis. CWP is heritable (48%–54%), but its genetic architecture is unknown and candidate gene studies have produced inconsistent results. We conducted a genome-wide association study to get insight into the genetic background of CWP. METHODS: Northern Europeans from UK Biobank comprising 6914 cases reporting pain all over the body lasting >3 months and 242 929 controls were studied. Replication of three independent genome-wide significant single nucleotide polymorphisms was attempted in six independent European cohorts (n=43 080; cases=14 177). Genetic correlations with risk factors, tissue specificity and colocalisation were examined. RESULTS: Three genome-wide significant loci were identified (rs1491985, rs10490825, rs165599) residing within the genes Ring Finger Protein 123 (RNF123), ATPase secretory pathway Ca (2+) transporting 1 (ATP2C1) and catechol-O-methyltransferase (COMT). The RNF123 locus was replicated (meta-analysis p=0.0002), the ATP2C1 locus showed suggestive association (p=0.0227) and the COMT locus was not replicated. Partial genetic correlation between CWP and depressive symptoms, body mass index, age of first birth and years of schooling were identified. Tissue specificity and colocalisation analysis highlight the relevance of skeletal muscle in CWP. CONCLUSIONS: We report a novel association of RNF123 locus and a suggestive association of ATP2C1 locus with CWP. Both loci are consistent with a role of calcium regulation in CWP. The association with COMT, one of the most studied genes in chronic pain field, was not confirmed in the replication analysis

Combinatorial detection of autoreactive CD8+ T cells with HLA-A2 multimers: a multi-centre study by the Immunology of Diabetes Society T Cell Workshop

Aims/hypothesis: Validated biomarkers are needed to monitor the effects of immune intervention in individuals with type 1 diabetes. Despite their importance, few options exist for monitoring antigen-specific T cells. Previous reports described a combinatorial approach that enables the simultaneous detection and quantification of multiple islet-specific CD8+ T cell populations. Here, we set out to evaluate the performance of a combinatorial HLA-A2 multimer assay in a multi-centre setting. Methods: The combinatorial HLA-A2 multimer assay was applied in five participating centres using centralised reagents and blinded replicate samples. In preliminary experiments, samples from healthy donors were analysed using recall antigen multimers. In subsequent experiments, samples from healthy donors and individuals with type 1 diabetes were analysed using beta cell antigen and recall antigen multimers. Results: The combinatorial assay was successfully implemented in each participating centre, with CVs between replicate samples that indicated good reproducibility for viral epitopes (mean %CV = 33.8). For beta cell epitopes, the assay was very effective in a single-centre setting (mean %CV = 18.4), but showed sixfold greater variability across multi-centre replicates (mean %CV = 119). In general, beta cell antigen-specific CD8+ T cells were detected more commonly in individuals with type 1 diabetes than in healthy donors. Furthermore, CD8+ T cells recognising HLA-A2-restricted insulin and glutamate decarboxylase epitopes were found to occur at higher frequencies in individuals with type 1 diabetes than in healthy donors. Conclusions/interpretation Our results suggest that, although combinatorial multimer assays are challenging, they can be implemented in multiple laboratories, providing relevant T cell frequency measurements. Assay reproducibility was notably higher in the single-centre setting, suggesting that biomarker analysis of clinical trial samples would be most successful when assays are performed in a single laboratory. Technical improvements, including further standardisation of cytometry platforms, will likely be necessary to reduce assay variability in the multi-centre setting

Plant sterols and plant stanols in the management of dyslipidaemia and prevention of cardiovascular disease

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