Stop as a next-to-lightest supersymmetric particle in constrained MSSM

So far the squarks have not been detected at the LHC indicating that they are heavier than a few hundred GeVs, if they exist. The lighter stop can be considerably lighter than the other squarks. We study the possibility that a supersymmetric partner of the top quark, stop, is the next-to-lightest supersymmetric particle in the constrained supersymmetric standard model. Various constraints, on top of the mass limits, are taken into an account, and the allowed parameter space for this scenario is determined. Observing stop which is the next-to-lightest supersymmetric particle at the LHC may be difficult.Comment: v2: A few references, a plot indicating used parameters, discussion about the role of parameters in determination of the stop NLSP, CCB minima and a comment about (g-2) added. Typos corrected. Version in PR

How Sovereign is Sovereign Credit Risk?

We study the nature of sovereign credit risk using an extensive sample of CDS spreads for 26 developed and emerging-market countries. Sovereign credit spreads are surprisingly highly correlated, with just three principal components accounting for more than 50 percent of their variation. Sovereign credit spreads are generally more related to the U.S. stock and high-yield bond markets, global risk premia, and capital flows than they are to their own local economic measures. We find that the excess returns from investing in sovereign credit are largely compensation for bearing global risk, and that there is little or no country-specific credit risk premium. A significant amount of the variation in sovereign credit returns can be forecast using U.S. equity, volatility, and bond market risk premia.

Peningkatan Penanganan Pengangkutan Barang Berbahaya di Bidang Pelayaran

Dalam rangka meningkatkan penanganan pengangkutan barang berbahaya di bidang pelayaran yang berhubungan dengan kepentingan masyarakat / stakeholder pelayaran, berbagai jenis dan bentuk pelayanan diberikan unit kerja pemerintah dalam hal ini Kementerian Perhubungan, namun masih dirasakan belum efektif dan efisien dalam pelaksanaannya. Oleh karena itu pengukuran kualitas pelayanan menjadi penting untuk mengevaluasi kinerja pelayanan yang telah dilakukan oleh unit kerja di pelabuhan. Kegiatan survei dilakukan kepada kinerja kesyahbandaran/ KPLP, Penyelenggara Pelabuhan PT. Pelindo, Ekspedisi Muatan Kapal Laut (sea freight forwarder), nakhoda dan mualim. Di fokuskan untuk menjawab identifikasi tentang kondisi eksisting pelayanan penanganan pengangkutan barang berbahaya di bidang pelayaran, hasil pengukuran untuk jenis pelayanan pengangkutan barang berbahaya yang diberikan unit kerja adalah upaya untuk memperbaiki kinerja pelayanan yang diberikan oleh pemerintah kepada masyarakat pelayaran. Penelitian ini menggunakan pendekatan kuantitatif dan kualitatif untuk menganalisis berbagai fenomena yang terjadi dalam proses pemberian pelayanan penanganan pengangkutan barang berbahaya. Data-data sesuai dengan indikator penelitian terdiri dari data primer kualitatif yang diperoleh langsung dari sumbernya,berupa hasil wawancara, observasi, dan dokumen dari narasumber yang terlibat langsung atas pemberian pelayanan penanganan pengangkutan barang berbahaya dari pemerintah

Evaluating prediction models for electricity consumption

This paper presents a system for visualizing electricity consumptiondata along with the implementation of a pattern recognition approach for peakprediction. Various classification algorithms and machine learning techniques aretested and discussed; in particular, Support Vector Machine (SVM), GaussianMixture Model (GMM) and hierarchical classifiers. Most notably, the bestalgorithms are able to detect 70% of the peaks occurring within the next 24 hours.Also, various ways of correlating energy consumption are considered in the presentcontext. Finally, a few directions for future work are discussed

The Dynamics of Sedimentary Systems and the Whimsicality of Policy Processes

Background, Aims, and Scope. Sediment management in coastal zones is taking place in high complex environments. Present management options do not have a sophisticated way of dealing with the actual complexity of the physical and the social systems and with the unpredictability that is inherent with these systems. Therefore, a new approach in both policy making and sediment management is needed that takes this complexity into account. The aim of this article is to explore the dynamics in social and natural systems and to draw the contours of this new approach for policy processes and sediment management that fits to the dynamics of the systems. Results and Discussion. The case studies show that chance events can occur in the biophysical and in the social system. In the three cases, players or actors in the decision process are left with the choice to adapt themselves to the occurring chance events or to refrain from any adaptive behaviour. Chance events can open up new possibilities by activating (new) actors and by coupling to new issues. If the situation is too locked-in (i.e. a stalemate) and is intentional on behalf of the actors, than the chance event will have no effect. T

Numerical modeling and validation of hydrothermal liquefaction of a lignin particle for biocrude production

publishedVersio

Relapse in clinically stable adult patients with schizophrenia or schizoaffective disorder: evidence-based criteria derived by equipercentile linking and diagnostic test accuracy meta-analysis

Background There is no consensus on defining relapse in schizophrenia, and scale-derived criteria with unclear clinical relevance are widely used. We aimed to develop an evidence-based scale-derived set of criteria to define relapse in patients with schizophrenia or schizoaffective disorder. Methods We searched the Yale University Open Data Access (YODA) for randomised controlled trials (RCTs) in clinically stable adults with schizophrenia or schizoaffective disorder, and obtained individual participant data on Positive and Negative Syndrome Scale (PANSS), Clinical Global Impression Severity (CGI-S), Personal and Social Performance (PSP), and Social and Occupational Functioning Assessment Scale (SOFAS). Our main outcomes were PANSS-derived criteria based on worsening in PANSS total score. We examined their relevance using equipercentile linking with CGI-S and functioning scales, and their test-performance in defining relapse with diagnostic test accuracy meta-analysis against CGI-S worsening (≥1-point increase together with a score ≥4 points) and psychiatric hospitalisation. Findings Based on data from seven RCTs (2354 participants; 1348 men [57·3%] and 1006 women [42·7%], mean age of 39·5 years [SD 12·0, range 17–89]; 303 Asian [12.9%], 255 Black [10.8%], 1665 White [70.7%], and other or unspecified 131 [5.6%]), an increase of 12 points or more in PANSS total (range 30–210 points) corresponded to clinically important deterioration in global severity of illness (≥1 point increase in CGI-S, range 1–7) and functioning (≥10 points decline in PSP or SOFAS, range 1–100). The interpretation of percentage changes varied importantly across different baseline scores. An increase of 12 points or more in PANSS total had good sensitivity and specificity using CGI-S as reference standard (sensitivity 82·1% [95% CI 77·1–86·4], specificity 86·9% [82·9–90·3]), as well as good sensitivity but lower specificity compared to hospitalisation (sensitivity 81·7% [74·1–87·7], specificity 69·2% [60·5–76·9]). Requiring either an increase in PANSS total or in specific items for positive and disorganization symptoms further improved test-performance. Cutoffs for situations where high sensitivity or specificity is needed are presented. Interpretation An increase of either 12 points or more in the PANSS total score, or worsening of specific positive and disorganisation symptom items could be a reasonable evidence-based definition of relapse in schizophrenia, potentially linking symptoms used to define remission and relapse. Percentage changes should not be used to define relapse because their interpretation depends on baseline scores. Funding German Research Foundation (grant number: 428509362)