A Practical Algorithm for the Management of Superficial Folliculitis of the Scalp: 10 Years of Clinical and Dermoscopy Experience

Introduction: Superficial folliculitis of the scalp (SFS) is a common complaint in clinical practice, and initial presentation may be difficult to differentiate as they may appear very similar to each other. Objectives: The aim of this thesis is to describe the pathologies that occur clinically as folliculitis of the scalp, identify their causes and characteristics and create a standardized classification. Methods: This is a retrospective clinical, dermoscopic and histopathological study over 10 years of dermatologic consultations. Only individuals with a confirmed diagnosis of SFS (updated diagnostic criteria or biopsy) were included. Results: In this review, we describe the various clinical features of different causes of SFS in ninety-nine cases and divided into infectious due to fungus, bacteria, or virus and inflammatory conditions such as rosacea, acneiform eruption and Ofuji syndrome. Conclusions: The clinician must differentiate SFS from other underlying scarring disorders to prevent poorer outcomes. We created an algorithm to help the clinician reach a proper diagnosis

Relationships between paranoid thinking, self-esteem and the menstrual cycle.

This study aimed to investigate whether paranoid experiences and levels of self-esteem fluctuate over the menstrual cycle and whether levels of self-esteem are lower when perceived persecution is felt to be deserved. Measures of anxiety, depression, persecution, deservedness and self-esteem were completed on-line by 278 women over their menstrual cycle. Responses were compared at the paramenstrual (3 days before and after menses onset) and mid-cycle phase. At the paramenstrual phase persecution, negative self-esteem, anxiety and depression were higher and positive self-esteem was lower than at mid-cycle. A greater proportion of women experienced persecution as deserved at the paramenstrual phase. This was associated with higher depression and negative self-esteem scores. Increased levels of deservedness significantly strengthened the relationship between persecution and negative, but not positive, self-esteem. These findings suggest that the paramenstrual phase is a time of vulnerability to increased paranoid experiences, an increased likelihood that feelings of persecution will feel deserved and lowered self-esteem. The findings support the view that interpersonal sensitivities may be key to menstrual cycle symptoms and have an impact on relationships. Further, the study illustrated that ideas developed for psychosis could make a valuable contribution to understanding and managing this aspect of menstruation-related distress

Eco-friendly one-pot synthesis of Prussian blue-embedded magnetic hydrogel beads for the removal of cesium from water

A simple one-step approach to fabricating Prussian blue-embedded magnetic hydrogel beads (PBMHBs) was fabricated for the effective magnetic removal of radioactive cesium (Cs-137) from water. Through the simple dropwise addition of a mixed aqueous solution of iron salts, commercial PB and polyvinyl alcohol (PVA) to an ammonium hydroxide (NH4OH) solution, the formation of hydrogel beads and the encapsulation of PB in beads were achieved in one pot through the gelation of PVA with in situ-formed iron oxide nanoparticles as the cross-linker. The obtained PB-MHBs, with 43.77 weight %of PB, were stable without releasing PB for up to 2 weeks and could be effectively separated from aqueous solutions by an external magnetic field, which is convenient for the large-scale treatment of Cs-contaminated water. Detailed Cs adsorption studies revealed that the adsorption isotherms and kinetics could be effectively described by the Langmuir isotherm model and the pseudo-second-order model, respectively. Most importantly, the PB-MHBs exhibited excellent selectivity for Cs-137 in (137)Cscontaminated simulated groundwater (55 Bq/g) with a high removal efficiency (>99.5%), and the effective removal of Cs-137 from real seawater by these PB-MHBs demonstrated the excellent potential of this material for practical application in the decontamination of Cs-137-contaminated seawate

Consensus over Random Graph Processes: Network Borel-Cantelli Lemmas for Almost Sure Convergence

Distributed consensus computation over random graph processes is considered. The random graph process is defined as a sequence of random variables which take values from the set of all possible digraphs over the node set. At each time step, every node updates its state based on a Bernoulli trial, independent in time and among different nodes: either averaging among the neighbor set generated by the random graph, or sticking with its current state. Connectivity-independence and arc-independence are introduced to capture the fundamental influence of the random graphs on the consensus convergence. Necessary and/or sufficient conditions are presented on the success probabilities of the Bernoulli trials for the network to reach a global almost sure consensus, with some sharp threshold established revealing a consensus zero-one law. Convergence rates are established by lower and upper bounds of the $\epsilon$-computation time. We also generalize the concepts of connectivity/arc independence to their analogues from the $*$-mixing point of view, so that our results apply to a very wide class of graphical models, including the majority of random graph models in the literature, e.g., Erd\H{o}s-R\'{e}nyi, gossiping, and Markovian random graphs. We show that under $*$-mixing, our convergence analysis continues to hold and the corresponding almost sure consensus conditions are established. Finally, we further investigate almost sure finite-time convergence of random gossiping algorithms, and prove that the Bernoulli trials play a key role in ensuring finite-time convergence. These results add to the understanding of the interplay between random graphs, random computations, and convergence probability for distributed information processing.Comment: IEEE Transactions on Information Theory, In Pres

Search for new phenomena in final states with an energetic jet and large missing transverse momentum in pp collisions at √ s = 8 TeV with the ATLAS detector

Results of a search for new phenomena in final states with an energetic jet and large missing transverse momentum are reported. The search uses 20.3 fb−1 of √ s = 8 TeV data collected in 2012 with the ATLAS detector at the LHC. Events are required to have at least one jet with pT > 120 GeV and no leptons. Nine signal regions are considered with increasing missing transverse momentum requirements between Emiss T > 150 GeV and Emiss T > 700 GeV. Good agreement is observed between the number of events in data and Standard Model expectations. The results are translated into exclusion limits on models with either large extra spatial dimensions, pair production of weakly interacting dark matter candidates, or production of very light gravitinos in a gauge-mediated supersymmetric model. In addition, limits on the production of an invisibly decaying Higgs-like boson leading to similar topologies in the final state are presente

Semi-automatic algorithm for construction of the left ventricular area variation curve over a complete cardiac cycle

<p>Abstract</p> <p>Background</p> <p>Two-dimensional echocardiography (2D-echo) allows the evaluation of cardiac structures and their movements. A wide range of clinical diagnoses are based on the performance of the left ventricle. The evaluation of myocardial function is typically performed by manual segmentation of the ventricular cavity in a series of dynamic images. This process is laborious and operator dependent. The automatic segmentation of the left ventricle in 4-chamber long-axis images during diastole is troublesome, because of the opening of the mitral valve.</p> <p>Methods</p> <p>This work presents a method for segmentation of the left ventricle in dynamic 2D-echo 4-chamber long-axis images over the complete cardiac cycle. The proposed algorithm is based on classic image processing techniques, including time-averaging and wavelet-based denoising, edge enhancement filtering, morphological operations, homotopy modification, and watershed segmentation. The proposed method is semi-automatic, requiring a single user intervention for identification of the position of the mitral valve in the first temporal frame of the video sequence. Image segmentation is performed on a set of dynamic 2D-echo images collected from an examination covering two consecutive cardiac cycles.</p> <p>Results</p> <p>The proposed method is demonstrated and evaluated on twelve healthy volunteers. The results are quantitatively evaluated using four different metrics, in a comparison with contours manually segmented by a specialist, and with four alternative methods from the literature. The method's intra- and inter-operator variabilities are also evaluated.</p> <p>Conclusions</p> <p>The proposed method allows the automatic construction of the area variation curve of the left ventricle corresponding to a complete cardiac cycle. This may potentially be used for the identification of several clinical parameters, including the area variation fraction. This parameter could potentially be used for evaluating the global systolic function of the left ventricle.</p