Miracle-dz/UniFAR-FTUs huggingface dataset:
The psychosis high-risk state: a comprehensive state-of-the-art review.

CONTEXT During the past 2 decades, a major transition in the clinical characterization of psychotic disorders has occurred. The construct of a clinical high-risk (HR) state for psychosis has evolved to capture the prepsychotic phase, describing people presenting with potentially prodromal symptoms. The importance of this HR state has been increasingly recognized to such an extent that a new syndrome is being considered as a diagnostic category in the DSM-5. OBJECTIVE To reframe the HR state in a comprehensive state-of-the-art review on the progress that has been made while also recognizing the challenges that remain. DATA SOURCES Available HR research of the past 20 years from PubMed, books, meetings, abstracts, and international conferences. STUDY SELECTION AND DATA EXTRACTION Critical review of HR studies addressing historical development, inclusion criteria, epidemiologic research, transition criteria, outcomes, clinical and functional characteristics, neurocognition, neuroimaging, predictors of psychosis development, treatment trials, socioeconomic aspects, nosography, and future challenges in the field. DATA SYNTHESIS Relevant articles retrieved in the literature search were discussed by a large group of leading worldwide experts in the field. The core results are presented after consensus and are summarized in illustrative tables and figures. CONCLUSIONS The relatively new field of HR research in psychosis is exciting. It has the potential to shed light on the development of major psychotic disorders and to alter their course. It also provides a rationale for service provision to those in need of help who could not previously access it and the possibility of changing trajectories for those with vulnerability to psychotic illnesses.
Time-Sharing-Based Synchronization and Performance Evaluation of Color-Independent Visual-MIMO Communication

In the field of communication, synchronization is always an important issue. The communication between a light-emitting diode (LED) array (LEA) and a camera is known as visual multiple-input multiple-output (MIMO), for which the data transmitter and receiver must be synchronized for seamless communication. In visual-MIMO, LEDs generally have a faster data rate than the camera. Hence, we propose an effective time-sharing-based synchronization technique with its color-independent characteristics providing the key to overcome this synchronization problem in visual-MIMO communication. We also evaluated the performance of our synchronization technique by varying the distance between the LEA and camera. A graphical analysis is also presented to compare the symbol error rate (SER) at different distances.
Estimation of needle tip location using ultrasound image processing and hypoechoic markers

Ultrasound guidance is a common method used in procedures such as peripheral nerve blocks and biopsies. Accurate determination of the location of the needle tip is critical in many such procedures. Visual graduations on the needle may give an external estimate of the depth of the needle tip, but the tip itself may be difficult to find in the ultrasound image even with in-plane imaging. The needle tip echo may also be occluded by other hyperechoic regions in the image. The objective of the current work was to develop a simple technique to accurately estimate the location of the needle tip in an ultrasound image, using a set of hypoechoic reference markings on the shaft of the needle, with image processing to improve accuracy and minimize error. A unique set of discrete hypoechoic markings was made along the shaft of a 14-gauge (2.1 mm nominal outer diameter) needle to provide a number of needle location reference points in the ultrasound image. Ultrasound scans were obtained of the needle in agar-based tissue mimicking phantoms using an 8.0 MHz linear array. The resulting images were cropped and binarized using an intensity filter before morphological operations were applied to isolate the needle echo in the image. A straight line was fitted to the top edge of the needle echo and up to three adjacent reference markings were found along this line. These were then used to estimate the actual position of the tip in the image. The accuracy of the location was affected by the resolution of the ultrasound image and the probe frequency. Redundancy in the number of markings used increased the robustness of the technique.
Synthesis, Characterization and Corrosion Behavior of Isomers of Conducting Poly–Toluidine on Mild Steel in Acid Medium

Isomers of Poly-toluidine have been synthesized using chemical oxidation method at 0°C using potassium dichromate as oxidant and hydrochloric acid as dopant. The synthesized polymers were characterized using IR, UV, TGA, DTA, XRD and SEM. The AC conductivity of POT, PMT, and PPT showed that they were semiconducting in nature. The corrosion behavior of the polymer on mild steel in acidic medium was studied by using electrochemical techniques . The studies showed that the inhibition increased with increase in concentration and reaches an optimum efficiency. The study further revealed that the inhibition efficiency followed the order PMT>PPT>POT. Polarization studies indicated that these three polymers act as mixed type corrosion inhibitors and EIS study showed that the dominant coating mechanism follows kinetic controlled corrosion mechanism.
The Relationship between Postural Stability and Lower-Limb Muscle Activity Using an Entropy-Based Similarity Index

The aim of this study is to see if the centre of pressure (COP) measurements on the postural stability can be used to represent the electromyography (EMG) measurement on the activity data of lower limb muscles. If so, the cost-effective COP data measurements can be used to indicate the level of postural stability and lower limb muscle activity. The Hilbert–Huang Transform method was used to analyse the data from the experimental designed to examine the correlation between lower-limb muscles and postural stability. We randomly selected 24 university students to participate in eight scenarios and simultaneously measured their COP and EMG signals during the experiments. The Empirical Mode Decomposition was used to identify the intrinsic-mode functions (IMF) that can distinguish between the COP and EMG at different states. Subsequently, similarity indices and synchronization analyses were used to calculate the correlation between the lower-limb muscle strength and the postural stability. The IMF5 of the COP signals and the IMF6 of the EMG signals were not significantly different and the average frequency was 0.8 Hz, with a range of 0–2 Hz. When the postural stability was poor, the COP and EMG had a high synchronization with index values within the range of 0.010–0.015. With good postural stability, the synchronization indices were between 0.006 and 0.080 and both exhibited low synchronization. The COP signals and the low frequency EMG signals were highly correlated. In conclusion, we demonstrated that the COP may provide enough information on postural stability without the EMG data.
When do Support Vector Machines learn fast ?

We establish learning rates to the Bayes risk for support vector machines (SVM’s) with hinge loss. Since a theorem of Devroye states that no learning algorithm can learn with a uniform rate to the Bayes risk for all probability distributions we have to restrict the class of considered distributions: in order to obtain fast rates we assume a noise condition recently proposed by Tsybakov and an approximation condition in terms of the distribution and the reproducing kernel Hilbert space used by the SVM. For Gaussian RBF kernels with varying widths we propose a geometric noise assumption on the distribution which ensures the approximation condition. This geometric assumption is not in terms of smoothness but describes the concentration of the marginal distribution near the decision boundary. In particular we are able to describe nontrivial classes of distributions for which SVM’s using a Gaussian kernel can learn with almost linear rate. AMS classification: primary 68Q32, secondary 62G20, 62G99, 68T05, 68T10, 41A46, 41A99
Fertility and Early-Life Mortality: Evidence from Smallpox Vaccination in Sweden

We examine how the introduction of smallpox vaccination affected early-life mortality and fertility in Sweden during the first half of the 19th century. We demonstrate that parishes in counties with higher levels of smallpox mortality prior to the introduction of vaccination experienced a greater decline in infant mortality afterwards. Exploiting this finding in an instrumental-variable approach reveals that this decline had a negative effect on the birth rate, while the number of surviving children and population growth remained unaffected. These results suggest that the decline in early-life mortality cannot account for the onset of the fertility decline in Sweden.
A Sequential Multiplicative Extended Kalman Filter for Attitude Estimation Using Vector Observations

In this paper, a sequential multiplicative extended Kalman filter (SMEKF) is proposed for attitude estimation using vector observations. In the proposed SMEKF, each of the vector observations is processed sequentially to update the attitude, which can make the measurement model linearization more accurate for the next vector observation. This is the main difference to Murrell’s variation of the MEKF, which does not update the attitude estimate during the sequential procedure. Meanwhile, the covariance is updated after all the vector observations have been processed, which is used to account for the special characteristics of the reset operation necessary for the attitude update. This is the main difference to the traditional sequential EKF, which updates the state covariance at each step of the sequential procedure. The numerical simulation study demonstrates that the proposed SMEKF has more consistent and accurate performance in a wide range of initial estimate errors compared to the MEKF and its traditional sequential forms.
Expression variation and covariation impair analog and enable binary signaling control

Due to noise in the synthesis and degradation of proteins, the concentrations of individual vertebrate signaling proteins were estimated to vary with a coefficient of variation (CV) of approximately 25% between cells. This high variation enables population-level regulation of cell functions but abolishes accurate single-cell signal transmission. Here we measure cell-to-cell variability of relative protein abundance using quantitative proteomics of individual Xenopus laevis eggs and cultured human cells and show that variation is typically much lower, in the range of 5–15%, compatible with accurate single-cell transmission. Furthermore, we show that MEK and ERK expression covary which improves controllability of the fraction of cells that activate bimodal ERK signaling, arguing that covariation has a role in facilitating population-level control of binary cell-fate decisions. Together, our experimental and model data argues for a control principle whereby low covariation limits signaling noise for accurate control analog single-cell signaling. In contrast, increased covariation widens the stimulus-range over which external inputs can regulate binary cell activation, thereby enabling accurate control of the fraction of activated cells at the population level.
Microleakage under Orthodontic Metal Brackets Bonded with Three Different Bonding Techniques with/without Thermocycling

Introduction: The aim of this study was to compare the microleakage of beneath the orthodontic brackets bonded with 3 different bonding techniques and evaluate the effect of thermocycling. Methods: One hundred and twenty premolars were randomly divided into 6 groups, received the following treatment: group 1: 37% phosphoric acid gel+Unite primer+Unite adhesive, group 2: 37% phosphoric acid gel+ Transbond XT primer+Transbond XT adhesive, group 3: Transbond plus Self Etching Primer (TSEP)+Transbond XT adhesive. Groups 4, 5, and 6 were similar to groups 1, 2, and 3, respectively. Evaluation of microleakage was done following to thermocycling test. After bonding, the specimens were sealed with nail varnish except for 1 mm around the brackets and then stained with 0.5% basic fuchsine. The specimens were sectioned at buccolingual direction in 2 parallel planes and evaluated under a stereomicroscope to determine the amount of microleakage at bracket-adhesive and adhesive-enamel interfaces from gingival and occlusal margins. Results: Microleakage was observed in all groups, and increased significantly after thermocycling at some interfaces of Unite adhesive group and conventional etching+Transbond XT adhesive group, but the increase was not significant in any interface of TSEP group. With or without thermocycling, TSEP displayed more microleakage than other groups. In most groups, microleakage at gingival margin was significantly higher than occlusal margin. Conclusion: Thermocycling and type of bonding technique significantly affect the amount of microleakage.
Altered Circadian Rhythms and Breast Cancer: From the Human to the Molecular Level

Circadian clocks are fundamental, time-tracking systems that allow organisms to adapt to the appropriate time of day and drive many physiological and cellular processes. Altered circadian rhythms can result from night-shift work, chronic jet lag, exposure to bright lights at night, or other conditioning, and have been shown to lead to increased likelihood of cancer, metabolic and cardiovascular diseases, and immune dysregulation. In cases of cancer, worse patient prognoses and drug resistance during treatment have also been observed. Breast, colon, prostate, lung, and ovarian cancers and hepatocellular carcinoma have all been linked in one way or another with altered circadian rhythms. Critical elements at the molecular level of the circadian system have been associated with cancer, but there have been fairly few studies in this regard. In this mini-review, we specifically focus on the role of altered circadian rhythms in breast cancer, providing an overview of studies performed at the epidemiological level through assessments made in animal and cellular models of the disease. We also address the disparities present among studies that take into account the rhythmicity of core clock and other proteins, and those which do not, and offer insights to the use of small molecules for studying the connections between circadian rhythms and cancer. This article will provide the reader with a concise, but thorough account of the research landscape as it pertains to altered circadian rhythms and breast cancer.
Model Learning for Probabilistic Movement Primitives

Probabilistic Movement Primitives (ProMPs) provide a framework for representing distributions over robot movement trajectories, combining or altering those distributions and deriving motor signals which lead to a reproduction of the encoded movements. In order to derive those signals for a given robot, a linear model of the robot dynamics is required. If the robot dynamics are known, such a linear model can be obtained by linearizing the non-linear dynamics for the current joint configuration of the robot. If the robot dynamics are unknown, one can try to derive them from the movement data with which the ProMP was created. This thesis presents and evaluates different Machine Learning methods which can be used to learn linear models for calculating motor signals of ProMPs as well as approaches to facilitate the reproduction of trajectory distributions despite the presence of errors in the learned models. Zusammenfassung Probabilistic Movement Primitives (ProMPs) bieten die Möglichkeit Wahrscheinlichkeitsverteilungen über Bewegungstrajektorien von Roboterbewegungen darzustellen, diese zu manipulieren oder zu kombinieren und Motorsignale herzuleiten, die diese Wahrscheinlichkeitsverteilungen reproduzieren. Um die erwähnten Signale für einen Roboter herzuleiten, wird ein lineares Model von dessen Dynamik benötigt. Wenn die entsprechenden, zumeist nichtlinearen, Dynamikgleichungen bekannt sind, kann das lineare Model durch Linearisierung der Dynamikgleichungen für den aktuellen Roboterzustand erhalten werden. Wenn die Dynamikgleichungen jedoch unbekannt sind, kann man versuchen, diese aus den Bewegungsdaten herzuleiten, mit denen die ProMP erstellt wurde. In dieser Arbeit werden verschiedene Machine Learning Methoden zum Lernen von linearen Modellen für die Berechnung von Motorsignalen für ProMPs sowie Ansätze, um die Reproduktion von Wahrscheinlichkeitsverteilungen über Trajektorien trotz Fehlern in den gelernten Modellen zu ermöglichen, vorgestellt und evaluiert.
Applying clustering coefficient to the pattern of international author collaboration in neuroimmunology and neuroinflammation

Aim: To apply cluster coefficient (CC) to the pattern of international author collaborations in neuroimmunology and neuroinflammation using data from Medline and to visualize results using Google maps and social network analysis (SNA). Methods: Selecting 2799 abstracts, author names, countries, and keywords on January 22, 2018 from Medline based on keyword neuroimmunology (or neuroinflammation) within the article title since 1982, we reported following features: (1) nation distribution for the 1st author’s nationality; (2) eminent journals and authors in the field of neuroimmunology and neuroinflammation; (3) notable keywords defined by authors representing both neuroimmunology and neuroinflammation; and (4) CCs in networks. We programmed Microsoft Excel VBA routines to extract data from Medline and used Google Maps and SNA Pajek software to display graphical representations with an easy-to-read feature for readers. Results: We found that: (1) the most number of papers in neuroimmunology and neuroinflammation are from the USA (902, 32.23%) and China (363, 12.97%); (2) the productive journals and authors in neuroimmunology and neuroinflammation are J Neuroinflammation and PLoS One, and Michael T. Heneka (Germany) and Richard M. Ransohoff (USA); (3) the most linked keywords are interleukin (IL), IL-1beta, and blood brain barrier; (4) author networks present higher CC than those nation networks. Conclusion: SNA provides wide and deep insight into the relationships among nations in co-author collaboration. The results can help readers in future submission to a journal in neuroimmunology and neuroinflammation.
Rethinking Children's Advertising Policies for the Digital Age

This article describes major changes in how video content and advertising is delivered to consumers. Digital technologies such as broadband allow consumers to stream or download programming. Smart phones and tablets allow consumers to view screen content virtually anywhere at any time. Advertising has become personalized and integrated with other content. Despite these major changes in the media markets, the framework for regulating advertising to children has not changed very much since the 1990s. This article argues that the existing regulatory framework must be reinvented to protect children in the digital age. It uses Google’s recently introduced YouTube Kids app (“YTK”), which is designed for use by children aged 5 and under, to illustrate a range of unfair or deceptive marketing practices – such as unboxing videos, brand channels, and influencer videos. Many of the videos available on the YTK app, would violate the FCC’s children’s television rules if they were shown on broadcast or cable television. The article describes the relative roles and effectiveness of the FCC and FTC in preventing advertising that takes advantage of children, who because their cognitive abilities are still developing, do not distinguish advertising from other content or understand the purpose of advertising. It identifies the traditional rationales for limiting advertising to children and finds that the same or greater concerns exist today. Finally, it discusses the prospects for updating protections for children in the digital age.
Pattern Type Example Derived Clauses Basic Patterns

Biomedical open information extraction (OpenIE) is an important task to extract rich structured information from biomedical literature. Previous work on OpenIE in general domain are restricted to subject-verb-oject relationships. Moreover, they ignore the entity type information, which leads to noisy and redundant output. Recent work on texture meta-pattern extraction produce structured nary relationships, but cannot deal with long and complicated sentence structures. We propose a framework that first resolve the long and complicated sentence structures and then use texture meta-patterns to extract the n-ary tuples with typed entities and their relationships. Our method achieves the highest precision in comparison with the state-of-the-art baselines, and keeps the distinctiveness and simplicity of extracted tuples. This work shows great promise in automatically extracting rich structured information from biomedical literature with high quality.
Level crossing analysis of the stock markets

We investigate the average frequency of positive slope να+ crossing for the returns of market prices. The method is based on stochastic processes in which no scaling feature is explicitly required. Using this method we define a new quantity to quantify the stage of development and activity of stock exchanges. We compare the Tehran and western stock markets and show that some, such as the Tehran (TEPIX) and New Zealand (NZX) stock exchanges, are emerging, and also that TEPIX is a non-active market and is financially motivated to absorb capital.
SMART: Saliency Map, Moments and Texture Features for Robust Image Authentication

: Image Authentication is the process of providing proof to a person or system that the images are indeed that claims to be. Image hashing is a technique used for image authentication and is very popular and ensures remarkable results. Global and Local feature extraction is enhanced for generating a hash that is sensitive to image content. Normal manipulations like JPEG coding, rotation, cropping, additive noise, gamma correction and scaling are robust enough so that the image content information can be recognized as authentic even if the image intensity is varied by these operations. The concern regarding content preserved hashing is that the salient regions need to be detected accurately so that local feature extraction can be applied in to the region of interest. A hybrid approach consisting of frequency prior, center prior and location prior along with watershed for segmentation is used for extracting the saliency regions in the image more efficiently with increasing localization capability in less hash length.
Tunicamycin, a new antibiotic. I. Isolation and characterization of tunicamycin.

Tunicamycin is a new antiviral antibiotic produced by Streptomyces lysosuperificus, nov. sp. The active substance in culture broth is purified by solvent extraction followed by chromatography on silicic acid. It has a molecular weight of about 870. The antibiotic is active against animal and plant viruses, Gram-positive bacteria, yeast and fungi. Tunicamycin is similar in some properties to a few known antibiotics but differs from them in certain special characteristics.