Effects of auditory masking on speech fluency in aphasia and apraxia of speech: Immediate and delayed responses

The purpose of the present study is to characterize the fluency response to auditory masking in ten adults with aphasia, using a time series methodology to account for non-independence of repeated data points and allow for a more fine-grained characterization of individual response patterns

A simultaneous [11C]raclopride positron emission tomography and functional magnetic resonance imaging investigation of striatal dopamine binding in autism

The social motivation hypothesis of autism posits that autism spectrum disorder (ASD) is characterized by impaired motivation to seek out social experience early in life that interferes with the development of social functioning. This framework suggests that impaired mesolimbic dopamine function underlies compromised responses to social rewards in ASD. Although this hypothesis is supported by functional magnetic resonance imaging (fMRI) studies, no molecular imaging study has evaluated striatal dopamine functioning in response to rewards in ASD. Here, we examined striatal functioning during monetary incentive processing in ASD and controls using simultaneous positron emission tomography (PET) and fMRI. Using a bolus+infusion protocol with the D2/D3 dopamine receptor antagonist [11C]raclopride, voxel-wise binding potential (BPND) was compared between groups (controls=12, ASD=10) in the striatum. Striatal clusters showing significant between-group BPND differences were used as seeds in whole-brain fMRI general functional connectivity analyses. Relative to controls, the ASD group demonstrated decreased phasic dopamine release to incentives in the bilateral putamen and left caudate, as well as increased functional connectivity between a PET-derived right putamen seed and the precuneus and insula. Within the ASD group, decreased phasic dopamine release in the putamen was related to poorer theory-of-mind skills. Our findings that ASD is characterized by impaired striatal phasic dopamine release to incentives provide support for the social motivation hypothesis of autism. PET-fMRI may be a suitable tool to evaluate novel ASD therapeutics targeting the striatal dopamine system

Лексические средства связности в речи телеведущего в жанре интерактивной белорусскоязычной телебеседы

Материалы XII Междунар. науч. конф. студентов, магистрантов, аспирантов и молодых ученых, Гомель, 16–17 мая 2019 г

CryptoDex: a randomised, double-blind, placebo-controlled phase III trial of adjunctive dexamethasone in HIV-infected adults with cryptococcal meningitis: study protocol for a randomised control trial.

BACKGROUND: Cryptococcal meningitis (CM) is a severe AIDS-defining illness with 90-day case mortality as high as 70% in sub-Saharan Africa, despite treatment. It is the leading cause of death in HIV patients in Asia and Africa.No major advance has been made in the treatment of CM since the 1970s. The mainstays of induction therapy are amphotericin B and flucytosine, but these are often poorly available where the disease burden is highest. Adjunctive treatments, such as dexamethasone, have had dramatic effects on mortality in other neurologic infections, but are untested in CM. Given the high death rates in patients receiving current optimal treatment, and the lack of new agents on the horizon, adjuvant treatments, which offer the potential to reduce mortality in CM, should be tested.The principal research question posed by this study is as follows: does adding dexamethasone to standard antifungal therapy for CM reduce mortality? Dexamethasone is a cheap, readily available, and practicable intervention. METHOD: A double-blind placebo-controlled trial with parallel arms in which patients are randomised to receive either dexamethasone or placebo, in addition to local standard of care. The study recruits patients in both Asia and Africa to ensure the relevance of its results to the populations in which the disease burden is highest. The 10-week mortality risk in the control group is expected to be between 30% and 50%, depending on location, and the target hazard ratio of 0.7 corresponds to absolute risk reductions in mortality from 30% to 22%, or from 50% to 38%. Assuming an overall 10-week mortality of at least 30% in our study population, recruitment of 824 patients will be sufficient to observe the expected number of deaths. Allowing for some loss to follow-up, the total sample size for this study is 880 patients. To generate robust evidence across both continents, we aim to recruit roughly similar numbers of patients from each continent. The primary end point is 10-week mortality. Ethical approval has been obtained from Oxford University's Tropical Research Ethics Committee (OxTREC), and as locally mandated at each site. TRIAL REGISTRATION: International Standard Randomised Controlled Trial Number: ISRCTN59144167 26-July-2012

Business plan for an online marketplace company

This Bachelor thesis has been created with the purpose of assisting the author in creating a business plan for a real business idea. The study provides knowledge and practical information on what the business plan is about and how to write a business plan for a startup company. The theoretical framework consists of materials related to a business plan, the concept of Lean Canvas and the question of why a business plan is important for a startup company. It discusses what entrepreneurs should pay attention to while attempting to do business planning for their startup companies in Finland. The empirical section of the thesis is the actual business plan of an online marketplace company. The business plan is written using Lean Canvas based on the author’s knowledge base and the thesis’s theoretical background. It provides information on the business idea, customer segment, market research, value proposition and so on. The analysis of the results indicates that the business idea is viable, though it involves certain level of risks and profitability is a long-term target. Starting a business in Finland requires determination and careful planning. A comprehensive business plan will act as a guide for business development and direction. In this thesis, Lean Canvas business plan model is selected as the main layout for the business plan

Topics in Splines and Applications

Splines provide a significant tool for the design of computationally economical curves and surfaces for the construction of various objects like automobiles, ship hulls, airplane fuselages and wings, propeller blades, shoe insoles, bottles, etc. It also contributes in the description of geological, physical, statistical, and even medical phenomena. Spline methods have proven to be indispensable in a variety of modern industries, including computer vision, robotics, signal and image processing, visualization, textile, graphic designs, and even media. This book aims to provide a valuable source on splines and their applications. It focuses on collecting and disseminating information in various disciplines including computer-aided geometric design, computer graphics, data visualization, data fitting, power systems, clinical and epidemiologic studies, disease detection, regression curves, social media, and biological studies. The book is useful for researchers, scientists, practitioners, and many others who seek state-of-the-art techniques and applications using splines. It is also useful for undergraduate senior students as well as graduate students in the areas of computer science, engineering, health science, statistics, and mathematics. Each chapter also provides useful information on software developments and their extensions

Bootstrap confidence cones for directional data

International audienc

Deep learning models integrating multi-sensor and -temporal remote sensing to monitor landslide traces in Vietnam

Landslides pose significant threats to lives and public infrastructure in mountainous regions. Real-time landslide monitoring presents challenges for scientists, often involving substantial costs and risks due to challenging terrain and instability. Recent technological advancements offer the potential to identify landslide-prone areas and provide timely warnings to local populations when adverse weather conditions arise. This study aims to achieve three key objectives: (1) propose indicators for detecting landslides in both field and remote sensing images; (2) develop deep learning (DL) models capable of automatically identifying landslides from fusion data of Sentinel-1 (SAR) and Sentinel-2 (optical) images; and (3) employ DL-trained models to detect this natural hazard in specific regions of Vietnam. Twenty DL models were trained, utilizing three U-shaped architectures, which include U-Net and U-Net3+, combined with different data-fusion choices. The training data consisted of multi-temporal Sentinel images and increased the accuracy of DL models using Adam optimizer to 99% in landslide detection with low loss function values. Using two bands of the Sentinel-1 could not define the characteristics of landslide traces. However, the integration between Sentinel-2 data and these bands makes the landslide detection process more effective. Therefore, the authors proposed a consolidated strategy based on three models: (1) UNet using four S2-bands, (2) UNet3+ using four S2-bands, (3) UNet using four S2-bands and VV S1-band, and (4) UNet using four S2-bands and VH S1-band for fully detect landslides. This integrated strategy uses the capabilities of each model and overcomes model result constraints to better describe landslide traces in varied geographical locations