Miracle-dz/UniFAR-FTUs huggingface dataset:
Making Sense of Listening: The IMAP Test Battery

The ability to hear is only the first step towards making sense of the range of information contained in an auditory signal. Of equal importance are the abilities to extract and use the information encoded in the auditory signal. We refer to these as listening skills (or auditory processing AP). Deficits in these skills are associated with delayed language and literacy development, though the nature of the relevant deficits and their causal connection with these delays is hotly debated. When a child is referred to a health professional with normal hearing and unexplained difficulties in listening, or associated delays in language or literacy development, they should ideally be assessed with a combination of psychoacoustic (AP) tests, suitable for children and for use in a clinic, together with cognitive tests to measure attention, working memory, IQ, and language skills. Such a detailed examination needs to be relatively short and within the technical capability of any suitably qualified professional. Current tests for the presence of AP deficits tend to be poorly constructed and inadequately validated within the normal population. They have little or no reference to the presenting symptoms of the child, and typically include a linguistic component. Poor performance may thus reflect problems with language rather than with AP. To assist in the assessment of children with listening difficulties, pediatric audiologists need a single, standardized child-appropriate test battery based on the use of language-free stimuli. We present the IMAP test battery which was developed at the MRC Institute of Hearing Research to supplement tests currently used to investigate cases of suspected AP deficits. IMAP assesses a range of relevant auditory and cognitive skills and takes about one hour to complete. It has been standardized in 1500 normally-hearing children from across the UK, aged 6-11 years. Since its development, it has been successfully used in a number of large scale studies both in the UK and the USA. IMAP provides measures for separating out sensory from cognitive contributions to hearing. It further limits confounds due to procedural effects by presenting tests in a child-friendly game-format. Stimulus-generation, management of test protocols and control of test presentation is mediated by the IHR-STAR software platform. This provides a standardized methodology for a range of applications and ensures replicable procedures across testers. IHR-STAR provides a flexible, user-programmable environment that currently has additional applications for hearing screening, mapping cochlear implant electrodes, and academic research or teaching.
An RFID Multicriteria Coarse- and Fine-Space Tag Antenna Design

A new optimization scheme combined with the space-mapping technology and the jumping-gene genetic algorithm (JGGA) is to replace the conventional direct genetic computational type of the optimization scheme for antenna designs. This utilizes the assumption that there is an equivalent linear mapping between the design-parameter ratio and the response ratio in two spaces on the condition that there is only a difference in simulation mesh setup between coarse and fine models of antennas. The design parameters and responses of an optimal individual in coarse space at each generation are collected during the JGGA parameter extraction. The above linear mapping is then used to produce candidates of new design parameters in fine space. A multicriteria decision-making selection strategy is employed to govern the optimization process. This scheme is applied to a novel radio frequency identification tag antenna with an artificial magnetic conductor ground. The operation results of the combination algorithm show great improvement in the optimization when compared with the previous work in the same field. Furthermore, the proposed antenna can show relatively tolerant reading distances in various platform environments through experiments.
Identification of nonliteral language in social media: A case study on sarcasm

With the rapid development of social media, spontaneously user‐generated content such as tweets and forum posts have become important materials for tracking people's opinions and sentiments online. A major hurdle for current state‐of‐the‐art automatic methods for sentiment analysis is the fact that human communication often involves the use of sarcasm or irony, where the author means the opposite of what she/he says. Sarcasm transforms the polarity of an apparently positive or negative utterance into its opposite. Lack of naturally occurring utterances labeled for sarcasm is one of the key problems for the development of machine‐learning methods for sarcasm detection. We report on a method for constructing a corpus of sarcastic Twitter messages in which determination of the sarcasm of each message has been made by its author. We use this reliable corpus to compare sarcastic utterances in Twitter to utterances that express positive or negative attitudes without sarcasm. We investigate the impact of lexical and pragmatic factors on machine‐learning effectiveness for identifying sarcastic utterances and we compare the performance of machine‐learning techniques and human judges on this task.
MONITOR THE USE OF ANTIBIOTICS IN INTENSIVE CARE UNITS WITH SPECIAL FOCUS ON RESTRICTED ANTIBIOTICS IN TERTIARY CARE HOSPITAL OF INDIA

Objective: The present study was to monitor the use of antibiotics with restricted antibiotics in intensive care units (ICUs). The aim of this study was to observe number of patients receiving antibiotic(s), to observe number of patient receiving restricted antibiotics(s), number of restricted antibiotic(s) forms filled in 48 hrs, observing number of instances where within three or more than three antibiotics given for more than 3 days, any adverse drug reaction and medication error related in ICUs. Methods: The study was done prospectively in ICUs of a tertiary care hospital. 200 patients were selected from ICUs on a random basis. The duration study was 6.5 months. All adult patients admitted in ICUs who received an antibiotic therapy within 24 hrs of admission were included. Outpatient department patients and patient admitted in the wards were not included in the study. Results: Among 200 patients, the total number of patients received antibiotic were 188 (94%), while 12 (6%) patients were not received. Among 188 patients, 51 patients received restricted antibiotics, i.e., 27.2% and 137 patients not received restricted antibiotic, i.e. 72.8%. Out of 188 patients received antibiotics including restricted antibiotics only 31 patients received three or more than three antibiotics for three or more than three days, which are 16.4% and 157 patients, not received three or more than three antibiotics for three or more than three days which were 83.6%. According to Antimicrobial Stewardship Program, physician prescribed restricted antibiotic must have to fill restricted antimicrobial form, among 51 patients, only 8 (15.6%) forms were received. Keywords: Antibiotics, Restricted antibiotics, Outpatient department, Antimicrobial stewardship program, Intensive care units.
About Learning in Recurrent Bistable Gradient Networks

Recurrent Bistable Gradient Networks are attractor based neural networks characterized by bistable dynamics of each single neuron. Coupled together using linear interaction determined by the interconnection weights, these networks do not suffer from spurious states or very limited capacity anymore. Vladimir Chinarov and Michael Menzinger, who invented these networks, trained them using Hebb's learning rule. We show, that this way of computing the weights leads to unwanted behaviour and limitations of the networks capabilities. Furthermore we evince, that using the first order of Hintons Contrastive Divergence algorithm leads to a quite promising recurrent neural network. These findings are tested by learning images of the MNIST database for handwritten numbers.
Efficient cooperative search of smart targets using UAV Swarms1

SUMMARY This work examines the Cooperative Hunters problem, where a swarm of unmanned air vehicles (UAVs) is used for searching one or more “evading targets,” which are moving in a predefined area while trying to avoid a detection by the swarm. By arranging themselves into efficient geometric flight configurations, the UAVs optimize their integrated sensing capabilities, enabling the search of a maximal territory.
Variation among populations of Diodia teres (Rubiaceae) in environmental maternal effects

Previous studies have quantified variation in environmental maternal effects (EME) within populations, but these effects could differ among populations as well. In this study we grew clonal replicates of individuals from three populations of the annual plant Diodia teres in their native and non‐native environments. Our goal was to estimate the effects of maternal environment and maternal population on seed and seedling traits. Seeds that were produced in this field study were then planted in two soil types to quantify effects of the offspring environment on seedling traits. There was substantial variation among populations for seed weight. We found population variation for EME, and maternal environment by offspring environment interactions. We conclude that variation among populations in EME may be an unrecognized component of local adaptation, and that attempts to control maternal effects by statistically accounting for variation in seed weight may be ineffective.
An economic evaluation of aripiprazole vs olanzapine adapted to the Italian setting using outcomes of metabolic syndrome and risk for diabetes in patients with schizophrenia

Objective To evaluate the cost-effectiveness of aripiprazole and olanzapine in patients with schizophrenia. Methods Data from a double-blind, randomized study demonstrating the efficacy of aripiprazole and olanzapine were used to observe new incidence of metabolic syndrome (26-week therapy) and to model the risk of developing diabetes over 5 years of therapy. Cumulative incidence of metabolic syndrome was compared using Kaplan–Meier estimates; diabetes risk was estimated using a validated, general population risk-prediction model. Economic assessment was conducted from the third-party payer perspective by evaluating pharmacotherapy costs of treating schizophrenia and medical costs associated with treating adverse metabolic effects in a hypothetical cohort of 1000 patients. Resource utilization and costs were derived from the underlying study and published data, using a 3% rate to discount costs and benefits. Results For the patients switched from olanzapine to aripiprazole, treatment with aripiprazole was a dominant cost-saving strategy. Use of aripiprazole avoided 184 events of metabolic syndrome over 26 weeks of treatment, contributing to a real-world (RW) cost savings of €2.53 per patient and a total savings of approximately €465.52 over a 5-year period. For the same cohort, the risk-prediction model indicated that 34 occurrences of diabetes could be avoided over 5 years, corresponding to a RW cost savings of €56.86 per patient and a total saving of approximately €1,933.24. These savings reflect avoided costs in treating adverse metabolic events and comparable costs in the acquisition of aripiprazole. Conclusions Maintenance aripiprazole therapy offers medical and economic benefits over olanzapine, reflected by reduced incidence of metabolic syndrome and diabetes and associated lower costs.
Effect of Dicycloplatin, a Novel Platinum Chemotherapeutical Drug, on Inhibiting Cell Growth and Inducing Cell Apoptosis

Dicycloplatin, a new supramolecular platinum-based antitumor drug, has been approved by the State Food and Administration (SFDA) of China. In this study, we investigated the anticancer activity of dicycloplatin in cancer cells and signaling pathways involved in dicycloplatin-induced apoptosis. Dicycloplatin inhibited the proliferation of cancer cells and increased the percentage of apoptosis in a concentration-dependent manner. Besides, some apoptosis related events were observed after treatment with dicycloplatin, including increase of reactive oxygen species (ROS), collapse of mitochondrial membrane potential (Δψm), release of cytochrome c from the mitochondria to the cytosol, upregulation of p53, which were accompanied by activation of caspase-9, caspase-3, caspase-8, and poly (ADP-ribose) polymerase cleavage in a concentration-dependent manner. The role of apoptosis in dicycloplatin-mediated cell death was further confirmed by the concomitant treatment with caspase-8 or caspase-9 inhibitors, which inhibited apoptosis and PARP cleavage. Intracellular glutathione (GSH) was also found to inhibit the cytotoxic effect of dicycloplatin. In conclusion, these findings suggest that dicycloplatin induces apoptosis through ROS stress-mediated death receptor pathway and mitochondrial pathway which is similar to carboplatin.
Does chronic victimization lead to a rejection attribution bias

ii ACKNOWLEDGEMENTS This project, from inception to completion, would not have been possible without the guidance and mentorship of Dr. Lauri Jensen-Campbell. I am grateful for her patience when I struggled, praise when I succeeded, and insistence on excellence and accuracy in every aspect of research. She has invested countless hours in teaching me the process of scientific research and writing, and I am thankful for her leadership. I also thank the members of my thesis committee, Dr. Angela Liegey-Dougall and Dr. Heidi Ewen, for their input and encouragement throughout the course of this project. I can not offer enough gratitude to the undergraduate research assistants who worked side-by-side with me during data collection and analysis, and offered support throughout the writing process. In particular I would like to thank Katharine Goodell and Linda Batto, whose exceptional quality of work and tireless dedication to the study was more than I could have ever hoped for. I am also grateful for the encouragement and assistance of Dr. Jennifer Knack and Madeline Rex-Lear, as well as a number of other graduate students. They each provided a unique perspective on graduate studies, kept me focused, offered valuable advice, and motivated me to press on in the face of obstacles. Finally, I am forever appreciative of the love and patience of Janell Farquhar, James Miller, Kathryn Hunt, and the many other friends and family members who have supported me in this process. Without them, I would never have started this journey.
An Efficient Reconfiguration Algorithm for Degradable VLSI/WSI Arrays

This paper considers the problem of reconfiguring two-dimensional degradable VLSI/WSI arrays under the constraint of row and column rerouting. The goal of the reconfiguration problem is to derive a fault-free subarray T from the defective host array such that the dimensions of T are larger than some specified minimum. This problem has been shown to be NP-complete under various switching and routing constraints. However, we show that a special case of the reconfiguration problem is optimally solvable in linear time. Using this result, a new fast and efficient reconfiguration algorithm is proposed. Empirical study shows that the new algorithm indeed produces good results in terms of the percentages of harvest and degradation of VLSI/WSI arrays.
The State Dependent Impact of Bank Exposure on Sovereign Risk

The theoretical literature remains inconclusive on whether changes in bank exposure towards the domestic sovereign have an adverse effect on the sovereign risk position via a diabolic loop in the sovereign-bank nexus or reduce perceived default risk by acting as a disciplinary device for the sovereign. In this paper we empirically analyze the impact of exogenous changes in bank exposure on the risk position of the sovereign within a Markov switching structural vector autoregressive in heteroscedasticity (MSH-SVAR) framework for a set of EMU countries. We add to the methodological literature by allowing for regime dependent shock transmissions according to the volatility state of the financial system. Finding support for both, a stabilizing and a destabilizing effect, we document a clear clustering among the country sample: Rising bank exposure increased default risk for the EMU periphery, but decreased credit risk for the core EMU countries during times of financial stress.
Reprogramming of primordial germ cells begins before migration into the genital ridge, making these cells inadequate donors for reproductive cloning

Germ cells undergo epigenetic modifications as they develop, which suggests that they may be ideal donors for nuclear transfer (cloning). In this study, nuclei from confirmed embryonic germ cells were used as donors to determine whether they are competent for cloning and at which stage they are most competent. Embryos cloned from migrating 10.5-days-postcoitum (dpc) primordial germ cells (PGCs) showed normal morphological development to midgestation but died shortly thereafter. In contrast, embryos cloned from later-stage germ cells were developmentally delayed at midgestation. Thus, donor germ cell age inversely correlated with the developmental stage attained by cloned embryos. The methylation status of the H19- and Snrpn-imprinting control regions in germ cell clones paralleled that of the donors, and revealed that demethylation, or erasure of imprints, was already initiated in PGCs at 10.5 dpc and was complete by 13.5 dpc. Similarly, clones derived from male 15.5-dpc germ cells showed increased methylation correlating with the initiation of de novo methylation that resets imprints at this stage, and clones from neonatal germ cells showed nearly complete methylation in the H19 imprinting control region. These results indicate that the epigenetic state of the donor nucleus is retained in cloned embryos, and that germ cells are therefore inadequate nuclear donors for cloning because they are either erasing or resetting epigenetic patterns.
Retrieval of Surface and Atmospheric Geophysical Variables over Snow-Covered Land from Combined Microwave and Infrared Satellite Observations

Surface temperature and emissivities, as well as atmospheric water vapor and cloud liquid water, have been calculated from Special Sensor Microwave Imager observations for snow-covered land areas using a neural network inversion scheme that includes first-guess information. A learning database to train the neural network is derived from a global collection of coincident surface and atmospheric parameters, extracted from the National Centers for Environmental Prediction reanalysis, from the International Satellite Cloud Climatology Project data, and from microwave emissivity atlases previously calculated. Despite the large space and time variability of the snow microwave response, the surface and atmospheric parameters are retrieved. Water vapor is estimated with a theoretical rms error of approximately 30%, verified against radiosonde measurements, that is almost the same as over snow-free land. The theoretical rms error of the surface skin temperature retrieval is 1.5 and 1.9 K, respectively, for clear and cloudy scenes. The surface skin temperatures are compared with the surface air temperatures measured at meteorological stations to verify that the expected differences are found. The space and time variations of the retrieved surface emissivities are evaluated by comparison with surface parameter variations such as surface air temperature, snow depth, and vegetation cover.
Clinical decision making in developmental language disorders

Considerations for Family-Guided Communication Assessment of Infants and Toddlers in Natural Environments Assessment of Pre-linguistic & Emerging Language Skills of Children with Developmental Language Disorders Assessment of Preschool & Early School-Aged Children with Developmental Language Disorders Assessment/Diagnosis of Adolescents and Young Adults: Spoken Language Disorders Assessment of Reading Comprehension and Written Expression in Adolescents and Adults Language Variation, Assessment, and Intervention Facilitation of Early Communicative Behaviors Syntax-Morphology Semantic Intervention: Enhancing Vocabulary Knowledge in Children with Language Impairment Addressing the Social Concomitants of Developmental Language Impairments Supporting the Development of Spoken Narrative Skills in Children with Language Impairment Early Literacy Development Spelling and Word-Level Reading: A Multilinguistic Approach Understanding and Remediating Text Comprehension Problems in School-Aged Children The Right to Write: Composition Instruction for Students with Language/Learning Disabilities Serving Secondary Students Facilitating Language Skills in Individuals Who Use Augmentative and Alternative Communication Legal Mandates: Impetus for Improving Assessment, Diagnosis, and Treatment of School-Age Children and Adolescents with Developmental Language Disorders Thoughts and Reflections on Developmental Language Disorders.
Оценка компаний при слияниях и поглощениях. Создание стоимости в частных компаниях / Valuation for M&A: Building Value in Private Companies

Эта книга концентрируется на практических вопросах оценки бизнеса компаний, относящихся к категории "закрытых" (ООО, ЗАО и т.д.). Простой и доступный язык позволяет понять общие принципы и методы, используемые при оценке бизнеса, необходимой не только для его покупки или продажи, но и в повседневной работе. При изложении алгоритмов оценки приводятся необходимые сведения фундаментального характера. Большое количество примеров, почерпнутых из обширной практики авторов, и подробное рассмотрение деталей дает возможность увидеть, как практически, шаг за шагом, выясняется стоимость предприятия. Эта книга без сомнения станет надежным навигатором-справочником в таком непростом деле, как оценка бизнеса. Книга заинтересует предпринимателей, менеджеров и аналитиков компаний любого размера, а также инвесторов и профессиональных оценщиков.
Hierarchical approach for abnormal acoustic event classification in an elevator

In this paper, we propose a hierarchical method to detect and classify abnormal acoustic events occurring in an elevator environment. The Gaussian Mixture Model (GMM) based event classifier essentially employs two types of acoustic features; Mel Frequency Cepstral Coefficient (MFCC) and Timbre. We explore the effectiveness of various combinations of the two features in terms of classification performance. In addition, we design a hierarchical approach for realizing acoustic event classification and compare it with a single-level approach. It can be verified from an experiment, that the classification performance is improved when the proposed hierarchical approach is applied. In particular, for detection of abnormal situations, we employ a maximum likelihood estimation approach for acoustic event recognition at the 1st step, and then on the 2nd step we determine the abnormal contexts by using the ratio of abnormal events to cumulative events during a certain period. For performance evaluation, we employ a database collected in an actual elevator under several scenarios. By experimental results, our proposed method demonstrates 91% correct detection rate and 2.5% error detection rate for abnormal context.
U-kitchen: application scenario

The research topic of U-spaces is drifting towards the practical implementation. We have presented application scenario of a ubiquitous kitchen environment. The scenario is made using some smart devices communicating to each other and sharing the context via a kitchen server. By addition of limited level of smartness in the appliances, ubiquitous services are developed that makes the job for an autonomous ubiquitous system far more easier and technical issues, less complex. One of our objectives in this paper is to increase the quality and reduce the link cost so that the convergence of large number of devices can be made possible.