Miracle-dz/UniFAR-FTUs huggingface dataset:
The Relationship between Maternal Biosocial Determinants and Infant Birth Weight

Background & aim: Low birth weight (LBW) is the center of focus as a cause of many social, emotional, and mental deficiencies. The identification of the probable causes of LBW is considered as an important measure in reducing the prevalence of this health problem. Regarding this, the present study was carried out to compare some of the mental and social traits in the mothers of normal weight newborns and those with LBW neonates. Methods: This cross-sectional study was conducted on the parents of 400 neonates selected by the proportional sampling technique in Isfahan, Iran. The participants were assigned into two groups of mothers including 200 subjects with LBW neonate and 200 cases with normal birth weight newborns. The data were collected using the Depression, Anxiety, and Stress Scale (DASS-42) developed by Lavibond and Lavibond in 1995 and the couple satisfaction index. Results: According to the results of the study, there was a significant difference between the two groups of mothers in terms of depression, stress, anxiety, age, medicine consumption, level of education, and marital satisfaction (P<0.001). However, the history of urinary tract infection was not significantly different between the two groups. Conclusion: As the findings of this study revealed, different aspects of maternal mental health can affect the pregnancy outcome through many pathways. Regarding this, the implementation of the interventions improving the maternal mental health might be useful in the reduction of the neonatal and pediatric mortality and morbidity.
The Human Capital That Matters: Expected Returns and High-Income Households

We propose a novel human capital model that decomposes aggregate income risk into high- and low-income risk. We find that high-income risk is priced, while low-income risk is insignificant. The high-income factor alone explains 77% of the cross-sectional variation in the twenty-five size and book-to-market portfolios, earns a risk premium of about 7% per year, and its pricing power extends to the full cross-section of individual stocks. It is also related to the value factor, suggesting that the value premium might be compensation for income risk. Overall, our evidence indicates that high-income risk is an important macroeconomic risk factor.
FACTORS AFFECTING RESTAURANT PURCHASE OF LOCALLY GROWN FOOD: A BINARY LOGIT ANALYSIS

This thesis uses primary survey data to identify and characterize the various types of New Hampshire food service establishments currently sourcing local food products ("local" being grown or raised in New England) and to assess the potential for increasing intermediate purchase of locally grown food products. Results from a recent direct-to-consumer survey revealed that consumers in northern New England have a negative propensity to consume produce that is purchased directly from growers or farmers markets, but consumers had a positive propensity to consume local and organically grown items overall. In other words, consumers in New England would like options for consuming local besides purchasing directly from farmers. Increasing local sourcing to intermediate channels, such as food service establishments, may help lower the opportunity cost of buying local food products for consumers. Currently, there is an information gap between New Hampshire restaurants and local food producers. This study examines which variables contribute to the likelihood that a New Hampshire food service establishment will make a local food purchase. The implementation of a state-wide survey is used to help examine various restaurant characteristics, perceptions, and practices that affect purchasing decisions for local food products. Based on previous research, it is hypothesized that small-midsized restaurants (serving less than 1,750 meals per week) will be more likely to source local food products. The data set is drawn from a survey of New Hampshire establishments with help from hospitality associations, state agencies, and individual restaurateur contacts. In the binary logistic regression model, a threshold parameter for the dependent variable is used. The dependent variable represents one of two values: y=1 when the respondent’s percentage of monthly local food purchases is 41%, and y=0 when the respondent’s percentage of monthly local food purchases is. The threshold parameter is based on the average percentage of monthly purchases of locally grown food products among foodservice establishments found by the Food Processing Center study. This screening process prevents establishments purchasing small percentages of local food from being classified as local buyers; therefore, the model identifies characteristics of only the major purchasers in the market. The model estimates revealed a negative propensity to consume local for restaurants serving less than 750 meals per week. The results also implied that restaurants that have been making food purchasing decisions longer than two years have a negative propensity to buy local. The significant negative coefficients on “length of autonomy” may be capturing the aversion to changing time withstanding business practices. The composite variables, Impacts, and Production were found to have a significant and positive effect on the propensity to buy local. Advocating the importance of personally knowing who and where their food came from may help increase intermediate purchase of locally grown food products.
Controlling International Joint Ventures: An Investigation of Australian Parent Partners

International joint ventures (IJVs) are an important modern organisational form, with their complexity presenting significant management and control issues. Our research uses a cross-sectional survey of Australian parent partners of IJVs to provide insights into the characteristics of Australian companies and their IJVs, performance outcomes and choices of parent partners management control systems (MCS) design in terms of operational areas they seek to control (focus), the extent to which they exercise control (extent) and the mechanisms of control used (formal and informal). Australian parent partners of IJVs generally are, partnering in countries close to Australia in the Asia-Pacific, in activities similar to those they undertake in Australia, contributing a significant amount of resources, but overall have only limited IJV experience. Australian parent partners focus on a limited set of controls, often with tighter formalised control structures. Finally, overall they are satisfied with the performance of their IJVs, with higher satisfaction for organisational learning and product/customer dimensions than financial performance.
Metrology of complex refractive index for solids in the terahertz regime using frequency domain spectroscopy

Frequency domain spectroscopy allows an experimenter to establish optical properties of solids in a wide frequency band including the technically challenging 10 THz region, and in other bands enabling metrological comparison between competing techniques. We advance a method for extracting the optical properties of high-index solids using only transmission-mode frequency domain spectroscopy of plane-parallel Fabry–Perot optical flats. We show that different data processing techniques yield different kinds of systematic error, and that some commonly used techniques have inherent systematic errors which are underappreciated. We use model datasets to cross-compare algorithms in isolation from experimental errors, and propose a new algorithm which has qualitatively different systematic errors to its competitors. We show that our proposal is more robust to experimental non-idealities such as noise or apodization, and extract the complex refractive index spectrum of crystalline silicon as a practical example. Finally, we advance the idea that algorithms are complementary rather than competitive, and should be used together as part of a toolbox for better metrology.
Use of natural antioxidants in dairy and meat products: a review of sensory and instrumental analyses

Oxidative deterioration is a significant contributing factor to the limited shelf life of foods containing lipids. The lipids in meats and dairy products make them susceptible to oxidation, limiting the amount of time that such products can be stored before a change in the sensory properties is evident. The use of rosemary oleoresin in meat products and fried foods has been extensively researched and used in commercialized foods. Since dry cheese and dairy products also contain lipids that are highly susceptible to oxidation, the use of a natural rosemary oleoresin may be beneficial in increasing the shelf life and sensory acceptability of these products as well. The overall objective of this report was to review the uses of a natural antioxidant, rosemary oleoresin, to inhibit oxidation and sensory changes in dairy and meat products and determine which areas need further study.
A broad-band signal control in sound reproduction system by temperature compensation of room impulse responses

We describe a method of compensating temperature fluctuation by linear-time-warping processing in a sound reproduction system. This technique is applied to impulse responses of room transfer functions, to achieve a high-quality sound reproduction system, particularly one that treats high-frequency components. First, the impulse responses of room transfer functions are measured before and after temperature fluctuation, and the former are converted into the latter by the proposed process. Next, we design inverse filters for the system, and evaluate the improvement of the reproduction accuracy and spectrum distortion. By using adequate warping ratio, we can improve the reproduction accuracy at any frequency.
DEVELOPMENT AND CHARACTERIZATION OF POLYVINYLIDENE FLUORIDE-IMIDAZOLIUM FUNCTIONALIZED POLYSULFONE BLEND ANION EXCHANGE MEMBRANE

Anion exchange membrane (AEM) is one of the core components of an alkaline fuel cell influencing the fuel cell’s performance, durability and stability. Out of the many anion exchange membranes reported so far, imidazolium functionalized polysulfone (PSf-ImOH) membrane has been identified to have high hydroxide ionic conductivity, reaching up to 50 mS cm at 20C. However, at high levels of ion exchange capacity, the membrane’s water uptake and swelling ratio increases significantly with temperature thus destabilizing it and making it unfit for potential use in high temperature alkaline fuel cells. This limitation of PSf-ImOH membranes has been overcome by blending it with polyvinylidene fluoride (PVDF) polymer, which is a thermally stable and highly hydrophobic polymer. PSf-ImOH membrane with a high degree of chloromethylation (180%) was synthesized and blended with PVDF at different weight ratios (PVDF / PSf-ImOH: 30/70, 50/50 and 70/30) to create a series of novel anion exchange membranes. The prepared membranes were characterized to study their structure, water uptake, swelling ratio, solubility in low boiling water soluble solvents, thermal stability, ion exchange capacity (IEC) and ionic conductivity (IC) at different temperatures. The 70% PVDF blend membrane demonstrated the better performance in terms of IEC, IC and water uptake properties compared to other membranes. Comparative studies on the water uptake and IC variation between the 70% PVDF blend membrane and pure PSfImOH membrane (having the same IEC as that of the blend membrane), clearly indicated the superiority and the promising use of the blend membrane in alkaline fuel cell especially for high temperature working condition.
Running head : SPEED-ACCURACY TRADEOFFS IN HUMAN SPEECH PRODUCTION Distribution A : Public Release 1 Speed-Accuracy Tradeoffs in Human Speech Production

Motor actions in speech production are both rapid and highly dexterous, even though speed and accuracy are often thought to conflict. Fitts’ law has served as a rigorous formulation of the fundamental speed-accuracy tradeoff in other domains of human motor action, but has not been directly examined in the domain of speech production. The present work seeks evidence for Fitts’ law in speech articulation kinematics by analyzing USC-TIMIT, a large database of real-time magnetic resonance imaging data of speech production. A theoretical framework for considering Fitts’ law in the domain of speech production is elucidated. Methodological challenges in applying Fitts-style analysis are addressed, including the definition and operational measurement of key variables in real-time MRI data. Results suggest the presence of clear tradeoffs between speed and accuracy for certain types of speech production actions, with wide variability across syllable position, and substantial variability also across subjects. Coda consonant targets immediately following the syllabic nucleus show the strongest evidence of this tradeoff, with correlations as high as 0.72 between movement time and difficulty. Results are discussed with respect to potential limitations of Fitts’ law in the context of speech production, as well as the theoretical context. Future improvements in application of Fitts’ law are discussed. Significance Statement: Fundamental tradeoffs between speed and accuracy represents some of the most robust and widely replicated laws of human motor action, having been reported in a wide variety of motor domains. These tradeoffs have not, however, been well-established for speech motor actions, which are some of the most rapid and dexterous that humans execute. Trading relationships between speed and accuracy can provide a window into speech control mechanisms in that they hold promise for explaining specific kinds of speech variability, and also directly relate to prominent functional and neural models of control of directed movement. The present work develops a theoretical basis for speed-accuracy tradeoffs in speech kinematics, and establishes the extent of such tradeoffs in speech through novel analysis. SPEED-ACCURACY TRADEOFFS IN HUMAN SPEECH PRODUCTION 3
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Effects influencing the compressive strength of a solid, fired clay brick

The aim of the paper was to analyze the effect of the different influencing factors on the compressive strength of a solid, clay brick. The effect of the surface polishing, the height, width and length of the specimens, the type of the sampling (drilled or cut) and the effect of the production technology were studied. Though being the moisture content of the specimen an important factor, it was not examined herein. More than 110 brick specimens were tested using two different types of measuring procedures: standard (destructive) compressive tests and Schmidt hammer (non-destructive) tests were carried out. Formulae were proposed for determining the normalized mean compressive strength from every possible type of specimens that were adequate for testing in case of this type of unit. It was found that the behaviour of the brick is orthotropic. It was proved that the effect of the height of the specimen has the most significant effect on the compressive strength. A linear relationship was found between the norma lized mean compressive strength and the Young´s modulus of the brick in each direction.
Lane Detection and Following Approach in Self-Driving Miniature Vehicles

The current work, discusses the various experiences, lessons learned and developed novelties, regarding the lane detection and lane following features of miniature autonomous vehicles. Particularly, we outline the work that was conducted, during our team’s participation in Carolo Cup 2016, which is an international competition on autonomous vehicle, held in Braunschweig, Germany. An overview of selected works from the relevant literature is presented, in order to illustrate the various techniques that are commonly adopted in order to implement the lane detection and following functions. The findings, in this regard, constitute of a set of the mostly referenced methods. Additionally, our adopted approach on the matter is extensively elucidated. The different improvements that were introduced to the existing algorithm, are quantified and visualized through an evaluation tool that was developed for this purpose. We conclude that the use of the said tool for analysis, increases the quality of the final product, which is of significant importance in embedded system, due to the fusion of software and hardware elements.
DEVELOPMENT OF A SUPERVISED SOFTWARE TOOL FOR AUTOMATED DETERMINATION OF OPTIMAL SEGMENTATION PARAMETERS FOR ECOGNITION

Image segmentation is one of the most important steps in object-based classification. The commercial software eCognition has been proven to be the most advanced software tool for object-based classification of high resolution remote sensing imagery. However, its segmentation process still relies on trial and error to find proper segmentation parameters. The segmentation process is very time consuming and the segmentation quality directly depends on the experience of the operator. To overcome this problem, a supervised software tool—Fuzzy-based Segmentation Parameter optimizer (FbSP optimizer)—was developed to determine the optimal segmentation parameters through a training process and a fuzzy logic analysis. The optimal segmentation parameters are then used in eCognition to segment the entire image, achieving an optimal segmentation result. The FbSP optimizer can radically increases the efficiency of segmentation parameter selection, and achieve improved segmentation results. It also reduces the influence of the operator’s experience on the quality of segmentation results.
Understanding Collective Behavior with the Concept of Core Clusters

Experts in collective behavior have been investigating how animals move together in groups for decades. Technical progress in recent years introducing smaller and more affordable GPS sensors has made it possible to study wider ranges of animals more closely than ever before. However, this results in more and more data, establishing the need for novel visual analytics solutions. State-of-the-art methods allow the recognition of clusters or often visited places of tracked animals but lack ways to recognize which animals are often together in the same groups. To close this gap, we propose an algorithm for the identification of so called core clusters as well as show how core clusters can be enriched with contextual information. Our proposed solution advances the understanding of experts analyzing collective behavior, especially, when inspecting animals with social relationships such as baboons. We demonstrate the usefulness of our approach as well as discuss our findings in a use case with real baboon data.
Modelling and unsupervised learning of symmetric deformable object categories

We propose a new approach to model and learn, without manual supervision, the symmetries of natural objects, such as faces or flowers, given only images as input. It is well known that objects that have a symmetric structure do not usually result in symmetric images due to articulation and perspective effects. This is often tackled by seeking the intrinsic symmetries of the underlying 3D shape, which is very difficult to do when the latter cannot be recovered reliably from data. We show that, if only raw images are given, it is possible to look instead for symmetries in the space of object deformations. We can then learn symmetries from an unstructured collection of images of the object as an extension of the recently-introduced object frame representation, modified so that object symmetries reduce to the obvious symmetry groups in the normalized space. We also show that our formulation provides an explanation of the ambiguities that arise in recovering the pose of symmetric objects from their shape or images and we provide a way of discounting such ambiguities in learning.
Government Policy, Credit Markets and Economic Activity

The US government has recently conducted large scale purchases of assets and implemented policies that reduced the cost of funds to financial institutions. Arguably these policies have helped to correct credit market dysfunctions, allowing interest rate spreads to shrink and output to begin a recovery. We study four models of financial frictions which explore different channels by which these effects might have occured. Recent events have sparked a renewed interest in leverage restrictions and the consequences of bailouts of the creditors of banks with under-performing assets. We use two of our models to consider the welfare and other effects of these policies.
Driftscan Surveys in the 21 cm Line with the Arecibo and Nançay Telescopes

Abstract Driftscan methods are highly efficient, stable techniques for conducting extragalactic surveys in the 21 cm line of neutral hydrogen. Holding the telescope still while the beam scans the sky at the sidereal rate produces exceptionally stable spectral baselines, increased stability for RFI signals, and excellent diagnostic information about system performance. Data can be processed naturally and efficiently by grouping long sequences of spectra into an image format, thereby allowing thousands of individual spectra to be calibrated, inspected and manipulated as a single data structure with standard tools that already exist in astronomical software. The behaviour of spectral standing waves (multi-path effects) can be appraised and excised in this environment, making observations possible while the Sun is up. The method is illustrated with survey data from Arecibo and Nançay.