Miracle-dz/UniFAR-FTUs huggingface dataset:
An empirical study of optimal access to external finance by small and medium enterprise start-ups

The aim of this study is to empirically examine the relationships between the determinants of start-up SME success, namely start-up awareness and management skills, and the finance suppliers. This study has proposed a framework that improves the ability of start-up SMEs to access external finance. Through descriptive and inferential statistical analyses of data from a survey of a sample of SMEs in South Africa, it was ascertained that the framework which maps the entrepreneur’s start-up awareness and requisite management skills with the finance providers’ requirements will make up a tool to assist start-up SMEs in developing optimal financing options to grow their businesses.
Assessment of Performance Measures for Public Health, Substance Abuse, and Mental Health

The U.S. Department of Health and Human Services is carrying out an ambitious new program to assure that funds for public health programs are spent as effectively as possible. Under the new program, every state will develop a set of performance objectives to measure its progress in terms of outcomes, processes, and capacity. In the first phase of the program, states are to propose such measures to be achieved over three to five years. This book examines the technical issues involved in the development of performance measures in 10 areas: mental health, substance abuse, HIV infection, sexually transmitted diseases, tuberculosis, immunization, chronic diseases, disability, rape, and emergency medical services. From more than 3,200 candidate measures proposed by researchers, policymakers, and public health professionals, the panel proposes more than 50 potential outcome measures. The book details the advantages and limitations of potential measures as well as the data sources that can support them. This volume will be an invaluable resource to everyone involved in public health.
Improving workplace productivity and corporate culture : perceptions and experiences of the effects of workplace massage

Australian workers’ compensation figures consistently reveal that physical and psychological injuries pose a costly burden to the Australian economy. Since the 1980s, many employers have increasingly been providing workplace massage programs to their staff as one initiative to redress this trend. Masseurs have promoted the effectiveness of this intervention for improving musculoskeletal disorders and reducing stress, and claim massage therapy contributes toward increased employee engagement with the workplace, thus resulting in increased productivity and reduced levels of absenteeism. Clearly, one of the underlying aims for employers in providing such facilities is to prevent and manage work-related injuries and stress. However, notwithstanding these claims, there remains a paucity of scholarly literature investigating: (a) reasons why managers implement and subsidise workplace massage, (b) what employees feel are the work-related effects such programs, and, (c) the therapeutic intentions of masseurs who offer this therapy. Using three conceptually linked studies, this thesis explores the stories of managers, employees, and therapists in order to gain a greater understanding of their perceptions about the overall benefits of workplace massage.
Dual-Channel Multiplier for Piecewise-Polynomial Function Evaluation for Low-Power 3-D Graphics

A dual-channel multiplier (DCM) for energy efficient second-order piecewise-polynomial function evaluation for 3-D graphics applications is presented in this paper. The performance of the evaluation process is highly dependent on the design of the multiplication and squaring structure. A novel hardware implementation for polynomial evaluation is presented. The proposed approach compensates the complex multipliers by using DCM which reduces the hardware complexity. The DCM scheme performs complex functions with power-efficient and area-efficient approach. The multiplier reduces the hardware computational effort in the piecewise polynomial approximation with uniform or nonuniform segmentation. For large operand input size, a multiplier adder converter and a dedicated radix-4 squaring unit are also proposed. These units achieve the least power consumption compared to previous approaches with large input word size. Comparison with general purpose multiplication has shown reduction in power, and delay by up to 36%, and 50%, respectively. The proposed technique exhibits up to 93% saving in power consumption compared to the current traditional schemes.
Study on Supply Chain Finance, Internal Control and SMEs Financing Constraints

Financing difficulties of small and medium-sized enterprises have always been a hot issue concerned by the government and academia, and supply chain finance is an effective way to relieve the financing constraints of SMEs. This paper uses the data of GEM listed companies from 2013 to 2015; uses the cash-cash flow sensitivity model to study the relationship between supply chain finance and financing constraints, and deeply explores the regulating action of internal control for relieving financing constraints of supply chain finance. The research found that supply chain finance can alleviate the financing constraints faced by GEM listed companies, and this relief effect is also affected by internal control of enterprises. Compared with enterprises with high internal control quality, supply chain finance has more obvious relief for enterprises financing constraints with low internal control quality.
Evaluation of 65% permethrin spot-on for prevention of canine visceral leishmaniasis: effect on disease prevalence and the vectors (Diptera: Psychodidae) in a hyperendemic area.

: A study was designed to examine the effect of 65% permethrin spot-on on the prevalence of canine visceral leishmaniasis and the abundance of sand flies in two neighborhoods in Corumba, Mato Grosso do Sul, Brazil known to have a high prevalence of visceral leishmaniasis. An enrollment survey was conducted to determine the prevalence of visceral leishmaniasis. Area residents were provided with information about the project; the study area was defined, and all dogs (160 in Cristo Redentor and 230 in Popular Velha) identified in the study area were enrolled. Three 65% permethrin spot-on treatments (June 15-25, July 13-15, and August 10-12) were administered to 150, 110, and 99 dogs, respectively, in Popular Velha, according to label recommendations. Dogs in Cristo Redentor were untreated controls. Visceral leishmaniasis was diagnosed periodically by indirect immunofluorescence assay. A reduction in canine visceral leishmaniasis prevalence was observed at the Popular Velha site. The infection rate for treated dogs 1 month following the final treatment was approximately 50% reduced from that observed before treatment(19.3% vs 9.6%). Conversely, the infection rate at the control site was more than 80% higher at the September sampling than that observed pretreatment (4.1% vs 7.4%). Similar numbers of sand flies were captured and identified from both sites throughout the study. The results suggest that regular use of 65% permethrin during months of high risk for canine visceral leishmaniasis can be a useful strategy for reducing the prevalence of this disease in hyperendemic areas. It should be stressed, however, that the success of this strategy depends not only on the efficacy of the product itself but also on the adoption of other control measures and on economic variables, considering the low purchasing power of the populations living in higher-risk neighborhoods.
Modeling the effectiveness of electronic customer relationship management (E-CRM) systems: empirical evidence from Pakistan

The purpose of this study is to find the relationship of service quality, loyalty, trust employee satisfaction and technology acceptance with the effectiveness of electronic customer relationship management. Organizations are introducing internet based technology to make their business convenient for the existing as well as potential customers and through their feedback also manage their performance. The research was conducted in the banking sector of Pakistan and data was collected from over 500 employees and customers including the top five banks of the country. The findings showed that only service quality and loyalty were the significant predictors of E_CRM system effectiveness. It is anticipated that results of this study will not only expand the scope of study for researchers at the academic level, but also may make policy makers and managers to realize the significance of E-CRM. Its implementation will ultimately result in achieving the higher level of customer satisfaction which is imperative in banking sector.
Assessment of health-enhancing physical activity-methodological issues

Designed to be an overall presentation of health-enhancing physical activity (HEPA); this volume is "state of the art" answering key questions in the field such as - why is physical activity important for health? , how much and what kind of physical activity is beneficial for health? , and how can physical activity be promoted for health? It successfully presents a population perspective of the potential and role of physical activity in the promotion of public health. This is essential reading for HEPA experts and actors in research, education, administration and service provision, providing the most recent theoretical and practical evidence base.
Evaporative tear film and contact lens factors associated with dry eye symptoms in contact lens wearers

ii ABSTRACT Contact lens-related dry eye is a significant problem, experienced by about one-half of all contact lens wearers. Generally, contact lens-related dry eye is termed " evaporative, " compared with other aqueous deficient dry eye diseases. However, few studies have confirmed indicators of evaporation relative to contact lens wear. The Contact Lens and Dry Eye Study (CLADES) is a cross-sectional/nested case-control study designed to study tear film, contact lens, ocular surface, and patient-related factors associated with self-reported dry eye disease in contact lens wearers. Although the study is not complete, the data and analyses presented in this dissertation are being used to guide the direction of further patient testing. Thus, the data presented here are strictly confidential. Data from 325 patients in the CLADES database were used for these analyses. Initial analyses were conducted using 274 patients who completed the Contact Lens Dry Eye Questionnaire (CLDEQ) on two occasions in order to determine reliability and classification issues relating to this screening instrument. Two datasets were then assembled in order to determine tear film, contact lens, and patient-related factors associated with self-reported dry eye. The full dataset (n = 325) includes all patients in the original dataset, and patients are classified based on their initial responses on the CLDEQ. The clean dataset (n = 216) includes only patients who completed the CLDEQ iii on two occasions (n = 274), and patients who do not misclassify their disease status upon re-administration of the survey (n = 58, 21.2%, p = < 0.0001). Logistic regression was used to determine patient-related factors that might be used to predict misclassification (i.e., change in classification), and this analysis revealed that women less than 45 years of age tended to be those that misclassified their disease status (odds ratio = 2.50, 95% confidence interval = 1.20, 5.20). Primary factors evaluated for a relation to disease status in these analyses included meibomian gland structural alterations, pre-lens tear film lipid layer thickness, non-invasive tear breakup time, hydrogel dehydration, and the use of a nominally characterized high water content lens. Secondary factors evaluated for a relation to disease status included things like socio-demographic information, U.S. Food and Drug Administration (FDA) hydrogel classification, hydrogel ionicity and material, phenol red thread testing, fluorescein corneal staining, and lissamine green conjunctival staining. Following univariate logistic regression analyses, multivariate models were built in order to determine significant factors associated with disease status. Factors that …
A Macro Stress Testing Framework for Assessing Financial Stability: Evidence from Malaysia

The main results of the macro stress testing exercise in this paper reveal that Malaysia’s banking sector is resilient, well diversified, and highly interconnected. Further, Malaysia has a thriving equity market, large bond market and growing private debt securities. Main results of the baseline scenario suggest a modest change in capital ratios; the post-stress test CAR and Tier 1 capital ratio are -1.64% and -1.38% respectively. The impact of all fundamental shocks on capital ratios under both adverse and severely adverse scenarios is significant. The aggregate capital shortfall in the form of needed capital injection (i.e. cost to the government from failed banks) under adverse scenario is 1.55% of the GDP (or $4.59 billion based on 2015 GDP of $296.22 billion). The capitalization needs became more severe in the severely adverse scenario, $10.52 billion (or 3.55% of 2015 GDP). The important conclusion of the macro stress testing is that no bank failed, faced a liquidation or suspension of license.
Generalized Linear Quaternion Complementary Filter for Attitude Estimation From Multisensor Observations: An Optimization Approach

Focusing on generalized sensor combinations, this paper deals with the attitude estimation problem using a linear complementary filter (CF). The quaternion observation model is obtained via a gradient descent algorithm. An additive measurement model is then established according to derived results. The filter is named as the generalized CF where the observation model is simplified as a linear one that is quite different from previous-reported brute-force nonlinear results. Moreover, we prove that representative derivative-based optimization algorithms are essentially equivalent to each other. Derivations are given to establish the state model based on the quaternion kinematic equation. The proposed algorithm is validated under several experimental conditions involving the free-living environment, harsh external field disturbances, and aerial flight test aided by robotic vision. Using the specially designed experimental devices, data acquisition and algorithm computations are performed to give comparisons on accuracy, robustness, time-consumption, and so on with representative methods. The results show that not only the proposed filter can give fast, accurate, and stable estimates in terms of various sensor combinations but also produces robust attitude estimation in the scenario of harsh situations, e.g., irregular magnetic distortion. Note to Practitioners—Multisensor attitude estimation is a crucial technique in robotic devices. Many existing methods focus on the orientation fusion of specific sensor combinations. In this paper, we make the problem more concise. The results given in this paper are very general and can significantly decrease the space consumption and computation burden without losing the original estimation accuracy. Such performance will be of benefit to robotic platforms requiring flexible and easy-to-tune attitude estimation in the future.
Contractor’s Technology Acceptance for Firm Sustainability Performance

The construction industry’s contributions to Greenhouse gas emissions have generated several discussions among the construction stakeholders in recent times. Granted that the construction industry has been contributing significantly to the economy as well as employment in most countries for decades, the industry’s resource consumption is, at the same time, damaging to a sustained human environment. This paper empirically explored the organizational technology orientation and perceived organizational usefulness that could improve construction Malaysian construction firm’s sustainability performance. Close-ended structured copies of questionnaire survey were employed to collect data from large Malaysian construction firms, and Partial Least Squares-Structural Equation Modeling technique was used to analyze the 172 responses. The results indicated that both technology orientation and perceived organizational usefulness are capable of influencing the construction firms’ sustainability performance. The implication is that this study’s model can predict the sustainability performance of the sampled construction firms. Some implications for research and practice, as well as future recommendations, were highlighted.
Learning from ranking data : theory and methods

Ranking data, i.e., ordered list of items, naturally appears in a wide variety of situations, especially when the data comes from human activities (ballots in political elections, survey answers, competition results) or in modern applications of data processing (search engines, recommendation systems). The design of machine-learning algorithms, tailored for these data, is thus crucial. However, due to the absence of any vectorial structure of the space of rankings, and its explosive cardinality when the number of items increases, most of the classical methods from statistics and multivariate analysis cannot be applied in a direct manner. Hence, a vast majority of the literature rely on parametric models. In this thesis, we propose a non-parametric theory and methods for ranking data. Our analysis heavily relies on two main tricks. The first one is the extensive use of the Kendall’s tau distance, which decomposes rankings into pairwise comparisons. This enables us to analyze distributions over rankings through their pairwise marginals and through a specific assumption called transitivity, which prevents cycles in the preferences from happening. The second one is the extensive use of embeddings tailored to ranking data, mapping rankings to a vector space. Three different problems, unsupervised and supervised, have been addressed in this context: ranking aggregation, dimensionality reduction and predicting rankings with features.The first part of this thesis focuses on the ranking aggregation problem, where the goal is to summarize a dataset of rankings by a consensus ranking. Among the many ways to state this problem stands out the Kemeny aggregation method, whose solutions have been shown to satisfy many desirable properties, but can be NP-hard to compute. In this work, we have investigated the hardness of this problem in two ways. Firstly, we proposed a method to upper bound the Kendall’s tau distance between any consensus candidate (typically the output of a tractable procedure) and a Kemeny consensus, on any dataset. Then, we have casted the ranking aggregation problem in a rigorous statistical framework, reformulating it in terms of ranking distributions, and assessed the generalization ability of empirical Kemeny consensus.The second part of this thesis is dedicated to machine learning problems which are shown to be closely related to ranking aggregation. The first one is dimensionality reduction for ranking data, for which we propose a mass-transportation approach to approximate any distribution on rankings by a distribution exhibiting a specific type of sparsity. The second one is the problem of predicting rankings with features, for which we investigated several methods. Our first proposal is to adapt piecewise constant methods to this problem, partitioning the feature space into regions and locally assigning as final label (a consensus ranking) to each region. Our second proposal is a structured prediction approach, relying on embedding maps for ranking data enjoying theoretical and computational advantages.
Mobile delay‐tolerant networks with energy‐harvesting and wireless energy transfer cooperation

We consider a mobile delay‐tolerant networks (MDTNs) with energy‐harvesting capabilities. In order to determine energy management policies that will improve network capacity and packet delivery ratio and maximize the system throughput, we consider a source node that seeks to send packets to a destination node. The optimal policy for the source varies according to its system state, which allows it to guarantee a maximum delivery probability rate. Our problem is modeled by decision theory; as a start, we are interested in the MDP to model and solve such sequential decision problems. Our goal is to optimize for each node, a utility depending on a random environment and decisions made by the node. As the MDP formalism reaches its limits when it is necessary to take into account the interactions between different several nodes, we will start using the graph‐based MDP where the state and action spaces are factorizable by variables. The transition functions and rewards are then decomposed into local functions and the dependency relations between the nodes are represented by a graph. To calculate the optimal policy, we propose Mean Field Approximation (MFA) and Approximate linear‐programming (ALP) algorithms for solving GMDP problem.
The relationships between cultural identity, family support and influence, colorectal cancer beliefs, and gender and an informed decision regarding colorectal cancer screening among African Americans

The colorectal cancer (CRC) mortality rate among African Americans is 45% higher than Caucasians and CRC screening rates among African Americans are lower than Caucasians (American Cancer Society, 2008). Informed decision-making may be a strategy to decreasing CRC disparities among African Americans. This study examined relationships between cultural identity, family support and influence, CRC beliefs, gender and an informed decision regarding CRC screening among older African Americans (N= 129). Bivariate correlations indicated that perceived family support and CRC beliefs were related to making an informed decision regarding CRC screening (r = .24, p<.01; r = .29, p< .01, respectively). Path analysis indicated that CRC beliefs explained 9% of the variance in an informed decision and cultural identity, family support and influence explained 36% of the variance in CRC beliefs. The path analysis of the overall model did not fit the data well. Gender differences among African American men and women were examined through bivariate correlations, t-tests and path analyses. Bivariate correlations indicated that among African American men, CRC and racial pride were related to an informed decision regarding CRC screening (r =.320, p =.006; r =.330, p=.005, respectively). Family support was related to CRC beliefs among African American men (r = .599; p =.000) and African American women (r = .447; p = .000). T-tests indicated that men were different than women in responses to certain cultural identity factors, CRC beliefs and family support (p= .05). Path analyses indicated that the gender covariate and male models did not fit the data well. However, the female model fit the data well (X = 5.10, ix 6df, p = .531, N=65, NFI = .905, CFI = 1.00, RMSEA = .000). Explained variance for an informed decision was 6% for the female model and 10% for the gender covariate and male models. Based on study results, older African Americans should be assessed for certain cultural factors, CRC beliefs and family support to increase informed decision making. Assessments and interventions should consider gender differences. Additional research is needed to understand the influences, supports and predictors of an informed decision to create efficacious CRC interventions and decision aids tailored for African Americans.