Miracle-dz/UniFAR-FTUs huggingface dataset:
Factors Leading to Customer Satisfaction in Dairy Industry:A Study in Indian Perspective

A key characteristic of many, if not all, of the very successful organisations is a supply chain that is truly connected to their customers. A customer driven supply chain starts with understanding the customer requirements, senses and responds rapidly to demand signals from all partners. The challenge is to successfully put in place the organisation structure, systems and processes which tackle the root causes of supply chain inefficiency. The importance of customer relationship management (CRM) within the supply chain is vitally important. The research paper attempts to find out the factors leading to customer satisfaction in Indian dairy industry. The study includes factor analysis in order to group the various practices into a smaller set of homogeneous factor. As per the result of the factor analysis performed on the agreement continuum of the customer questionnaire, five factors emerged prominently, i.e. customer services, customer problem solving capability, value for money offers, product quality, and product & service reliability. The most prominent factor that emerged is the customer services, followed by customer problem solving capability, value for money offers, product quality, and last factor is product & service reliability.
Emergent Syntax : Insights from Imperatives

A generative theory of emergent syntax aims to reduce UG to a more plausible size, with increased roles for the PLD and a domain-general Minimax acquisition bias. I examine the syntax of imperatives in this light, advancing an analysis that captures the centrality of the addressee. Imperatives provide acquirers with crucial information about their language, from which they actively generalise. Acknowledgements My sincere thanks go to my supervisor, Theresa Biberauer; for help with the data, to Hanna Ajer, Nadine Chappalley, Valentina Colasanti, Anna Exenberger, Andres Faraone-Pirie, Joji Mendoza, Rodrigo Ranero Echeverria, and Thomas Wood; and to everyone else who helped (distract) me. Word Count This thesis contains 20,481 words, an allowance having been granted for glosses and translations. Declaration This dissertation is the result of my own work and includes nothing which is the outcome of work done in collaboration except where specifically indicated in the text.
Detection and Recognition of Subpixel Targets with Hypotheses Dependent Background Power

We consider the problem of detecting and recognizing the subpixel targets in sea background when the background power may be different under the null hypothesis – where it is assumed to be known – and the alternative multiple hypotheses. This situation occurs when the presence of the target triggers a decrease in the background power (subpixel targets). We extend the formulation of the Matched Subspace Detector (MSD) to the case where the background power is only known under the null hypothesis using the generalized likelihood ratio test (GLRT) for the multiple hypotheses case. The obtained multiple hypotheses test is based on the Modified MSD test (MMSD). We discuss the difference between the two detection and recognition systems: based on the MSD and MMSD tests. Numerical simulations attest to the validity of the performance analysis.
The Private Use of Credit Ratings: Evidence from Mutual Fund Investment Mandates

Fixed income markets rely on delegated asset management, where fund managers’ portfolio decisions are directed and restricted by investment mandates. We use textual analysis to classify U.S. fixed income funds’ mandate contents. Credit ratings can be used in mandates to define investable assets. Despite the shortcomings of ratings revealed in the global financial crisis, their use in mandates has steadily increased over the past two decades. By 2018, ratings are used by 94% of fixed income mutual funds. Credit ratings are an integral feature of contracting in financial markets and our results point to a lack of practically useful alternatives.
Diffusion of innovation theory for information technology decision making in organisational strategy

Over the past two decades, there has been rapid change in technologies and their innovations. Organisations’ continuous increasing reliance on information technology (IT) is therefore challenged. This has inevitably caused many organisations to adopt “quick fixes”, to support and enable their strategies. What is even more problematic is how the technologies are innovatively used or diffused, which is expected to transform, support and enable competiveness. This study has two primary objectives: (i) to examine the factors that influence the diffusion of information systems (IS) and technologies (IS/IT) in enabling and supporting organisational strategy and (ii) to gain a better understanding of how decisions are made in the course of applying technologies for organisational strategy. The Diffusion of Innovation (DOI) was employed as a lens to examine influencing factors and how decisions are made in applying technologies for organisational strategy. The factors that influence the diffusion of IS/IT includes organisational structure, communication across the hierarchy, the obligatory passage point (OPP) of people, know-how of technologies and implication of process. The decisions that guide the way in which IS/IT are diffused to support and enable organisational strategy were found to be threefold as depicted in the framework: organisation, technology and governance.
Bootstrapping smart cities through a self-sustainable model based on big data flows

We have a clear idea today about the necessity and usefulness of making cities smarter, the potential market size, and trials and tests. However, it seems that business around Smart Cities is having difficulties taking off and is thus running short of projected potentials. This article looks into why this is the case and proposes a procedure to make smart cities happen based on big data exploitation through the API stores concept. To this end, we first review involved stakeholders and the ecosystem at large. We then propose a viable approach to scale business within that ecosystem. We also describe the available ICT technologies and finally exemplify all findings by means of a sustainable smart city application. Over the course of the article, we draw two major observations, which are seen to facilitate sustainable smart city development. First, independent smart city departments (or the equivalent) need to emerge, much like today's well accepted IT departments, which clearly decouple the political element of the improved city servicing from the underlying technologies. Second, a coherent three-phase smart city rollout is vital, where in phase 1 utility and revenues are generated; in phase 2 only-utility service is also supported; and in phase 3, in addition, a fun/leisure dimension is permitted.
Trabecular bone strength patterns at the proximal tibial epiphysis

The longitudinal compressive strength of trabecular bone from the human proximal tibial epiphysis was investigated in 12 autopsy specimens using multiple penetration tests with a small diameter indentor. Strength profiles were visualized by three‐dimensional computerized reconstruction as a function of location on the resection surfaces. There were large variations of the maximal values between individuals, but the patterns obtained were remarkably uniform. The medial condyle showed the highest peak value in all but one knee with a mean medial‐to‐lateral peak value‐ratio of 1.7. At the medial condyle the high strength area was relatively large with peak values being obtained centrally and anteriorly; the lateral condyle showed a more restricted, posteriorly localized area a high strength. Beneath the menisci, bone strength gradually decreased toward the margins of the condyles; likewise, bone strength decreased to reach very low values at the intercondylar region. There was a significant reduction of bone strength with the distance from the subchondral resection surface. This reduction was most pronounced at the high strength areas.
The Impacts Mechanisms of Regulatory Focus on Entrepreneurial Decision Making

Decision regulation was neglected in the research domain of entrepreneurial decision. After investigating 277 entrepreneurs, the paper analyzed the effects of regulatory focus on the decision making by ANCOVA and regression analysis. The findings indicated the criteria of decision making were significantly varied according to groups of regulatory focus. Meanwhile, the relationships of opportunity recognition and decision making had three distinctive modes. Keywordsentrepreneurship; entrepreneurial decision making; regulatory focus; opportunity recognition
Guilt by Association: On Iffy Propositions and the Proper Treatment of Mental-Models Theory

On montre que l’absence de distinction entre predictions logiques et predictions psychologiques chez Evans, Handley et Over (2003) a donne naissance a de pseudo-arguments qui rendent la theorie des modeles mentaux (TMM) de Johnson-Laird & Byrne (2002) coupable par association avec des hypotheses connues pour etre invalides psychologiquement. On montre aussi que la theorie des modeles mentaux permet differentes interpretations du « si », parmi lesquelles l’interpretation conjonctive (‘p et q’) et l’interpretation probabiliste (‘si p, alors peut-etre q’ ou ‘peut-etre si p, alors q’) qui sont selon Evans et al. hors de portee de la theorie des modeles mentaux. Il apparait en conclusion que la science n’a rien a gagner d’une lecture rapide et simplificatrice de theories dont la refutation devient du coup aisee.
Empirical Study on Abnormal CNG Refilling Behaviors Based on Single Attribute

This study used mainly boxplot method to detect abnormal CNG refueling behaviors. The ownership of CNG vehicles in China has ranked the first in the world for many years. However, due to difficulties such as approval of land, CNG filling stations are difficult to meet the increasing demand for refueling. Therefore, the boxplot method was used to study more than 0.25 million CNG refilling records from a secondary CNG filling station in Tianjin to improve the refilling efficiency in this article. The study found that there were about 2.5% abnormal refilling behaviors based on volume, initial pressure and final pressure separately. To verify those results, another unsupervised learning method of kernel density estimation was used to estimate the probability density of each attribute. Finally, it was found that repeated refilling actions were the main reasons of abnormal behaviors detected based on volume attribute. The results suggested that the way to reduce abnormal CNG refilling behaviors was to avoid repeated refilling actions.
The forward-backward averaging technique applied to TLS-ESPRIT processing

Certain array geometries greatly simplify and enhance high resolution array processing. Two techniques are used-the ESPRIT algorithm, which employs two shifted but otherwise identical subarrays, and forward-backward averaging, which can be applied to axis-symmetrical arrays. The former has been shown to provide an efficient solution to bearing estimation while the latter incorporates the a priori knowledge about the symmetry, effectively increasing the number of data vectors available and decorrelating coherent or highly correlated signals. A combination of the two techniques implies a special array geometry that includes uniformly spaced linear arrays. The resulting algorithm yields parameter estimates that are constrained on the unit circle, satisfying the postulated data model provided merely that the arguments of these estimates are distinct. However, if the arguments of some parameter estimates coincide in a given scenario, the ESPRIT algorithm does not yield different results for distinct signals and these estimates can be rejected. Perhaps the most significant advantage of combining forward-backward averaging with ESPRIT parameter estimation is the substantial reduction in computational complexity that can be achieved. Based on the centro-Hermitian property of the data and noise covariance matrices, the computational complexity of the ESPRIT solution is reduced almost by a factor of four and the algorithm can be formulated entirely over the field of real numbers.
A systematic review of the psychometric properties of instruments for assessing the quality of the physical environment in healthcare

AIM To identify instruments measuring the quality of the physical healthcare environment, describe their psychometric properties. BACKGROUND The physical healthcare environment is regarded as a quality factor for health care. To facilitate evidence-based design there is a need for valid and usable instruments that can evaluate the design of the healthcare environment. DESIGN Systematic psychometric review. DATA SOURCES A systematic literature search in Medline, CINAHL, Psychinfo, Avery index and reference lists of eligible papers (1990-2016). REVIEW METHOD Consensus based standards for selection of health measurement instruments guidelines were used to evaluate psychometric data reported. RESULTS Twenty-three instruments were included. Most of the instruments are intended for healthcare environments related to the care of older people. Many of the instruments were old, lacked strong, contemporary theoretical foundations, varied in the extent to which they had been used in empirical studies and in the degree to which their validity and reliability had been evaluated. CONCLUSIONS Although we found many instruments for measuring the quality of the physical healthcare environment, none met all of our criteria for robustness. Of the instruments, The Multiphasic environmental assessment procedure, The Professional environment assessment protocol and The therapeutic environment screening have been used and tested most frequently. The Perceived hospital quality indicators are user centred and combine aspects of the physical and social environment. The Sheffield care environment assessment matrix has potential as it is comprehensive developed using a theoretical framework that has the needs of older people at the centre. However, further psychometric and user-evaluation of the instrument is required.
The effect of training in mindfulness and affect consciousness on the therapeutic environment for patients with psychoses: an explorative intervention study.

RATIONALE The ward atmosphere and the relationships between patients and staff contribute to the improvement in symptoms and psychiatric patient functioning and satisfaction. The quality of the therapeutic relationship is connected to the degree of self-reflection and self-awareness by the staff. OBJECTIVE To examine the effect of two different training programmes for healthcare professionals on the ward atmosphere in wards for psychotic patients. DESIGN AND METHODS Exploratory intervention study with two eight-week interventions of mindfulness training and affect-consciousness training. The outcome was measured on mindfulness and on relevant subscales of the Ward Atmosphere Scale. Data were collected by means of questionnaires and analysed using paired samples t-tests and repeated measures anova. RESULTS Two groups professionals (n = 27 & n = 23) participated in the study. Improvements indicated that both interventions had a positive impact on the ward atmosphere. STUDY LIMITATIONS The exploratory design and the small samples size make definitive conclusions difficult. Patient assessment on the ward atmosphere scale would have strengthened the validity of the results. CONCLUSION The ward atmosphere in two different wards for psychotic patients improved after staff training in mindfulness or affect consciousness. There were differences in change profiles for the groups in accordance with the differences in the two interventions. PRACTICE IMPLICATIONS We recommend awareness on the quality of the ward atmosphere in wards for psychotic patients. Both training in mindfulness and affect consciousness can support healthcare professionals in their awareness.
In-Data vs . Near-Data Processing : The Case for Processing in Resistive CAM

Near-data in-storage processing research has been gaining momentum in recent years. Typical processing-in-storage architecture places a single or several processing cores inside the storage and allows data processing without transferring it to the host CPU. Since this approach replicates von Neumann architecture inside storage, it is exposed to the problems faced by von Neumann architecture, especially the bandwidth wall. We present a novel processing-in-storage system based on Resistive Content Addressable Memory (RCAM). RCAM functions simultaneously as a storage and a massively parallel associative processor. RCAM processing-in-storage resolves the bandwidth wall faced by conventional processing-in-storage architectures by keeping the computing inside the storage arrays, thus implementing indata, rather than near-data, processing. We show that RCAM based processing-in-storage architecture may outperform existing in-storage designs and accelerator based designs. RCAM processing-in-storage implementation of K-means achieves speedup of 4.6—68 relative to CPU, GPU and FPGA based solutions. For K-Nearest Neighbors, RCAM processing-in-storage achieves speedup of 17.9—17,470 and for Smith-Waterman sequence alignment it reaches speedup of almost 5 over a GPU cluster based solution.
Restricted mating dispersal and strong breeding group structure in a mid‐sized marsupial mammal (Petrogale penicillata)

Ecological genetic studies have demonstrated that spatial patterns of mating dispersal, the dispersal of gametes through mating behaviour, can facilitate inbreeding avoidance and strongly influence the structure of populations, particularly in highly philopatric species. Elements of breeding group dynamics, such as strong structuring and sex‐biased dispersal among groups, can also minimize inbreeding and positively influence levels of genetic diversity within populations. Rock‐wallabies are highly philopatric mid‐sized mammals whose strong dependence on rocky terrain has resulted in series of discreet, small colonies in the landscape. Populations show no signs of inbreeding and maintain high levels of genetic diversity despite strong patterns of limited gene flow within and among colonies. We used this species to investigate the importance of mating dispersal and breeding group structure to inbreeding avoidance within a ‘small’ population. We examined the spatial patterns of mating dispersal, the extent of kinship within breeding groups, and the degree of relatedness among brush‐tailed rock‐wallaby breeding pairs within a colony in southeast Queensland. Parentage data revealed remarkably restricted mating dispersal and strong breeding group structuring for a mid‐sized mammal. Breeding groups showed significant levels of female kinship with evidence of male dispersal among groups. We found no evidence for inbreeding avoidance through mate choice; however, anecdotal data suggest the importance of life history traits to inbreeding avoidance between first‐degree relatives. We suggest that the restricted pattern of mating dispersal and strong breeding group structuring facilitates inbreeding avoidance within colonies. These results provide insight into the population structure and maintenance of genetic diversity within colonies of the threatened brush‐tailed rock‐wallaby.
Cost of Capital for Agricultural Cooperatives

The cost of capital is important in the financial management of agricultural cooperatives. A measure of the cost of capital is required when evaluating various aspects of strategic business plans, e.g., selecting a financial leverage position, calculating the profitability of alternative investment opportunities, measuring economic value-added, and comparing various merger and acquisition plans. The task of determining the appropriate cost of capital to use requires a careful analysis of the effect of alternative financing choices which are open to a cooperative. This report considers the close relationship between the cost of capital and capital structure. Ways are examined to determine the cost of capital by a cooperative. The report sequentially identifies: principles of capital structure and cost of capital, guidelines for capital structure choice, and applications of these guidelines through cooperative case examples. These applications are a starting point for cooperatives to develop capital positions and consider alternative assumptions about financing sources and their potential impacts on the overall cost of capital. To determine the overall cost of capital for a selected capital structure, a cooperative must first determine its cost of equity capital. The cost of equity capital cannot be derived directly from the market, as in the case of a publicly traded firm. Thus, there is no ideal method for determining the cost of capital for a cooperative. So an innovative approach is needed. The opportunity cost of funds approach relates the cost of capital to the rates of return from alternative uses of capital (i.e., the assets side of the balance sheet). The focus is on the expected (or required) rates of return from alternative investments which reflects the degree of risk involved. The discounted cash flow approach relates the cost of capital to the alternative sources of capital (i.e., the liabilities and equity capital side of the balance sheet). The component costs of equity and debt capital are combined into an overall cost of capital for the cooperative. Both approaches require making some assumptions to determine the cost of equity capital for a cooperative.
An Overview : Dynamic Contrast Enhanced Imaging of Prostate Cancer

For many years, medical imaging focused on the anatomy of the body by taking a picture of the organs. Latest techniques allow us to investigate physiological and even molecular features of the imaged tissue. The interpretation of such images requires thus a thorough understanding of the imaging technique as well as a deep understanding of the biology and physiology of the healthy and diseased organ.
Strategic timing of commercial-scale tidal energy investment

The many uncertainties in tidal energy conversion combine to form a significant barrier to raising private-sector capital. Mitigation and management of risk are essential if the industry is to attract equity investors. One way to manage the risk is through investment timing. The option to time an investment has value, which can be estimated. An analysis of an invest-vs-delay decision revealed a persistent, economicallyrational incentive to delay. Further inquiry identified a strategic rationale for delaying investment in tidal energy projects, given the uncertainty still present in the undertaking. As the largest sensitivity in the value of delay is the volatility of the investment’s expected cash flows, an investigation into the prevalent uncertainties was undertaken. This paper summarizes the real option valuation model. It then reports on results of a qualitative study of the predominant uncertainties facing developers and conditions that would help move the industry along. Predominant uncertainties reported revolve around technology reliability; site and resource knowledge; prospects for buildout; predictability of government policy and supports; prospects of off-take agreements; and supply chain capacity and costs. These are related back to the variables in the real option pricing model. The model is relevant for companies wishing to systematically evaluate timing options and communicate project value to the investment community. It can also be used by governments to evaluate the design of policies and financial supports in a way that is consistent with the priorities of financial markets.