Miracle-dz/UniFAR-FTUs huggingface dataset:
Cost Analysis of Selected Patient Categories within a Dermatology Department Using an ABC Approach

Background: Present trends in hospital management are facilitating the utilization of more accurate costing methods, which potentially results in superior cost-related information and improved managerial decision-making. However, the Activity-Based Costing method (ABC), which was designed for cost allocation purposes in the 1980s, is not widely used by healthcare organizations. This study analyzes costs related to selected categories of patients, those suffering from psoriasis, varicose ulcers, eczema and other conditions, within a dermatology department at a Czech regional hospital. Methods: The study was conducted in a hospital department where both inpatient and outpatient care are offered. Firstly, the diseases treated at the department were identified. Further costs were determined for each activity using ABC. The study utilized data from managerial and financial accounting, as well as data obtained through interviews with departmental staff. Using a defined cost-allocation procedure makes it possible to determine the cost of an individual patient with a given disease more accurately than via traditional costing procedures. Results: The cost analysis focused on the differences between the costs related to individual patients within the selected diagnoses, variations between inpatient and outpatient treatments and the costs of activities performed by the dermatology department. Furthermore, comparing the costs identified through this approach and the revenue stemming from the health insurance system is an option. Conclusions: Activity-Based Costing is more accurate and relevant than the traditional costing method. The outputs of ABC provide an abundance of additional information for managers. The benefits of this research lie in its practically-tested outputs, resulting from calculating the costs of hospitalization, which could prove invaluable to persons involved in hospital management and decision-making. The study also defines the managerial implications of the performed cost analysis for the hospital management. Based on the analysis results, it is possible to standardize activities and performance appraisal (Benchmarking), and provide all necessary information for hospital budgeting practices, especially Activity-Based Budgeting (ABB).
RESEARCH ON THEORETICAL ANALYSIS AND STATISTICAL EXAMINATION OF MANUFACTURING ENTERPRISE'S SERVICE ENHANCEMENT BASED ON STRUCTURAL EQUATION MODELING

According to recent statistical data and empirical research, the importance of service in manufacturing industry has been significantly strengthened and the melting tendency between relative service and manufacturing process is obvious. More and more manufacturing enterprises have adopted differentiation service strategy to acquire competitive advantage for high profit. Commercial products which reflect service enhancing effect can be chosen as empirical analysis objectives. Dynamic capability theory, customer equity management theory and enterprise growth theory are comprehensively applied in analyzing inner mechanism of service enhancing effect. Through literature research and enterprise interview, the theoretical model of enhancing service effect can be constructed and divided into three layers such as dynamic capability, customer equity management and enterprise growth performance. Based on collected one hundred and seventy four questionnaires, structural equation modeling method can be applied in measuring the validity of theoretical model through empirical research. The measuring coefficients such as x 2 /df (equals to 1.845), RMSEA (equals to 0.072), TLI (equals to 0.913) and CFI (equals to 0.964) have all matched the statistical measuring level and standard path coefficients can be calculated so as to verify hypotheses for find out valuable academic rules. The measuring results discover that customer equity has positive effect on enterprise growth performance, and dynamic capability has positive effect on enterprise growth performance through the intermediate effect of customer equity.
Theoretical aspects of synergetic model formulation in the economic systems innovative-investment development

Different approaches to the interpretation of the category "investment" and "innovation" have been presented and evaluated in this article. The basic characteristics and particular qualities of investigated definition have been mentioned. The article shows that the basis of theoretical understanding of the investment and innovation process is showing of any economic system as a complex open system, which allows to use the principles of synergetic campaign for the development of effective models of transition systems from one state to another, qualitatively new state, and also makes it possible to search for universal principles of self-organization and evolution of complex economic systems. The author of the article suggests the model which allows describing qualitatively the self-consistent evolutionary action of investment and innovation processes of economic systems. In the framework of the adiabatic approximation shows the solution of the model, corresponding to the equation of the LandauKhalatnikov synergy potential coincides with a similar potential for the usual Lorentz system.
A middleware for parallel processing of large graphs

With the increasing "data deluge" scientists face today, the analysis and processing of large datasets of structured data is a daring task. Among such data, large graphs are gaining particular importance with the growing interest on social networks and other complex networks. Given the dimensions considered, parallel processing is essential. However, users are generally not experts in writing parallel code to handle such structures. In this work we present Rendero, a middleware that makes it possible to easily describe graph algorithms in a form adequate for parallel execution. The system is based on the Bulk-Synchronous programming model and offers a vertex-based abstraction. Our current implementation offers good speed-up and scale-up results for large graphs ranging from tens of thousands to millions of vertices and edges in some cases.
Categorization of research surveys and reviews on human activities

Due the recently increased number of survey papers, we consider important to offer an evaluation of the different types of current survey papers to assess their benefits and inform the readers regarding their categories. The field selected here is the Human Activity Recognition (HAR), although its idea can be applied to other research areas as well. Thus, a variety of survey papers are studied thoroughly and compared for this categorization. From each paper a short synopsis is presented in order the reader to understand the concepts behind it. In order to objectively assess their importance, we formulate a maturity metric by using a set of significant features, that best describe the significance and contribution of the HAR research. Finally the anticipated result of this paper, is to serve as a reference point for the “dos' and don'ts” regarding the survey papers, and lay a foundation for further research, thoughts, discussion, and improvements of them, towards maturity and usefulness.
Immuno-oncology combinations: raising the tail of the survival curve

There have been exponential gains in immuno-oncology in recent times through the development of immune checkpoint inhibitors. Already approved by the U.S. Food and Drug Administration for advanced melanoma and non-small cell lung cancer, immune checkpoint inhibitors also appear to have significant antitumor activity in multiple other tumor types. An exciting component of immunotherapy is the durability of antitumor responses observed, with some patients achieving disease control for many years. Nevertheless, not all patients benefit, and efforts should thus now focus on improving the efficacy of immunotherapy through the use of combination approaches and predictive biomarkers of response and resistance. There are multiple potential rational combinations using an immunotherapy backbone, including existing treatments such as radiotherapy, chemotherapy or molecularly targeted agents, as well as other immunotherapeutics. The aim of such antitumor strategies will be to raise the tail on the survival curve by increasing the number of long term survivors, while managing any additive or synergistic toxicities that may arise with immunotherapy combinations. Rational trial designs based on a clear understanding of tumor biology and drug pharmacology remain paramount. This article reviews the biology underpinning immuno-oncology, discusses existing and novel immunotherapeutic combinations currently in development, the challenges of predictive biomarkers of response and resistance and the impact of immuno-oncology on early phase clinical trial design.
Substrains of Inbred Mice Differ in Their Physical Activity as a Behavior

Recent studies strengthen the belief that physical activity as a behavior has a genetic basis. Screening wheel-running behavior in inbred mouse strains highlighted differences among strains, showing that even very limited genetic differences deeply affect mouse behavior. We extended this observation to substrains of the same inbred mouse strain, that is, BALB/c mice. We found that only a minority of the population of one of these substrains, the BALB/c J, performs spontaneous physical activity. In addition, the runners of this substrain cover a significantly smaller distance than the average runners of two other substrains, namely, the BALB/c ByJ and the BALB/c AnNCrl. The latter shows a striking level of voluntary activity, with the average distance run/day reaching up to about 12 kilometers. These runners are not outstanders, but they represent the majority of the population, with important scientific and economic fallouts to be taken into account during experimental planning. Spontaneous activity persists in pathological conditions, such as cancer-associated cachexia. This important amount of physical activity results in a minor muscle adaptation to endurance exercise over a three-week period; indeed, only a nonsignificant increase in NADH transferase+ fibers occurs in this time frame.
Frequency Offset Cancellation for IEEE802.15.4a Based Ranging

IEEE 802.15. 4a is an amendment to 802.15. 4 for an alternative PHY. The principal interest of IEEE 802.15. 4a is in providing communications and high precision ranging / location capability. In this paper, we present the performance metrics for ranging schemes. The analysis based on the performance metrics characterizes the features of ranging schemes as follows. For the TWR scheme, due to its turn around time, the frequency offset results in significant ranging error. Since SDS-TWR takes more than two times bandwidth of that by TWR, which results in not only lower capacity, but also higher sensitivity to mobility than that of TWR. We cancel the ranging error from the frequency offset in a different way. We introduce a frequency Ratio based TWR (R-TWR) scheme, which cancels the ranging error based on the ratio of the frequency on the originator side to the frequency on the responder side. We prove that the ranging accuracy of R-TWR scheme can reach the same order as that of SDS-TWR, while the capacity and sensitivity to mobility keep same as TWR scheme.
Stochastic Contextual Bandits with Known Reward Functions

Many sequential decision-making problems in communication networks can be modeled as contextual bandit problems, which are natural extensions of the well-known multi-armed bandit problem. In contextual bandit problems, at each time, an agent observes some side information or context, pulls one arm and receives the reward for that arm. We consider a stochastic formulation where the context-reward tuples are independently drawn from an unknown distribution in each trial. Motivated by networking applications, we analyze a setting where the reward is a known non-linear function of the context and the chosen arm's current state. We first consider the case of discrete and finite context-spaces and propose DCB($\epsilon$), an algorithm that we prove, through a careful analysis, yields regret (cumulative reward gap compared to a distribution-aware genie) scaling logarithmically in time and linearly in the number of arms that are not optimal for any context, improving over existing algorithms where the regret scales linearly in the total number of arms. We then study continuous context-spaces with Lipschitz reward functions and propose CCB($\epsilon, \delta$), an algorithm that uses DCB($\epsilon$) as a subroutine. CCB($\epsilon, \delta$) reveals a novel regret-storage trade-off that is parametrized by $\delta$. Tuning $\delta$ to the time horizon allows us to obtain sub-linear regret bounds, while requiring sub-linear storage. By exploiting joint learning for all contexts we get regret bounds for CCB($\epsilon, \delta$) that are unachievable by any existing contextual bandit algorithm for continuous context-spaces. We also show similar performance bounds for the unknown horizon case.
Static analysis of function calls in Erlang

Functions and their relations can aect numerous properties and metrics of a functional program. To identify and represent the functions and their calling connections, software analysers commonly apply semantic function analysis, which derives the static call graph of the program, based on its source code. Function calls however may be dynamic and complex, making it dicult to statically identify the callee. Dynamic calls are determined just at run-time, static analysis therefore cannot be expected to fully identify every call. Nevertheless, by utilising the results of a properly performed data-flow analysis as well as taking ambiguous references into account, numerous dynamic calls are discoverable and representable. We consider cases where the identifiers of the callee are statically determined, but they flow into the call expression from a dierent program point, and also, we manage to handle function calls whose identifiers are not fully identifiable at compile-time. By utilising the improved reference analysis, we extend the static call graph with various information about dynamic function calls. We investigate such a function call analysis in the programming language Erlang.
Dynamic activity‐induced manganese‐dependent contrast magnetic resonance imaging (DAIM MRI)

Activity‐induced manganese‐dependent contrast (AIM) MRI is a hemodynamic‐independent functional MRI method that used manganese ion as an MR‐detectable contrast agent. In AIM, MnCl2 is infused intra‐arterially after the blood‐brain barrier (BBB) is opened with a hyperosmolar agent. Upon functional stimulation of the brain, Mn2+ accumulates in the active region(s) by entering active cells through voltage‐gated Ca2+ channels, causing local signal increases in T1‐weighted images. The contrast of AIM MRI depends strongly on the depth of anesthesia, and the low levels used in somatosensory stimulation studies can lead to significant nonspecific accumulation of manganese ion throughout the brain. The purpose of this study was to produce an AIM functional map of somatosensory stimulation, which separates the stimulation‐specific signal increase from the nonspecific activation due to light anesthesia. A dynamic AIM (DAIM) paradigm was developed, which used sequential MR scans during MnCl2 infusion, prior to and following functional stimulation of the brain. Stimulation‐specific functional maps were produced using time‐course analysis. The new method was tested during glutamate administration and electric stimulation of the rat forepaw. It was shown that DAIM maps are better confined to the specific region of brain activated by somatosensory stimulation as compared to AIM MRI. Magn Reson Med 48:927–933, 2002. © 2002 Wiley‐Liss, Inc.
Catastrophic Risk and Securities Design

The anomalies, inefficiencies and difficulties in the market for catastrophic bonds are so pronounced as to lead strongly to the inference that psychological factors have a major impact on the pricing of these bonds, and on the lack of acceptance they have encountered from investors. In this article, we examine major factors influencing the market for catastrophe bonds. Most of the economic factors involved-considered either singly or in combination-are insufficient to account for the magnitude of the anomalies observed. Decades ago, irregularities in the orbit of the planet Uranus allowed astronomers to deduce the existence of another planet, subsequently named Pluto. Since the economic forces at work in the marketplace cannot satisfactorily explain the situation in the catastrophe-bond marketplace, we infer that the gravitational pull of psychological forces is at work. We discuss eight psychological dynamics that may influence the pricing, mispricing, acceptance or lack of acceptance of catastrophe bonds. Losses from catastrophic events represent an increasing problem for the property and casualty insurance industry. These losses have significant repercussions not only for insurance firms, but also for governmental policy makers and consumers in the insurance market. In principle, one way to deal with these risks is through securitizing them. Doing so would allow spreading risks of local disasters across global capital markets. However, previous attempts at securitizing insurance risks have, by most accounts, met with minimal success. This paper examines possible barriers to securitization, focusing on behavioral responses to such novel instruments. These barriers include the difficulties of conveying the associated risks, even to investors who are sophisticated about finance. Our analyses will draw on research in behavioral decision making and psychology. They will lead to proposals for empirical research and general strategies for making securities design more consonant with investor behavior.
Retail Brand Equity and Consumer Learning

Retail brand equity is a critical differentiator in today's competitive marketplace. However, retail managers have few metrics that they can rely on to manage their brand equity. In this paper, we propose a structural model to describe how retail brand equity is formed in each consumer's mind based on his/her consumption experiences across product categories provided by the retailer. Based on the behavioral research on brand equity and consumer inference, we represent consumers' beliefs about the qualities of the retail brand and the product categories as nodes that are linked in an associative network. This associative network enables consumers to generalize what they learn from one product category to the other categories as well as to the retailer. We integrate this associative belief structure into a Bayesian learning model, which can be estimated empirically from individual purchase data across categories. The model is applied to a direct mail retailer that sells products in three major categories. We analyze the complete transaction history of a sample of customers over ten and a half year period. The results show the existence of learning within and across product categories as well as considerable heterogeneity in learning across consumers. The model provides a tool to track the evolution of brand equity at the individual consumer level. Among the retailer's current best customers, we find that the retail brand equity contributes about 6% to the annual revenue. We also show how the model can be used to identify the key product category that influences brand equity in consumers' learning process.
A new shape retrieval approach based on the multi-resolution Contour-based descriptor

Object shape features provide powerful clue to objects similarity matching and retrieval. This paper will propose a novel multi-resolution contour-based feature called derivative distance descriptor (DER) for shape retrieval. The experiments are conducted on the MPEG-7 CE1 part B to test the performance of retrieval. Since user may input an incomplete shape as a query one, the experiment of incomplete shapes retrieval will be conducted on the incomplete contour representation (ICR) test to show the retrieval efficiency. Journal of Information Technology and Applications Vol. 6, No. 2, pp. 40-51 2012
" How To Gain Competitiveness in a Mexican Small-Sized Company : A Systemic Approach "

Much of the recent quality tendencies and movements have provoked that many and different models and methodologies as well, emerge in order to get more market competitiveness for companies. Total Quality Management (TQM) is, undoubtedly, one of them. However, TQM presents some adaptation problems due to Mexico’s culture. An adequate use of methodology and its model conceptualization for small and medium-sized industry, seems to be the central problems to address on this culture conflict, essentially, if we consider that this kind of industry is the productive support for Mexico. The purpuse of this paper is twofold. The first, is to show how this “problematique” should be addressed through a methodology with a systemic perspective. The second purpose, is to go beyond the utilization of this methodology, showing some results from an application in a small-sized company in the center region of Mexico.
Cyclic tensile stretch modulates osteogenic differentiation of adipose-derived stem cells via the BMP-2 pathway

Introduction Mechanical forces play critical roles in the development and remodelling process of bone. As an alternative cell source for bone engineering, adipose-derived stem cells (ASCs) should be fully investigated for their responses to mechanical stress and the mechanisms responsible for osteogenic induction in response to mechanical signals. Material and methods We hypothesized that appropriate application of uniaxial cyclic tensile strain to ASCs could increase bone morphogenetic protein-2 (BMP-2) expression and improve osteogenesis of ASCs. To test our hypothesis, ASCs from the same flask of the same donor were subjected to tensile strain with different patterns in order to eliminate the difference of donor site and passage. After surface markers investigation, the osteo-induced ASCs were subjected to uniaxial cyclic tensile stretch with the following two loading patterns: long duration continuous pattern (6 h, 1 HZ, 2000 µɛ) and short duration consecutive pattern (17 min every day for 10 consecutive days, 1 HZ, 2000 µɛ). Then osteogenic related genes were analysed by real-time PCR. Results The ASCs were positive for the markers STRO-1, CD90 and CD44 and negative for CD34. Cyclic tensile strain of 6 continuous h’ duration significantly increased gene expressions of BMP-2 and Runx2, and depressed OCN mRNA expression. In contrast, mechanical loading of 17 min every day did not significantly affect gene expression of BMP-2, Runx2, OCN or ALP. Conclusions We indicate that ASCs may sense mechanical loading in a duration-dependent manner and cyclic tensile stretch may modulate the osteogenic differentiation of ASCs via the BMP-2 signalling pathway.
The MEANING approach for automatic acquisition of sense examples

ExRetriever characterises each sense of a word as a specific query. This is automatically done by using a particular query construction strategy, which is defined a priory by an expert. Each different strategy can take into account the information related to words and available into a lexical knowledge base in order to automatically generate the set of queries. The current version of ExRetriever is able to use different lexical databases (through the Mcr) and different corpora (SemCor, BNC, the Web, etc.) through a common API. In order to easily implement different query construction strategies, ExRetriever has been powered with a declarative language. This language allows the manual definition of complex query construction strategies and it is briefly described in the fowolling section.