Miracle-dz/UniFAR-FTUs huggingface dataset:
Information Acumen: The Understanding and Use of Knowledge in Modern Business

From the Publisher: The present period has been called the Information Age. Until now, however, historians have by and large passed over the use and generation of business information. This wide-ranging book provides a new historical perspective by drawing upon concepts and models from economics, business and economic history, management studies, and the sociology and history of science. It will make an important contribution to our understanding of the role of information in business strategies and industrial policy, and marks a step towards a more sophisticated evaluation of information management styles past and present. The authors, distinguished scholars from several European countries, the USA and Japan, explore the 'information society' through focusing on ideas about the meaning and the economic function of business information. Theories of scientific management, the effect of organizational structures and the spread of ideas are studied historically and in contemporary situations throughout the world. At a time when efficient information use is expected to give particular competitive advantage to firms, this book will be of special interest to all those responsible for the use of information in large organizations as well as to scholars, including historians, economists, sociologists and management scientists.
Importance of Behavior and Morphological Traits for Controlling Body Temperature in Littorinid Snails

For organisms living in the intertidal zone, temperature is an important selective agent that can shape species distributions and drive phenotypic variation among populations. Littorinid snails, which occupy the upper limits of rocky shores and estuaries worldwide, often experience extreme high temperatures and prolonged aerial emersion during low tides, yet their robust physiology—coupled with morphological and behavioral traits—permits these gastropods to persist and exert strong grazing control over algal communities. We use a mechanistic heat-budget model to compare the effects of behavioral and morphological traits on the body temperatures of five species of littorinid snails under natural weather conditions. Model predictions and field experiments indicate that, for all five species, the relative contribution of shell color or sculpturing to temperature regulation is small, on the order of 0.2–2 °C, while behavioral choices such as removing the foot from the substratum or reorienting the shell can lower body temperatures by 2–4 °C on average. Temperatures in central California rarely exceeded the thermal tolerance limits of the local littorinid species during the study period, but at sites where snails are regularly exposed to extreme high temperatures, the functional significance of the tested traits may be important. The mechanistic approach used here provides the ability to gauge the importance of behavioral and morphological traits for controlling body temperature as species approach their physiological thresholds.
Wind Power Impact on System Frequency Deviation and an ESS based Power Filtering Algorithm Solution

Wind power is the fastest growing renewable energy. However due to its stochastic nature, fluctuating wind power results in adverse impacts on power systems, including system frequency deviations. Study on system frequency response in this paper shows power systems are more sensitive to the medium frequency power fluctuations (between 0.01 and 1 Hz), while the majority of wind power fluctuations are located in that regions and below. For small standalone power systems, even a modest wind penetration will lead to considerable system frequency deviation by the wind. To diminish the wind power impact on system frequency, an energy storage system (ESS) based wind power filtering algorithm is proposed in this paper, aimed at attenuation of those medium frequency fluctuations. Electromagnetic transient simulation results quantitatively demonstrate the effectiveness of this algorithm; the wind power is smoothed out and the system frequency deviations are limited to an acceptable level
The noncalciotropic actions of vitamin D: recent clinical developments

Purpose of reviewThis review summarizes recently described actions of 1,25-dihydroxyvitamin D beyond its function in calcium homeostasis and bone metabolism. Recent findings1,25-Dihydroxyvitamin D stimulates the innate immune system, facilitating the clearance of infections such as tuberculosis. Hypovitaminosis D has been associated with several autoimmune disorders, various malignancies, and cardiovascular risk factors in a number of recent epidemiologic reports. Based on these observational reports, vitamin D and its analogues are being evaluated for the prevention and treatment of a variety of conditions, with early findings showing mixed results. SummaryThe broad tissue distribution of the 25-hydroxyvitamin D 1α-hydroxylase enzyme and the vitamin D receptor establish a role for 1,25-dihydroxyvitamin D in the pathophysiology of various disease states and provide new therapeutic targets for vitamin D and its analogues.
Gamification system to support family-based behavioral interventions for childhood obesity

Childhood obesity is becoming one of the most serious public health problems both in health and economic terms. This paper introduces a technological solution, “OB CITY” that supports the management of childhood obesity. The system mainly uses the behavior treatment, providing two types of user terminal for the parents and the children, through an establishment of a children's social network game, letting parents grow children with a scientific way, and letting children have good living habits and learn the relevant knowledge in the game, and get a normal value of BMI. The system is in a definition phase, and will be validated with user interaction experts, leading to a first mockup to be tested with end-users.
OPTICAL COHERENCE TOMOGRAPHY ANGIOGRAPHY FEATURES OF DIABETIC RETINOPATHY

Purpose: To describe the optical coherence tomography angiography features of diabetic retinopathy. Methods: Using a 70 kHz optical coherence tomography and the split-spectrum amplitude decorrelation angiography algorithm, 6 mm × 6 mm 3-dimensional angiograms of the macula of 4 patients with diabetic retinopathy were obtained and compared with fluorescein angiography for features cataloged by the Early Treatment of Diabetic Retinopathy Study. Results: Optical coherence tomography angiography detected enlargement and distortion of the foveal avascular zone, retinal capillary dropout, and pruning of arteriolar branches. Areas of capillary loss obscured by fluorescein leakage on fluorescein angiography were more clearly defined on optical coherence tomography angiography. Some areas of focal leakage on fluorescein angiography that were thought to be microaneurysms were found to be small tufts of neovascularization that extended above the inner limiting membrane. Conclusion: Optical coherence tomography angiography does not show leakage but can better delineate areas of capillary dropout and detect early retinal neovascularization. This new noninvasive angiography technology may be useful for routine surveillance of proliferative and ischemic changes in diabetic retinopathy.
NaCl Induces Flavonoid Biosynthesis through a Putative Novel Pathway in Post-harvest Ginkgo Leaves

The flavonoids in the extracts of Ginkgo leaves have been shown to have great medical value: thus, a method to increase the flavonoid contents in these extracts is of significant importance for human health. In the present study, we investigated the changes in flavonoid contents and the corresponding gene expression levels in post-harvest Ginkgo leaves after various treatments. We found that both ultraviolet-B and NaCl treatment induced flavonoid accumulation. However, gene expression analysis showed that the increases in flavonoid contents were achieved by different pathways. Furthermore, post-harvest Ginkgo leaves responded differently to NaCl treatment compared with naturally grown leaves in both flavonoid contents and corresponding gene expression. In addition, combined treatment with ultraviolet-B and NaCl did not further increase the flavonoid contents compared with ultraviolet-B or NaCl treatment alone. Our results indicate the existence of a novel mechanism in response to NaCl treatment in post-harvest Ginkgo leaves, and provide a technique to increase flavonoid content in the pharmaceutical industry.
Task Context Dependency of Explanation Strategy in Instruction Dialogue

When an expert explains some operation to a novice, different explanation strategies are used for first time explanation, review explanation, and re-explanation for recovery from communication failure. In this paper, first by analyzing dialogue instruction dialogue corpus, we reveal how task context as well as discourse context determines tile experts’ explanation strategy, then, based on the empirical results, we also introduce a m(’chanism for selecting the most appropriate utterance content and dialogue control strategy for an instruction dialogue.
Effectiveness of Random Testing of Embedded Systems

Embedded systems like those used in automobiles have two peculiar attributes - they are reactive systems where each reaction is influenced by the current state of the system, and their inputs come from small domains. We hypothesise that, because inputs come from small domains, random testing is likely to cover all values in the domain and hence have an effectiveness comparable to other techniques. We also hypothesise that because of the reactive nature long sequences of interactions will be important for testing effectiveness. To test these hypotheses we conducted three experiments on three pieces of code selected from an automotive application. The first two experiments were designed to compare the effectiveness of randomly generated test cases against test cases that achieve the modified condition decision coverage (MCDC) and also evaluate the impact of length of the test cases on effectiveness. The third experiment compares the effectiveness of handwritten test cases against randomly generated test cases of similar length. Our objective is to help practitioners choose an effective technique to test their systems. Our findings from the limited experiments indicate that random test case generation is as effective as manual test generation at the system level. However, for unit testing test case generation to achieve MCDC coverage is more effective than random generation. Combining unit test cases with system level testing increases effectiveness. Our final observation is that increasing the test case length improves the effectiveness of a test suite both at the unit and system level.
Colour segmentation for multiple low dynamic range images using boosted cascaded classifiers

This paper proposes a multi-camera system approach to real-time colour segmentation using a cascade of AdaBoost colour classifiers with error-correcting codes (AdaBoost ECC) trained on arbitrary low-dynamic range cameras. As compared to traditional High-Dynamic Range systems that require the consolidation of multiple low-dynamic range (LDR) images to produce a single HDR image or a single tone mapped image, the proposed approach feeds directly on the LDR images, and is therefore less computationally intensive. Furthermore, the proposed approach can be employed without necessitating any spectrometric calibration of the cameras. It treats each chromatic/achromatic channel of the multi-camera system as a feature vector, allowing for a multi-dimensional colour search space over a combination of different cameras and colour spaces, without any theoretical limit to the number and type of cameras. A scene plagued with spatially-varying illumination conditions was used to test the efficacy of the proposed system. A dataset of over 89,000 samples were used for training the AdaBoost classifiers to learn eight colour categories in a matter of minutes. The experiments showed that under these extreme illumination conditions, the classifier using three cameras achieved 93% correct classification compared to less than 75% when using a single camera.
Find the Best to Share

In a virtual enterprise, how to find the best expert to share their experience and information is an important way to improve work efficiency. Semantic matching provides a basic technique to solve this problem. In this paper, semantic matching is measured by a semantic attractive force model, which is based on a domain ontology, and semantic distance computation is a core problem in semantic matching. The depth of ontology tree is considered when computing semantic distance then an agent could account semantic attractive force of optional information and chooses the best matching information to share with each other
Bounded Constrained Filtering for GPS/INS Integration

This paper considers estimation problems where inequality constraints are imposed on the outputs of linear systems and can be modeled by nonlinear functions. In this case, censoring functions can be designed to constrain measurements for use by filters and smoothers. It is established that the filter and smoother output estimates are unbiased, provided that the underlying probability density functions are even and the censoring functions are odd. The Bounded Real Lemma is employed to ensure that the output estimates satisfy a performance criterion. A global positioning system (GPS) and inertial navigation system (INS) integration application is discussed in which a developed solution exhibits improved performance during GPS outages when a priori information is used to constrain the altitude and velocity measurements.
Removal of ring artifacts in CT imaging through detection and correction of stripes in the sinogram

Due to malfunctioning and mis-calibration of cells in digital x-ray detectors as well as impurities on the scintillator screens, stripe artifacts arise in the sinogram which in turn generate ring artifacts in the reconstructed x-ray computed tomography images. In this paper, a novel technique is proposed for the detection and removal of stripe artifacts in a sinogram with a view to suppress the ring artifacts from the tomographic images. To accurately detect the stripe creating pixels using a derivative-based algorithm, at first the sinogram is windowed to create a sub-sinogram by keeping the pixel of examination at the center position in the sub-sinogram. The other pixels in the sub-sinogram are selected from a polyphase component of the sinogram. A new mathematical index is proposed here to isolate the strong and weak ring-generating stripes from the good ones. For the correction of strong ring artifacts resulting from the defective detector elements and dusty scintillator crystals, 2D variable window moving average and weighted moving average filters are proposed in this work. On the other hand, a conventionally trusted constant bias correction scheme is adopted to correct the responses of the mis-calibrated detector elements. To evaluate and compare the performance of the proposed algorithm, real micro-CT images acquired from two flat panel detectors under different operating conditions are used. Experimental results show that the proposed method can remove ring artifacts more effectively without imparting noticeable distortion in the image as compared to a recently reported technique in the literature.
OutlierD: an R package for outlier detection using quantile regression on mass spectrometry data

UNLABELLED It is important to preprocess high-throughput data generated from mass spectrometry experiments in order to obtain a successful proteomics analysis. Outlier detection is an important preprocessing step. A naive outlier detection approach may miss many true outliers and instead select many non-outliers because of the heterogeneity of the variability observed commonly in high-throughput data. Because of this issue, we developed a outlier detection software program accounting for the heterogeneous variability by utilizing linear, non-linear and non-parametric quantile regression techniques. Our program was developed using the R computer language. As a consequence, it can be used interactively and conveniently in the R environment. AVAILABILITY An R package, OutlierD, is available at the Bioconductor project at http://www.bioconductor. org
A progress assessment to evaluate pharmacy students' knowledge prior to beginning advanced pharmacy practice experiences.

OBJECTIVE To develop an assessment that would (1) help doctor of pharmacy (PharmD) students review therapeutic decision making and build confidence in their skills, (2) provide pharmacy practice residents with the opportunity to lead small group discussions, and (3) provide the assessment committee with program-level assessment data. DESIGN A case-based interactive assessment was developed and delivered to PharmD students immediately prior to advanced pharmacy practice experiences (APPEs). The assessment used an audience response system to allow immediate feedback followed by small group discussions led by pharmacy-practice residents. Students self-assessed their knowledge and confidence levels and developed personalized learning objectives for APPEs. ASSESSMENT Eighty-nine percent of students found the assessment useful, and pharmacy practice residents reported that it was helpful in developing precepting skills. The college assessment committee was able to use the data to supplement the ongoing College curricular mapping process. CONCLUSIONS An interactive assessment process can help students build confidence for experiential training, provide a learning opportunity for pharmacy residents, and produce program-level data for college assessment purposes. Planned modifications of the assessment include expanding the content areas covered and adding ability-based assessments such as communication skills.
Orthostatic hypotension predicts mortality in elderly men: the Honolulu Heart Program.

BACKGROUND Population-based data are unavailable concerning the predictive value of orthostatic hypotension on mortality in ambulatory elderly patients, particularly minority groups. METHODS AND RESULTS With the use of data from the Honolulu Heart Program's fourth examination (1991 to 1993), orthostatic hypotension was assessed in relation to subsequent 4-year all-cause mortality among a cohort of 3522 Japanese American men 71 to 93 years old. Blood pressure was measured in the supine position and after 3 minutes of standing, with the use of standardized methods. Orthostatic hypotension was defined as a drop in systolic blood pressure (SBP) of >/=20 mm Hg or in diastolic blood pressure of >/=10 mm Hg. Overall prevalence of orthostatic hypotension was 6.9% and increased with age. There was a total of 473 deaths in the cohort over 4 years; of those who died, 52 had orthostatic hypotension. Four-year age-adjusted mortality rates in those with and without orthostatic hypotension were 56.6 and 38.6 per 1000 person-years, respectively. With the use of Cox proportional hazards models, after adjustment for age, smoking, diabetes mellitus, body mass index, physical activity, seated systolic blood pressure, antihypertensive medications, hematocrit, alcohol intake, and prevalent stroke, coronary heart disease and cancer, orthostatic hypotension was a significant independent predictor of 4-year all-cause mortality (relative risk 1.64, 95% CI 1.19 to 2.26). There was a significant linear association between change in systolic blood pressure from supine position to standing and 4-year mortality rates (test for linear trend, P<0.001), suggesting a dose-response relation. CONCLUSIONS Orthostatic hypotension is relatively uncommon, may be a marker for physical frailty, and is a significant independent predictor of 4-year all-cause mortality in this cohort of elderly ambulatory men.
Adaptive consensus and algebraic connectivity estimation in sensor networks with chebyshev polynomials

In the recent years a lot of effort has been devoted to the problem of finding distributed algorithms that achieve a fast consensus. The distributed evaluation of polynomials improves the convergence speed to the consensus keeping the good properties of standard methods. The drawback about using polynomials is that they usually require some knowledge about the network in order to have good convergence properties. In this paper we consider the consensus method using Chebyshev polynomials and present an algorithm to compute, in a distributed way, the parameters that make the method get the optimal convergence rate. One of the parameters coincides with the second largest eigenvalue of the weight matrix, i.e., the algebraic connectivity, and we prove the convergence of the algorithm to it. We also present three variants of the algorithm to converge to this parameter in a faster way and to consider changes in the communication topology. We evaluate our algorithm in a simulated environment showing its performance in a wide set of networks.
Cloning, expression and purification of Mycobacterium tuberculosis ESAT-6 and CFP-10 antigens

Background and Objectives ESAT-6 (6-kDaearly secretory antigenic target) and CFP-10 (10-kDa culture filtrate protein) have been described as dominant antigens recognized by T-cells and considered as virulence factors in Mycobacterium tuberculosis. The aim of this study was to clone, express and purify recombinant ESAT-6 andCFP-10 proteins of M. tuberculosis in soluble form. Materials and Methods ESAT-6 andCFP-10 genes were amplified by PCR, cloned into pET32a (+) vector, and overexpress-ed using isopropyl-beta-D-thiogalactopyranoside in E. coli BL21 (DE3). ESAT-6 andCFP-10 proteins were purified by Ni-NTA affinity chromatography and were detected by anti- ESAT-6 and anti -CFP-10 antibodies. Results ESAT-6 andCFP-10 genes were successfully expressed and purified. Anti- ESAT-6 and anti-CFP-10 antibodies were produced after induction of immunization against purified ESAT-6 andCFP-10 proteins in rabbit. Conclusion In this study, we cloned, expressed and purified sufficient amounts of ESAT-6 andCFP-10 and it would be tested for the development of diagnostic kit for M. tuberculosis in future.
Inferring signalling networks from images

The mapping of signalling networks is one of biology's most important goals. However, given their size, complexity and dynamic nature, obtaining comprehensive descriptions of these networks has proven extremely challenging. A fast and cost‐effective means to infer connectivity between genes on a systems‐level is by quantifying the similarity between high‐dimensional cellular phenotypes following systematic gene depletion. This review describes the methodology used to map signalling networks using data generated in the context of RNAi screens.