Miracle-dz/UniFAR-FTUs huggingface dataset:
A Hybrid Phase-Shift Modulation Technique for DC/DC Converters With a Wide Range of Operating Conditions

This paper presents a new hybrid phase-shift modulation technique which is able to provide soft switching for the entire operating conditions of dc/dc converters. The proposed phase-shift modulation technique does not require any extra active/passive circuitry to guarantee soft-switching. In addition, the proposed technique can be applied to the general category of power circuit topologies for dc/dc converters, which use a full-bridge inverter in their power circuit. The proposed hybrid phase-shift modulation technique includes two distinct modulation strategies based on the operating condition of the converter. Thus, it has a variable structure that can optimize the performance for various operating conditions. The main advantages of the proposed technique are the achievement of soft-switching independent of the load condition, and optimized performance. Theoretical analysis and simulation/experimental results demonstrate the superior performance of the proposed hybrid phase-shift modulation technique over the conventional one.
A policy system to support adaptability and security on body sensors

Policy-based management enables flexible adaptive behaviour by supporting dynamic loading, enabling and disabling of policies without shutting down nodes. This overcomes many of the limitations of sensor node operating systems, such as TinyOS, which do not support dynamic modification of code. This paper presents the design, implementation and evaluation of an efficient policy system called Finger supports both event condition action rules which provide a simple means to dasiaprogrampsila adaptive behaviour and authorisation policies to protect node services and resources from external access. The system performance in terms of processing latency and resource usage is evaluated.
Are Delaware Firms Oranges? Fundamental Attributes and the Delaware Effect

Is choice of incorporation state associated with differences in firms' fundamental attributes? We show that firms incorporated in Delaware are larger, younger, less profitable, more risky, spend more in R&D, and have larger Tobin's Q than non-Delaware U.S. firms. Furthermore, we show that, compared to non-Delaware firms, Delaware firms on average issue accounting statements that are more conservatively biased (thus biasing Daines' (2001) financial measures), and that Wall Street analysts issue more optimistic earnings growth projections for Delaware firms. Then we revisit Daines (2001), which suggests that Delaware-incorporated firms command a value premium over non-Delaware U.S. firms. While Daines' study controls for most of the important attributes of Delaware firms, it does not control for accounting bias and analysts' forecasts. Upon controlling for either one of these two attributes, the Delaware value premium disappears.
Spatio-Temporal Low Count Processes with Application to Violent Crime Events

There is significant interest in being able to predict where crimes will happen, for example to aid in the efficient tasking of police and other protective measures. We aim to model both the temporal and spatial dependencies often exhibited by violent crimes in order to make such predictions. The temporal variation of crimes typically follows patterns familiar in time series analysis, but the spatial patterns are irregular and do not vary smoothly across the area. Instead we find that spatially disjoint regions exhibit correlated crime patterns. It is this indeterminate inter-region correlation structure along with the low-count, discrete nature of counts of serious crimes that motivates our proposed forecasting tool. In particular, we propose to model the crime counts in each region using an integer-valued first order autoregressive process. We take a Bayesian nonparametric approach to flexibly discover a clustering of these region-specific time series. We then describe how to account for covariates within this framework. Both approaches adjust for seasonality. We demonstrate our approach through an analysis of weekly reported violent crimes in Washington, D.C. between 2001-2008. Our forecasts outperform standard methods while additionally providing useful tools such as prediction intervals.
Maintaining Optimal CEO Incentives Through Equity Grants and CEO Portfolio Rebalancing

This paper examines the joint hypotheses that firms set optimal levels for CEO incentives, and that firms and CEOs jointly correct deviations from these optimal levels through equity grants and CEO portfolio rebalancing. I investigate two equity-based CEO incentives, pay-for-performance sensitivity and risk-taking incentive. Pay-for-performance sensitivity is defined as the change in CEO wealth for a given change in the firm's stock price, while risk-taking incentive the sensitivity of CEO wealth to equity risk. I find that firms' and CEOs' combined annual adjustment to pay-for-performance sensitivity or risk-taking incentive is negatively related to the degree that each incentive deviates from its target level at the beginning of the year, consistent with firms and CEOs jointly correcting the incentive deviations. Overall, the findings suggest that firms and CEOs coordinate their equity-granting and portfolio-rebalancing decisions to manage optimal CEO incentive levels consistent with economic theory.
Productivity, Performance Measurement and Management in Logistics

Provides a critique of the present state of the art of productivity and performance measurement and management in logistics. The nature of logistics makes normal measures of productivity, based on an output/input concept, not always appropriate. Indicator or proxy approaches can be more suitable and would relate the quality of the system to total cost, complementing conventional total productivity thinking. Highlights the main ingredients of strategic logistics performance. Develops analytical frameworks and models to aid management in planning and decision making, both operationally and strategically. Discusses the challenges of such integrated approaches, accentuating the effectiveness of the productivity philosophy in logistics. The competitive key battlegrounds include quality, productivity, speed and innovation, all linked to good business ethics. Compares Japanese and Western logistics management approaches to productivity and performance.
Multimodal deep neural nets for detecting humor in TV sitcoms

We propose a novel approach of combining acoustic and language features to predict humor in dialogues with a deep neural network. We analyze data from three popular TV-sitcoms whose canned laughters give an indication of when the audience would react. We model the setup-punchline sequential relation of conversational humor with a Long Short-Term Memory network, with utterance encodings obtained from two Convolutional Neural Networks, one to model word-level language features and the other to model frame-level acoustic and prosodic features. Our neural network framework is able to improve the F-score of over 5% over a Conditional Random Field baseline trained on a similar acoustic and language feature combination, achieving a much higher recall. It is also more effective over a language features-only setting, with a F-score of 10% higher. It also has a good generalization performance, reaching in most cases precision values of over 70% when trained and tested over different sitcoms.
Development and Validation of a Six-Gene Recurrence Risk Score Assay for Gastric Cancer

Purpose: This study was aimed at developing and validating a quantitative multigene assay for predicting tumor recurrence after gastric cancer surgery. Experimental Design: Gene expression data were generated from tumor tissues of patients who underwent surgery for gastric cancer (n = 267, training cohort). Genes whose expression was significantly associated with activation of YAP1 (a frequently activated oncogene in gastrointestinal cancer), 5-year recurrence-free survival, and 5-year overall survival were first identified as candidates for prognostic genes (156 genes, P < 0.001). We developed the recurrence risk score (RRS) by using quantitative RT-PCR to identify genes whose expression levels were significantly associated with YAP1 activation and patient survival in the training cohort. Results: We based the RRS assay on 6 genes, IGFBP4, SFRP4, SPOCK1, SULF1, THBS, and GADD45B, whose expression levels were significantly associated with YAP1 activation and prognosis in the training cohort. The RRS assay was further validated in an independent cohort of 317 patients. In multivariate analysis, the RRS was an independent predictor of recurrence [HR, 1.6; 95% confidence interval (CI), 1.02–2.4; P = 0.03]. In patients with stage II disease, the RRS had an HR of 2.9 (95% CI, 1.1–7.9; P = 0.03) and was the only significant independent predictor of recurrence. Conclusions: The RRS assay was a valid predictor of recurrence in the two cohorts of patients with gastric cancer. Independent prospective studies to assess the clinical utility of this assay are warranted. Clin Cancer Res; 22(24); 6228–35. ©2016 AACR.
Targeted label‐free quantification of interleukin‐8 in PMA‐activated U937 cell secretome by nanoLC‐ESI‐MS/MS‐sSRM

Monocytes are a part of the innate immune system. Their differentiation into macrophages changes their cellular proteome and secretome. Particularly secretome components such as cytokines are crucial for immune response and inflammation in many diseases. Differentiation of human lymphoma cell line U937 can be triggered by phorbol 12‐myristate 13‐acetate (PMA). Screening of the cytokine release in U937 upon PMA stimulation by cytometric bead array almost exclusively showed interleukin‐8 (IL‐8). Next, a label‐free nanoLC‐ESI‐MS/MS‐sSRM method for quantification of IL‐8 in the cell secretome was established and applied to monitor the time kinetics of PMA treatment in different concentrations. Targeted secretome analysis was achieved by scheduled SRM‐MS using one proteotypic peptide as precursor ion and four mass transitions. Label‐free quantification was performed by external calibration using IL‐8 standard. Validation results indicated that the method was suited for the quantification of IL‐8 in the secretome. The maximal IL‐8 release of 62.4 ng/mL was observed after incubating cells treated by 50 ng/mL PMA for 48 h. The method can now be used for quantification of IL‐8 release from different cells under various conditions. Furthermore, it can be easily expanded to other secreted proteins detected by untargeted screening methods.
Respecting Autonomy Without Disclosing Information

There is widespread agreement that it would be both morally and legally wrong to treat a competent patient, or to carry out research with a competent participant, without the voluntary consent of that patient or research participant. Furthermore, in medical ethics it is generally taken that that consent must be informed. The most widely given reason for this has been that informed consent is needed to respect the patient's or research participant's autonomy. In this article I set out to challenge this claim by considering in detail each of the three most prominent ways in which 'autonomy' has been conceptualized in the medical ethics literature. I will argue that whilst these accounts support the claim that consent is needed if the treatment of competent patients, or research on competent individuals, is to respect their autonomy, they do not support the claim that informed consent is needed for this purpose.
Zróżnicowany rozwój polskich regionów i jego konsekwencje

Conducting the regional policy both in the scale of the European Union, as well as domestic requires having the uniform information system about regions. However every state has one's peculiar organizations territorial, in frames which described individuals of the administrative division are functional for. For the purposes of the European Union however a universal system which all members of Bond can become part of is essential. He is this system hierarchical, five levels ranking of statistical NUTS individuals (Nomenklature of Units Territories for Statistics). It is applied in the process of the newsgathering, conducting statistical surveys and making their results available in spatial diameters. In the article analysis of diversifying the development of Polish regions and his influence on the size of raising EU funds were conducted
Chlorococcum humicola (Nageli) Rabenhorst as a Renewable Source of Bioproducts and Biofuel

Among the diverse new generation biomass yielding species, green algae are the most promising organisms. Compared to biomass production of other organisms, production of algae is less laborious, quite fast, and more economical. Moreover, eutrophicated waters get naturally purified in the cultivation process of algae. Algal biomass from monoculture of specific species, which are rich in carbohydrates, proteins and lipids, is considered a good source of diverse bio-products and feed-stock for food, feeds and bio-fuels. Quantity and quality of algal biomass for specific products depend on the species and strains as well as environmental conditions of cultivation. In this connection, biomass productivity and oil-yield of a local strain of Chlorococcum humicola (Nageli) Rabenhorst was assessed in Bold’s Basal Medium. Long-term storage capacity of the alga was tried by entrapping the algal cells in sodium alginate beads, which showed viability up to 14 months. Estimation of total carbohydrate, protein, lipid and chemical characterization of oil as well as the feasibility of its conversion to biodiesel revealed the industrial potential of this local strain as a source of food and biofuel. Fatty acid profiling of the extracted oil showed that 70% are mono-saturated and 12.2 % are nutritionally important polyunsaturated fatty acids. The oil could be effectively trans-esterified to methyl esters and the conversion was confirmed by FTIR spectroscopy. Further standardization of the mass production of the alga in natural environmental conditions for biomass and oil is progressing to optimize its value as globally competent food, nutraceutical and biofuel resource.
A meta-learning framework for pattern classification by means of data complexity measures

It is widely accepted that the empirical behavior of classiflers strongly depends on available data. For a given problem, it is rather di-cult to guess which classifler will provide the best performance or to set a proper expectation on classiflcation performance. Traditional experimental studies consist of presenting accuracy of a set of classiflers on a small number of problems, without analyzing why a classifler outperforms other classiflcation algorithms. Recently, some researchers have tried to characterize data complexity and relate it to classifler performance. In this paper, we present a general meta-learning framework based on a number of data complexity measures. We also discuss the applicability of this method to several problems in pattern analysis.
Regional Logistics Demand Forecasting Based on Multiple Linear Regression

Regional logistics forecasting is the key step in regional logistics planning and logistics resources rationalization. Because regional economy is the inherent and determinative factor of regional logistics demand,it is feasible to forecast regional logistics demand by economic indexes which can accelerate the harmonious development of regional logistics industry and regional economy. In this paper,total cargo volume was predicted according to the GDP,total retail sales of consumer goods and sales of fixed assets from 2001 to 2012 in ChaLing County,which resorted to multiple linear regression models and the Eviews software. It's demonstrated that multiple linear regression model of forecasting value is more accurate and effective compared to the actual value and forecast the logistics demand in the future which is within the region.
Carrier-scale programmable networks: wholesaler platform and resource optimization

This paper explores the potential benefits of programmable networks for telecommunication carriers. It particularly focuses on using a programmable network to offer a new type of wholesale product by adding value to the wholesale of pure carriage. By augmenting the wholesale of carriage with the wholesale of network-based computation, the need for server overlay deployment to support retail service providers is reduced or eliminated. The paper develops an efficient algorithm for allocation and management of computation and transport resources within the network infrastructure. This algorithm is designed to optimize a large network supporting many retail service providers and can be used by the wholesaler for the optimal management of scarce computational and transport resources. The algorithm is based on the Lagrangian relaxation method and provides error bounds so that the accuracy of the solution can be ascertained. Numerical results are presented and the benefit of the optimization for a simple multi-service scenario is assessed.
Design of energy-efficient location-based cloud services using cheap sensors

Purpose – Detecting and tracking the position of a mobile user has become one of the important subjects in many mobile applications. Such applications use location based services (LBS) for learning and training user movements in different places (cities, markets, airports, stations) along different modes of transport (bus, car, cycle, walk). To date, GPS is the key solution to all LBS but repeated GPS querying is not economical in terms of the battery life of the mobile phone. The purpose of this paper is to study how cheap and energy‐efficient air pressure sensors measuring the altitude could be used, as a complement to the dominant GPS system. The location detection and route tracking task is then accomplished by matching the collected altitude traces with the altitude curves of stored data to find the best matching routes.Design/methodology/approach – The cornerstone of the authors' approach is that a huge amount of route data, collected with GPS devices, is available in various cloud services. In orde.
Bicyclist and environmental factors associated with fatal bicycle-related trauma in Ontario.

OBJECTIVE To identify bicyclist and environmental factors associated with fatal bicycle-related trauma in Ontario. DESIGN Retrospective study. SETTING Ontario. PARTICIPANTS Information was extracted from the provincial coroner's reports on 212 people who had died of bicycle-related injuries in Ontario between 1986 and 1991. OUTCOME MEASURES Age, sex and helmet use of the bicyclist, time and place of the event, type of bicyclist or motorist error(s) and use of alcohol by bicyclist or motorist. RESULTS Only 32% of the deaths involved bicyclists under 15 years of age. The male-female ratio was 3.5. Over 75% of the cases involved head injury; however, only 8 (4%) of the bicyclists had been wearing a helmet. In 91% of the cases death occurred as the result of a bicycle-motor vehicle collision. Most (65%) of the deaths for which the time was known occurred between 4 pm and 8 am. Bicyclist error was the main cause of crash for 26 (79%) of the children less than 10 years old; it was also the main cause of crash among the bicyclists aged 10 to 19 years (43 [55%]) and those aged 45 years or more (15 [44%]). However, motorist error was the most common cause of collision in the group of cyclists 20 to 44 years of age (42 [63%]). Alcohol was detected in the blood of 7% of the bicyclists killed; alcohol had been consumed by 30% of the motorists who claimed not to have seen the cyclist. CONCLUSIONS Bicycle-related deaths result from factors that are generally avoidable. Identifiable risk factors other than lack of helmet use suggest that additional research is required to determine the benefits of preventive interventions aimed at reducing the number of such deaths. Age-specific strategies appear warranted.
(μ-3-Acetyl-5-carboxylato-4-methylpyrazolido-1:2κ4 N 2,O 3:N 1,O 5)-μ-chlorido-tetrapyridine-1κ2 N,2κ2 N-chlorido-1κCl-dicopper(II) propan-2-ol solvate

The title compound, [Cu2(C7H6N2O3)Cl2(C5H5N)4]·C3H8O, is a binuclear pyrazolate complex, in which the two CuII atoms have different coordination numbers and are connected by a bridging Cl atom. One CuII atom has a distorted square-pyramidal coordination environment formed by two pyridine N atoms, one bridging Cl atom and an N,O-chelating pyrazolate ligand. The other CuII atom adopts an octahedral geometry defined by two pyridine N atoms at the axial positions, two Cl atoms and the coordinated pyrazolate ligand in the equatorial plane. An O—H⋯O hydrogen bond connects the complex molecules and propan-2-ol solvent molecules into pairs. These pairs form columns along the a axis.
Ammonia Measurements and Emissions from a California Dairy Using Point and Remote Sensors

Ammonia (NH3) is an important trace gas species in the atmosphere that can have negative impacts on human, animal, and ecosystem health. Agriculture has been identified as the largest source of NH3, specifically livestock operations. NH3 emissions from a commercial dairy in California were investigated during June 2008. Cattle were held in open-lot pens, except for young calves in hutches with shelters. Solid manure was stored in the open-lot pens. Liquid manure from feed lanes was passed through a solids settling basin and stored in a holding pond. Passive sensors and openpath Fourier transform infrared spectrometers (OP-FTIR) were deployed around the facility to measure NH3 concentrations. Emissions from pens and the liquid manure system (LMS) were estimated using inverse modeling. Mean emission factors (EFs) for the entire facility were 140.5 ±42.5 g d animal from the passive sampler data and 199.2 ±22.0 g d animal from the OP-FTIR data, resulting in the facility’s summer emissions calculated at 265.2 ±80.2 kg d and 375.4 ±27.1 kg d, respectively. These EFs are within the range of values reported in the literature. Both concentrations and emissions exhibited a strong diurnal cycle, peaking in the late afternoon. Total facility emissions exhibited significant positive correlations with temperature and wind speed. The findings of this study show that NH3 emissions from a commercial dairy can vary by a factor of 10 or more throughout the day, and EFs can vary by two orders of magnitude when compared to other U.S. dairies, based on literature values.
Estimating the Greenland ice sheet surface mass balance contribution to future sea level rise using the regional atmospheric climate model MAR

Abstract. To estimate the sea level rise (SLR) originating from changes in surface mass balance (SMB) of the Greenland ice sheet (GrIS), we present 21st century climate projections obtained with the regional climate model MAR (Modele Atmospherique Regional), forced by output of three CMIP5 (Coupled Model Intercomparison Project Phase 5) general circulation models (GCMs). Our results indicate that in a warmer climate, mass gain from increased winter snowfall over the GrIS does not compensate mass loss through increased meltwater run-off in summer. Despite the large spread in the projected near-surface warming, all the MAR projections show similar non-linear increase of GrIS surface melt volume because no change is projected in the general atmospheric circulation over Greenland. By coarsely estimating the GrIS SMB changes from GCM output, we show that the uncertainty from the GCM-based forcing represents about half of the projected SMB changes. In 2100, the CMIP5 ensemble mean projects a GrIS SMB decrease equivalent to a mean SLR of p4 p 2 cm and p9 p 4 cm for the RCP (Representative Concentration Pathways) 4.5 and RCP 8.5 scenarios respectively. These estimates do not consider the positive melt–elevation feedback, although sensitivity experiments using perturbed ice sheet topographies consistent with the projected SMB changes demonstrate that this is a significant feedback, and highlight the importance of coupling regional climate models to an ice sheet model. Such a coupling will allow the assessment of future response of both surface processes and ice-dynamic changes to rising temperatures, as well as their mutual feedbacks.