Miracle-dz/UniFAR-FTUs huggingface dataset:
Operational scheduling of Virtual Power Plants in the presence of energy storages and demand response programs for participating in the energy market

The Virtual Power Plant (VPP) concept is developed in order to improve handling and visibility of Distributed Energy Resources (DERs) for system operators and other market players by making an appropriate interface among these system components. Using this concept, DERs could be considered as a substitution for Conventional Power Plants (CPPs) in both forms of production energy and capacity. In this paper, an operational model for optimal day ahead electrical and thermal scheduling of a VPP for participating in the energy market is proposed where participation of energy storage systems and demand response programs are also taken into account. The proposed model is tested on a large scale VPP composed of various types of DERs and is solved using Mixed Integer Linear Programming (MILP) solver XPRESS under GAMS software. The results demonstrated that implementation of demand response programs would decrease total operation costs of VPP as well as its dependency on the upstream network.
Matching Jobs to Resources in Distributed Desktop Grid Environments

Desktop grids use opportunistic sharing to exploit large collections of personal computers and workstations across the Internet and can achieve tremendous computing power with low cost. However, current systems are typically based on a traditional client-server architecture, which has inherent shortcomings with respect to robustness, reliability and scalability. In this paper, we propose a decentralized, robust, highly available, and scalable infrastructure to match incoming jobs to available resources. The key idea behind our proposed system is to leverage information provided by an underlying peer-to-peer system to create a hierarchical Rendezvous Node Tree, which performs the matching efficiently. Our experimental results obtained via simulation show that we can effectively match jobs with varying levels of resource constraints to available nodes and maintain good load balance in a fully decentralized heterogeneous computational environment.
Fatigue Crack Length Sizing Using a Novel Flexible Eddy Current Sensor Array

The eddy current probe, which is flexible, array typed, highly sensitive and capable of quantitative inspection is one practical requirement in nondestructive testing and also a research hotspot. A novel flexible planar eddy current sensor array for the inspection of microcrack presentation in critical parts of airplanes is developed in this paper. Both exciting and sensing coils are etched on polyimide films using a flexible printed circuit board technique, thus conforming the sensor to complex geometric structures. In order to serve the needs of condition-based maintenance (CBM), the proposed sensor array is comprised of 64 elements. Its spatial resolution is only 0.8 mm, and it is not only sensitive to shallow microcracks, but also capable of sizing the length of fatigue cracks. The details and advantages of our sensor design are introduced. The working principal and the crack responses are analyzed by finite element simulation, with which a crack length sizing algorithm is proposed. Experiments based on standard specimens are implemented to verify the validity of our simulation and the efficiency of the crack length sizing algorithm. Experimental results show that the sensor array is sensitive to microcracks, and is capable of crack length sizing with an accuracy within ±0.2 mm.
Distributed Clustering for Wireless Sensor Networks

Wireless sensor networks is a key technology for new ways of interaction between computers and the physical environment. However, the energy constrained and limited computing resources of the sensor nodes present major challenges in gathering data. Since sensor nodes are densely deployed, redundant data may occur. While cluster-based data gathering is efficient at energy and bandwidth, it's difficult to cluster network efficiently. In this work, a new distributed clustering algorithm for ubiquitous sensor network is presented. Clustering is based on the distance between nodes and the number in a cluster for wireless sensor networks. Simulation results show that the proposed algorithm balances the energy dissipation over the whole network thus increase the amount of data delivery to the sink
A platform for massive heterogeneous astronomical data retrieval

The efficiency of data retrieval from massive heterogeneous astronomical catalogs, as well as integration of various astronomical data retrieval services, are both key problems in astronomical data retrieval. This paper introduces a platform for Massive Heterogeneous Astronomical Data Retrieval (MHADR) which has been applied to the data center of National Astronomical Observatory of China. It proposes an index mechanism based on cross-matching to retrieve massive heterogeneous astronomical data resources from multiple catalogs efficiently. And on the platform it integrates various data retrieval services using the structure of four modules. ConeSearch service is implemented as a sample service of the platform. And the experiment shows the cross-matching in the retrieval costs nearly 25s, which implies the high efficiency cross-matching.
Health promotion in the workplace: employers and employee's perspectives

With Obesity rates hitting epidemic proportions, healthcare costs are increasingly becoming a drain on society and the impact is telling on the global economy. There is no quick solution to addressing the obesity issue, however targeting certain cohorts, via campaigns and initiatives, such as the working population, are deemed worthwhile. This dissertation examines the issue of health promotion as a public health concern and a workplace concern. Using qualitative method of research via focus groups, views and opinions of employers and employees working in companies in Ireland, are gathered on health promotion specifically relating to workplace wellbeing initiatives. Motivating employees to make a lifestyle changes and methods of promoting workplace health initiatives are also explored. In particular, on whether there is merit in using social media to promote workplace wellbeing initiatives during, and beyond the confines of, the working day. Four focus groups with 3 – 7 people in each were formed, two using employer’s perspectives, and two using employees perspectives (21 individuals in total). The semi-structured discussion sessions educed participants’ views on workplace health promotion. Transcripts were taken verbatim, using a combination of transcribe notes and audio recordings. These were then analysed manually using an inductive thematic analysis procedure as outlined by Braun and Clarke (2006). Findings for this qualitative research show that stress is the number one factor affecting workplaces and their employees. This is predominantly caused by the aftermath of the 2008 economic downturn, and the resultant in financial pressures for individuals and subsequently workplaces. Many employers have embarked on engagement strategies to alleviate stress through health promotion. Stress is the number one concern for employees and workplaces, and directly linked to the economic downturn and financial pressures. Employee engagement strategies to alleviate stress are employed to alleviate stress with positive feedback. Sourcing health information via the internet search engine Google the first point for a number of people. Web-based strategies integrated with supports may prove be an innovative approach to addressing public and workplace health campaigns in the future.
HIGHER EDUCATION INSTITUTIONS AND SOCIAL PERFORMANCE: EVIDENCE FROM PUBLIC AND PRIVATE UNIVERSITIES

The paper proposes that universities should make social responsibility part of their triple bottom lines – economic, environment and social. The aim of the paper is to examine public and private universities’ approach to social responsibilities in a developing country. 10 years of annual reports from 2000–2009 were obtained and scrutinised into social performance categories proposed by Puukka (2008): promotion of well-being; promotion of knowhow; promotion of ownership and community involvement. The findings show that the two universities have responded differently to social responsibility. The more traditional public university which struggled to preserve its organizational identity focused its social responsibilities internally (towards existing students and staff) rather than towards the outside communities. It is interesting to note that the private university employed a very distinctive strategy by using social responsibility platforms to not only preserve its legitimacy but actually as part of its response to the ever-changing demands and pressures. These findings revealed that social responsibility was important to universities for survival, or at least for enhancing their legitimacy.
Distributed calibration of a camera sensor network

Wireless camera sensor networks are finding potential applications in the areas of sensing and control. Such applications require the camera nodes of the network be calibrated precisely. This paper proposes a simple algorithm to perform distributed calibration of a camera sensor network that has been deployed in an unknown environment. The camera sensor nodes use their imaging abilities in collaboration with a cooperative moving target to determine their positions and orientations. The proposed algorithm requires simple arithmetic calculations and hence, it can be programmed on to low power processors. Its correctness, reliability and scalability for a large scale network have been validated by performing simulations using Player/Stage robotic simulations software. The algorithm has been implemented practically on a real time camera sensor network.
Fast Femoral Artery Segmentation from Black-Blood MRI

With the prevalence of about 3% in the general Chinese population, peripheral arterial disease (PAD) has become a serious health issue. To address this issue, vessel wall imaging techniques have been introduced to assess the burden of PAD in terms of vessel wall thickness, area or volume. Recent advances in a 3D black-blood MRI sequence known as the 3D MSDE prepared rapid gradient echo sequence (3D MERGE) have allowed the acquisition of vessel wall images with up to 50 cm coverage, facilitating noninvasive and detailed PAD assessment. This work introduces an algorithm that combines 2D slice-based segmentation and 3D user editing to allow for efficient plaque burden analysis of 3D MERGE femoral artery images. The 2D slice-based segmentation approach is based on propagating segmentation results of contiguous 2D slices. The 3D image volume was then reformatted using the curved planar reformation (CPR) technique. User editing of the segmented contours was performed on the CPR views taken at different angles. The method was evaluated on 6 femoral artery images. Lumen and outer wall boundaries segmented using the proposed algorithm were assessed by comparison with manual segmentation. The Mean Absolute Difference (MAD) between the semi automatically segmented lumen boundaries and the manually segmented boundaries was 0.23 ±0.20mm and the MAD between the semi automatically segmented wall boundaries and the manually segmented boundaries was 0.25±0.14mm. The time required for the entire semi automated segmentation process was only 1-2% of the time required for manual segmentation.
Filter Paper Blood Spot Enzyme Linked Immunoassay for Insulin and Application in the Evaluation of Determinants of Child Insulin Resistance

Background In large-scale epidemiology, bloodspot sampling by fingerstick onto filter paper has many advantages, including ease and low costs of collection, processing and transport. We describe the development of an enzyme-linked immunoassay (ELISA) for quantifying insulin from dried blood spots and demonstrate its application in a large trial. Methods We adapted an existing commercial kit (Mercodia Human Insulin ELISA, 10-1113-01) to quantify insulin from two 3-mm diameter discs (≈6 µL of blood) punched from whole blood standards and from trial samples. Paediatricians collected dried blood spots in a follow-up of 13,879 fasted children aged 11.5 years (interquartile range 11.3–11.8 years) from 31 trial sites across Belarus. We quantified bloodspot insulin levels and examined their distribution by demography and anthropometry. Results Mean intra-assay (n = 157) coefficients of variation were 15% and 6% for ‘low’ (6.7 mU/L) and ‘high’ (23.1 mU/L) values, respectively; the respective inter-assay values (n = 33) were 23% and 11%. The intraclass correlation coefficient between 50 paired whole bloodspot versus serum samples, collected simultaneously, was 0.90 (95% confidence interval 0.85 to 0.95). Bloodspot insulin was stable for at least 31 months at −80°C, for one week at +30°C and following four freeze-thaw cycles. Paediatricians collected a median of 8 blood spots from 13,487 (97%) children. The geometric mean insulin (log standard deviation) concentrations amongst 12,812 children were 3.0 mU/L (1.1) in boys and 4.0 mU/L (1.0) in girls and were positively associated with pubertal stage, measures of central and peripheral adiposity, height and fasting glucose. Conclusions Our simple and convenient bloodspot assay is suitable for the measurement of insulin in very small volumes of blood collected on filter paper cards and can be applied to large-scale epidemiology studies of the early-life determinants of circulating insulin.
CEO Power on Corporate Performance in Chinese Market

This paper examines the CEO power on corporate performance in Chinese market from 1999 to 2004. The empirical results indicate that CEO power and corporate performance are positively related, but CEO power and performance variability are negatively related. This conclusion is not consistent with Adams, RB. 's, because of the particularity of Chinese market system. Based on the conclusion, we suggest some solutions which combine the restraint and incentive mechanism to the high concentration of CEO power.
Liver Image Mosaicing System Based on Scale Invariant Feature Transformand Point Set Matching Method

Image mosaic is an important research content in digital image processing, and could be used to solve the prob- lem of observing large objects with narrow view, such as 360 degree panorama stitching. Microscopic observation of liver biopsy is a commonly used method in diagnosing liver diseases, which are always rely on the whole liver slice. Therefore, the liver pathological microscopic image mosaic is the best way to formulate it. This paper proposes a liver image mosaic- ing system based on scale invariant feature transform and point set matching method, which includes the feature point se- lection and location process to find the extremum point, screen them, and precisely position them. This system takes the affine transformation as the motion model, and adopts a new matching algorithm for the rigid transformation to accelerate solving the motion parameter. The design and implementation of the liver image mosaicing system have completed more than 100 cases successfully, which shows the effectiveness and robustness of our algorithms.
Revenue Optimization for Group-Buying Websites

Group-buying websites represented by Groupon.com are very popular in electronic commerce and online shopping nowadays. They have multiple slots to provide deals with significant discounts to their visitors every day. The current user traffic allocation mostly relies on human decisions. We study the problem of automatically allocating the user traffic of a group-buying website to different deals to maximize the total revenue and refer to it as the Group-buying Allocation Problem (\GAP). The key challenge of \GAP\ is how to handle the tipping point (lower bound) and the purchase limit (upper bound) of each deal. We formulate \GAP\ as a knapsack-like problem with variable-sized items and majorization constraints. Our main results for \GAP\ can be summarized as follows. (1) We first show that for a special case of \GAP, in which the lower bound equals the upper bound for each deal, there is a simple dynamic programming-based algorithm that can find an optimal allocation in pseudo-polynomial time. (2) The general case of \GAP\ is much more difficult than the special case. To solve the problem, we first discover several structural properties of the optimal allocation, and then design a two-layer dynamic programming-based algorithm leveraging those properties. This algorithm can find an optimal allocation in pseudo-polynomial time. (3) We convert the two-layer dynamic programming based algorithm to a fully polynomial time approximation scheme (FPTAS), using the technique developed in \cite{ibarra1975fast}, combined with some careful modifications of the dynamic programs. Besides these results, we further investigate some natural generalizations of \GAP, and propose effective algorithms.
B-cell Epitope Mapping of Helicobacter pylori Neutrophil-Activating Protein

Helicobacter pylori is a major cause of chronic gastritis, peptic ulcer disease, and associated with gastric carcinoma. H. pylori Neutrophil-activating protein (HP-NAP) is one of the major virulence factors. It has been shown that HP-NAP is a good candidate antigen for a multi-epitopes vaccine against H. pylori. However, the B-cell epitopes of HP-NAP are largely unknown. Bioinformatic and immunological approaches are used to map B-cell epitopes of this antigen. Four high antigenic peptides located in different regions were found by B cell epitope prediction. Three mAbs were produced by using recombinant HP-NAP-GST as the immunogen by the standard hybridoma technique. The immunohistochemical staining showed that mAbs against HP-NAP specifically reacted with clinical strains of H. pylori. Three different mimicry B-cell epitopes as mimotopes of HP-NAP protein are identified through screening the phage displayed peptide libraries with these mAbs.
INTELLECTUAL CAPITAL LITERATURE REVIEW: MEASUREMENT, REPORTING AND MANAGEMENT

The rise of the “new economy”, one principally driven by information and knowledge, is attributed to the increased prominence of intellectual capital (IC) as a business and research topic. Intellectual capital is implicated in recent economic, managerial, technological, and sociological developments in a manner previously unknown and largely unforeseen. Whether these developments are viewed through the filter of the information society, the knowledge‐based economy, the network society, or innovation, there is much to support the assertion that IC is instrumental in the determination of enterprise value and national economic performance. First, we seek to review some of the most significant extant literature on intellectual capital and its developed path. The emphasis is on important theoretical and empirical contributions relating to the measurement and reporting of intellectual capital. The second part of this paper identifies possible future research issues into the nature, impact and value of intellectual management and reporting.
Empirical Study of Online Auction Seller Switching: The Case of Yahoo vs. Ruten in Taiwan

Most online auction platform providers (OAPPs) agree that the majority of their profits comes from users, i.e., their buyers and sellers. The major concern of OAPPs is how to gain and lock in users in order to maintain and enhance a competitive edge. Customer switching is one of the primary problems of all companies, including OAPPs. This study focused on online auction sellers and attempted to understand their switching behavior. We developed an integrated model that consisted of OAPP strategies (anti-switching and anti-lock-in), value-based factors (platform qualities and switching costs), lock-in factors (network effects), and perceived values to explore the switching intentions of online auction sellers. The model was tested using a field study of 248 sellers from two online auction websites. The results show that OAPP strategies will affect switching costs which affect perceived value which, in turn, impacts a seller’s switching behavior. Our findings indicate that value-based factors directly influence perceived value which could suitably explain a seller’s decision to switch from one OAPP to another. The study suggests that OAPPs should develop strategies and leverage the network effect to avoid customer switching.
Gait recognition using gait Gaussian image

In this paper, we proposed a new spatio-temporal based method for human gait recognition, named as Gait Gaussian Image (GGI). Gait Gaussian image is a period based gait technique, which is used for feature extraction of gait image over a gait cycle. The features derived from GGI are classified through Nearest neighbor method. Simulations and results are calculated on two benchmark datasets i.e. CASIA-B and Soton. Experimental results show the efficiency and effectiveness of the proposed method.
An open implementation of the SIFT detector and descriptor

This note describes an implementation of the Scale-Invariant Feature Transform (SIFT) detector and descriptor [1]. The implementation, which is compatible with D. Lowe’s implementation, is distributed along with the source code. Designed for the MATLAB environment, the code is broken into several M and MEX files that enable running selected portions of the algorithm. The SIFT detector and descriptor are discussed in depth in [1]. Here we only describe the interface to our implementation and, in the Appendix, we discuss some technical details.
Fatigue in Multiple Sclerosis: Assessing Pontine Involvement Using Proton MR Spectroscopic Imaging

Background/Objective The underlying mechanism of fatigue in multiple sclerosis (MS) remains poorly understood. Our study investigates the involvement of the ascending reticular activating system (ARAS), originating in the pontine brainstem, in MS patients with symptoms of fatigue. Methods Female relapsing-remitting MS patients (n = 17) and controls (n = 15) underwent a magnetic resonance spectroscopic imaging protocol at 1.5T. Fatigue was assessed in every subject using the Fatigue Severity Scale (FSS). Using an FSS cut-off of 36, patients were categorized into a low (n = 9, 22 ± 10) or high (n = 10, 52 ± 6) fatigue group. The brain metabolites N-acetylaspartate (NAA) and total creatine (tCr) were measured from sixteen 5x5x10 mm3 spectroscopic imaging voxels in the rostral pons. Results MS patients with high fatigue had lower NAA/tCr concentration in the tegmental pons compared to control subjects. By using NAA and Cr values in the cerebellum for comparison, these NAA/tCr changes in the pons were driven by higher tCr concentration, and that these changes were focused in the WM regions. Discussion/Conclusion Since there were no changes in NAA concentration, the increase in tCr may be suggestive of gliosis, or an imbalanced equilibrium of the creatine and phosphocreatine ratio in the pons of relapsing-remitting MS patients with fatigue.
When is a Social 1 Running Head : AFFILIATION AND COOPERATION When is a Social Dilemma not a Dilemma ? Group Affiliation and Social Goals Transform Payoffs for Cooperation

Social dilemmas arise when people follow their own best interests, yet the consequence of their separate choices is sub-optimal for all of them. Mo netary payoffs, however, do not necessarily define best interests. “Best” is constructed and ca n depend strongly on social context. Two studies successfully manipulated and measured group affiliation. Increased saliency of the group and of social goals rendered cooperative action mor e likely. These results have practical implications for avoiding real-world social dilemma s. Some of the factors underlying cooperation changed, however, when monetary payoffs and cooperative success were delayed 6 months. Affiliation is partly oriented toward the h re-and-now.