Miracle-dz/UniFAR-FTUs huggingface dataset:
Solving Call Center Agent Scheduling Problem through Improved Adaptive Genetic Algorithm

With the emergence of call center and its wide applications in enterprises, the schedule of agents becomes a core problem for reasonably deploying the human resources in call center and improving the productive force of the call center. This study uses improved adaptive genetic algorithm (IAGA) to solve scheduling problem for a 24-hours call center. This paper builds a mathematical model to describe the constraints of the agent scheduling problem with the object for minimizing the gap between demand forecast and actual work volume in each time period. in order to solve the defects of existing search algorithm, this paper uses IAGA to get the optimal solution of the optimization problem. Satisfactorily, the simulation results have turned out that the method possesses a better solving effect in faster test speed.
EWS/FLI1 Regulates EYA3 in Ewing Sarcoma via Modulation of miRNA-708, Resulting in Increased Cell Survival and Chemoresistance

Ewing sarcoma is an aggressive pediatric cancer of the bone and soft tissue, in which patients whose tumors have a poor histologic response to initial chemotherapy have a poor overall prognosis. Therefore, it is important to identify molecules involved in resistance to chemotherapy. Herein, we show that the DNA repair protein and transcriptional cofactor, EYA3, is highly expressed in Ewing sarcoma tumor samples and cell lines compared with mesenchymal stem cells, the presumed cell-of-origin of Ewing sarcoma, and that it is regulated by the EWS/FLI1 fusion protein transcription factor. We further show that EWS/FLI1 mediates upregulation of EYA3 via repression of miR-708, a miRNA that targets the EYA3 3′-untranslated region, rather than by binding the EYA3 promoter directly. Importantly, we show that high levels of EYA3 significantly correlate with low levels of miR-708 in Ewing sarcoma samples, suggesting that this miR-mediated mechanism of EYA3 regulation holds true in human cancers. Because EYA proteins are important for cell survival during development, we examine, and show, that loss of EYA3 decreases survival of Ewing sarcoma cells. Most importantly, knockdown of EYA3 in Ewing sarcoma cells leads to sensitization to DNA-damaging chemotherapeutics used in the treatment of Ewing sarcoma, and as expected, after chemotherapeutic treatment, EYA3 knockdown cells repair DNA damage less effectively than their control counterparts. These studies identify EYA3 as a novel mediator of chemoresistance in Ewing sarcoma and define the molecular mechanisms of both EYA3 overexpression and of EYA3-mediated chemoresistance. Mol Cancer Res; 10(8); 1098–108. ©2012 AACR.
Integrated AC/DC converter with no-load over-voltage protection and safe start-up

This paper presents early measurement results of an integrated AC/DC converter, discusses about the start-up problem which was not addressed in our previous work and shows a way to solve it. The AC/DC converter converts the AC voltage of the power grid to regulated 3V DC voltage without need to bulky step-down transformer. Over-voltage problem at light load and no-load conditions due to lack of step-down transformer, is solved by an additional circuitry which prevents the converted voltage from rising high and damaging the converter. To reach less output ripple, a capacitor-less low drop-out (LDO) regulator is cascaded to the output of the converter. The measurements were done for both full-load and half-load of 17mA and 10mA respectively, and it was confirmed that the no-load over-voltage protection scheme works fine. The circuit has been implemented in a 0.35 μm 4M/2P CMOS silicon-on-insulator (SOI) technology with using both 3.3 V and 5V transistors.
Dynamic Topological Mapping with Biobotic Swarms

In this paper, we present an approach for dynamic exploration and mapping of unknown environments using a swarm of biobotic sensing agents, with a stochastic natural motion model and a leading agent (e.g., an unmanned aerial vehicle). The proposed robust mapping technique constructs a topological map of the environment using only encounter information from the swarm. A sliding window strategy is adopted in conjunction with a topological mapping strategy based on local interactions among the swarm in a coordinate-free fashion to obtain local maps of the environment. These maps are then merged into a global topological map which can be visualized using a graphical representation that integrates geometric as well as topological feature of the environment. Localized robust topological features are extracted using tools from topological data analysis. Simulation results have been presented to illustrate and verify the correctness of our dynamic mapping algorithm.
A note on scaling cosmologies, geodesic motion and pseudo-susy

One-parameter solutions in supergravity carried by scalars and a metric trace out curves on the scalar manifold. In ungauged supergravity these curves describe a geodesic motion. It is known that a geodesic motion sometimes occurs in the presence of a scalar potential and for time-dependent solutions this can happen for scaling cosmologies. This note contains a further study of such solutions in the context of pseudo-supersymmetry for multi-field systems whose first-order equations we derive using a Bogomol'nyi-like method. In particular we show that scaling solutions that are pseudo-BPS must describe geodesic curves. Furthermore we clarify how to solve the geodesic equations of motion when the scalar manifold is a maximally non-compact coset such as occurs in maximal supergravity. This relies upon a parametrization of the coset in the Borel gauge. We then illustrate this with the cosmological solutions of higher-dimensional gravity compactified on a $n$-torus.
Encryption in High Dynamic Range Images for RGBE Format

This paper presents a new encryption scheme of high dynamic range (HDR) images. HDR images are more and more popular and network bandwidth is large enough to transmit large data, therefore, HDR images need to be properly protected, such as encryption. Here we use a new tool to achieve the purpose of encryption. The features of elementary cellular automata (ECA) that make us choose it as an encryption tool. ECA allows this encryption scheme be implemented easily and executed efficiently. The experimental results prove this encryption scheme sufficient security and doesn't need expensive computing resources.
10 Conclusion. Reflections on Present and Future: towards an Ontological Approach to LMOOCs

This concluding chapter gives an overview of the affordances and weaknesses of LMOOCs mentioned in the previous chapters, before situating them in a larger framework of ontological specification. A second angle of attack is to test LMOOCs from an educational engineering point of view. Finally, directions for LMOOC research are given in the light of current CALL research challenges. LMOOCs will or will not survive depending on their genuine ontological specification.
Title Passivity-based control for hybrid systems with applications to mechanical systems exhibiting impacts

Motivated by applications of systems interacting with their environments, we study the design of passivity-based controllers for a class of hybrid systems in which the energy dissipation may only happen along either the continuous or the discrete dynamics. A general definition of passivity, encompassing the said special cases, is introduced and, along with detectability and solution conditions, linked to stability and asymptotic stability of compact sets. The proposed results allow to take advantage of the passivity property of the system at flows or at jumps and are employed to design passivity-based controllers for the class of hybrid systems of interest. Two applications, one pertaining to a point mass physically interacting with a wall and another about controlling a ball bouncing on an actuated surface, illustrate the definitions and results throughout the paper.
Liquid–liquid phase separation in particles containing organics mixed with ammonium sulfate, ammonium bisulfate, ammonium nitrate or sodium chloride

Abstract. As the relative humidity varies from high to low values in the atmosphere, particles containing organic species and inorganic salts may undergo liquid–liquid phase separation. The majority of the laboratory work on this subject has used ammonium sulfate as the inorganic salt. In the following we studied liquid–liquid phase separation in particles containing organics mixed with the following salts: ammonium sulfate, ammonium bisulfate, ammonium nitrate and sodium chloride. In each experiment one organic was mixed with one inorganic salt and the liquid–liquid phase separation relative humidity (SRH) was determined. Since we studied 23 different organics mixed with four different salts, a total of 92 different particle types were investigated. Out of the 92 types, 49 underwent liquid–liquid phase separation. For all the inorganic salts, liquid–liquid phase separation was never observed when the oxygen-to-carbon elemental ratio (O : C) g 0.8 and was always observed for O : C
Use of Sildenafil to Facilitate Weaning From Inhaled Nitric Oxide in Children With Pulmonary Hypertension Following Surgery for Congenital Heart Disease

Pulmonary hypertension frequently complicates the postoperative management of patients after congenital cardiac surgery. Inhaled nitric oxide is an effective treatment option, but rebound pulmonary hypertension can occur upon its withdrawal. Sildenafil may facilitate its withdrawal by restoring cyclic guanosine monophosphate availability via phosphodiesterase-5 inhibition. The purpose of this study was to evaluate the use of sildenafil in facilitating weaning from inhaled nitric oxide after congenital cardiac surgery in patients who had previously failed weaning, and to compare the effects of sildenafil on pulmonary and systemic hemodynamics. Children who received sildenafil after cardiovascular surgery during a 23-month period at Riley Hospital for Children were identified. Medical records were retrospectively reviewed to determine sildenafil and nitric oxide dosing, pulmonary and systemic blood pressures, and adverse effects. Oral sildenafil was administered to 7 children who had failed attempts at inhaled nitric oxide weaning. Inhaled nitric oxide was weaned from 29.8 ± 5.9 ppm prior to sildenafil initiation to 12.2 ± 3.4 ppm (mean ± SE; P = .024) in the 24 hours after sildenafil. Mean pulmonary artery and systemic arterial pressure were unchanged from baseline when measured 1 hour after sildenafil dosing (mean pulmonary artery pressure, 29 ± 1 to 27 ± 0.7 mm Hg, P = .066; mean systemic arterial pressure, 56 ± 1.2 to 54 ± 1.2 mm Hg, P = .202). Sildenafil may facilitate withdrawal of inhaled nitric oxide and prevent rebound pulmonary hypertension in patients previously failing inhaled nitric oxide weaning attempts.
A Study of Factors Affecting the Intention of Usage in MOOC

Massive Open Online Course(MOOC) is recently being spread worldwide around the U.S.A, and contrary to existing online lectures, it is a type of lecture allowing the communication between the instructor and each student. With the expansion of MOCC system use, this study aimed to investigate what factors make the people needing to be educated use a MOOC. For this aim, this study set a research model which on the basis of TAM(Technology Acceptance Mechanism) and empirically analyzed the model and identified the relationships among influential factors.
Informatyka Ekonomiczna Business Informatics Vangel v. Ajanovski: Model and Implementation of a Self-adaptive Social Modeling Demand Forecast Variance in a Distributed Supply Chain Network Using Generalized Stochastic Petri Nets

There is a trade-off in Supply Chain Management Systems between efficiency and demand variability. When no variation occurs in consumer need, order cycle, product portfolios, and in distribution lead time, then the supply chain would be just a routine business process. Unfortunately, in practice this is not often the case. Thus, ranking demand variability is one of the prime challenges to reduce safety stock without affecting customer demand. This paper studies supply chain demand variability with multiple suppliers, manufacturers, distributors, wholesalers, retailers, and customers as tiers, and each stage as an echelon that faces stochastic demand volatility. A Generalized Stochastic Petri-Net (GSPN) model is proposed in a distributed scenario to synchronize the response capabilities among the players in the chain, and to lower down the supplier demand variance with scheduled ordering policies. Maintaining a uniform inventory stock throughout the chain has two main effects: the bullwhip effect (BWE) will be negligible, and uncertainty in decision making at each echelon will be reduced substantially.
An approach to robust unsupervised speaker adaptation

In this letter, we propose an approach to robust unsupervised speaker adaptation. Usually, recognition errors made on the adaptation utterances mislead parameter estimation when a speaker adaptation algorithm is operated in an unsupervised mode. In order to alleviate this problem, we first adapt a Gaussian mixture model (GMM) and then transform the hidden Markov model (HMM) parameters according to the information extracted from GMM adaptation.
Groups definable in linear o-minimal structures: the non-compact case

Abstract Let = ⟨M, +, <, 0, S⟩ be a linear o-minimal expansion of an ordered group, and G = ⟨G, ⊕,eG ) an n-dimensional group definable in . We show that if G is definably connected with respect to the t-topology, then it is definably isomorphic to a definable quotient group U/L. for some convex ∨-definable subgroup U of ⟨Mn , +⟩ and a lattice L of rank equal to the dimension of the ‘compact part’ of G.
Instantaneous pitch estimation based on empirical wavelet transform

In this paper, a novel approach is proposed specially for capturing the instantaneous pitch that may reveals some innate character of the speech. Firstly, the original signal is decomposed into several modes with empirical wavelet transform, and then the mode containing the pitch is picked out, finally the instantaneous pitch is calculated via Hilbert transform. Intensive evaluation and direct comparisons with existing method are conducted with the standard Chinese and English speech database, all showing the effectiveness of the proposed method in acquiring the instantaneous pitch.
Knowledge Fusion in Semantic Grid

Just as the Web is shifting its focus from information and communication and emphasizes the need to reuse of knowledge as a huge distributed knowledge base, the semantic grid in which information and services are given well-defined meaning extends the current grid to enable software agents, users, and programs to work in cooperation. How to process the different sources of information, in particular, to combine a variety of sources of knowledge to assist users with effective reasoning or collaborative problem-solving, is one of great barrier in realizing the above vision. Against this background, we propose a knowledge fusion and integration approach based on statistical decision theory and Bayesian analysis for the semantic grid
Channel Training Signal Design for Reciprocal Multiple Antenna Systems With Beamforming

Fast and efficient channel estimation is key to achieving high data rate performance in mobile and vehicular communication systems, where the channel is fast time-varying. To this end, this work proposes and optimizes channel-dependent training schemes for reciprocal Multiple-Input Multiple-Output (MIMO) channels with beamforming (BF) at the transmitter and receiver. First, assuming that Channel State Information (CSI) is available at the receiver, a channel-dependent Reverse Channel Training (RCT) signal is proposed that enables efficient estimation of the BF vector at the transmitter with a minimum training duration of only one symbol. In contrast, conventional orthogonal training requires a minimum training duration equal to the number of receive antennas. A tight approximation to the capacity lower bound on the system is derived, which is used as a performance metric to optimize the parameters of the RCT. Next, assuming that CSI is available at the transmitter, a channel-dependent forward-link training signal is proposed and its power and duration are optimized with respect to an approximate capacity lower bound. Monte Carlo simulations illustrate the significant performance improvement offered by the proposed channel-dependent training schemes over the existing channel-agnostic orthogonal training schemes.
Actionable insights through association mining of exchange rates: A case study

Association mining is the methodology within data mining that researches associations among the elements of a given set, based on how they appear together in multiple subsets of that set. Extensive literature exists on the development of efficient algorithms for association mining computations, and the fundamental motivation for this literature is that association mining reveals actionable insights and enables better policies. This motivation is proven valid for domains such as retailing, healthcare and software engineering, where elements of the analyzed set are physical or virtual items that appear in transactions. However, the literature does not prove this motivation for databases where items are “derived items”, rather than actual items. This study investigates the association patterns in changes of exchange rates of US Dollar, Euro and Gold in the Turkish economy, by representing the percentage changes as “derived items” that appear in “derived market baskets”, the day on which the observations are made. The study is one of the few in literature that applies such a mapping and applies association mining in exchange rate analysis, and the first one that considers the Turkish case. Actionable insights, along with their policy implications, demonstrate the usability of the developed analysis approach.
Design and Evaluation of RFID Deployments in a Trauma Resuscitation Bay

We examined configuring a radio frequency identification (RFID) equipment for the best object use detection in a trauma bay. Unlike prior work on RFID, we 1) optimized the accuracy of object use detection rather than just object detection; and 2) quantitatively assessed antenna placement while addressing issues specific to tag placement likely to occur in a trauma bay. Our design started with an analysis of the environment requirements and constraints. We designed several antenna setups with different number of components (RFID tags or antennas) and their orientations. Setups were evaluated under scenarios simulating a dynamic medical setting. We used three metrics with increasing complexity and bias: read rate, received signal strength indication distribution distance, and target application performance. Our experiments showed that antennas above the regions with high object density are most suitable for detecting object use. We explored tagging strategies for challenging objects so that sufficient readout rates are obtained for computing evaluation metrics. Among the metrics, distribution distance was correlated with target application performance, and also less biased and simpler to calculate, which made it an excellent metric for context-aware applications. We present experimental results obtained in the real trauma bay to validate our findings.
Minimizing the Number of Tardy Jobs with Chance Constraints and Linearly Associated Stochastically Ordered Processing Times

We consider the single-machine sequencing model with stochastic processing times and the problem of minimizing the number of stochastically tardy jobs. In general, this problem is NP-hard. Recently, however, van den Akker and Hoogeveen found some special cases that could be solved in polynomial time. We generalize their findings by providing a polynomial solution for any stochastically ordered processing times. We then show that the algorithm applies as well to basic linearly associated processing times, thus allowing more realistic modeling of positive dependencies.
b-sheet Topology Prediction with High Precision and Recall for b and Mixed a / b Proteins

The prediction of the correct b-sheet topology for pure b and mixed a=b proteins is a critical intermediate step toward the three dimensional protein structure prediction. The predicted beta sheet topology provides distance constraints between sequentially separated residues, which reduces the three dimensional search space for a protein structure prediction algorithm. Here, we present a novel mixed integer linear optimization based framework for the prediction of b-sheet topology in b and mixed a=b proteins. The objective is to maximize the total strand-to-strand contact potential of the protein. A large number of physical constraints are applied to provide biologically meaningful topology results. The formulation permits the creation of a rank-ordered list of preferred b-sheet arrangements. Finally, the generated topologies are re-ranked using a fully atomistic approach involving torsion angle dynamics and clustering. For a large, non-redundant data set of 2102 b and mixed a=b proteins with at least 3 strands taken from the PDB, the proposed approach provides the top 5 solutions with average precision and recall greater than 78%. Consistent results are obtained in the b-sheet topology prediction for blind targets provided during the CASP8 and CASP9 experiments, as well as for actual and predicted secondary structures. The b-sheet topology prediction algorithm, BeST, is available to the scientific community at http:// selene.princeton. edu/BeST/. Citation: Subramani A, Floudas CA (2012) b-sheet Topology Prediction with High Precision and Recall for b and Mixed a/b Proteins. PLoS ONE 7(3): e32461. doi:10.1371/journal.pone. 0032461 Editor: Vladimir N. Uversky, University of South Florida College of Medicine, United States of America Received November 16, 2011; Accepted January 26, 2012; Published March 9, 2012 Copyright: 2012 Subramani and Floudas. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Funding: CAF gratefully acknowledges financial support from the National Science Foundation and National Institutes of Health (R01 GM52032; R24 GM069736). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Competing Interests: The authors have declared that no competing interests exist. * E-mail: floudas@titan.princeton. edu
Cofactor Independent Phosphoglycerate Mutase of Brugia malayi Induces a Mixed Th1/Th2 Type Immune Response and Inhibits Larval Development in the Host

Lymphatic filariasis is a major debilitating disease, endemic in 72 countries putting more than 1.39 billion people at risk and 120 million are already infected. Despite the significant progress in chemotherapeutic advancements, there is still need for other measures like development of an effective vaccine or discovery of novel drug targets. In this study, structural and immunological characterization of independent phosphoglycerate mutase of filarial parasite Brugia malayi was carried out. Protein was found to be expressed in all major parasite life stages and as an excretory secretory product of adult parasites. Bm-iPGM also reacted to all the categories of human bancroftian patient's sera including endemic normals. In vivo immunological behaviour of protein was determined in immunized BALB/c mice followed by prophylactic analysis in BALB/c mice and Mastomys coucha. Immunization with Bm-iPGM led to generation of a mixed Th1/Th2 type immune response offering 58.2% protection against larval challenge in BALB/c and 65–68% protection in M. coucha. In vitro studies confirmed participation of anti-Bm-iPGM antibodies in killing of B. malayi infective larvae and microfilariae through ADCC mechanism. The present findings reveal potential immunoprotective nature of Bm-iPGM advocating its worth as an antifilarial vaccine candidate.