Miracle-dz/UniFAR-FTUs huggingface dataset:
Based on Particle Swarm Optimization Algorithm of Cloud Computing Resource Scheduling in Mobile Internet

Mobile Internet due to the limitation of the mobile terminal power supply, transmission and calculation of the need to adopt energy saving strategy, also due to the terminal mobility, mobile Internet topology change. Therefore, mobile Internet cloud computing resources allocation need both energy efficiency and assure the time characteristics of mobile business; Aiming at this problem, this paper presents a maximum energy efficiency optimization, in the restrictive conditions at the same time, guarantee the minimum time delay the business. According to the characteristics of the optimization problems, both the distribution of the improved algorithm is proposed, the algorithm based on particle swarm optimization (pso) algorithm, build the search direction matrix of orientation, the simulation results show that the proposed allocation algorithm can effectively improve the efficiency of energy utilization, and ensure that the time delay of the business requirements.
Improving the Diagnostic Capabilities of a Performance Optimization Approach

Understanding the performance of a system is difficult because it is affected by every aspect of the design, code and execution environment. Performance maintenance tools can assist in getting a better understanding of the system by monitoring and analyzing performance data. In previous work, we have presented an approach which assists the performance expert in obtaining insight into and subsequently optimizing the performance of a deployed application. This approach is based on the classification results made by a single classifier. Following results from literature, we have extended this approach with the possibility of using a set (ensemble) of classifiers, in order to improve the classification results. While this ensemble is maintained with the goal of optimizing its accuracy, the completeness (or coverage) is neglected. In this paper, we present a method for improving both the coverage and accuracy of an ensemble. By doing so, we improve the diagnostic capabilities of our existing approach, i.e., the range of possible causes it is able to identify as the bottleneck of a performance issue. We present several metrics for measuring coverage and comparing two classifiers. We evaluate our approach on real performance data from a large industrial application. From our evaluation we get a strong indication that our approach is capable of improving the diagnostic capabilities of an ensemble, while maintaining at least the same degree of accuracy.
The effectiveness of intralesional injection of platelet‐rich plasma in accelerating the healing of chronic ulcers: an experimental and clinical study

The purpose of this prospective experimental and clinical study is to evaluate the effectiveness of the intralesional injection of platelet‐rich plasma (PRP), in the management of non‐healing chronic wounds. Skin defects were created in the ears of 20 white New Zealand rabbits. In the study group, autologous PRP was injected intralesionally. The control group was treated conservatively. Nineteen out of 20 cases of the study group healed within a mean time of 24·9 days. In the control group, seven defects healed within a mean period of 26·7 days, seven ulcers did not heal at day 28 and in six cases a full thickness ear defect was recorded. For a 3‐year period, 26 patients with chronic ulcers underwent surgical debridement and intralesional injection of PRP. A histological study was performed before and 7 days after PRP injection. Ten patients healed within a mean period of 7 weeks. In 16 cases, PRP prepared the wound bed for the final and simpler reconstructive procedure. Intralesional injection is a newly described method for application of PRP and represents an effective therapeutic option when dealing with non‐healing wounds.
Electron spin resonance of chlorophyll and the origin of signal I in photosynthesis.

A comparison has been made between Signal I, the photo-electron spin resonance signal associated with the primary light conversion act in photosynthesis, and free-radical signals generated in various chlorophyll species in vitro. The esr signals obtained from chlorophyll.monomer, (Chl.L)(+.), chlorophyll dimer, (Chl(2))(+.), and chlorophyll oligomer, (Chl(2))(n) (+.), are broader than Signal I, whereas the chlorophyll-water adduct, (Chl.H(2)O)(n) (+.), gives a signal very much narrower than Signal I. The unusually narrow signal from (Chl.H(2)O)(n) (+.) has been ascribed to spin migration, or to unpaired spin delocalization over a large number of chlorophyll molecules. The linewidth of Signal I can be accounted for by a similar delocalization process. A theoretical relationship between the esr linewidth and the number of chlorophyll molecules, N, over which an unpaired spin is delocalized, takes the form DeltaH(N) = 1/ radicalN.DeltaH(M), where DeltaH(M) is the linewidth of monomer (Chl.L)(+.). This relationship for N = 2 accounts well for the linewidths of Signal I in green algae, blue-green algae, and photosynthetic bacteria in both the (1)H- and (2)H-forms. The linewidth of Signal I (as well as the optical properties of reaction-center chlorophyll) are consistent with unpaired spin delocalization over an entity containing two chlorophyll molecules, (Chl.H(2)O.Chl)(+.).
Functional analysis of LDLR promoter and 5′ UTR mutations in subjects with clinical diagnosis of familial hypercholesterolemia

Familial hypercholesterolemia (FH) is a dominant disorder due to mutations in the LDLR gene. Several mutations in the LDLR promoter are associated with FH. Screening of 3,705 Spanish FH patients identified 10 variants in the promoter and 5′ UTR. Here, we analyse the functionality of six newly identified LDLR variants. Mutations located in the LDLR promoter regulatory elements R2 and R3 (c.−155_‐150delACCCCinsTTCTGCAAACTCCTCCC, c.−136C>G, c.−140C>G, and c.−140C>T) resulted in 6 to 15% residual activity in reporter expression experiments and changes in nuclear protein binding affinity compared to wild type. No reduction was observed when cells were transfected with c. −208T, c. −88A, and c. −36G mutant fragments. Our results indicate that mutations localized in R2 and R3 are associated with hypercholesterolemia, whereas mutations outside the LDLR response elements are not a cause of FH. This data emphasizes the importance of functional analysis of variants in the LDLR promoter to determine their association with the FH phenotype.Hum Mutat 32:1–5, 2011. © 2011 Wiley‐Liss, Inc.
Maintenance of Social Anxiety in Stuttering: A Cognitive-Behavioral Model.

Purpose Stuttering is a speech disorder frequently accompanied by anxiety in social-evaluative situations. A growing body of research has confirmed a significant rate of social anxiety disorder among adults who stutter. Social anxiety disorder is a chronic and disabling anxiety disorder associated with substantial life impairment. Several influential models have described cognitive-behavioral factors that contribute to the maintenance of social anxiety in nonstuttering populations. The purpose of the present article is to apply these leading models to the experience of social anxiety for people who stutter. Method Components from existing models were applied to stuttering in order to determine cognitive-behavioral processes that occur before, during, and after social-evaluative situations, which may increase the likelihood of stuttering-related social fears persisting. Results Maintenance of social anxiety in stuttering may be influenced by a host of interrelated factors, including fear of negative evaluation, negative social-evaluative cognitions, attentional biases, self-focused attention, safety behaviors, and anticipatory and postevent processing. Conclusion Given the chronic nature of social anxiety disorder, identifying factors that contribute to the persistence of stuttering-related social fears has the potential to inform clinical practice and the development of psychological treatment programs to address the speech and psychological needs of people who stutter with social anxiety.
Antineutrophil cytoplasmic antibodies induce human monocytes to produce oxygen radicals in vitro.

OBJECTIVE Antineutrophil cytoplasmic antibodies (ANCA) are believed to play a pathogenetic role in necrotizing small-vessel vasculitis. While the involvement of neutrophils in this disease has been extensively studied in vitro, we undertook to analyze thoroughly the contribution of monocytes to tissue destruction in systemic vasculitis. METHODS Monocytes obtained from normal human individuals were stimulated by ANCA isolated from patients with active vasculitis. The formation of oxygen radicals was measured by a fluorometric assay using 2',7'-dichlorofluorescin diacetate. RESULTS ANCA induced monocytes to produce oxygen radicals, resulting in a mean 43% increase (range 21-84%) in oxygen radical formation compared with normal IgG. The formation of reactive oxygen species was time and concentration dependent and was also induced by ANCA F(ab')2 fragments. Normal nonspecific IgG or their corresponding F(ab')2 fragments induced no release or very little release of oxygen radicals. Preincubation of monocytes with the Fcy receptor type II-blocking monoclonal antibody IV.3 before addition of ANCA greatly reduced formation of oxygen radicals. Using ligand affinity chromatography with proteinase 3 (PR3) and myeloperoxidase (MPO), ANCA were further purified by depletion of patient IgG. The stimulation of monocytes with these pure PR3- and MPO-ANCA confirmed that cellular activation was specifically induced by ANCA. CONCLUSION These results show that ANCA induce the formation of reactive oxygen species in human monocytes. These findings support the notion that ANCA specifically activate monocytes by several mechanisms to participate in the inflammatory process of ANCA-associated vasculitis.
The monetary and banking development of Singapore and Malaysia

The first edition of the book was published in 1974, and received a book award for best non-fiction in English presented by the National Book Development Council of Singapore in 1976, while the Second Edition published in 1986, saw much more econometric-statistical analysis. This Third Edition highlights the role of banking and finance in the economic development of Singapore and Malaysia; recent developments in Singapore and Malaysia are analysed; and special topics are presented in Epilogues 1 and 2.
Synthesis of positive controls for the global CLF stabilization of systems

In this paper, we propose an explicit formula for bounded continuous feedback laws taking values in the interval U ≔ [r<sup>−</sup>, r<sup>+</sup>] that renders an affine system globally asymptotically stable. The case of bounded positive feedback controls (r<sup>−</sup> = 0) is also included. Additionally, the problem of designing a marginally robust control function is addressed.
Multi-Channel Recordings from Peripheral Nerves : 3 . Evaluation of Selectivity using Electrical Stimulation of Individual Digits

3. Evaluation of Selectivity using Electrical Stimulation of Individual Digits. K.D. Strange (a), P.R. Christensen (b), Y. Chen (a), K. Yoshida (c), and J.A. Hoffer (a,b) a. School of Kinesiology, Simon Fraser University, Burnaby, BC, V5A 1S6, Canada b. School of Engineering Science, Simon Fraser University, Burnaby, BC, V5A 1S6, Canada c. Division of Neuroscience, University of Alberta, Edmonton, AB, T6G 1K7, Canada.
Large-scale Subspace Clustering by Fast Regression Coding

Large-Scale Subspace Clustering (LSSC) is an interesting and important problem in big data era. However, most existing methods (i.e., sparse or low-rank subspace clustering) cannot be directly used for solving LSSC because they suffer from the high time complexity-quadratic or cubic in n (the number of data points). To overcome this limitation, we propose a Fast Regression Coding (FRC) to optimize regression codes, and simultaneously train a nonlinear function to approximate the codes. By using FRC, we develop an efficient Regression Coding Clustering (RCC) framework to solve the LSSC problem. It consists of sampling, FRC and clustering. RCC randomly samples a small number of data points, quickly calculates the codes of all data points by using the non-linear function learned from FRC, and employs a large-scale spectral clustering method to cluster the codes. Besides, we provide a theorem guarantee that the non-linear function has a first-order approximation ability and a group effect. The theorem manifests that the codes are easily used to construct a dividable similarity graph. Compared with the state-of-the-art LSSC methods, our model achieves better clustering results in large-scale datasets.
Tetraaquabis[(1-carboxylatomethyl-1,3-benzimidazol-3-ium-3-yl)acetato-κO]palladium(II) dihydrate

In the title compound, [Pd(C11H9N2O4)2(H2O)4]·2H2O, the palladium(II) cation lies on an inversion centre and is hexacoordinated by two carboxylate O atoms from two (1-carboxylatomethyl-1,3-benzimidazol-3-ium-3-yl)acetate ligands and four water molecules, with a slightly distorted octahedral geometry. O—H⋯O hydrogen bonds link the molecules together.
Extensión de juegos definidos en Sistemas de Conjuntos.

Este trabajo de investigacion, fundamentalmente, propone un nuevo modelo para la generalizacion del iniciado por Myerson (1977), Con este objetivo se analizan estructuras estables para la union de coaliciones con interseccion no vacia, que tienen como caso particular a las situaciones de comunicacion. Por otro lado, se establece una estrecha relacion entre las estructuras de cooperacion u-estables y las situaciones de comunicacion en hipergrafos debidas a Myerson (1980) y estudiadas por van den nouweland, Boom y Tijs (1992). Las herramientas basicas que han permitido esta generalizacion, asi como el analisis y caracterizacion del valor de Myerson de posicion en este contexto han sido la introduccion del concepto de base y de un procedimiento recursivo que genera las coaliciones factibles. Asimismo, se plantean metodos para un computo mas eficaz del valor de Myerson y de posicion respectivamente y se estudian bajo que condiciones estos valores son elementos del core del juego restringido (lo cual ha obligado a investigar la transmision de la convexidad del juego original a los juegos introducidos).
Near-optimal selection of parallel inputs in Bayesian experimental design for systems biology

This study concerns the efficient design of experiments in the context Bayesian model selection, and is primarily motivated by applications to systems biology. We introduce a design method to select an informative subset of inputs, each with unit cost, under a given budget constraint. The inputs are applied as interventions to the biological system, either in parallel or in sequence, each time starting from the same initial conditions. The method aims at maximizing a Bayesian information-theoretic objective: the mutual information between models and data. By taking advantage of submodularity, we prove by reduction that our design method is computationally efficient and near-optimal, as it requires only a polynomial number of evaluations of the objective to yield near-optimal value. It follows from the reduction that the constant factor of the introduced approximation dominates all efficient design techniques, unless P=NP. We discuss the main theoretical properties of the method, as well as practical design choices and current limitations of the approach.
A human-inspired controller for fluid human-robot handovers

Handovers are seamless events that occur frequently and naturally between people. Although previous works have focused on the design of robot handover controllers synthesizing one of the phases of a handover (approaching, passing, or retracting) in an isolated manner, we take a different approach and treat the handover as a single continuous entity. In this paper we present a novel bi-directional and human-inspired handover controller using insights we learned from human-human experiments. We model the dynamics of the handover in a continuous and time-independent way yielding robust and fluid behavior. We implemented our approach on a robot platform consisting of a 7-DoF robotic arm with a 16-DoF humanoid hand. Our results show that resulting humanrobot handovers are smooth and reduce internal forces with the human compared to traditional switching approaches.
Value co-creation by customer-to-customer communication: social media and face-to-face for case of airline service selection.

One of the foundational of service science and of study of value-creation in service systems is service-dominant logic (S-D logic). S-D logic especially emphasizes the role of customers; that is, each customer is recognized as an active co-creator of knowledge and service value. Most studies on the value co-creation process have concentrated on the in- teraction between customers and providers. In contrast, this research is investigating co-creation of value and the notion of “value in use” that is central to the service-dominant logic by focusing on value co-creation from the customer per- spective, especially in terms of how customers are engaging in experiences by clarifying what different influences are produced by their exchange of information about the providers. The basic framework of the present research is a proc- ess model of value co-creation of service system, i.e., co-experience and co-definition. The main purpose is to investi- gate how new value is co-created by mutual interaction among customers by using Airline service selection as a typical case to clarify influences on the value co-creation process produced by different ways of customer-to-customer com- munication: social media and face-to-face communication. By agent-based simulation we compare learning efficiency and learning performance of the two communication styles of the customers. Learning efficiency is measured by the distance between the average payoff of the customers and that of the provider, while learning performance is measured by the average payoff obtained from Nash Equilibrium by the game played with the provider. The simulation results found that communication style influences the learning efficiency by customers as well as the learning performance. Social media is a good way when few customers know the provider correctly or have limited knowledge of the commu- nity, while face-to-face is a good way when quite a many customers know the provider correctly or trust on reputation of the provider in the community. The research results indicate that it is crucial for the provider, to establish trust with the customers.
Interference mitigaion between femtocell and macrocell

Femtocell is no longer a new concept to the public in the 21st century, which witnesses the tremendous advancement of high-tech. In terms of interference mitigation between networks, particularly, there are already a large amount of available measures, such as hybrid spectrum usage and self-optimizing that make great contribution to network optimization. This paper illustrates three types of interference in the cooperation of macro-femto cells from the aspect of the efficient spectrum utilization. Meanwhile, we also introduce an advanced version of Femtocell called Attocell, which shows the advantages of next generation Femto-communication by comparison.
Reconstructing gene regulatory network based on candidate auto selection method

The reconstruction of gene regulatory network (GRN) is a great challenge in systems biology and bioinformatics, and methods based on Bayesian network (BN) draw most of attention because of its inherent probability characteristics. As NP-hard problems, most of the BN methods often adopt the heuristic search, but they are time-consuming for biological networks with a large number of nodes. To solve this problem, this paper presents a Candidate Auto Selection algorithm (CAS) based on mutual information and breakpoint detection to limit the search space in order to accelerate the learning process. The proposed algorithm automatically restricts the neighbors of each node to a small set of candidates before structure learning. Then based on CAS algorithm, we propose a globally optimal greedy search method (CAS+G), which focuses on finding the high-scoring network structure, and a local learning method (CAS+L), which focuses on faster learning the structure with small loss of quality. Results show that the proposed CAS algorithm can effectively identify the neighbor nodes of each node. In the experiments, the CAS+G method outperforms the state-of-the-art method on simulation data for inferring GRNs, and the CAS+L method is significantly faster than the state-of-the-art method with little loss of accuracy. Hence, the CAS based algorithms are more suitable for GRN inference.
Characteristics of natural mentoring relationships from the perspectives of homeless youth.

PROBLEM Homeless youth experience high risks for poor mental health outcomes. The purpose of this qualitative study was to explore the characteristics of natural mentoring relationships among homeless youth and to identify possible mechanisms that can enhance social support for this population. METHODS Semi-structured interviews were conducted with 23 homeless youth aged 14-21 who had natural mentors. The interviews focused on how youth met their natural mentors, the function of these relationships, and how natural mentoring relationships differed from other relationships in the youth's social networks. FINDINGS Main themes that emerged from the interviews included parental absence, natural mentors as surrogate parents, and social support from mentors. CONCLUSIONS Findings suggest that social supports provided by mentors enhance youth's adaptive functioning and may promote resilience, thus the use of natural mentors may be an important untapped asset in designing interventions to improve outcomes for homeless youth.
Registration-based interpolation real-time volume visualization

Rendering tomographic data sets is a computationally expensive task, and often accomplished using hardware acceleration. The data sets are usually anisotropic as a result of the process used to acquire them. A vital part of rendering them is the conversion of the discrete signal back into a continuous one, via interpolation. On graphics hardware, this is often achieved via simple linear interpolation. We present a novel approach for real-time anisotropic volume data interpolation on a graphics processing unit and draw comparisons to standardized interpolation alternatives. Our approach uses a pre-computed set of cross-slice correspondences to compensate for missing data. We perform a qualitative analysis using sparse data sets, investigating both visual quality, as well divergence from the ground truth, testing the limits of the interpolation method. Our method produces high quality interpolation with a moderate performance impact compared to alternatives. It is ideal for reconstructing sparse data sets, as well as minimizing quality loss while scaling large amounts of data to fit on most mobile graphics cards.
9-Vinylanthracene Based Fluorogens: Synthesis, Structure-Property Relationships and Applications

Fluorescent dyes with aggregation-induced emission (AIE) properties exhibit intensified emission upon aggregation. They are promising candidates to study biomolecules and cellular changes in aqueous environments when aggregation formation occurs. Here, we report a group of 9-position functionalized anthracene derivatives that were conveniently synthesized by the palladium-catalyzed Heck reaction. Using fluorometric analyses, these dyes were confirmed to show AIE behavior upon forming aggregates at high concentrations, in viscous solvents, and when poorly solubilized. Their photophysical properties were then further correlated with their structural features, using density functional theory (DFT) calculation. Finally, we demonstrated their potential applications in monitoring pH changes, quantifying globular proteins, as well as cell imaging with confocal microscopy.