Miracle-dz/UniFAR-FTUs huggingface dataset:
An incentive-based supplier selection mechanism to support green supply chains

Supplier selection is an important decision for an enterprise to realize a sustainable production. However, almost all works, which concerned the environmental issues, focused on the supplier selection or evaluation methods, rather than the incentive mechanism urging the participants to improve their decisions (reduce the harm to the environment). In this paper, not only are the commercial factors (price, quantity, and lead time), but also the environment factors (green factors and carbon dioxide emissions) of the suppliers are considered during the selection. The determinations of the green factors and the total carbon dioxide emissions depend on the analysis of the history trade data. An incentive supplier selection mechanism, which urges the agents to improve their decisions to reduce the harm to the environment, is proposed. Numerical calculations are provided to verify the feasibility and the superiority of the proposed model.
THE NASA-UC ETA-EARTH PROGRAM. II. A PLANET ORBITING HD 156668 WITH A MINIMUM MASS OF FOUR EARTH MASSES

We report the discovery of HD 156668 b, an extrasolar planet with a minimum mass of MPsin i = 4.15 M⊕. This planet was discovered through Keplerian modeling of precise radial velocities from Keck-HIRES and is the second super-Earth to emerge from the NASA-UC Eta-Earth Survey. The best-fit orbit is consistent with circular and has a period of P = 4.6455 days. The Doppler semi-amplitude of this planet, K = 1.89 m s−1, is among the lowest ever detected, on par with the detection of GJ 581 e using HARPS. A longer period (P ≈ 2.3 years), low-amplitude signal of unknown origin was also detected in the radial velocities and was filtered out of the data while fitting the short-period planet. Additional data are required to determine if the long-period signal is due to a second planet, stellar activity, or another source. Photometric observations using the Automated Photometric Telescopes at Fairborn Observatory show that HD 156668 (an old, quiet K3 dwarf) is photometrically constant over the radial velocity period to 0.1 mmag, supporting the existence of the planet. No transits were detected down to a photometric limit of ∼3 mmag, ruling out transiting planets dominated by extremely bloated atmospheres, but not precluding a transiting solid/liquid planet with a modest atmosphere.
Engaging race and racism for socially just intergroup relations: The impact of intergroup dialogue on college campuses in the United States

ABSTRACT This study examines the impact of interracial/interethnic dialogue, a model of intergroup contact that highlights the salience of racial and ethnic group membership, to improve intergroup relations on college campuses. A field experiment involving 737 participants demonstrated that participants randomized to enrol in an intergroup dialogue course increased thinking about and understanding of race and racial/ethnic group membership more than the randomized control group participants who were wait-listed for the course. This effect of intergroup dialogue was found both at the end of course and a year later. Furthermore, such racial engagement was associated with greater (a) motivation to bridge intergroup differences, (b) structural understanding of racial and ethnic inequality, and (c) behavioural commitment to redress inequality 1 year later. The study highlights a colour-conscious, as opposed to colourblind, model for multicultural and social justice education and provides causal evidence for its effects.
Measuring and Analysis of Urban Competitiveness of Chinese Provincial Capitals in 2010 under the Constraints of Major Function-Oriented Zoning Utilizing Spatial Analysis

Urban competitiveness aids local development by encouraging the exploitation of opportunities for economic development and by enhancing overall performance. Previous studies have evaluated urban competitiveness primarily from an economic perspective and few studies have considered locational conditions as factors that might influence local industrialization and urbanization. In response to the publishing of a national plan for the development of major function-oriented zones (MFOZs) in 2010, the present essay employs MFOZs as constraints to enable a balanced and comprehensive study of urban competitiveness that includes four dimensions of competitiveness: Economic, social-cultural, environmental, and locational (accessibility and hypsography). A four-level hierarchical indicator system and an entropy weighting method were used to assess the urban competitiveness of 31 Chinese provincial capitals based on a spatial analysis of data acquired in 2010 using Geographic Information System technology. The results reveal the overall ranking of provincial capitals in terms of urban competitiveness and their performances with respect to the four dimensions of competitiveness. Unlike previous studies, this analysis was performed by overlaying the strategy of the national MFOZ with the urban competitiveness rankings. The development orientation of each provincial city is discussed according to its characteristics of urban competitiveness under the conditions of a MFOZ.
Principles for the design of performance-oriented interaction techniques

Applications of virtual environments (VEs) are becoming increasingly interactive, allowing the user to not only look around a three-dimensional world, but also to navigate the space, manipulate virtual objects, and give commands to the system. Thus, it is crucial that researchers and developers understand the issues related to 3D interfaces and interaction techniques. In this chapter, we explore the space of possible interaction techniques for several common tasks, and offer guidelines for their use in VE applications. These guidelines are drawn largely from empirical research results.
A Symmetric Approach Elucidates Multisensory Information Integration

Recent advances in neuronal multisensory integration suggest that the five senses do not exist in isolation of each other. Perception, cognition and action are integrated at very early levels of central processing, in a densely-coupled system equipped with multisensory interactions occurring at all temporal and spatial stages. In such a novel framework, a concept from the far-flung branch of topology, namely the Borsuk-Ulam theorem, comes into play. The theorem states that when two opposite points on a sphere are projected onto a circumference, they give rise to a single point containing their matching description. Here we show that the theorem applies also to multisensory integration: two environmental stimuli from different sensory modalities display similar features when mapped into cortical neurons. Topological tools not only shed new light on questions concerning the functional architecture of mind and the nature of mental states, but also provide an empirically assessable methodology. We argue that the Borsuk-Ulam theorem is a general principle underlying nervous multisensory integration, resulting in a framework that has the potential to be operationalized.
Dependency Tree-Based Anaphoricity Determination for Coreference Resolution

This paper proposes a new scheme to determine the tree span structure for tree kernel-based anaphoricity determination in coreference resolution. Given a sentence and current mention, it gets all the dependencies, encodes the order of all the words, constructs the corresponding dependency tree and keeps the nodes and the paths related with current mention based on constituent dependencies, while removing the noisy information, eventually leading to a dynamical dependency tree (DDT). Evaluation on the ACE 2003 corpus shows that the DDT is effective for anaphoricity determination, and that applying our anaphoricity determination module in coreference resolution achieves the improvement of performance.
A New Approach for Enhancing Image Retrieval using Neutrosophic Sets

paper adopts a novel model for Content-Based Image Retrieval (CBIR) system depending on an excellent segmentation strategy and combination of Visual Descriptors (VDs). The presented model is divided into four main phases: image segmentation, visual descriptors, Dimensionality Reduction (DR) and similarity matching. An improved segmentation technique based on Neutrosophic Sets (NSs) is proposed and applied to see their ability and accuracy to segment images. In relative to the VDs, the geometrical moments are used to extract the shape of an object, the modified Stricker method to the color extraction is proposed and the MPEG-7 edge histogram descriptor is presented for each of them. Experimental results presented show that the proposed model provides precise image retrieval in a short time. KeywordsGMs, EHD, Evaluation function, ANMRR
Advancing the Boundaries of High-Connectivity Network Simulation with Distributed Computing

The availability of efficient and reliable simulation tools is one of the mission-critical technologies in the fast-moving field of computational neuroscience. Research indicates that higher brain functions emerge from large and complex cortical networks and their interactions. The large number of elements (neurons) combined with the high connectivity (synapses) of the biological network and the specific type of interactions impose severe constraints on the explorable system size that previously have been hard to overcome. Here we present a collection of new techniques combined to a coherent simulation tool removing the fundamental obstacle in the computational study of biological neural networks: the enormous number of synaptic contacts per neuron. Distributing an individual simulation over multiple computers enables the investigation of networks orders of magnitude larger than previously possible. The software scales excellently on a wide range of tested hardware, so it can be used in an interactive and iterative fashion for the development of ideas, and results can be produced quickly even for very large networks. In con-trast to earlier approaches, a wide class of neuron models and synaptic dynamics can be represented.
The Role of Sirt1 in Bile Acid Regulation during Calorie Restriction in Mice

Sirtuin 1 (Sirt1) is an NAD+-dependent protein deacetylase that is proposed to mediate many health-promoting effects of calorie restriction (CR). We recently reported that short-term CR increased the bile acid (BA) pool size in mice, likely due to increased BA synthesis in liver. Given the important role of Sirt1 in the regulation of glucose, lipid, as well as BA metabolism, we hypothesized that the CR-induced increase in BAs is Sirt1-dependent. To address this, the present study utilized genetically-modified mice that were Sirt1 loss of function (liver knockout, LKO) or Sirt1 gain of function (whole body-transgenic, TG). Three genotypes of mice (Sirt1-LKO, wild-type, and Sirt1-TG) were each randomly divided into ad libitum or 40% CR feeding for one month. BAs were extracted from various compartments of the enterohepatic circulation, followed by BA profiling by UPLC-MS/MS. CR increased the BA pool size and total BAs in serum, gallbladder, and small intestine. The CR-induced increase in BA pool size correlated with the tendency of increase in the expression of the rate-limiting BA-synthetic enzyme Cyp7a1. However, in contrast to the hypothesis, the CR-induced increase in BA pool size and Cyp7a1 expression was still observed with ablated expression of Sirt1 in liver, and completely suppressed with whole-body overexpression of Sirt1. Furthermore, in terms of BA composition, CR increased the ratio of 12α-hydroxylated BAs regardless of Sirt1 genotypes. In conclusion, the CR-induced alterations in BA pool size, BA profiles, and expression of BA-related genes do not appear to be dependent on Sirt1.
The Local Boundary Detection Model (LBDM) and its Application in the Study of Expressive Timing

In this paper two main topics are addressed. Firstly, the Local Boundary Detection Model (LBDM) is described; this computational model enables the detection of local boundaries in a melodic surface and can be used for musical segmentation. The proposed model is tested against the punctuation rule system developed by Friberg et al. (1998) at KTH, Stockholm. Secondly, the expressive timing deviations found in a number of expert piano performances are examineded in relation to the local boundaries discovered by LBDM. As a result of a set of preliminary experiments, it is suggested that the assumption of final-note lengthening of a melodic gesture is not always valid and that, in some cases, the end of a melodic group is marked by lengthening the second-to-last note (or, seeing it from a different viewpoint, by delaying the last note).
Novel Multiple Impression based Multimodal Fingerprint Recognition System

As population grow, the task of fingerprint verification system becomes increasingly more difficult. However performance improvement of biometric based verification system is an interesting and emerging area. In fingerprint verification systems, there are usually multiple enrolled impressions for a same finger. The performance of the systems can be improved by combining these impressions at enrollment level as well as testing level. In this research paper we use a method of score level fusion using multiple enrollment and multiple testing impressions to achieve higher accuracy. Experimental results show that a larger improvement can be obtained by using fusion of multiple enrollments and one testing impression scheme than other one to one matching. Experiment conducted with FVC2000, FVC 2002 and our own (BAMU) database. For the evaluation performance measures (FAR), (FRR), Recognition rate (RR) Equal Error Rate (EER) and Receiver Operating Characteristics curve (ROC) has been used.
Multilinear pose and body shape estimation of dressed subjects from image sets

In this paper we propose a multilinear model of human pose and body shape which is estimated from a database of registered 3D body scans in different poses. The model is generated by factorizing the measurements into pose and shape dependent components. By combining it with an ICP based registration method, we are able to estimate pose and body shape of dressed subjects from single images. If several images of the subject are available, shape and poses can be optimized simultaneously for all input images. Additionally, while estimating pose and shape, we use the model as a virtual calibration pattern and also recover the parameters of the perspective camera model the images were created with.
Evaluating the Effects of Land Use Planning for Non-Point Source Pollution Based on a System Dynamics Approach in China

Urbanization is proceeding rapidly in several developing countries such as China. This accelerating urbanization alters the existing land use types in a way that results in more Non-Point Source (NPS) pollution to local surface waters. Reasonable land use planning is necessary. This paper compares seven planning scenarios of a case study area, namely Wulijie, China, from the perspective of NPS pollution. A System Dynamics (SD) model was built for the comparison to adequately capture the planning complexity. These planning scenarios, which were developed by combining different land use intensities (LUIs) and construction speeds (CSs), were then simulated. The results show that compared to scenario S1 (business as usual) all other scenarios will introduce more NPS pollution (with an incremental rate of 22%-70%) to Wulijie. Scenario S6 was selected as the best because it induced relatively less NPS pollution while simultaneously maintaining a considerable development rate. Although LUIs represent a more critical factor compared to CSs, we conclude that both LUIs and CSs need to be taken into account to make the planning more environmentally friendly. Considering the power of SD in decision support, it is recommended that land use planning should take into consideration findings acquired from SD simulations.
Dancing with the pacifiers: infant's perizhivanya in a Brazilian early childhood education centre

ABSTRACT This study captures the possibilities of infants’ interactions in a Brazilian Early Childhood Education Centre. It contributes to an increasing number of educational research that is capturing the specificities of how young children use their understandings of context through gestures and verbal forms of language to create meanings as they develop social relationships with their peers and adults. The meanings of these interactions are explored based on the Vygotskyan notion of perezhivanie. The research design was guided by ethnography in education principles. Participant researchers used fieldnotes and video recording to capture infants’ interactions at the centre. For the purposes of this study, events were selected that related to the use of the cultural artefact pacifier. While teachers and families regarded the pacifier as an artefact that calms infants, helping them settle into a new environment, this study expands infants use of pacifiers as they also became artefacts to be explored and part of infants’ social relations with each other. The events analysed highlight the biology/culture and emotion/cognition unities in infants’ processes of development. This study argues for expanding teachers’ practices in a process of appreciating what infants’ intentions are and what they are communicating.
Spillovers in Space: Does Geography Matter?

We simultaneously assess the contributions to productivity of three sources of research and development spillovers: geographic, technology and product-market proximity. To do this, we construct a new measure of geographic proximity that is based on the distribution of a firm's inventor locations rather than its headquarters, and we report both parametric and semiparametric estimates of our geographic- distance functions. We find that: i) Geographic space matters even after conditioning on horizontal and technological spillovers; ii) Technological proximity matters; iii) Product-market proximity is less important; iv) Locations of researchers are more important than headquarters but both have explanatory power; and v) Geographic markets are very local.
Roles and Trust in Interorganizational Systems

While trust is widely acknowledged as to be important for the efficient operation of interorganizational business arrangements, the formation of trust remains challenging. In this paper we discuss the trust building potential of inter-firm coordination roles as organizational means in virtual organizations. Thus, we introduce the coordination role concept and proceed by defining three different dimensions of trust in dynamic business networks to explain the role’s effects: (1) network trust, (2) trust in coordination roles, and (3) the specific interorganizational trust. The work of two sociologists - Coleman and Giddens – serve as a basis for our assumption that coordination roles positively influence overall trust in virtual organizations. We conclude with a discussion of factors contributing to the perceived trustworthiness of roles and their occupants, which is necessary for the functioning of the concept.
A Feedback based method for License plate image binarization

License plate image binarization is a critical step in Automatic Number Plate Recognition(ANPR) systems and is essential for character segmentation. Generally Otsu(global) or adaptive(local) thresholding methods are commonly used, but each of them may have a shortcoming in terms of segmenting all the characters accurately or Optical Character Recognition(OCR) reading when the plate is not cropped exactly. In this paper we propose a feedback based approach which fuses global and local thresholding methods. Local thresholding method is applied first to extract the character candidates and plate is cropped exactly using the spatial information of the extracted characters. Global thresholding method is applied over the re-cropped plate. Experimental results show the recovery of the number plate reading using the proposed method which are missed or inaccurately read when the global or local thresholding methods are used individually.
Image-based Subspace Analysis for Face Recognition

In classical statistical pattern recognition tasks, we usually represent data samples with ndimensional vectors, i.e. data is vectorized to form data vectors before applying any technique. However in many real applications, the dimension of those 1D data vectors is very high, leading to the “curse of dimensionality“. The curse of dimensionality is a significant obstacle in pattern recognition and machine learning problems that involve learning from few data samples in a high-dimensional feature space. In face recognition, Principal component analysis (PCA) and Linear discriminant analysis (LDA) are the most popular subspace analysis approaches to learn the low-dimensional structure of high dimensional data. But PCA and LDA are based on 1D vectors transformed from image matrices, leading to lose structure information and make the evaluation of the covariance matrices high cost. In this chapter, straightforward image projection techniques are introduced for image feature extraction. As opposed to conventional PCA and LDA, the matrix-based subspace analysis is based on 2D matrices rather than 1D vectors. That is, the image matrix does not need to be previously transformed into a vector. Instead, an image covariance matrix can be constructed directly using the original image matrices. We use the terms “matrix-based“ and “image-based“ subspace analysis interchangeably in this chapter. In contrast to the covariance matrix of PCA and LDA, the size of the image covariance matrix using image-based approaches is much smaller. As a result, it has two important advantages over traditional PCA and LDA. First, it is easier to evaluate the covariance matrix accurately. Second, less time is required to determine the corresponding eigenvectors (Jian Yang et al., 2004). A brief of history of image-based subspace analysis can be summarized as follow. Based on PCA, some image-based subspace analysis approaches have been developed such as 2DPCA (Jian Yang et al., 2004), GLRAM (Jieping Ye, 2004), Non-iterative GLRAM (Jun Liu & Songcan Chen 2006; Zhizheng Liang et al., 2007), MatPCA (Songcan Chen, et al. 2005), 2DSVD (Chris Ding & Jieping Ye 2005), Concurrent subspace analysis (D.Xu, et al. 2005) and so on. Based on LDA, 2DLDA (Ming Li & Baozong Yuan 2004), MatFLDA (Songcan Chen, et al. 2005), Iterative 2DLDA (Jieping Ye, et al. 2004), Noniterative 2DLDA (Inoue, K. & Urahama, K. 2006) have been developed until date. The main purpose of this chapter is to give you a generalized overview of those matrix-based approaches with detailed mathematical theory behind that. All algorithms presented here are up-to-date till Jan. 2007.