Miracle-dz/UniFAR-FTUs huggingface dataset:
Anatomical mirroring: real-time user-specific anatomy in motion using a commodity depth camera

This paper presents a mirror-like augmented reality (AR) system to display the internal anatomy of a user. Using a single Microsoft V2.0 Kinect, we animate in real-time a user-specific internal anatomy according to the user's motion and we superimpose it onto the user's color map, as shown in Fig.1. e. The user can visualize his anatomy moving as if he was able to look inside his own body in real-time. A new calibration procedure to set up and attach a user-specific anatomy to the Kinect body tracking skeleton is introduced. At calibration time, the bone lengths are estimated using a set of poses. By using Kinect data as input, the practical limitation of skin correspondance in prior work is overcome. The generic 3D anatomical model is attached to the internal anatomy registration skeleton, and warped on the depth image using a novel elastic deformer, subject to a closest-point registration force and anatomical constraints. The noise in Kinect outputs precludes any realistic human display. Therefore, a novel filter to reconstruct plausible motions based on fixed length bones as well as realistic angular degrees of freedom (DOFs) and limits is introduced to enforce anatomical plausibility. Anatomical constraints applied to the Kinect body tracking skeleton joints are used to maximize the physical plausibility of the anatomy motion, while minimizing the distance to the raw data. At run-time, a simulation loop is used to attract the bones towards the raw data, and skinning shaders efficiently drag the resulting anatomy to the user's tracked motion. Our user-specific internal anatomy model is validated by comparing the skeleton with segmented MRI images. A user study is established to evaluate the believability of the animated anatomy.
A Method for Mode Selection in a dynamic network for Device-to-Device Communication for 5G

In 5G network, two types of mode are possible: cellular mode (CU) and device-to-device (D2D) mode. The communicating devices are in their proximity area they communicate in D2D mode otherwise, communicated in CU mode by the help of base station (BS). In the dynamic network, the communicating devices are free to move in any direction even though in communication; therefore, the communicating devices may change their mode. In conventional method, the communicating devices do not change their mode in communication. In this paper, we propose a mode selection method for the dynamic network. In this method, the communicating devices can change their mode (from CU to D2D) in communication. The communicating devices check their mode a regular interval by broadcasting packet in network. The mode selection is depends on signal-to-interference-plus-noise ratio (SINR), proximity distance, and battery consumption. The simulation has been done in OMNET++. A comparison with the conventional method shows that our method increases throughput, reduce the delay and power depilation up to 30%.
Perceived Social Support, Social Interest, and Mental Health: Testing a Mediator Model

Abstract:The positive relationship between social support and mental health is well documented. Tang, Pu, and Yao (2009) suggested that the relationship might be mediated by a third variable, which provides the basis for the current study. We examined the mediating effects of social interest on perceived social support and mental health. Participants were 102 university students who completed measures of social interest, mental health, social desirability, and perceived social support. Using Baron and Kenny’s (1986) causal steps approach, a hierarchical linear regression was conducted to assess the mediating effects of social interest. The results indicate a full mediation effect of social interest on the relationship between perceived social support and mental health. We found that the relationship between perceived social support and mental health became nonsignificant because of the mediating effects of social interest.
The role of leisure in meaning-making and engagement with life

Abstract The purpose of this conceptual paper is to identify and describe the role of leisure in meaningful engagement with life, informed by leisure and positive psychology literature on these topics. Specifically, the paper identifies the key elements or factors of leisure-induced meaningful engagement with life. In particular, the paper emphasizes the contributions of leisure pursuits to maintaining: (a) a joyful life, (b) a connected life, (c) a discovered life, (d) a composed life, and (e) an empowered life. Not only do these elements seem to represent distinct factors of meaningful engagement with life through leisure, but multiple meanings can be also gained from a single leisure-engagement experience, and these meaning themes can be interconnected. The role of leisure in meaning-making and engagement is important, considering unique distinct characteristics of leisure as freely chosen, self-determined/autonomous, and intrinsically motivated engagement.
A closed-form estimator for the multivariate GARCH ( 1 , 1 ) model

We provide a closed-form estimator based on the VARMA representation for the unrestricted multivariate GARCH(1,1). We show that all parameters can be derived using basic linear algebra tools. We show that the estimator is consistent and asymptotically normal distributed. Our results allow also to derive a closed form for the parameters in the context of temporal aggregation of multivariate GARCH(1,1) by solving the equations as in Hafner [2008].
Feature Selection Based on Joint Mutual Information

A feature/input selection method is proposed based on joint mutual information. The new method is better than the existing methods based on mutual information in eliminating redundancy in the inputs. It is applied in a real world application to nd 2-D viewing coordinates for data visualization and to select inputs for a neural network classiier. The result shows that the new method can nd many good 2-D projections which cannot be found by the existing methods.
On the State of the Art in Verification and Validation in Cyber Physical Systems TR-ARiSE-2014-001

It is widely held that debugging cyber-physical systems (CPS) is challenging. However, few empirical studies quantitatively and qualitatively capture the state of the art and the state of the practice in debugging CPS and analyze what major research gaps remain. This paper presents an empirical study of verification and validation in CPS through three complementary methods: a structured on-line survey of CPS developers and researchers, semi-structured interviews with professional CPS developers from various backgrounds, and a qualitative analysis of state of the art in research related to CPS testing. We find that traditional verification and validation methodologies are not sufficient for cyber-physical systems, and we identify several potential avenues for future work. Our key findings include: (i) many CPS developers do not use traditional verification and validation methodologies and rely heavily on trial and error; (ii) simulation alone is not enough to capture dangerous bugs in CPS; (iii) it is widely acknowledged that the main challenges in CPS debugging are related to models of software systems, models of physics, and integration of cyber and physics models. These findings aid in identifying research directions to address the identified key challenges in CPS verification and validation.
UPlan: A Versatile Urban Growth Model for Transportation Planning

Urban models useful in transportation planning are reviewed, focusing especially on ones that are based on geographic information system (GIS) software. Then UPlan, a simple model written by the authors in the ArcView GIS, is described. Several different applications of UPlan are outlined, involving transportation planning and analysis of the growthinducing effects of new facilities, to demonstrate its use. Such models are coming into use for National Environmental Policy Act of 1969 assessments and for joint land use and transportation planning.
Chromatin Immunoprecipitation-Based Screen To Identify Functional Genomic Binding Sites for Sequence-Specific Transactivators

ABSTRACT In various human diseases, altered gene expression patterns are often the result of deregulated gene-specific transcription factor activity. To further understand disease on a molecular basis, the comprehensive analysis of transcription factor signaling networks is required. We developed an experimental approach, combining chromatin immunoprecipitation (ChIP) with a yeast-based assay, to screen the genome for transcription factor binding sites that link to transcriptionally regulated target genes. We used the tumor suppressor p53 to demonstrate the effectiveness of the method. Using primary and immortalized, nontransformed cultures of human mammary epithelial cells, we isolated over 100 genomic DNA fragments that contain novel p53 binding sites. This approach led to the identification and validation of novel p53 target genes involved in diverse signaling pathways, including growth factor signaling, protein kinase/phosphatase signaling, and RNA binding. Our results yield a more complete understanding of p53-regulated signaling pathways, and this approach could be applied to any number of transcription factors to further elucidate complex transcriptional networks.
Effect of stealthy bad data injection on network congestion in market based power system

In a smart grid, the strong coupling between cyber and physical operations makes power systems vulnerable to cyber attacks. Changing the traditional structure of power systems and integrating communication devices are beneficial for better monitoring and decisionmaking by System Operators but increases the chance of being maliciously attacked. The communication links can be hacked so that the attacker can alter the power flow and power injection measurements, which are used to estimate the states of power system. In this paper, we formulate an attack strategy that can change the congestion of transmission lines without being detectable. Moreover, the financial benefit in an Ex-Post market is also investigated. Simulation results on an IEEE 30-Bus test system shows both the changes of congestion and the potential financial benefit gained by an attacker.
Free Space Estimation for Autonomous Navigation

One of the issues in autonomous navigation is the free space estimation. This paper presents an original framework and a method for the extraction of such an area by using a stereovision system. The v- disparity algorithm is extended to provide a reliable and precise road pro¯le on all types of roads. The free space is estimated by classifying the pixels of the disparity map. This classi¯cation is performed by using the road pro¯le and the u-disparity image. Each stage of the algorithm is presented and experimental results are shown.
Dynamic Fuzzy-Neural Network Controller for Induction Motor Drive

⎯ In this paper, a novel approach for robust trajectory tracking of induction motor drive is presented. By combining variable structure systems theory with fuzzy logic concept and neural network techniques, a new algorithm is developed. Fuzzy logic was used for the adaptation of the learning algorithm to improve the robustness of learning and operating of the neural network. The developed control algorithm is robust to parameter variations and external influences. It also assures precise trajectory tracking with the prescribed dynamics. The algorithm was verified by simulation and the results obtained demonstrate the effectiveness of the designed controller of induction motor drives which considered as highly non linear dynamic complex systems and variable characteristics over the operating conditions.
Prediction of fetal infection in cases with cytomegalovirus immunoglobulin M in the first trimester of pregnancy: a retrospective cohort.

BACKGROUND Interpretation of positive cytomegalovirus (CMV) immunoglobulin M (IgM) in the first trimester of pregnancy is ill-defined. We aimed to quantify the risk of fetal transmission in women with positive CMV IgM in the first trimester. METHODS A retrospective cohort of women (2009-2011) was tested for CMV immunoglobulin G (IgG) and IgM before 14 weeks of gestation. IgG avidity was tested with 2 assays (LIAISON and VIDAS). CMV polymerase chain reaction (PCR) was done in maternal serum, amniotic fluid, or neonatal urine at birth. RESULTS A total of 4931 consecutive women were screened; 201 presented with positive or equivocal IgM and with high, intermediate, or low IgG avidity in 58.7%, 18.9%, and 22.3%, respectively. In 72 women with low or intermediate avidity, fetal transmission was 23.6%. In multivariate analysis, positive CMV PCR in maternal serum, decreasing avidity index with both LIAISON and VIDAS, and low IgG titers were all associated with fetal transmission (odds ratio [OR], 12.38 [95% confidence interval {CI}, 1.77-86.33], P = .011; OR, 0.16 [95% CI, .03-.95], P = .044; OR, 0.54 [95% CI, .11-.88], P = .028; and OR, 0.27 [95% CI, .29-.84], P = .010, respectively). CONCLUSION This study demonstrates a significant association between the risk of vertical transmission and the avidity index combined with CMV PCR in maternal serum or IgG titers. This allows calculation of incremental risk of fetal transmission upon which informed choice can be based and could lead to a better pickup rate of fetal infection while decreasing unnecessary invasive procedures.
Investigating human-human and human-computer collaborative learning and memory in healthy ageing : the role of collaborator identity and social cognition

Learning and memory abilities decline with age; however collaborative learning with a familiar partner has been found to improve older adults’ performance on memory tasks and reduce these age-related differences. However it is unclear whether collaborating with a familiar partner is more beneficial to learning compared with collaborating with a stranger. Similarly, it is unclear whether older adults collaborate similarly with human and computer partners. The aim of this PhD thesis is to understand the role of collaborator identity on collaborative learning, and to investigate whether collaborative learning is as efficient and accurate with a range of learning partners. While collaborative learning is a socially-based memory task, the relationships between collaborative learning and social cognition have not yet been explored. The secondary aim of this thesis is to use experimental collaborative learning paradigms alongside standardised and experimental measures of social cognition to explore whether social cognition accounts for a significant amount of variance in collaborative learning performance with different partners. Two studies compare younger and older adults’ learning with familiar and unfamiliar partners on different collaborative learning paradigms. Two subsequent studies compare older adults’ learning on computerised versions of the collaborative learning tasks with partners they perceive to be humans or computers based on recordings of natural human or synthetic speech respectively. In all studies, measures of social cognition were used to assess whether social abilities affect learning outcomes with different partner types. When comparing older and younger adults’ results, familiarity had no effect on learning or immediate or delayed recall performance. Older adults initially took longer to complete the learning trials but performed with similar efficiency as younger adults by the final trials. Younger and older adults recalled collaboratively learned information with comparable accuracy after a delay of one hour, however after one week, older adults recalled the route less accurately than younger adults. Social cognition was not related to collaborative learning with familiar partners, but was related with unfamiliar partners, suggesting that those who are better able to take the perspective of another person may benefit during interactive learning. Social cognition was related to collaborative learning with perceived human partners but not perceived
Social Protection Discussion Paper Series Household Vulnerability and Child Labor: the Effect of Shocks, Credit Rationing and Insurance Social Protection Unit Human Development Network the World Bank

Social Protection Discussion Papers are not formal publications of the World Bank. They present preliminary and unpolished results of analysis that are circulated to encourage discussion and comment; citation and the use of such a paper should take account of its provisional character. The findings, interpretations, and conclusions expressed in this paper are entirely those of the author(s) and should not be attributed in any manner to the World Bank, to its affiliated organizations or to members of its Board of Executive Directors or the countries they represent.
Mobility-Based Clustering in VANETs Using Affinity Propagation

The recent research in cluster-based MAC and routing schemes for Vehicle Ad Hoc Networks (VANETs) motivates the necessity for a stable VANET clustering algorithm. Due to the highly mobile nature of VANETs, mobility must play an integral role in cluster formation. We present a novel, mobility-based clustering scheme for Vehicle Ad hoc Networks, which utilizes the Affinity Propagation algorithm in a distributed manner. The proposed algorithm considers typical vehicular mobility during cluster formation, which produces clusters with high stability. Simulation results confirm the superior performance of the proposed algorithm, when compared to other accepted mobility-based clustering techniques. Clustering performance is measured in terms of average cluster head duration, average cluster member duration, average rate of cluster head change, and average number of clusters.
Structural Requirements of Human Ether-a-go-go–related Gene Channels for Block by Bupivacaine

Background: Local anesthetics interact with human ether-a-go-go–related gene (HERG) channels via the aromatic amino acids Y652 and F656 in the S6 region. This study aimed to establish whether the residues T623, S624, and V625 residing deeper within the pore are also involved in HERG channel block by bupivacaine. In addition, the study aimed to further define the role of the aromatic residues Y652 and F656 in bupivacaine inhibition by mutating these residues to threonine. Methods: Alanine and threonine mutants were generated by site-directed mutagenesis. Electrophysiologic and pharmacologic properties of wild-type and mutant HERG channels were established using two-electrode voltage-clamp recordings of Xenopus laevis oocytes expressing HERG channels. Results: Tail currents at −120 mV through HERG wild-type channels were inhibited with an IC50 value of 132 ± 22 &mgr;m (n = 33). Bupivacaine (300 &mgr;m) inhibited wild-type tail currents by 62 ± 12% (n = 7). Inhibition of HERG tail currents by bupivacaine (300 &mgr;m) was reduced by all mutations (P < 0.001). The effect was largest for F656A (inhibition 5 ± 2%, n = 6) in the lower S6 region and for T623A (inhibition 13 ± 4%, n = 9) near the selectivity filter. Introducing threonine at positions 656 and 652 significantly reduced inhibition by bupivacaine compared with HERG wild type (P < 0.001). Conclusions: The authors’ results indicate that not only the aromatic residues Y652 and F656 but also residues residing deeper within the pore and close to the selectivity filter of HERG channels are involved in inhibition of HERG channels by the low-affinity blocker bupivacaine.
Generic Framework Market Context Preference Model Preference Model Preference Model Market Context Preference Model Preference Model Preference Model

Introduction In marketing there are (at least) two separate worlds of knowledge: information about consumers (from surveys, panel data, etc.) and information about purchase decisions (from aggregate sales data and similar). Relating these two worlds is difficult because the consumer views cannot be easily traced to a part of the sales data (or vice versa) – there is no " psychological " model that bridges this gap (although there have been some attempts at making one). Part of the problem is that the standard method is to take a model structure that is a prior acceptable (to academics and other experts), parameterise it to fit the data and finally present the results to practitioners (those who actually have to try and make sense of the results in terms of costly marketing decisions). The data is thus used to try and adapt a theoretical model to specific market of concern. However this means that the meaning of the model is in the hands of the academic or expert who formulates and manipulates the model – the practitioners are left with a black-box model and (if they are lucky) some results. Unless the model-maker and the person with experience in the market happen to be the same person then, necessarily, the model will have to be applied somewhat 'blindly' to the market and its formulation will be unable to make use of the context-dependent domain knowledge of the practitioner. In contrast to this traditional 'division of labour', we propose an approach whereby the final model is constructed, in part, by the practitioner (and optionally a computer) but within a framework devised by academic modellers. Thus we seek to delay some of the model specification. This is done at three different levels: 1. we have specified a general framework for relating a certain type of consumer preference model to aggregate data, based on expert advice, our experience , and multiple trials of frameworks to find what works – this can be thought of as a meta-model because it relates a class of specific models to results (this will be called the 'generic framework'); 2. a marketing practitioner specifies some information to constrain the possibilities inherent in the general framework to those that are relevant to a particular market based on their knowledge of their market – this provides the semantic framework for the specific models (we will call the 'market context'); 3. within …
Static Analysis for the pi-Calculus with Applications to Security

Abstract Control Flow Analysis is a static technique for predicting safe and computable approximations to the set of values that the objects of a program may assume during its execution. We present an analysis for the π-calculus that shows how names will be bound to actual channels at run time. The result of our analysis establishes a super-set of the set of channels to which a given name may be bound and of the set of channels that may be sent along a given channel. Besides a set of rules that permits one to validate a given solution, we also offer a constructive procedure that builds solutions in low polynomial time. Applications of our analysis include establishing two simple security properties of processes. One example is that P has no leaks: P offers communication to the external environment through public channels only and confines its secret channels within itself. The other example is connected to the no read-up/no write-down property of Bell and LaPadula: once processes are given levels of security clearance, we check that a process at a high level never sends channels to processes at a lower level.
Prognostic factors in patients after definitive chemoradiation using involved‐field radiotherapy for esophageal cancer in a phase II study

A prospective study was performed on the use of chemoradiotherapy (CRT) for esophageal cancer (EC) with involved‐field radiation therapy (IFRT), based on 18‐fluorodeoxyglucose positron‐emission tomography. Prognostic factors for overall survival (OS) were analyzed.