Miracle-dz/UniFAR-FTUs huggingface dataset:
Who Cares about Others' Privacy: Personalized Anonymization of Moving Object Trajectories

The preservation of privacy when publishing spatiotemporal traces of mobile humans is a field that is receiving growing attention. However, while more and more services offer personalized privacy options to their users, few trajectory anonymization algorithms are able to handle personalization effectively, without incurring unnecessary information distortion. In this paper, we study the problem of Personalized (K,�)anonymity , which builds upon the model of (k,δ)-anonymity, while allowing users to have their own individual privacy and service quality requirements. First, we propose efficient modifications to state-of-the-art (k,δ)-anonymization algorithms by introducing a novel technique built upon users’ personalized privacy settings. This way, we avoid over-anonymization and we decrease information distortion. In addition, we utilize datasetaware trajectory segmentation in order to further reduce information distortion. We also study the novel problem of
A Variable-Grain Logic Cell and Routing Architecture for a Reconfigurable IP Core

In the present study, we investigate the use of reconfigurable logic devices (RLDs) as intellectual properties (IPs) for system on a chip (SoC). Using RLDs, SoCs can achieve both high performance and high flexibility. However, conventional RLDs have problems related to performance, area, and power consumption. In order to resolve these problems, we investigated the features of RLD architecture. RLDs are classified into fine-grained and coarse-grained devices based on their architecture. Generally, the granularity of an RLD is limited to either type, which means that a device can only achieve high performance in applications that are suited to its architecture. Therefore, we propose a variable-grain logic cell (VGLC) architecture that can overcome the trade-off between fine-grained and coarse-grained architectures, which are required for the implementation of random and arithmetic logics, respectively. The VGLC is based on a 4-bit adder including configuration bits, which can perform arithmetic and random logic operations unlike the LUT. In the present paper, a local interconnection architecture for the VGLC is proposed. Several types of local interconnections composed of different crossbars are compared, and the trade-off between hardware resources and flexibility is discussed. Using local interconnection, the routing area is reduced by a maximum of 49%.
On the effectiveness and applicability of mouse dynamics biometric for static authentication: A benchmark study

Mouse dynamics, the analysis of individuals' distinctive mouse actions, has been proposed as a biometric to discriminate legitimate users from impostors. Some researchers have explored this domain and showed promising results, but few examined the effectiveness and applicability of this technique, particularly regarding the inconsistent evaluation conditions, unacceptably long authentication time, and unshared data set. In this work, we perform a benchmark study of the baseline capabilities of mouse dynamics for static authentication. Using the data collected under a tightly-controlled environment from 26 subjects, we develop a repeatable evaluation procedure to investigate the performance of this technique at a continuum of authentication times and various classifiers. The results show that the longer the authentication time, the better the accuracy. The equal-error rate reduces from 14.26% to 2.64%, as the authentication time increases from 11 seconds to 110 seconds. Further, the technique is able to meet the European standard for commercial biometric technology if a longer authentication time is allowed. We also publish our data set and discuss a number of avenues for future research, which we believe are necessary to advance the state of the art in this area.
A framework to represent and mine knowledge evolution from Wikipedia revisions

State-of-the-art knowledge representation in semantic web employs a triple format (subject-relation-object). The limitation is that it can only represent static information, but cannot easily encode revisions of semantic web and knowledge evolution. In reality, knowledge does not stay still but evolves over time. In this paper, we first introduce the concept of "quintuple representation" by adding two new fields, state and time, where state has two values, either in or out, to denote that the referred knowledge takes effective or becomes expired at the given time. We then discuss a two-step statistical framework to mine knowledge evolution into the proposed quintuple representation. Utilizing extracted quintuple properly, it not only can reveal knowledge changing history but also detect expired information. We evaluate the proposed framework on Wikipedia revisions, as well as, common web pages currently not in semantic web format.
Effects of culture brokering on individual well-being and family dynamics in a sample of immigrant young adults from Eastern Europe

The current study explored the effects of culture brokering on the well-being and family dynamics of immigrant young adults from Eastern Europe. Data were collected from 197 first generation immigrant youth (M age = 22.93, SD = 2.89) from 12 different countries in Eastern Europe. The majority of the participants were female (63.5%) and had lived in the United States on average for 10 years. Participants completed a one-time online survey, answering questions about their brokering experiences, as well as about their well-being, family-dynamics, perception of their parents’ acculturation, and demographic variables. With respect to culture brokering, participants completed a well-established measure of language brokering which assesses the frequency of brokering as well as individual’s feelings toward brokering. A newly developed measure of procedural brokering, which also assessed frequency as well as feelings, was used to assess a new dimension of culture brokering. Data show that youth who are more educated and have lived in the United States for a longer period of time tend to broker less for their parents. Findings also indicate that negative feelings toward language brokering are related to depressive mood of young adults, but this relationship is mediated by family conflict. Similarly, family conflict mediated the relationship between frequency of procedural brokering and depressive mood. The results highlight the importance of understanding the complex family dynamics of immigrant families. Implications for further research and practice are discussed in detail.
Genetic polymorphisms contribute to acute kidney injury after coronary artery bypass grafting.

BACKGROUND Acute kidney injury is one of the most serious complications after cardiac surgery. Genetic polymorphisms are reported to be associated with postoperative renal impairment. The aim of this study was to investigate the relationship between selected gene polymorphisms and acute kidney injury after cardiac surgery. METHODS Two hundred forty-eight elective coronary artery bypass grafting procedure patients were enrolled in the study. Angiotensin-converting enzyme (ACE) II, ID, and DD, apolipoprotein E (APO E), and angiotensin II type 1 receptor (AGTR1) A1166C genotypes were detected by polymerase chain reaction. Plasma levels of ACE were analyzed by enzyme-linked immunosorbent assay. Acute kidney injury after cardiac surgery was graded according to the RIFLE (risk, injury, failure, loss, and end-stage kidney disease) classification. RESULTS In our study, 21.8% of patients had acute renal impairment after cardiac surgery. Among the 54 patients with acute kidney injury, ACE D allele frequency was 0.620. The plasma levels of ACE were significantly higher in the D allele carriers (P = .018). Three of the 54 patients with acute kidney injury were APO E epsilon 4 allele carriers (P = .002). AGTR1 C allele carriers constituted 46% of all patients with postoperative acute kidney injury. There was no statistically significant difference between A allele homozygotes and C allele carriers with respect to postoperative renal dysfunction (P > .05). CONCLUSIONS The present findings support the hypothesis that ACE I/D and APO E gene polymorphisms may play a role in the development of acute kidney injury after cardiac surgery. However, AGTR1 does not have a unique association with postoperative renal impairment.
Directional Summation in Non-direction Selective Retinal Ganglion Cells

Retinal ganglion cells receive inputs from multiple bipolar cells which must be integrated before a decision to fire is made. Theoretical studies have provided clues about how this integration is accomplished but have not directly determined the rules regulating summation of closely timed inputs along single or multiple dendrites. Here we have examined dendritic summation of multiple inputs along On ganglion cell dendrites in whole mount rat retina. We activated inputs at targeted locations by uncaging glutamate sequentially to generate apparent motion along On ganglion cell dendrites in whole mount retina. Summation was directional and dependent13 on input sequence. Input moving away from the soma (centrifugal) resulted in supralinear summation, while activation sequences moving toward the soma (centripetal) were linear. Enhanced summation for centrifugal activation was robust as it was also observed in cultured retinal ganglion cells. This directional summation was dependent on hyperpolarization activated cyclic nucleotide-gated (HCN) channels as blockade with ZD7288 eliminated directionality. A computational model confirms that activation of HCN channels can override a preference for centripetal summation expected from cell anatomy. This type of direction selectivity could play a role in coding movement similar to the axial selectivity seen in locust ganglion cells which detect looming stimuli. More generally, these results suggest that non-directional retinal ganglion cells can discriminate between input sequences independent of the retina network.
Rotation Schemes in Politics - an Experimental Examination

Rotation schemes in political organizations imply the temporary exclusion of some organization's members (outsiders) from decision-making. Consequently, only a fraction of members (insiders) has a direct influence in the decision-making process, whose results, however, concern and affect all members of the organization. Even though rotation schemes have been implemented in some political organizations - and are about to become more important in the European Union in the course of future enlargements - the political and economic consequences of rotation schemes, compared to an encompassing representation system, have not been thoroughly studied. We examine the effects of rotation schemes on the provision of a public good in groups. In particular, we study the degree of cooperation of (rotating) insiders and outsiders in an experiment and compare cooperation in rotation schemes with cooperation levels without rotation.
Rab18 and Rab43 have key roles in ER-Golgi trafficking

Rabs and Arfs/Arls are Ras-related small GTPases of particular relevance to membrane trafficking. It is thought that these proteins regulate specific pathways through interactions with coat, motor, tether and SNARE proteins. We screened a comprehensive list of Arf/Arl/Rab proteins, previously identified on purified Golgi membranes by a proteomics approach (37 in total), for Golgi or intra-Golgi localization, dominant-negative and overexpression phenotypes. Further analysis of two of these proteins, Rab18 and Rab43, strongly indicated roles in ER-Golgi trafficking. Rab43-T32N redistributed Golgi elements to ER exit sites without blocking trafficking of the secretory marker VSVG-GFP from ER to cell surface. Wild-type Rab43 redistributes the p150Glued subunit of dynactin, consistent with a specific role in regulating association of pre-Golgi intermediates with microtubules. Overexpression of wild-type GFP-Rab18 or incubation with any of three siRNAs directed against Rab18 severely disrupts the Golgi complex and reduces secretion of VSVG. Rab18 mutants specifically enhance retrograde Golgi-ER transport of the COPI-independent cargo β-1,4-galactosyltransferase (Galtase)-YFP but not the COPI-dependent cargo p58-YFP from the Golgi to ER in a photobleach assay. Rab18-S22N also potentiated brefeldin-A-induced ER-Golgi fusion. This study is the first comprehensive application of large-scale proteomics to the cell biology of small GTPases of the secretory pathway.
CD164 promotes lung tumor-initiating cells with stem cell activity and determines tumor growth and drug resistance via Akt/mTOR signaling

CD164 is a cell adhesion molecule that increases hematopoietic stem cell proliferation, adhesion, and migration via C-X-C chemokine receptor type 4 (CXCR4) signaling. Emerging evidence indicates that elevated CD164 expression is associated with aggressive metastasis, advanced stages, and shorter overall survival in lung cancer. However, no data are available regarding the clinical significance of CD164 expression in lung cancer. This study explores whether CD164 promotes tumor-initiation and drug resistance through the stem cell property. Using tissue microarrays, we determine that CD164 expression is correlated with clinicopathological characteristics in human lung cancer. The CD164 overexpression in normal lung epithelial cells (BEAS2B cells) leads to malignant transformation in vitro, tumorigenicity in xenografted mice, stem cell-like property, and drug resistance through ATP-binding cassette transporters. The CD164 overexpression increases CXCR4 expression and activates Akt/mTOR signaling. Rapamycin, an mTOR inhibitor, hinders cell proliferation along with sphere formation in vitro and impedes tumor growth in vivo. In conclusion, we have provided evidence that CD164 promotes the growth of lung tumor-initiating cells with stem cell properties and induces tumor growth and drug resistance through Akt/mTOR signaling. Therefore, identification of CD164 as a cancer stem cell therapeutic marker may develop an effective therapy in patients with chemoresistant lung cancer.
Efficient Language Identification using Anchor Models and Support Vector Machines

Anchor models have been recently shown to be useful for speaker identification and speaker indexing. The advantage of the anchor model representation of a speech utterance is its compactness (relative to the original size of the utterance) which is achieved with only a small loss of speaker-relevant information. This paper shows that speaker-specific anchor model representation can be used for language identification as well, when combined with support vector machines for doing the classification, and achieve state-of-the-art identification performance. On the NIST-2003 language identification task, it has reached an equal error rate of 4.8% for 30 second test utterances
Optimal strategies for weighted ray search

Searching for a hidden target is an important algorithmic paradigm with numerous applications. We introduce and study the general setting in which a number of targets, each with a certain weight, are hidden in a star-like environment that consists of $m$ infinite, concurrent rays, with a common origin. A mobile searcher, initially located at the origin, explores this environment in order to locate a set of targets whose aggregate weight is at least a given value $W$. The cost of the search strategy is defined as the total distance traversed by the searcher, and its performance is evaluated by the worst-case ratio of the cost incurred by the searcher over the cost of an on optimal, offline strategy with (some) access to the instance. This setting is a broad generalization of well-studied problems in search theory; namely, it generalizes the setting in which only a single target is sought, as well as the case in which all targets have unit weights. We consider two models depending on the amount of information allowed to the offline algorithm. In the first model, which is the canonical model in search theory, the offline algorithm has complete information. Here, we propose and analyze a strategy that attains optimal performance, using a parameterized approach. In the second model, the offline algorithm has only partial information on the problem instance (i.e., the target locations). Here, we present a strategy of asymptotically optimal performance that is logarithmically related to $m$. This is in stark contrast to the full information model in which a linear dependency is unavoidable.
Single-and Double-incision Double-bundle ACL Reconstruction

Double-bundle anterior cruciate ligament (ACL) reconstruction is intended to replicate the anatomy and the function of the anteromedial and posterolateral bundles of the native ACL to improve patients' satisfaction and knee stability. We prospectively assigned 75 consecutive patients with an isolated ACL lesion to one of three sequential groups of 25 patients each. Group I received a single-bundle, single-incision transtibial ACL reconstruction. Groups II and III received a double-bundle reconstruction with a single-incision transtibial technique or a double-bundle, twoincision outside-in technique, respectively. We obtained subjective International Knee Documentation Committee and Knee Injury and Osteoarthritis Outcome Score evaluations and objective International Knee Documentation Committee scores and KT-1000 measurements preoperatively and at followup. All patients reached a minimum followup of 2 years. KT side-to-side difference in Groups I, II, and III were 2.4, 1.6 and 1.4 mm, respectively. Group III had fewer patients with a positive pivot shift than Group I. The double-bundle double-incision outside-in ACL reconstruction resulted in improved anteroposterior stability and less residual pivot shift than single-incision single-bundle technique.Level of Evidence: Level II, therapeutic study. See Guidelines for Authors for a complete description of levels of evidence.
Neighborhood Preserving Orthogonal PNMF Feature Extraction for Hyperspectral Image Classification

In this paper, we propose a manifold geometry based projective nonnegative matrix factorization linear dimensionality reduction method, called neighborhood preserving orthogonal projective nonnegative matrix factorization (NPOPNMF), for feature extraction of hyperspectral image. By adding constraints on projective nonnegative matrix factorization (PNMF) that each data point can be represented as a linear combination of its neighbors, NPOPNMF preserves local neighborhood geometrical structure of hyperspectral data in the reduced space, and overcomes the Euclidean limitation of PNMF. The metric structure of original high-dimensional hyperspectral data space is preserved due to the orthogonality of projection matrix. NPOPNMF can be performed in either supervised or unsupervised mode according to the construction of adjacency graph and it can improve the discriminant performance of PNMF. Theoretical analysis and experimental results on hyperspectral data sets demonstrate that the proposed method is an effective and promising method for hyperspectral image feature extraction.
Job Cognition and Justice Influencing Organizational Attachment

Organizational attachment echoes the psychological bond between employee and employer relations, differing from affective component of commitment in terms of employees’ psychological and behavioral involvement. This study examines the extent to which employee perception about procedural, distributive justice and job cognition contributes toward organizational attachment in India. The effect of justice and job cognition variables relates differently to previous studies from western part of the globe. First, in past studies, procedural justice predicted commitment, whereas, for Indian employees, distributive justice contributed to organizational attachment. Second, the contribution of extrinsic job cognition in organizational attachment was evident in the model developed using Structural Equation Modeling (SEM; AMOS). Organizations must take cognizance of the outcomes exhibited by the behavior of managers while following the laid down policies and processes. Cognition of fairness at workplace and attachment can play key role in limiting retention. Practical implications and future research directions are discussed.
Energy efficient SVM classifier using approximate computing

Approximate computing is a promising approach to reduce great power consumption in modern very large scale integration (VLSI) systems. In this paper, a novel approximate adder with a much simplified carry compensation scheme is proposed. Besides, an approximate fixed-width multiplier with a low-cost compensation unit is introduced. To evaluate the effectiveness of the proposed approximate computing units, the application of the approximate computing in support vector machine (SVM) is investigated. Simulation results show that the approximation errors have negligible impact on the classification accuracy. Under the TSMC 90nm CMOS technology, the synthesis results indicate that the SVM classifier using approximate computing can reduces the power-delay product (PDP), area and critical path delay by 32.4%, 18.7% and 16.0%, respectively, compared to the same classifier with accurate computation units.
Arginine-rich cell-penetrating peptide-modified extracellular vesicles for active macropinocytosis induction and efficient intracellular delivery

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