Miracle-dz/UniFAR-FTUs huggingface dataset:
DLS@CU: Sentence Similarity from Word Alignment and Semantic Vector Composition

We describe a set of top-performing systems at the SemEval 2015 English Semantic Textual Similarity (STS) task. Given two English sentences, each system outputs the degree of their semantic similarity. Our unsupervised system, which is based on word alignments across the two input sentences, ranked 5th among 73 submitted system runs with a mean correlation of 79.19% with human annotations. We also submitted two runs of a supervised system which uses word alignments and similarities between compositional sentence vectors as its features. Our best supervised run ranked 1st with a mean correlation of 80.15%.
Efficient detection of deletions induced by a single treatment of mitomycin C in transgenic mouse gpt delta using the Spi− selection

Transgenic rodent mutation assays permit the detection and molecular analysis of various types of gene mutations, such as base changes and frameshifts, in a number of tissues. It is reported, however, that deletion mutations are not efficiently detected by the assays, in particular those using lambda phage shuttle vectors. Recently, a new transgenic mouse model, i.e., gpt delta, has been developed to selectively detect some types of deletions by Spi− selection. Spi− selection has an advantage over the other selections to preferentially identify deletions because only lambda phages deficient in both the red and gam gene functions are allowed to form phage plaques. In this study, we examined whether in vivo deletions induced by the treatment of mitomycin C (MMC) are detectable by the Spi− assay in the mouse model. The mice were treated with MMC (0.5, 1.0, 2.0, and 4.0 mg/kg, single intraperitoneal injection) and sacrificed 14 days after the dosing. The treatment at 4.0 mg/kg approximately doubled the mutant frequency of Spi− in the bone marrow, i.e., 2.52 × 10−6 vs. 1.31 × 10−6. The molecular analyses using polymerase chain reaction (PCR) and DNA sequencing indicated that seven Spi− mutants at 4.0 mg/kg group had deletions with molecular sizes from 0.8 kilo basepairs (kb) to 8.5 kb, whereas no such deletions were observed in the Spi− mutants in the control group. The results suggest that deletions induced by MMC in the bone marrow are efficiently detectable by Spi− selection and also that the molecular analyses are useful to evaluate the significance of a marginal increase in mutant frequency in the transgenic rodent mutation assays. Environ. Mol. Mutagen. 34:106–111, 1999 © 1999 Wiley‐Liss, Inc.
Human recombinant heat shock protein 70 affects the maturation pathways of dendritic cells in vitro and has an in vivo adjuvant activity

Heat shock proteins (HSPs) are potent inducers of an antigen‐specific immunological response. A role of chaperon of immunogenic peptides and a direct effect on APC activation and function have been described. However, the signal transduction events involved in the activation of human APCs are poorly characterized. We investigated, using human monocyte‐derived dendritic cells (DCs), the signal transduction pathways activated by a human recombinant HSP70 (r)HSP70 purified from eukaryotic cells. rHSP70 effectively induced a partial maturation of DCs in vitro and a significant increase in the titers of antigen‐specific IgG when used as a vaccine adjuvant in vivo. rHSP70 did not desensitize human DCs to LPS stimulation and retained its adjuvant properties in C3H/HeJ mice, which are LPS‐resistant as a result of a mutation in TLR‐4, ruling out the potential interference of LPS contamination. Effects on DC maturation and in vivo functions correlate to the ability of rHSP70 to activate IκB‐α/NF‐κB and ERK1/2 pathways in human DCs. No activation of p38 was induced in the same experimental conditions. Our data suggest that the IκB‐α/NF‐κB pathway has a critical role in the partial maturation of DCs induced by rHSP70.
Damping Feedback Stabilization for Cyclic Interconnections Systems: Oscillations Suppression and Synchronization

Abstract This paper considers the problem of stabilizing (bio)chemical reaction networks that can be represented as cyclic interconnections. The objective of the paper is to present a constructive way to compute a dissipative potential function for the system. This potential is then used for constructing a smooth feedback stabilizing controller. We obtain a characteristic one-form for the system by taking the interior product of a non vanishing two-form with respect to the drift vector field. A homotopy operator is then constructed locally around the desired equilibrium, leading to the computation of a dissipative potential for the system. The dynamics of the system is then decomposed into an exact part and an anti-exact one. The exact part is generated by a potential, that is used to construct the smooth stabilizing feedback, under the so-called weak Jurdjevic-Quinn conditions. We consider the problems of oscillations suppression and synchronization of oscillators as illustrations of potential applications of the proposed method.
The framingham risk score, diet, and inflammatory markers in Korean men with metabolic syndrome

The Framingham risk score (FRS) has been used to assess the risk of a cardiovascular event and to identify patients for risk factor modifications. Therefore, the purpose of this study was to evaluate the relationship of the FRS with dietary intake and inflammatory biomarkers. We conducted a cross-sectional study of 180 men (49.2 ± 10.2 years) with MS. Serum levels of high sensitive C-reactive protein (hs-CRP), interleukin-6 (IL-6), and adiponectin were examined. Participants were asked to complete the food frequency questionnaire (FFQ) using the previous 1 year as a reference point. The absolute cardiovascular disease (CVD) risk percentage over 10 years was calculated to estimate the FRS, which was classified as low risk (< 10%), intermediate risk (10-20%), and high risk (> 20%). Mean intake of polyunsaturated fatty acids was lower in subjects who had > 20% FRS than in subjects who had < 10% FRS (3.7 ± 1.9 g/day vs. 4.7 ± 1.9 g/day; P < 0.05). Significant differences in the Index of Nutritional Quality of protein, phosphorus, iron, vitamin A, vitamin B1, niacin, vitamin B6, and vitamin C were observed between the > 20% FRS group and the < 10% FRS group (P < 0.05). IL-6 concentrations were significantly lower in subjects with a < 10% FRS than in subjects who were 10-20% FRS or > 20% FRS (0.91 ± 0.26 vs. 1.48 ± 033 vs. 2.72 ± 0.57 pg/mL, respectively; P < 0.05). IL-6 and dietary intake of polyunsaturated fatty acids together explained 6.6% of the variation in FRS levels in a stepwise multiple regression model. Our results provide some evidence that dietary intake in the higher CVD risk group was inferior to that in the lower risk group and that dietary fat intake and IL-6 were associated with FRS and MS in Korean men.
Modeling and pricing cloud service elasticity for geographically distributed applications

Cloud service providers (CSP) strive to effectively provision their cloud resources to ensure that their hosted distributed applications meet their performance guarantees. However, accurately provisioning the inter-data centers network resources remains a challenging problem due to the cloud hosted applications' workload fluctuation. In this paper, we propose a novel approach that enables a CSP to offer Elasticity-as-a-Service (EaaS) for inter-data centers communication in order to guarantee the performance of distributed cloud applications. The contributions of the proposed work are two fold; first, we develop an efficient approach that enables the CSP to estimate and reserve the pool of network resources needed to fulfill the demands imposed by the network workload fluctuations of applications subscribing to this service. The approach allows the CSP to offer communication EaaS at differentiated levels based on the degree of bandwidth-sensitivity of the distributed cloud applications. In order to capture the inter-data centers network activity of hosted applications, we model their workloads using Markovian modeling. The second contribution is a novel dynamic pricing mechanism for network EaaS offerings that can be employed by the CSP to maximize the expected long-term revenue, and to regulate network elastic demands. Performance evaluation results demonstrate the efficiency of our proposed approach, the higher accuracy of our prediction method, and the increase in the CSPs net profit.
Secure protocol transformation via “expansion”: from two-party to groups

The design of simple cryptographic protocols for elementary two-party (session oriented) tasks (such as entity authentication and key transport) has had a history (starting with [NS78]) where security has been quite evasive. Only recently we have seen protocol designs which are both provably secure and efficient Currently, much attention of the designers of network systems and services is directed towards group operations, which will enable such important tasks as one-to-many distribution of content, group collaborative efforts, etc over the Internet and Intranets [Be98]. Rather than designing each group oriented task from scratch, we move in this work towards a more methodological approach, which derives a design of group (multicast) protocols from two-party ones. The approach, which we call secure protocol expansion, maintains the efficiency of the basic design and at the same tune preserves provable security. It enables us to achieve efficient and secure protocols for a large variety of group tasks. We consider basic group authentication and key transport protocols, as well as functional protocol extensions like multicast perfect forward secrecy, group access-control, group announcement and termination.
Work-in-Progress : Testing Autonomous Cyber-Physical Systems using Fuzzing Features derived from Convolutional Neural Networks

Autonomous cyber-physical systems rely onmodern machine learning methods such as deep neural networks to control their interactions with the physical world. Testing of such intelligent cyberphysical systems is a challenge due to the huge state space associated with high-resolution visual sensory inputs. In this paper, we demonstrate how fuzzing the input using patterns obtained from the convolutional filters of an unrelated convolutional neural network can be used to test the correctness of vision algorithms implemented in intelligent cyber-physical systems. Our method discovers interesting counterexamples to the pedestrian detection algorithm implemented in the popular OpenCV library. Our approach also unearths counterexamples to the correct behavior of an autonomous car similar to NVIDIA’s end-to-end self-driving deep neural net running on the Udacity open-source simulator.
Stimulation of Suicidal Erythrocyte Death by Ellipticine

Ellipticine is a potent antineoplastic alkaloid effective in part by triggering apoptosis. Mechanisms involved in ellipticine‐induced apoptosis include mitochondrial depolarization and DNA damage. Erythrocytes lack mitochondria and nuclei but may nevertheless enter suicidal death or eryptosis, which is characterized by cell shrinkage and phosphatidylserine translocation to the erythrocyte surface. Stimulators of eryptosis include increase in cytosolic Ca2+ activity ([Ca2+]i), ceramide formation and oxidative stress. This study tested whether ellipticine stimulates eryptosis. Phosphatidylserine exposure at the cell surface was estimated from annexin V binding, cell volume from forward scatter (FSC), [Ca2+]i from Fluo‐3 fluorescence, ceramide abundance from binding of specific antibodies and reactive oxygen species from 2′,7′‐dichlorodihydrofluorescein diacetate fluorescence. A 24‐hr exposure of human erythrocytes to ellipticine (5 μg/ml) significantly increased the percentage of annexin V binding cells, ceramide abundance and oxidative stress. Ellipticine did not significantly modify [Ca2+]i, and the stimulation of annexin V binding by ellipticine (5 μg/ml) did not require the presence of extracellular Ca2+. Ellipticine (5 μg/ml) did not significantly modify FSC. Ionomycin (1 μM, 1 hr) decreased FSC, an effect slightly but significantly blunted by ellipticine (5 μg/ml). Ellipticine thus stimulates phosphatidylserine translocation in the erythrocyte cell membrane, an effect at least partially due to stimulation of oxidative stress and ceramide formation.
Motor Recovery and Axonal Plasticity With Short-Term Amphetamine After Stroke

Background and Purpose— There is considerable debate regarding the efficacy of amphetamine to facilitate motor recovery after stroke or experimental brain injury. Different drug dosing and timing schedules and differing physical rehabilitation strategies may contribute to outcome variability. The present study was designed to ascertain (1) whether short-term amphetamine could induce long-term functional motor recovery in rats after an ischemic lesion modeling stroke in humans; (2) how different levels of physical rehabilitation interact with amphetamine to enhance forelimb-related functional outcome; and (3) whether motor improvement was associated with axonal sprouting from intact corticoefferent pathways originating in the contralesional forelimb motor cortex. Methods— After permanent middle cerebral artery occlusion, rats received vehicle or amphetamine during the first postoperative week (2 mg/kg, subcutaneously on Postoperative Days 2, 5, and 8). In both treatment groups, separate cohorts of rats were exposed to different levels of “physical rehabilitation” represented by a control environment, enriched environment, or enriched environment with additional sessions of focused activity. Skilled forelimb performance was assessed using the forelimb reaching task and ladder rung walk test. Anterograde tracing with biotinylated dextran amine was used to assess new fiber outgrowth to denervated motor areas. Results— All treatment groups showed significant motor improvement as compared with control-housed, vehicle-treated animals. However, animals housed in an enriched environment that received amphetamine paired with focused activity sessions performed significantly better than any other treatment group and was the only group to achieve complete motor recovery (ie, reached preoperative performance) by 8 weeks. This recovery was associated with axonal sprouting into deafferentated subcortical areas from contralesional projection neurons. Conclusions— This study suggests that, after stroke, short-term pairing of amphetamine with sufficiently focused activity is an effective means of inducing long-term improvement in forelimb motor function. The anatomic data suggests that corticoefferent plasticity in the form of axonal sprouting contributes to the maintenance of motor recovery.
Personality Validity: The Role of Schemas and Motivated Reasoning

We explored the role of schemas and motivated reasoning in personality assessment. Utilizing a sample of 299 participants, we investigated whether applying for a specific job leads applicants to adopt a schema. Once adopting the schema, the respondents use that schema in a way that inaccurately reflects what their behavior is. Consequently, as hypothesized, there is a lowering of validities, in comparison with assessing personality in a neutral setting. An intriguing implication of our research is that personality measurement for selection might be shifted from the employment setting to more neutral settings, such as a counselor setting, in order to be optimized.
P2P Volunteers for Reliable Server Farms

In recent years, there are more and more critical services being developed on the Internet with high requirements on availability and reliability. Distributed Denial-of-Service (DDoS) has become widespread and many web services have already been attacked. Server farms are one of the key approaches to improving the availability and reliability. However, due to the high maintenance cost and the “site disaster” problem of server farms, we are looking for cheaper infrastructure that is logically and geographical distributed to provide highly reliable services in spite of attacks and server failures. In this paper we provide highly reliable, attack resilient servers by using P2P farms of volunteers. The volunteer group can be dynamically constructed, is scalable and is resistant to service failures resulting from a the loss of a few peers.In our approach, the system will first form a self-organizing group of peers who are interested in a service. Then statistical and operational data, service response delay, client request pattern, and so on are collected. Finally, the system applies this information to select new servers, and integrate into the server farm till the target level of service is met.
Arbitrarily shaped sub-block motion prediction in texture map compression using depth information

When transmitting the so-called “texture-plus-depth” video format, texture and depth maps from the same viewpoint exhibit high correlation. Coded bits from one map can then be used as side information to encode the other. In this paper, we propose to use the depth information to divide the corresponding block in texture map into arbitrarily shaped regions (sub-blocks) for separate motion estimation (ME) and motion compensation (MC). We implemented our proposed sub-block motion prediction (MP) method for texture map coding using depth information as a new coding mode (z-mode) in H.264. Nonetheless, in practical experiments one can observe either a misalignment between texture and depth edges, or an aliasing effect at the texture boundaries. To overcome this issue, z-mode offers two MC types: i) non-overlapping MC, and ii) overlapping MC. In the latter case, overlapped sub-blocks after ME are alpha-blended using a properly designed filter. Moreover, the MV of each sub-block in z-mode is predicted using a Laplacian-weighted average of MVs of neighboring blocks of similar depth. Experimental results show that using z-mode, coding performance of the texture map can be improved by up to 0.7dB compared to native H.264 implementation at high bitrate.
Laplacian pyramids for deep feature inversion

Modern feature extraction pipelines, especially the ones using deep networks, involve an increasing variety of elements. With layered approaches heaping abstraction upon abstraction, it becomes difficult to understand what it is that these features are capturing. One appealing way of solving this puzzle is feature visualization, where features are mapped back to the image domain. Our work improves the generic approach of performing gradient descent (GD) in the image space to match a given set of features to achieve a visualization. Specifically, we note that coarse features of an image like blobs, outlines etc. are useful by themselves for classification purposes. We develop an inversion scheme based on this idea by recovering coarse features of the image before finer details. This is done by modeling the image as the composition of a Laplacian Pyramid. We show that by performing GD on the pyramid in a level-wise manner, we can recover meaningful images. Results are presented for inverting a shallow network: the densely calculated SIFT as well as a deep network: Krizehvsky et al.'s Imagenet CNN (Alexnet).
Improving Recall and Transfer Skills Through Vocabulary Building in Web-Based Second Language Learning: An Examination by Item and Feedback Type

purpose of this study is to investigate the effectiveness of response modes by item and feedback type in a web- based language learning program. The subjects of this study, 122 Korean tenth graders learning English as a foreign language, were placed into groups of four and were given a web-based language learning program consisting of two different varieties of item type (multiple choice and constructed response) and two forms of feedback (explicit and implicit). The results of this study suggest that the constructed response mode has a greater effect than the multiple- choice mode on the recall and the transfer of the students' learning. Second, the explicit response mode has a greater effect than the implicit response mode on the recall and the transfer of the students' learning. Third, there is an interactional effect between the item response mode and the feedback response mode in web-based language learning.
Forensic judgment and decision making

This chapter describes the decision making process by forensic experts. Forensic testimony is generally considered more reliable than most other forms of evidence and plays a key role in establishing guilt or innocence. Despite exaggerations in the media, automated, computerized methods are of limited capability and require experts to make judgment calls at various steps. Abductive reasoning is often required, perhaps inviting confirmation bias, particularly with decision making often based on reaching weight-of-evidence thresholds. Forensic scientists are expected to help find a conclusive outcome rather than the probabilistic one more compatible with scientific reasoning, and the need for rapid closure can lead to decisions based on incomplete data. Yet the interpretation of bottom-up information based on top-down information may lead to distortions, as in any type of data-driven decision making. Many of the same biases and difficulties that undermine human reasoning in other contexts reappear here too.
Sparse Overcomplete Latent Variable Decomposition of Counts Data

An important problem in many fields is the analysis of counts data to extract meaningful latent components. Methods like Probabilistic Latent Semantic Analysis (PLSA) and Latent Dirichlet Allocation (LDA) have been proposed for this purpose. However, they are limited in the number of components they can extract and lack an explicit provision to control the "expressiveness" of the extracted components. In this paper, we present a learning formulation to address these limitations by employing the notion of sparsity. We start with the PLSA framework and use an entropic prior in a maximum a posteriori formulation to enforce sparsity. We show that this allows the extraction of overcomplete sets of latent components which better characterize the data. We present experimental evidence of the utility of such representations.
Islamic Homosexualities: Culture, History, and Literature

The dramatic impact of Islamic fundamentalism in recent years has skewed our image of Islamic history and culture. Stereotypes depict Islamic societies as economically backward, hyper-patriarchal, and fanatically religious. But in fact, the Islamic world encompasses a great diversity of cultures and a great deal of variation within those cultures in terms of gender roles and sexuality. The first collection on this topic from a historical and anthropological perspective, Homosexuality in the Muslim World reveals that patterns of male and female homosexuality have existed and often flourished within the Islamic world. Indeed, same-sex relations have, until quite recently, been much more tolerated under Islam than in the Christian West. Based on the latest theoretical perspectives in gender studies, feminism, and gay studies, Homosexuality in the Muslim World includes cultural and historical analyses of the entire Islamic world, not just the so-called Middle East. Essays show both age-stratified patterns of homosexuality, as revealed in the erotic and romantic poetry of medieval poets, and gender-based patterns, in which both men and women might, to varying degrees, choose to live as members of the opposite sex. The contributors draw on historical documents, literary texts, ethnographic observation and direct observation by both Muslim and non-Muslim authors to show the considerable diversity of Islamic societies and the existence of tolerated gender and sexual variances.