Miracle-dz/UniFAR-FTUs huggingface dataset:
AN INTERFACE FOR IMAGE RETRIEVAL AND ITS EXTENSION TO VIDEO RETRIEVAL

Semantic video retrieval is still an open problem. While many works exist in analyzing the video contents, few ones present the retrieval results to the users and interact with him/her. In this article, firstly, we propose a 2D graphic interface adapted to the problem of image retrieval that enables a bidirectional communication: from the system towards the user to visualize the current research results and from the user towards the system so that the user can provide some relevance feedback information to refine his/her query. In this interface, the visualization shows the image query in the middle of the screen and the result images in a 2D plan with distances showing the similarity measures between images and the query. We propose also a method of relevance feedback in form of validation, in this interface, for image retrieval. This approach has been implemented and tested with different image databases. Secondly, we analyze the extension of this approach for video retrieval. For this, we extract the key frames from video and use them to represent the research results of video as well as to do the relevance feedback.
Estimating the Margin of Victory for Instant-Runoff Voting

A general definition is proposed for the margin of victory of an election contest. That definition is applied to Instant Runoff Voting (IRV) and several estimates for the IRV margin of victory are described: two upper bounds and two lower bounds. Given round-by-round vote totals, the time complexity for calculating these bounds does not exceed O(C2 log C), where C is the number of candidates. It is also shown that calculating the larger and more useful of the two lower bounds can be viewed, in part, as solving a longest path problem on a weighted, directed, acyclic graph. Worst-case analysis shows that neither these estimates, nor any estimates based only on tabulation round-by-round vote totals, are guaranteed to be within a constant factor of the margin of victory. These estimates are calculated for IRV elections in Australia and California. Pseudo code for calculating these estimates is provided.
An Adaptive Power Efficient Packet Scheduling Algorithm for Wimax Networks

Admission control schemes and scheduling algorithms are designed to offer QoS services in 802.16/802.16e networks and a number of studies have investigated these issues. But the channel condition and priority of traffic classes are very rarely considered in the existing scheduling algorithms. Although a number of energy saving mechanisms have been proposed for the IEEE 802.16e, to minimize the power consumption of IEEE 802.16e mobile stations with multiple real-time connections has not yet been investigated. Moreover, they mainly consider non real- time connections in IEEE 802.16e networks. In this paper, we propose to design an adaptive power efficient packet scheduling algorithm that provides a minimum fair allocation of the channel bandwidth for each packet flow and additionally minimizes the power consumption. In the adaptive scheduling algorithm, packets are transmitted as per allotted slots from different priority of traffic classes adaptively, depending on the channel condition. Suppose if the buffer size of the high priority traffic queues with bad channel condition exceeds a threshold, then the priority of those flows will be increased by adjusting the sleep duty cycle of existing low priority traffic, to prevent the starvation. By simulation results, we show that our proposed scheduler achieves better channel utilization while minimizing the delay and power consumption.
ASLR-Guard: Stopping Address Space Leakage for Code Reuse Attacks

A general prerequisite for a code reuse attack is that the attacker needs to locate code gadgets that perform the desired operations and then direct the control flow of a vulnerable application to those gadgets. Address Space Layout Randomization (ASLR) attempts to stop code reuse attacks by making the first part of the prerequisite unsatisfiable. However, research in recent years has shown that this protection is often defeated by commonly existing information leaks, which provides attackers clues about the whereabouts of certain code gadgets. In this paper, we present ASLR-Guard, a novel mechanism that completely prevents the leaks of code pointers, and render other information leaks (e.g., the ones of data pointers) useless in deriving code address. The main idea behind ASLR-Guard is to render leak of data pointer useless in deriving code address by separating code and data, provide a secure storage for code pointers, and encode the code pointers when they are treated as data. ASLR-Guard can either prevent code pointer leaks or render their leaks harmless. That is, ASLR-Guard makes it impossible to overwrite code pointers with values that point to or will hijack the control flow to a desired address when the code pointers are dereferenced. We have implemented a prototype of ASLR-Guard, including a compilation toolchain and a C/C++ runtime. Our evaluation results show that (1) ASLR-Guard supports normal operations correctly; (2) it completely stops code address leaks and can resist against recent sophisticated attacks; (3) it imposes almost no runtime overhead (< 1%) for C/C++ programs in the SPEC benchmark. Therefore, ASLR-Guard is very practical and can be applied to secure many applications.
Political Contagion in Currency Crises

Existing models of contagious currency crises are summarized and surveyed, and it is argued that more weight should be put on political factors. Towards this end, the concept of political contagion introduced, whereby contagion in speculative attacks across currencies arises solely because of political objectives of countries. A specific model of membership' contagion is presented. The desire to be part of a political-economic union, where maintaining a fixed exchange rate is a condition for membership and where the value of membership depends positively on who else is a member, is shown to give rise to potential contagion. We then present evidence suggesting that political contagion may have been important in the 1992-3 EMS crisis.
Adaptive Clock Scheduling for pipelined structures

This paper introduces a technique called Adaptive Inverter Chain Based Clock Scheduling, which can observe and compensate delay variations in pipelined structures. The main idea behind the method is to expose the data and the clock to the same variations such that the register data sampling process is not disturbed by variations. The proposed scheme also includes a mechanism to detect time failures and to take counter actions to recover from such situations. When compared with other state of the art proposals, which require the augmentation of the registers, our proposal requires a relative smaller area overhead due to the fact that it is focussed on clock and not on data. Moreover our simulations indicate that, depending on the specific delay variations and pipeline logic delay sensitivity to input data patterns, it can enable an up to 46% performance improvement.
Diabetic muscle infarction

A 44-year-old woman presented with a 3-week history of acute and persistent pain and swelling in her right calf. She had a 7-year history of type 2 diabetes mellitus and had started peritoneal dialysis 3 years previously. She denied antecedent trauma. On physical examination, she was febrile with a temperature of 38.2 C. A localized tender mass approximately 10 cm 6 cm was palpable in her swollen right calf without overlying warmth or erythema. Laboratory studies showed leucocytes 12.6 10/L, glycosylated haemoglobin 9.8%, creatine kinase 66 U/L, and erythrocyte sedimentation rate 106 mm/h. Deep vein thrombosis or pyomyositis were tentatively diagnosed. Duplex ultrasonography of right calf deep veins was normal.Muscleaspirationandbiopsywereattempted. However, magnetic resonance (MR) imaging showed highsignal intensity in the subcutis, deep fascia, and muscles on T2-weighted images (Fig. 1) and a MR angiogram showed poor distal run-off in the posterior tibial artery in the late arterial phase (Fig. 2), consistent with diabetic muscle infarction (DMI). With analgesics and rest, the calf pain andmass entirely resolved over the ensuing 4 weeks. DMI, a less-recognized complication of diabetes mellitus, typically presents with acute painful swelling and/or a tender firm mass in the lower extremity. Clinically, it can be misdiagnosed as deep vein thrombosis, cellulitis, pyomyositis, haematoma, myositis ossificans or soft tissue neoplasm. Laboratory findings in DMI are neither sensitive nor specific and the treatment of DMI is supportive.
Cognitive deficits and functional outcome in schizophrenia

Cognitive dysfunction is a core feature of schizophrenia. Deficits are moderate to severe across several domains, including attention, working memory, verbal learning and memory, and executive functions. These deficits pre-date the onset of frank psychosis and are stable throughout the course of the illness in most patients. Over the past decade, the focus on these deficits has increased dramatically with the recognition that they are consistently the best predictor of functional outcomes across outcome domains and patient samples. Recent treatment studies, both pharmacological and behavioral, suggest that cognitive deficits are malleable. Other research calls into question the meaningfulness of cognitive change in schizophrenia. In this article, we review cognitive deficits in schizophrenia and focus on their treatment and relationship to functional outcome.
Fingerprint's Core Point Detection Using Orientation Field

Fingerprint recognition is a widely used biometricidentification mechanism. In case of correlation based fingerprintrecognition detection of a consistent registration point is a crucialissue; this point can be a core point of a fingerprint. Manytechniques have been proposed but success rate is highlydependent on input used and accurate core point detection is stillan open issue. Here we discuss a core point detection algorithmwhich is computationally simple and gives consistent detection ofa core point. The proposed technique is based on orientation fieldof the fingerprint which is calculated using gradient basedtechnique and optimized neighborhood averaging to generate asmoother orientation field, on which we operate a speciallydesigned mask for detecting core point as the orientation field inthe region of the core point is different than the other area.Though all fingerprints don’t possess core point still thisalgorithm is useful to detect high curvature regions. Thisalgorithm is helpful in the development of correlation basedAutomatic Fingerprint Recognition System (AFIS).
Therapeutic Effects of Yoga for Children: A Systematic Review of the Literature

Purpose: We completed a systematic review of the literature on the effect of yoga on quality of life and physical outcome measures in the pediatric population. We explored various databases and included case–control and pilot studies, cohort and randomized controlled trials that examined yoga as an exercise intervention for children. Summary of Key Points: Using the Sackett levels of evidence, this article reviews the literature on yoga as a complementary mind–body movement therapy. We address the research through three practice patterns according to the Guide to Physical Therapist Practice and provide considerations for the inclusion of yoga into clinical practice. Statement of Conclusions and Recommendations for Clinical Practice: The evidence shows physiological benefits of yoga for the pediatric population that may benefit children through the rehabilitation process, but larger clinical trials, including specific measures of quality of life are necessary to provide definitive evidence.
Correlated evolution of sternal keel length and ilium length in birds

The interplay between the pectoral module (the pectoral girdle and limbs) and the pelvic module (the pelvic girdle and limbs) plays a key role in shaping avian evolution, but prior empirical studies on trait covariation between the two modules are limited. Here we empirically test whether (size-corrected) sternal keel length and ilium length are correlated during avian evolution using phylogenetic comparative methods. Our analyses on extant birds and Mesozoic birds both recover a significantly positive correlation. The results provide new evidence regarding the integration between the pelvic and pectoral modules. The correlated evolution of sternal keel length and ilium length may serve as a mechanism to cope with the effect on performance caused by a tradeoff in muscle mass between the pectoral and pelvic modules, via changing moment arms of muscles that function in flight and in terrestrial locomotion.
Effects of Surface Modification of Titania on In Vitro Apatite-Forming Ability

Surface properties of a material play a significant role in manipulating biological response of living body to artificial materials. The aim of this work was put on bioactivity assessment of TiO2 ceramic after thermal treatment and further surface activation with UV-light. The in vitro apatite-forming ability was examined by soaking the samples into the simulated body fluid for several days. The research shows that nanostructural surface and UV irradiation accelerates formation of apatite on TiO2 pellets.
Gram-Stain Plus MALDI-TOF MS (Matrix-Assisted Laser Desorption Ionization-Time of Flight Mass Spectrometry) for a Rapid Diagnosis of Urinary Tract Infection

Microbiological confirmation of a urinary tract infection (UTI) takes 24–48 h. In the meantime, patients are usually given empirical antibiotics, sometimes inappropriately. We assessed the feasibility of sequentially performing a Gram stain and MALDI-TOF MS mass spectrometry (MS) on urine samples to anticipate clinically useful information. In May-June 2012, we randomly selected 1000 urine samples from patients with suspected UTI. All were Gram stained and those yielding bacteria of a single morphotype were processed for MALDI-TOF MS. Our sequential algorithm was correlated with the standard semiquantitative urine culture result as follows: Match, the information provided was anticipative of culture result; Minor error, the information provided was partially anticipative of culture result; Major error, the information provided was incorrect, potentially leading to inappropriate changes in antimicrobial therapy. A positive culture was obtained in 242/1000 samples. The Gram stain revealed a single morphotype in 207 samples, which were subjected to MALDI-TOF MS. The diagnostic performance of the Gram stain was: sensitivity (Se) 81.3%, specificity (Sp) 93.2%, positive predictive value (PPV) 81.3%, negative predictive value (NPV) 93.2%, positive likelihood ratio (+LR) 11.91, negative likelihood ratio (−LR) 0.20 and accuracy 90.0% while that of MALDI-TOF MS was: Se 79.2%, Sp 73.5, +LR 2.99, −LR 0.28 and accuracy 78.3%. The use of both techniques provided information anticipative of the culture result in 82.7% of cases, information with minor errors in 13.4% and information with major errors in 3.9%. Results were available within 1 h. Our serial algorithm provided information that was consistent or showed minor errors for 96.1% of urine samples from patients with suspected UTI. The clinical impacts of this rapid UTI diagnosis strategy need to be assessed through indicators of adequacy of treatment such as a reduced time to appropriate empirical treatment or earlier withdrawal of unnecessary antibiotics.
Enhancing the MD-Strengthening and Designing Scalable Families of One-Way Hash Algorithms

One-way hash algorithms are an indispensable tool in data security. Over the last decade or so a number of one-way hash algorithms have been designed and many of them have been used in numerous applications. Recent progress in cryptanalytic attacks on one-way hash algorithms by Wang and co-workers, however, has brought up the urgency of research into new and more secure algorithms. The goal of this paper is two-folded. On one hand we propose a simple technique to affix authentication tags to messages prior to being hashed by an iterative oneway hash algorithm with the aim of increasing the overall security of the algorithm against cryptanalytic attacks. One the other hand we advocate the importance of a system oriented approach towards the design and deployment of new families of one-way hash algorithms that support greater scalability and facilitate migration to newer member algorithms upon the compromise of deployed ones. We base our observations on a common sense premise that there is no specific one-way hash algorithm can remain secure forever and it will eventually be broken by a cryptanalytic attack faster than exhaustive research. ∗Corporate Information Security, Wachovia Bank, 1525 West T. Harris Blvd, Charlotte, NC 28288, USA. {neil.kauer, tony.suarez}@wachovia.com †Information Security and Assurance Center, UNC Charlotte, 9201 University City Blvd, Charlotte, NC 28223, USA. yzheng@uncc.edu
Tagging Personal Photos with Transfer Deep Learning

The advent of mobile devices and media cloud services has led to the unprecedented growing of personal photo collections. One of the fundamental problems in managing the increasing number of photos is automatic image tagging. Existing research has predominantly focused on tagging general Web images with a well-labelled image database, e.g., ImageNet. However, they can only achieve limited success on personal photos due to the domain gaps between personal photos and Web images. These gaps originate from the differences in semantic distribution and visual appearance. To deal with these challenges, in this paper, we present a novel transfer deep learning approach to tag personal photos. Specifically, to solve the semantic distribution gap, we have designed an ontology consisting of a hierarchical vocabulary tailored for personal photos. This ontology is mined from $10,000$ active users in Flickr with 20 million photos and 2.7 million unique tags. To deal with the visual appearance gap, we discover the intermediate image representations and ontology priors by deep learning with bottom-up and top-down transfers across two domains, where Web images are the source domain and personal photos are the target. Moreover, we present two modes (single and batch-modes) in tagging and find that the batch-mode is highly effective to tag photo collections. We conducted personal photo tagging on 7,000 real personal photos and personal photo search on the MIT-Adobe FiveK photo dataset. The proposed tagging approach is able to achieve a performance gain of $12.8\%$ and $4.5\%$ in terms of NDCG@5, against the state-of-the-art hand-crafted feature-based and deep learning-based methods, respectively.
International Journal of Behavioral Nutrition and Physical Activity Environmental Determinants of Active Travel in Youth: a Review and Framework for Future Research

Background: Many youth fail to meet the recommended guidelines for physical activity. Walking and cycling, forms of active travel, have the potential to contribute significantly towards overall physical activity levels. Recent research examining the associations between physical activity and the environment has shown that environmental factors play a role in determining behaviour in children and adolescents. However, links between the environment and active travel have received less attention.
C-Planarity of C-Connected Clustered Graphs Part I - Characterization

We present a characterization of the c-planarity of c-connected clustered graphs. The characterization is based on the interplay between the hierarchy of the clusters and the hierarchy of the triconnected and biconnected components of the graph underlying the clustered graph. In a companion paper [2] we exploit such a characterization to give a linear time c-planarity testing and embedding algorithm.
Learning Models for Object Recognition from Natural Language Descriptions

We investigate the task of learning models for visual object recognition from natural language descriptions alone. The approach contributes to the recognition of fine-grain object categories, such as animal and plant species, where it may be difficult to collect many images for training, but where textual descriptions of visual attributes are readily available. As an example we tackle recognition of butterfly species, learning models from descriptions in an online nature guide. We propose natural language processing methods for extracting salient visual attributes from these descriptions to use as ‘templates’ for the object categories, and apply vision methods to extract corresponding attributes from test images. A generative model is used to connect textual terms in the learnt templates to visual attributes. We report experiments comparing the performance of humans and the proposed method on a dataset of ten butterfly categories.
Generation of ρ0 cells utilizing a mitochondrially targeted restriction endonuclease and comparative analyses

Eukaryotic cells devoid of mitochondrial DNA (ρ0 cells) were originally generated under artificial growth conditions utilizing ethidium bromide. The chemical is known to intercalate preferentially with the mitochondrial double-stranded DNA thereby interfering with enzymes of the replication machinery. ρ0 cell lines are highly valuable tools to study human mitochondrial disorders because they can be utilized in cytoplasmic transfer experiments. However, mutagenic effects of ethidium bromide onto the nuclear DNA cannot be excluded. To foreclose this mutagenic character during the development of ρ0 cell lines, we developed an extremely mild, reliable and timesaving method to generate ρ0 cell lines within 3–5 days based on an enzymatic approach. Utilizing the genes for the restriction endonuclease EcoRI and the fluorescent protein EGFP that were fused to a mitochondrial targeting sequence, we developed a CMV-driven expression vector that allowed the temporal expression of the resulting fusion enzyme in eukaryotic cells. Applied on the human cell line 143B.TK− the active protein localized to mitochondria and induced the complete destruction of endogenous mtDNA. Mouse and rat ρ0 cell lines were also successfully created with this approach. Furthermore, the newly established 143B.TK− ρ0 cell line was characterized in great detail thereby releasing interesting insights into the morphology and ultra structure of human ρ0 mitochondria.
Isolating and understanding concurrency errors using reconstructed execution fragments

In this paper we propose Recon, a new general approach to concurrency debugging. Recon goes beyond just detecting bugs, it also presents to the programmer short fragments of buggy execution schedules that illustrate how and why bugs happened. These fragments, called reconstructions, are inferred from inter-thread communication surrounding the root cause of a bug and significantly simplify the process of understanding bugs. The key idea in Recon is to monitor executions and build graphs that encode inter-thread communication with enough context information to build reconstructions. Recon leverages reconstructions built from multiple application executions and uses machine learning to identify which ones illustrate the root cause of a bug. Recon's approach is general because it does not rely on heuristics specific to any type of bug, application, or programming model. Therefore, it is able to deal with single- and multiple-variable concurrency bugs regardless of their type (e.g., atomicity violation, ordering, etc). To make graph collection efficient, Recon employs selective monitoring and allows metadata information to be imprecise without compromising accuracy. With these optimizations, Recon's graph collection imposes overheads typically between 5x and 20x for both C/C++ and Java programs, with overheads as low as 13% in our experiments. We evaluate Recon with buggy applications, and show it produces reconstructions that include all code points involved in bugs' causes, and presents them in an accurate order. We include a case study of understanding and fixing a previously unresolved bug to showcase Recon's effectiveness.