Miracle-dz/UniFAR-FTUs huggingface dataset:
Stanford-UBC Entity Linking at TAC-KBP, Again

This paper describes the joint Stanford-UBC knowledge base population system for the entity linking tasks. We participated in both the English and the cross-lingual tasks, using a dictionary from strings to possible Wikipedia titles, taken from our 2009 submission. This dictionary is based on frequencies of Wikipedia back-links, and it provides a strong context-independent baseline. For the English track, we improved on the results given by the dictionary by disambiguating entities using a distantly supervised classifier, trained on context extracted from Wikipedia. Since we did not use any text from the Wikipedia pages associated with the knowledge base nodes for the dictionary, we submitted that run to the no wiki text track, and the one using the distantly supervised classifier to the wiki text track. Our work focused on disambiguating among articles, allowing for very simple NIL strategies: the system returned NIL whenever selected Wikipedia articles were not present in the KB; moreover, NILs were then clustered only according to the target string. These simple approaches were sufficient for our runs to score above the median entry in each of their respective tracks for the English task; for the cross-lingual task, there was only one track, and our submissions (using the English-specific, context-independent dictionaries) fell below the median.
Secure Continuous Aggregation in Wireless Sensor Networks

Continuous aggregation is usually required in many sensor applications to obtain the temporal variation information of aggregates. However, in a hostile environment, the adversary could fabricate false temporal variation patterns of the aggregates by manipulating a series of aggregation results through compromised nodes. Existing secure aggregation schemes conduct one individual verification for each aggregation result, which could incur great accumulative communication cost and negative impact on transmission scheduling for continuous aggregation. In this paper, we identify distinct design issues for protecting continuous in-network aggregation and propose a novel scheme to detect false temporal variation patterns. Compared with the existing schemes, our scheme greatly reduces the verification cost by checking only a small part of aggregation results to verify the correctness of the temporal variation patterns in a time window. A sampling-based approach is used to check the aggregation results, which enables our scheme independent of any particular in-network aggregation protocols as opposed to existing schemes. We also propose a series of security mechanisms to protect the sampling process. Both theoretical analysis and simulations show the effectiveness and efficiency of our scheme.
A fully integrated wafer-scale sub-mm3 FBAR-based wireless mass sensor

A wireless sub-mm3 FBAR-based mass sensor fully integrated in a hermetic package is demonstrated. We propose a wafer-scale commercially viable manufacturing process for the integration of the sensor and the interface circuitry. The drift in frequency of the FBAR sensor due to temperature, aging and stress is reduced by a factor of 10 through an integrated differential measurement. The sensor achieves a sensitivity of 0.45kHz. cm2/ng and consumes 14.7mW including the wireless link. The operation of the sensor has been demonstrated in thin film deposition and wireless humidity sensing experiments.
Nucleotide Excision Repair Is Associated with the Replisome and Its Efficiency Depends on a Direct Interaction between XPA and PCNA

Proliferating cell nuclear antigen (PCNA) is an essential protein for DNA replication, DNA repair, cell cycle regulation, chromatin remodeling, and epigenetics. Many proteins interact with PCNA through the PCNA interacting peptide (PIP)-box or the newly identified AlkB homolog 2 PCNA interacting motif (APIM). The xeroderma pigmentosum group A (XPA) protein, with a central but somewhat elusive role in nucleotide excision repair (NER), contains the APIM sequence suggesting an interaction with PCNA. With an in vivo based approach, using modern techniques in live human cells, we show that APIM in XPA is a functional PCNA interacting motif and that efficient NER of UV lesions is dependent on an intact APIM sequence in XPA. We show that XPA−/− cells complemented with XPA containing a mutated APIM sequence have increased UV sensitivity, reduced repair of cyclobutane pyrimidine dimers and (6–4) photoproducts, and are consequently more arrested in S phase as compared to XPA−/− cells complemented with wild type XPA. Notably, XPA colocalizes with PCNA in replication foci and is loaded on newly synthesized DNA in undamaged cells. In addition, the TFIIH subunit XPD, as well as XPF are loaded on DNA together with XPA, and XPC and XPG colocalize with PCNA in replication foci. Altogether, our results suggest a presence of the NER complex in the vicinity of the replisome and a novel role of NER in post-replicative repair.
The impact of protein characterization in structural proteomics

Protein characterization plays a role in two key aspects of structural proteomics. The first is the quality assessment of the produced protein preparations. Obtaining well diffracting crystals is one of the major bottlenecks in the structure‐determination pipeline. Often, this is caused by the poor quality of the protein preparation used for crystallization trials. Hence, it is essential to perform an extensive quality assessment of the protein preparations prior to crystallization and to use the results in the evaluation of the process. Here, a protein‐production and crystallization strategy is proposed with threshold values for protein purity (95%) and monodispersity (85%) below which a further optimization of the protein‐production process is strongly recommended. The second aspect is the determination of protein characteristics such as domains, oligomeric state, post‐translational modifications and protein–protein and protein–ligand interactions. In this paper, applications and new developments of protein‐characterization methods using MS, fluorescence spectroscopy, static light scattering, analytical ultracentrifugation and small‐angle X‐ray scattering within the EC Structural Proteomics in Europe contract are described. Examples of the application of the various methods are given.
Using conditional mutation to increase the efficiency of mutation analysis

Assessing testing strategies and test sets is a crucial part of software testing. Mutation analysis is, among other approaches, a suitable technique for this purpose. However, compared with other methods it is rather time-consuming and applying mutation analysis to large software systems is still problematic. This paper presents a versatile approach, called conditional mutation, which increases the efficiency of mutation analysis. This new method significantly reduces the time overhead for generating and executing the mutants. Results are reported for eight investigated programs up to 373,000 lines of code and 406,000 generated mutants. Furthermore, conditional mutation has been integrated into the Java 6 Standard Edition compiler. Thus, it is widely applicable and not limited to a certain testing tool or framework.
De Novo Synthesis of VP16 Coordinates the Exit from HSV Latency In Vivo

The mechanism controlling the exit from herpes simplex virus latency (HSV) is of central importance to recurrent disease and transmission of infection, yet interactions between host and viral functions that govern this process remain unclear. The cascade of HSV gene transcription is initiated by the multifunctional virion protein VP16, which is expressed late in the viral replication cycle. Currently, it is widely accepted that VP16 transactivating function is not involved in the exit from latency. Utilizing the mouse ocular model of HSV pathogenesis together with genetically engineered viral mutants and assays to quantify latency and the exit from latency at the single neuron level, we show that in vivo (i) the VP16 promoter confers distinct regulation critical for viral replication in the trigeminal ganglion (TG) during the acute phase of infection and (ii) the transactivation function of VP16 (VP16TF) is uniquely required for the exit from latency. TG neurons latently infected with the VP16TF mutant in1814 do not express detectable viral proteins following stress, whereas viruses with mutations in the other major viral transcription regulators ICP0 and ICP4 do exit the latent state. Analysis of a VP16 promoter/reporter mutant in the background of in1814 demonstrates that the VP16 promoter is activated in latently infected neurons following stress in the absence of other viral proteins. These findings support the novel hypothesis that de novo expression of VP16 regulates entry into the lytic program in neurons at all phases of the viral life cycle. HSV reactivation from latency conforms to a model in which stochastic derepression of the VP16 promoter and expression of VP16 initiates entry into the lytic cycle.
Alzheimer's disease-like pathological features in transgenic mice expressing the APP intracellular domain

The hypothesis that amyloid-β (Aβ) peptides are the primary cause of Alzheimer's disease (AD) remains the best supported theory of AD pathogenesis. Yet, many observations are inconsistent with the hypothesis. Aβ peptides are generated when amyloid precursor protein (APP) is cleaved by presenilins, a process that also produces APP intracellular domain (AICD). We previously generated AICD-overexpressing transgenic mice that showed abnormal activation of GSK-3β, a pathological feature of AD. We now report that these mice exhibit additional AD-like characteristics, including hyperphosphorylation and aggregation of tau, neurodegeneration and working memory deficits that are prevented by treatment with lithium, a GSK-3β inhibitor. Consistent with its potential role in AD pathogenesis, we find AICD levels to be elevated in brains from AD patients. The in vivo findings that AICD can contribute to AD pathology independently of Aβ have important therapeutic implications and may explain some observations that are discordant with the amyloid hypothesis.
Network Analysis of Navigation Paths of Tourists’ Trip Planning and Power Structure of the Online Tourism in China

In order to investigate the power structure of the online tourism domain in China, this study adopted a lab experiment and a network analysis method to examine the navigational paths of vacation planning behavior of Chinese college students. The analyses included the websites involved in the information search, network statistics of navigational paths, and clickthrough patterns between different types of websites. The navigational path network is a small-world network with shorter average path lengths and shorter network diameter than a web hyperlink network. The tourists generally followed a path of starting web page, general search engines, Online Travel Agencies (OTAs), and finally a specific business website. The clickthrough pattern indicated that search engines and OTAs were major intermediaries and thus exerted a higher power in the online tourism domain in China.
Bedside Sensor Platform Architecture for UbiSAS in Ubiquitous Sensor Network

Many new services have emerged to realize ubiquitous computing environments, owing to the increasing supply of sensor networks. In this paper, we propose bedside sensor platform of UbiSAS (ubiquitous sleep aid service) in 4-layered architecture in the subset of ubiquitous computing for refreshing human sleep. The 4-layered architecture consists of a bedside sensor platform, a context-aware framework, an intelligent agent and service interaction. We define each layered framework and its function. And we examine technical feasibility. Humans can recover their health through a refreshing sleep from fatigue. So we propose more effective and most suitable bedside sensor platform methodology for refreshing sleep in this paper
Risk-adapted Therapy of Pediatric Hodgkin Lymphoma in Upper Egypt

Hodgkin's lymphoma (HL) is a highly curable malignant disease. Contemporary treatment for children and adolescents with Hodgkin’s disease often uses a combined-modality approach with multi-agent chemotherapy and involved-field radiotherapy. This approach has yielded excellent results, with long-term disease-free survival ranged from 85% to 100% in patients with early-stage disease and of more than 60% in those with more advanced disease [1]. Because cure is likely for the majority of children presenting with HL, attention to long-term treatment complications has become increasingly important. Risk-adapted therapy for children with HL is directed toward high survival, minimal toxicity and optimal quality of life. This approach assigns intensity of therapy according to the risk criteria at presentation, with the parameters most frequently used to assign risk are the presence of "B" symptoms, bulk of presenting mass, mediastinal lymphadenopathy, extra nodal extension, number of involved nodal regions and Ann Arbor stage [2]. The objectives of this study are to assess the outcome of the HL patients treated with risk-adapted therapy approach at pediatric oncology department in South Egypt Cancer Institute (SECI) and to assess the prognostic factors of survival in pediatric HL patients.
On querying historical evolving graph sequences

In many applications, information is best represented as graphs. In a dynamic world, information changes and so the graphs representing the information evolve with time. We propose that historical graph-structured data be maintained for analytical processing. We call a historical evolving graph sequence an EGS. We observe that in many applications, graphs of an EGS are large and numerous, and they often exhibit much redundancy among them. We study the problem of efficient query processing on an EGS and put forward a solution framework called FVF. Through extensive experiments on both real and synthetic datasets, we show that our FVF framework is highly efficient in EGS query processing.
Localisation and characterization of acid mucopolysaccharides in the early chick blastoderm.

Acid mucopolysaccharides in the extracellular compartment of early chick blastoderms (16 h of incubation) were labelled with tritiated glucosamine and/or [35S]sulphate. The incorporation pattern was studied autoradiographically. Treatment with testicular hyaluronidase revealed a testicular hyaluronidase-sensitive fraction, mainly at the periphery of Middle Layer and Deep Layer cells, and a testicular hyaluronidase-resistant fraction, mainly at the ventral side of the Upper Layer. A biochemical analysis, utilizing chondroitinase ABC and nitrous acid, followed by cellulose acetate electrophoresis, demonstrated the synthesis of a non-sulphated fraction, i.e. hyaluronic acid and/or chondroitin, and a sulphated fraction, comprising two undersulphated components, i.e. chondroitin sulphate, and heparan sulphate or heparin. The appearance of different AMPS in specific areas of the early chick blastoderm is regarded as an early specialization of the extracellular compartment.
Texture analysis using dual tree M-band and Rényi entropy. Application to osteoporosis diagnosis on bone radiographs

In this paper, we propose a new method based on texture analysis for trabecular bone disease diagnosis. For this purpose, we present a working model based on a preprocessing step followed by a projection on a 1D oriented axis at a defined angle. First, the dual-tree transform M-band is applied on the 1D obtained signal. Then, the Rényi based information measure is computed on sub-bands coefficients in order to characterize the anisotropy which is strongly present in our application related to bone radiograph characterization. Finally, the Wilcoxon test is used on the Rényi entropies obtained for each subband and the K nearest neighborhoods classifier is used with the Rényi divergence as a distance. Applied on two different populations composed of osteoporotic (OP) patients and control (CT) subjects, a classification rate of 98% is achieved which provides a good discrimination between OP patients and CT subjects.
GPU-based segmentation of dental X-ray images using active contours without edges

Image data is of immense practical importance in medical informatics. In teeth-related radiograph research, the information of teeth shape is the most critical factor for achieving highly automated diagnosis. Automated image segmentation, which aims at automated extraction of region boundary features, plays a fundamental role in understanding image content for searching and mining in medical image. Therefore, accurate segmentation is an essential but difficult task due to low contrast between regions of interest and uneven exposure of the dental X-ray image. To address this problem, several segmentation approaches have been proposed in the literature, with many of them providing rather promising results. In this paper, we will look at a model by Chan-Vese that detects objects not defined by gradient. We will then implement this algorithm on the GPU and see what kind of speedup we can get compared to serial CPU implementations. Finally we will quantity our results as well as make a qualitative evaluation of the method with respect to how it performs for segmenting medical images.
XELOX vs. FOLFOX in metastatic colorectal cancer: An updated meta-analysis

ABSTRACT This meta-analysis aims to evaluate chemotherapy with XELOX (capecitabine plus oxaliplatin) versus FOLFOX (fluorouracil plus oxaliplatin) as a treatment for metastatic colorectal cancer (mCRC) in terms of efficacy and safety. Only randomized controlled trials (RCTs) comparing XELOX versus FOLFOX were included. A total of 4,363 patients from eight RCTs were available for analysis. Pooled analysis revealed that there were no statistical differences between both arms in OS, and ORR. XELOX arm had a higher incidence of thrombocytopenia, hand-foot syndrome, and diarrhea, whereas neutropenia had a higher incidence in the FOLFOX group. For mCRC, the effect of XELOX is similar to FOLFOX.
Learning approach to optical tomography

Optical tomography has been widely investigated for biomedical imaging applications. In recent years optical tomography has been combined with digital holography and has been employed to produce high-quality images of phase objects such as cells. In this paper we describe a method for imaging 3D phase objects in a tomographic configuration implemented by training an artificial neural network to reproduce the complex amplitude of the experimentally measured scattered light. The network is designed such that the voxel values of the refractive index of the 3D object are the variables that are adapted during the training process. We demonstrate the method experimentally by forming images of the 3D refractive index distribution of Hela cells.
Engineering planar separator algorithms

We consider classical linear-time planar separator algorithms, determining for a given planar graph a small subset of its nodes whose removal divides the graph into two components of similar size. These algorithms are based on planar separator theorems, which guarantee separators of size O(&sqrt;n) and remaining components of size at most 2n/3 (where n denotes the number of nodes in the graph). In this article, we present a comprehensive experimental study of the classical algorithms applied to a large variety of graphs, where our main goal is to find separators that do not only satisfy upper bounds, but also possess other desirable characteristics with respect to separator size and component balance. We achieve this by investigating a number of specific alternatives for the concrete implementation and fine-tuning of certain parts of the classical algorithms. It is also shown that the choice of several parameters influences the separation quality considerably. Moreover, we propose as planar separators the usage of fundamental cycles, whose size is at most twice the diameter of the graph: For graphs of small diameter, the guaranteed bound is better than the O(&sqrt;n) bounds, and it turns out that this simple strategy almost always outperforms the other algorithms, even for graphs with large diameter.
Evaluating the Effects of White Matter Multiple Sclerosis Lesions on the Volume Estimation of 6 Brain Tissue Segmentation Methods

BACKGROUND AND PURPOSE: The accuracy of automatic tissue segmentation methods can be affected by the presence of hypointense white matter lesions during the tissue segmentation process. Our aim was to evaluate the impact of MS white matter lesions on the brain tissue measurements of 6 well-known segmentation techniques. These include straightforward techniques such as Artificial Neural Network and fuzzy C-means as well as more advanced techniques such as the Fuzzy And Noise Tolerant Adaptive Segmentation Method, fMRI of the Brain Automated Segmentation Tool, SPM5, and SPM8. MATERIALS AND METHODS: Thirty T1-weighted images from patients with MS from 3 different scanners were segmented twice, first including white matter lesions and then masking the lesions before segmentation and relabeling as WM afterward. The differences in total tissue volume and tissue volume outside the lesion regions were computed between the images by using the 2 methodologies. RESULTS: Total gray matter volume was overestimated by all methods when lesion volume increased. The tissue volume outside the lesion regions was also affected by white matter lesions with differences up to 20 cm3 on images with a high lesion load (≈50 cm3). SPM8 and Fuzzy And Noise Tolerant Adaptive Segmentation Method were the methods less influenced by white matter lesions, whereas the effect of white matter lesions was more prominent on fuzzy C-means and the fMRI of the Brain Automated Segmentation Tool. CONCLUSIONS: Although lesions were removed after segmentation to avoid their impact on tissue segmentation, the methods still overestimated GM tissue in most cases. This finding is especially relevant because on images with high lesion load, this bias will most likely distort actual tissue atrophy measurements.
Decentralized control of large scale switched Takagi-Sugeno systems

This paper deals with decentralized stabilization of large scale switched nonlinear systems under arbitrary switching laws. A global large scale switched system can be split into a set of smaller interconnected switched Takagi Sugeno fuzzy subsystems. Then, in order to stabilize the overall closed-loop system, a set of switched non-PDC controllers is employed. The latter is designed based on Linear Matrix Inequalities (LMI) conditions obtained from a multiple switched non quadratic like-Lyapunov candidate function. A numerical example is proposed to illustrate the effectiveness of the suggested decentralized switched controller design approach.