Miracle-dz/UniFAR-FTUs huggingface dataset:
Semantic tagging of unknown proper nouns

In this paper, we describe a context-based method to semantically tag unknown proper nouns (U-PNs) in corpora. Like many others, our system relies on a gazetteer and a set of context-dependent heuristics to classify proper nouns. However, proper nouns are an open-end class: when parsing new fragments of a corpus, even in the same language domain, we can expect that several proper nouns cannot be semantically tagged. The algorithm that we propose assigns to an unknown PN an entity type based on the analysis of syntactically and semantically similar contexts already seen in the application corpus. The performance of the algorithm is evaluated not only in terms of precision, following the tradition of MUC conferences, but also in terms of information gain, an information theoretic measure that takes into account the complexity of the classification task.
Sol–gel fabrication of a non-laminated graphene oxide membrane for oil/water separation

A non-laminated graphene oxide membrane crosslinked by polyethyleneimine was prepared via a one-step sol–gel process. In the as-prepared membrane, the GO nanosheets remain disordered as in the sol state to form a randomly arranged GO self-assembled structure, which results in a much higher flux compared with the general laminated GO membrane prepared via vacuum filtration or spin coating because of the lower flow resistance. Furthermore, this random self-assembly of GO nanosheets gives rise to a hierarchical micro/nanoscale rough structure on the membrane surface. Along with the crosslinking reaction, PEI was grafted onto the GO nanosheets to make them hydrophilic. Combining the hydrophilic surface chemistry with the micro/nanoscale hierarchical surface structure, the non-laminated GO membrane exhibited the desired superhydrophilic and underwater superoleophobic properties. We have tested the membrane to separate a series of surfactant-free and surfactant-stabilized oil-in-water emulsions. A high separation efficiency (>99%) and flux were achieved using only gravity without any extra power, much larger than commercial filtration membranes with similar permeation properties. Moreover, the membrane shows an outstanding antifouling performance for oil droplets and can be recycled easily for long-term use.
Finite-Geometry Low-Density Parity-Check Codes for Channels with Stuck-at Defects

We investigate the use of finite-geometry low-density parity-check (FG-LDPC) codes for channels with stuckat defects. Such a channel is corrupted by a stuck-at defect pattern in addition to the usual channel-induced noise. When the defect pattern is known to the encoder but not to the decoder, the capacity of the channel is the same as if the defect pattern were also revealed to the decoder. Capacity-achieving codes for such channels require a good quantization code embedded inside a good errorcorrecting code. The main idea of this paper is that such an embedding may be realized by taking advantage of the cyclic or quasi-cyclic structure of FG-LDPC codes, which allows a quantization codes with low trellis complexity to be constructed. Combining this with the good errorcorrecting capability of low-density parity-check codes, we demonstrate that FG-LDPC codes offers good performance on channels with stuck-at defects.
Multi-target visual tracking with aerial robots

We study the problem of tracking mobile targets using a team of aerial robots. Each robot carries a camera to detect targets moving on the ground. The overall goal is to plan for the trajectories of the robots in order to track the most number of targets, and accurately estimate the target locations using the images. The two objectives can conflict since a robot may fly to a higher altitude and potentially cover a larger number of targets at the expense of accuracy. We start by showing that k ≥ 3 robots may not be able to track all n targets while maintaining a constant factor approximation of the optimal quality of tracking at all times. Next, we study the problem of choosing robot trajectories to maximize either the number of targets tracked or the quality of tracking. We formulate this problem as the weighted version of a combinatorial optimization problem known as the Maximum Group Coverage (MGC) problem. A greedy algorithm yields a 1/2 approximation for the weighted MGC problem. Finally, we evaluate the algorithm and the sensing model through simulations and preliminary experiments.
An Adaptive Learning Rate for RBFNN Using Time-Domain Feedback Analysis

Radial basis function neural networks are used in a variety of applications such as pattern recognition, nonlinear identification, control and time series prediction. In this paper, the learning algorithm of radial basis function neural networks is analyzed in a feedback structure. The robustness of the learning algorithm is discussed in the presence of uncertainties that might be due to noisy perturbations at the input or to modeling mismatch. An intelligent adaptation rule is developed for the learning rate of RBFNN which gives faster convergence via an estimate of error energy while giving guarantee to the l 2 stability governed by the upper bounding via small gain theorem. Simulation results are presented to support our theoretical development.
High Mobility Group Box 1 Is Upregulated After Spinal Cord Injury and Is Associated With Neuronal Cell Apoptosis

Study Design. Cerebrocortical culture and rat spinal cord injury (SCI) model were used to examine the expression of high mobility group box 1 (HMGB1), TNF-&agr;, and Rage by reverse transcription polymerase chain reaction (RT-PCR) and immunohistochemical examination. In addition, relationship between upregulation of HMGB1 and neural cells apoptosis was evaluated after SCI. Objective. To evaluate the upregulation of HMGB1, TNF-&agr;, and Rage after SCI. Summary of Background Data. It is known that the mode of delayed neuronal cell death after SCI is apoptosis. Apoptotic cell death is influenced by several injury-promoting factors which include pro-inflammatory cytokines. Inhibition of apoptosis promotes neurologic improvement following SCI. However, the factors which transmit inflammatory signaling following SCI have not yet been clarified in detail. HMGB1 was reported as an important mediator of inflammation. We examined the expression of HMGB1, TNF-&agr; and Rage following acute SCI. Methods. Expression of HMGB1, TNF-&agr; and Rage was examined by RT-PCR and immunohistochemical examination. Apoptotic cell death was evaluated by TUNEL methods. Results. HMGB1 was exported from nuclei to cytoplasm in active caspase-3 positive apoptotic cell in vitro. In addition, HMGB1, TNF-&agr;, and Rage was expressed in same cell after NMDA treatment. RT-PCR revealed that expression of HMGB1 and TNF-&agr; was upregulated following SCI. Immunohistochemical examination revealed that the numbers of HMGB1-, TNF-&agr;-, and Rage-positive cells were increased following SCI. The number of TUNEL-positive cells was significantly increased at 12 hours after injury, and was maximal at 72 hours after injury. However, HMGB1- and TNF-&agr;-positive cells were maximal in number 48 hours after injury, while Rage-positive cells were maximal in number at 24 hours after injury. These data suggest that HMGB1, TNF-&agr;, and Rage were upregulated following SCI but preceding the apoptotic cell death. Conclusion. Our findings suggest that HMGB1 play a role in the induction of apoptosis via inflammatory reaction.
Application of High Pressure Torsion to Bulk Samples

High pressure torsion (HPT) is a well-known procedure to impart severe plastic deformation (SPD) into metallic materials. It was reported that HPT produces grain sizes finer than those using other SPD processes such as equal-channel angular pressing (ECAP). However, the application of HPT has been restricted to thin disk samples. In this study, an HPT process was developed for use with bulk samples. This process is designated as Bulk-HPT for comparison with conventional Disk-HPT. Cylindrical samples of an Al-3%Mg-0.2%Sc alloy having dimensions of 10 mm in diameter and 8.6 mm in height were prepared for Bulk-HPT. The samples were strained under a pressure of 1 GPa for 2 turns at room temperature. Microstructural observations revealed that the samples contained regions having a grain size of ~130 nm. Tensile testing showed a superplastic ductility ~480 % at 673 K with an initial strain rate of 3.3x10-2 s-1.
Rule-Based Situation Inference for Connected Vehicles

This paper describes a method for inferring dynamic situations based on rules applied to carprobes and dynamic events that are sent from connected vehicles in real-time. Rules are categorized into four patterns depending on the input and output of cloud services we provide. The proposed service enables users to configure how to convert the collected data into useful information as a kind of collective intelligence.
Simultaneous Detection and Identification of Common Cell Culture Contaminant and Pathogenic Mollicutes Strains by Reverse Line Blot Hybridization

ABSTRACT We have developed a reverse line blot (RLB) hybridization assay to detect and identify the commonest mollicutes causing cell line contamination (Mycoplasma arginini, Mycoplasma fermentans, Mycoplasma hyorhinis, Mycoplasma orale, and Acholeplasma laidlawii) and human infection (Mycoplasma pneumoniae, Mycoplasma hominis, Mycoplasma genitalium, Ureaplasma parvum, and Ureaplasma urealyticum). We developed a nested PCR assay with “universal” primers targeting the mollicute 16S-23S rRNA intergenic spacer region. Amplified biotin-labeled PCR products were hybridized to membrane-bound species-specific oligonucleotide probes. The assay correctly identified reference strains of 10 mollicute species. Cell cultures submitted for detection of mollicute contamination, clinical specimens, and clinical isolates were initially tested by PCR assay targeting a presumed mollicute-specific sequence of the 16S rRNA gene. Any that were positive were assessed by the RLB assay, with species-specific PCR assay as the reference method. Initially, 100 clinical and 88 of 92 cell culture specimens gave concordant results, including 18 in which two or more mollicute species were detected by both methods. PCR and sequencing of the 16S-23S rRNA intergenic spacer region and subsequent retesting by species-specific PCR assay of the four cell culture specimens for which results were initially discrepant confirmed the original RLB results. Sequencing of amplicons from 12 cell culture specimens that were positive in the 16S rRNA PCR assay but negative by both the RLB and species-specific PCR assays failed to identify any mollicute species. The RLB hybridization assay is sensitive and specific and able to rapidly detect and identify mollicute species from clinical and cell line specimens.
Statistical heterogeneity in systematic reviews of clinical trials: a critical appraisal of guidelines and practice

Objective: Heterogeneity between study results can be a problem in any systematic review or meta-analysis of clinical trials. Identifying its presence, investigating its cause and correctly accounting for it in analyses all involve difficult decisions for the researcher. Our objectives were: to collate recommendations on the subject of dealing with heterogeneity in systematic reviews of clinical trials; to investigate current practice in addressing heterogeneity in Cochrane reviews; and to compare current practice with recommendations. Methods: We review guidelines for those undertaking systematic reviews and examine how heterogeneity is addressed in practice in a sample of systematic reviews, and their protocols, from the Cochrane Database of Systematic Reviews. Results: Advice to reviewers is on the whole consistent and sensible. However, examination of a sample of Cochrane protocols and reviews demonstrates that the advice is difficult to follow given the small numbers of studies identified in many systematic reviews, the difficulty of pre-specifying important effect modifiers for subgroup analysis or meta-regression and the unresolved debate concerning fixed versus random effects metaanalyses. There was disagreement between protocols and reviews, often either regarding choice of important potential effect modifiers or due to the review identifying too few studies to perform planned analyses. Conclusion: Guidelines that address practical issues are required to reduce the risk of spurious findings from investigations of heterogeneity. This may involve discouraging statistical investigations such as subgroup analyses and meta-regression, rather than simply adopting a cautious approach to their interpretation, unless a large number of studies is available. The notion of a priori specification of potential effect modifiers for a retrospective review of studies is ill-defined, and the appropriateness of using a statistical test for heterogeneity to decide between analysis strategies is suspect.
Requirement analysis, Architectural design and Formal verification of a multi-agent based University Information Management System

This paper presents an approach based on the analysis, design, and formal verification of a multi-agent based university Information Management System (IMS). University IMS accesses information, creates reports and facilitates teachers as well as students. An orchestrator agent manages the coordination between all agents. It also manages the database connectivity for the whole system. The proposed IMS is based on BDI agent architecture, which models the system based on belief, desire, and intentions. The correctness properties of safety and liveness are specified by First-order predicate logic.
Correction: A Transposable Element within the Non-canonical Telomerase RNA of Arabidopsis thaliana Modulates Telomerase in Response to DNA Damage

Long noncoding RNAs (lncRNAs) have emerged as critical factors in many biological processes, but little is known about how their regulatory functions evolved. One of the best-studied lncRNAs is TER, the essential RNA template for telomerase reverse transcriptase. We previously showed that Arabidopsis thaliana harbors three TER isoforms: TER1, TER2 and TER2S. TER1 serves as a canonical telomere template, while TER2 is a novel negative regulator of telomerase activity, induced in response to double-strand breaks (DSBs). TER2 contains a 529 nt intervening sequence that is removed along with 36 nt at the RNA 3’ terminus to generate TER2S, an RNA of unknown function. Here we investigate how A. thaliana TER2 acquired its regulatory function. Using data from the 1,001 Arabidopsis genomes project, we report that the intervening sequence within TER2 is derived from a transposable element termed DSB responsive element (DRE). DRE is found in the TER2 loci of most but not all A. thaliana accessions. By analyzing accessions with (TER2) and without DRE (TER2Δ) we demonstrate that this element is responsible for many of the unique properties of TER2, including its enhanced binding to TERT and telomerase inhibitory function. We show that DRE destabilizes TER2, and further that TER2 induction by DNA damage reflects increased RNA stability and not increased transcription. DRE-mediated changes in TER2 stability thus provide a rapid and sensitive switch to fine-tune telomerase enzyme activity. Altogether, our data shows that invasion of the TER2 locus by a small transposon converted this lncRNA into a DNA damage sensor that modulates telomerase enzyme activity in response to genome assault.
ITRS lithography roadmap: status and challenges

Abstract Recent ITRS lithography roadmaps show a big technology decision approaching the semiconductor industry about how to do leading edge lithography. The need is rapidly approaching for the industry to select an option for the 22-nm half pitch, but no decision has been made yet. The main options for the 22-nm half pitch are extreme ultraviolet (EUV), ArF immersion lithography with multiple patterning, and maskless lithography. For the 16-nm half pitch, directed self-assembly (DSA) is also an option. The EUV has the most industry investment and is the closest to current lithography in the way it works but still faces challenges in tool productivity and defect-free masks. The nanoimprint needs to overcome the defect, contamination, and overlay challenges before it can be applied to the semiconductor production. Maskless lithography may be used first for prototyping and small volume products where mask costs per chip produced would be very high. Double patterning could be extended to multiple pattering, but would give tremendous process complexity and exponentially rising mask costs due to the many exposures needed per level. The DSA, which only recently has emerged from the research stage, has the potential for very high resolution but represents a huge change in how critical dimensions are formed and controlled.
Reference Price Distributions and Stock Returns: An Analysis Based on the Disposition Effect

This paper provides evidence that reference price distributions can predict stocks’ expected returns. We develop a model based on the disposition effect by considering shareholders’ trading activities with different relative capital gains. The model suggests that both disposition-prone investors’ incentives to sell shares and their paper capital gains impact stock performance over a subsequent period. By applying four proxy variables this paper finds that a stock with higher mean and skewness of relative capital gains holds a higher return in the cross-section of the Chinese stocks. The empirical evidence supports our model’s implications. In addition, the average capital gain is the key explanatory variable for variations in returns for winner stocks, and the skewness of capital gains works as the key variable for loser stocks in the Chinese stock markets. These findings hold true when the factors identified in the related literature are taken into consideration.
Achievable throughput of multiple access spectrum systems based on cognitive relay

Cognitive relays form a special cooperation relationship among users in cognitive radio networks, and help increase the transmission rates of both primary users and secondary users. However, we observe that in certain scenarios, the use of relays may deteriorate the performance. In this paper, we propose a novel scheme in the MAC layer, called CodeAssist, by using network coding. It renders every relayed packet useful and recoverable as long as a sufficient number of coded packets are received by the intended terminal. CodeAssist is designed to apply network coding in every relay buffer, and moreover, leads to a lower bound of relayed packets for each secondary user. We also show numerical results for further demonstrations of the improved performance with CodeAssist.
Zero-Shot Learning via Revealing Data Distribution

This paper presents a method of zero-shot learning (ZSL) which poses ZSL as the missing data problem, rather than the missing label problem. While most popular methods in ZSL focus on learning the mapping function from the image feature space to the label embedding space, the proposed method explores a simple yet effective transductive framework in the reverse mapping. Our method estimates data distribution of unseen classes in the image feature space by transferring knowledge from the label embedding space. It assumes that data of each seen and unseen class follow Gaussian distribution in the image feature space and utilizes Gaussian mixture model to model data. The signature is introduced to describe the data distribution of each class. In experiments, our method obtains 87.38% and 61.08% mean accuracies on the Animals with Attributes (AwA) and the Caltech-UCSD Birds-200-2011 (CUB) datasets respectively, which outperforms the runner-up methods significantly by 4.95% and 6.38%. In addition, we also investigate the extension of our method to open-set classification.
An Approach of Content-Based Image Retrieval Based on Image Salient Region

The traditional CBIR (Content based image retrieval) global descriptor can't extract local features effectively, while the SIFT (Scale Invariant Feature Transform) algorithm only focus on local object features matching, and can not satisfy the need of fuzzy CBIR queries based on visual feeling. In view of this contradiction, an approach is proposed based on image salient region, in which the SIFT algorithm and the traditional CBIR color descriptors are combined, the entropy of salient point is used to distinguish the salient and non-salient regions of image. We use centroid weighted histogram and dominant color descriptor of MPEG-7 to describe the salient and non-salient region respectively, which not only effectively extract the local features of image objects, but also overcome the SIFT algorithm for high dimension, and vulnerable to interference with the global features. Experiments show that for general image retrieval application, the proposed method has better retrieval performance, with better robustness for geometric and perspective transform.
Achieving desired thickness gradients on flat and curved substrates

A mathematical model has been developed for the calculation of the film thickness distribution on flat, spinning, and curved substrates deposited by the magnetron sputtering technique. With the use of the model it is possible to design shield or mask shapes to intercept material between source and substrate to achieve a particular gradient in film thickness. Such considerations have significant relevance in the deposition of multi-layer thin films for x- ray and neutron optics in which the allowable deviation in the measured thickness gradient from the desired is a few tenths of a percent. Examples of the procedure used to obtain uniform coatings on flat and curved substrates has been given. Further, the consequences of target wear on the film thickness distribution has been considered. Finally, the consequence of spinning the substrate through the deposition region to improve uniformity has also been considered. Good agreement between initial experimental result sand the theoretical calculations has been shown.
An ontological approach to evidence-based medicine and meta-analysis

The "evidence-based medicine" (EBM) paradigm is centered on the concept of "best evidence" and clinical studies based on this approach are more likely to be considered by physicians in their practice. In this paper we describe an ontology representing the concepts involved in evidence-based medicine and meta-analysis and show how an ontological approach can be applied both for revisiting EBM conceptual foundations and for allowing a more effective knowledge-based information retrieval in literature.
Maple: scalable multi-dimensional range search over encrypted cloud data with tree-based index

Cloud computing promises users massive scale outsourced data storage services with much lower costs than traditional methods. However, privacy concerns compel sensitive data to be stored on the cloud server in an encrypted form. This posts a great challenge for effectively utilizing cloud data, such as executing common SQL queries. A variety of searchable encryption techniques have been proposed to solve this issue; yet efficiency and scalability are still the two main obstacles for their adoptions in real-world datasets, which are multi-dimensional in general. In this paper, we propose a tree-based public-key Multi-Dimensional Range Searchable Encryption (MDRSE) to overcome the above limitations. Specifically, we first formally define the leakage function and security of a tree-based MDRSE. Then, by leveraging an existing predicate encryption in a novel way, our tree-based MDRSE efficiently indexes and searches over encrypted cloud data with multi-dimensional tree structures (i.e., R-trees). Moreover, our scheme is able to protect single-dimensional privacy while previous efficient solutions fail to achieve. Our scheme is selectively secure, and through extensive experimental evaluation on a large-scale real-world dataset, we show the efficiency and scalability of our scheme.