Miracle-dz/UniFAR-FTUs huggingface dataset:
Modified Overlap-Add and Overlap-Save Convolution Algorithms for Real Signals

Modified overlap-save and overlap-add algorithms for filtering a real signal by an N-tap finite impulse response filter are delineated. These algorithms compute two N-sample output blocks simultaneously at every processing step using 2N-point transforms, while the traditional methods compute only one N-sample block with the same length transforms. They achieve streamline processing for real signals but incur an additional delay of N samples
The use of drugs in patients who have undergone bariatric surgery

According to the World Health Organization, obesity has become an epidemic in the 21st century affecting around 300 million people of all ages worldwide. Clinical treatment modalities for this disease are limited and ineffective when it comes to morbidly obese patients (body mass index – the weight in kilograms divided by height in meters squared – surpasses 40 kg/m2). Therefore, the alternative, surgical treatment, is the best option for these patients, namely gastric restrictive procedures or an intestinal bypass culminating in a malabsorptive syndrome. In the past 20 years, there has been a 70% increase in the number of bariatric procedures all over the world. The main pharmacokinetic consequence observed in the postoperative period of these individuals is a higher or lower absorption of orally administered drugs.
Ultrahydrous stishovite from high-pressure hydrothermal treatment of SiO2

Stishovite (SiO2 with the rutile structure and octahedrally coordinated silicon) is an important high-pressure mineral. It has previously been considered to be essentially anhydrous. In this study, hydrothermal treatment of silica glass and coesite at 350–550 °C near 10 GPa produces stishovite with significant amounts of H2O in its structure. A combination of methodologies (X-ray diffraction, thermal analysis, oxide melt solution calorimetry, secondary ion mass spectrometry, infrared and nuclear magnetic resonance spectroscopy) indicate the presence of 1.3 ± 0.2 wt % H2O and NMR suggests that the primary mechanism for the H2O uptake is a direct hydrogarnet-like substitution of 4H+ for Si4+, with the protons clustered as hydroxyls around a silicon vacancy. This substitution is accompanied by a substantial volume decrease for the system (SiO2 + H2O), although the stishovite expands slightly, and it is only slightly unfavorable in energy. Stishovite could thus be a host for H2O at convergent plate boundaries, and in other relatively cool high-pressure environments.
Suboptimum multiuser receivers for convolutionally coded asynchronous DS-CDMA systems

Motivated by the high complexity of the optimal sequence estimator for convolutionally coded asynchronous code-division multiple-access (CDMA) systems, developed by Giallorenzi and Wilson (see ibid., vol.44, no.8, p.997, 1996), and the potentially poor performance of the conventional receiver due to multiuser interference and the near-far problem, we examine relatively simple multiuser receivers which perform nearly as well as the optimal receiver. The multiuser receivers discussed are of two types. The first set of approaches are partitioned approaches that treat the multiuser interference equalization problem and the decoding problem separately. The second set of approaches are integrated approaches that perform both the equalization and decoding operations together. We study linear, decision feedback, and trellis/tree-based approaches in each category. The asymptotic efficiency of this receiver relative to an uncoded coherent binary phase shift keying (BPSK) receiver (termed asymptotic multiuser coding gain, or AMCG) is used as a performance criterion throughout. Also, computer simulations are used whenever the computation of the AMCG is not feasible. It is shown that a number of the approaches which are introduced achieve a high performance level with a moderate complexity.
Header Space Analysis: Static Checking for Networks

Today's networks typically carry or deploy dozens of protocols and mechanisms simultaneously such as MPLS, NAT, ACLs and route redistribution. Even when individual protocols function correctly, failures can arise from the complex interactions of their aggregate, requiring network administrators to be masters of detail. Our goal is to automatically find an important class of failures, regardless of the protocols running, for both operational and experimental networks. To this end we developed a general and protocol-agnostic framework, called Header Space Analysis (HSA). Our formalism allows us to statically check network specifications and configurations to identify an important class of failures such as Reachability Failures, Forwarding Loops and Traffic Isolation and Leakage problems. In HSA, protocol header fields are not first class entities; instead we look at the entire packet header as a concatenation of bits without any associated meaning. Each packet is a point in the {0,1}L space where L is the maximum length of a packet header, and networking boxes transform packets from one point in the space to another point or set of points (multicast). We created a library of tools, called Hassel, to implement our framework, and used it to analyze a variety of networks and protocols. Hassel was used to analyze the Stanford University backbone network, and found all the forwarding loops in less than 10 minutes, and verified reachability constraints between two subnets in 13 seconds. It also found a large and complex loop in an experimental loose source routing protocol in 4 minutes.
Metabolism of [D10]Phenanthrene to Tetraols in Smokers for Potential Lung Cancer Susceptibility Assessment: Comparison of Oral and Inhalation Routes of Administration

Polycyclic aromatic hydrocarbons (PAHs) are believed to be among the causative agents for lung cancer in smokers. PAHs require metabolic activation for carcinogenicity. One pathway produces diol epoxides that react with DNA, causing mutations. Because diol epoxides are converted to tetraols, quantitation of tetraols can potentially be used to identify smokers who may be at higher risk for lung cancer. Our approach uses [D10]phenanthrene, a labeled version of phenanthrene, a noncarcinogenic PAH structurally analogous to carcinogenic PAH. Although smokers are exposed to PAH by inhalation, oral dosing would be more practical for phenotyping studies. Therefore, we investigated [D10]phenanthrene metabolism in smokers after administration by inhalation in cigarette smoke or orally. Sixteen smokers received 10 μg of [D10]phenanthrene in a cigarette or orally. Plasma and urine samples were analyzed for [D10]r-1,t-2,3,c-4-tetrahydroxy-1,2,3,4-tetrahydrophenanthrene ([D10]PheT), the major end product of the diol epoxide pathway, by gas chromatography-negative ion chemical ionization-tandem mass spectrometry. The ratios of [D10]PheT (oral dosing/inhalation) in 15 smokers were 1.03 ± 0.32 and 1.02 ± 0.35, based on plasma area under the concentration-time curve (0-∞) and total 48-h urinary excretion, respectively. Overall, there was no significant difference in the extent of [D10]PheT formation after the two different routes of exposure in smokers. A large interindividual variation in [D10]PheT formation was observed. These results demonstrate that the level of [D10]PheT in urine after oral dosing of [D10]phenanthrene can be used to assess individual capacity of PAH metabolism by the diol epoxide pathway.
A strategy for optimizing and evaluating behavioral interventions

Background: Although the optimization of behavioral interventions offers the potential of both public health and research benefits, currently there is no widely agreed-upon principled procedure for accomplishing this.Purpose: This article suggests a multiphase optimization strategy (MOST) for achieving the dual goals of program optimization and program evaluation in the behavioral intervention field.Methods: MOST consists of the following three phases: (a) screening, in which randomized experimentation closely guided by theory is used to assess an array of program and/or delivery components and select the components that merit further investigation; (b) refining, in which interactions among the identified set of components and their interrelationships with covariates are investigated in detail, again via randomized experiments, and optimal dosage levels and combinations of components are identified; and (c) confirming, in which the resulting optimized intervention is evaluated by means of a standard randomized intervention trial. To make the best use of available resources, MOST relies on design and analysis tools that help maximize efficiency, such as fractional factorials.Results: A slightly modified version of an actual application of MOST to develop a smoking cessation intervention is used to develop and present the ideas.Conclusions: MOST has the potential to husband program development resources while increasing our understanding of the individual program and delivery components that make up interventions. Considerations, challenges, open questions, and other potential benefits are discussed.
LogBase: A Scalable Log-structured Database System in the Cloud

Numerous applications such as financial transactions (e.g., stock trading) are write-heavy in nature. The shift from reads to writes in web applications has also been accelerating in recent years. Write-ahead-logging is a common approach for providing recovery capability while improving performance in most storage systems. However, the separation of log and application data incurs write overheads observed in write-heavy environments and hence adversely affects the write throughput and recovery time in the system. In this paper, we introduce LogBase -- a scalable log-structured database system that adopts log-only storage for removing the write bottleneck and supporting fast system recovery. It is designed to be dynamically deployed on commodity clusters to take advantage of elastic scaling property of cloud environments. LogBase provides in-memory multiversion indexes for supporting efficient access to data maintained in the log. LogBase also supports transactions that bundle read and write operations spanning across multiple records. We implemented the proposed system and compared it with HBase and a disk-based log-structured record-oriented system modeled after RAMCloud. The experimental results show that LogBase is able to provide sustained write throughput, efficient data access out of the cache, and effective system recovery.
Integrating Source-Language Context into Log-Linear Models of Statistical Machine Translation

The translation features typically used in state-of-the-art statistical machine translation (SMT) model dependencies between the source and target phrases, but not among the phrases in the source language themselves. A swathe of research has demonstrated that integrating source context modelling directly into log-linear phrase-based SMT (PB-SMT) and hierarchical PB-SMT (HPB-SMT), and can positively influence the weighting and selection of target phrases, and thus improve translation quality. In this thesis we present novel approaches to incorporate source-language contextual modelling into the state-of-the-art SMT models in order to enhance the quality of lexical selection. We investigate the effectiveness of use of a range of contextual features, including lexical features of neighbouring words, part-of-speech tags, supertags, sentence-similarity features, dependency information, and semantic roles. We explored a series of language pairs featuring typologically different languages, and examined the scalability of our research to larger amounts of training data. While our results are mixed across feature selections, language pairs, and learning curves, we observe that including contextual features of the source sentence in general produces improvements. The most significant improvements involve the integration of long-distance contextual features, such as dependency relations in combination with part-of-speech tags in Dutch-to-English subtitle translation, the combination of dependency parse and semantic role information in English-to-Dutch parliamentary debate translation, supertag features in English-to-Chinese translation, or combination of supertag and lexical features in English-to-Dutch subtitle translation. Furthermore, we investigate the applicability of our lexical contextual model in another closely related NLP problem, namely machine transliteration.
An entity-driven recursive neural network model for chinese discourse coherence modeling

Chinese discourse coherence modeling remains a challenge taskin Natural Language Processing field.Existing approaches mostlyfocus on the need for feature engineering, whichadoptthe sophisticated features to capture the logic or syntactic or semantic relationships acrosssentences within a text.In this paper, we present an entity-drivenrecursive deep modelfor the Chinese discourse coherence evaluation based on current English discourse coherenceneural network model. Specifically, to overcome the shortage of identifying the entity(nouns) overlap across sentences in the currentmodel, Our combined modelsuccessfully investigatesthe entities information into the recursive neural network freamework.Evaluation results on both sentence ordering and machine translation coherence rating task show the effectiveness of the proposed model, which significantly outperforms the existing strong baseline.
Inference of transcriptional regulatory network by bootstrapping patterns

MOTIVATION Transcriptional regulatory networks, which consist of linkages between transcription factors (TF) and target genes (TGene), control the expression of a genome and play important roles in all aspects of an organism's life cycle. Accurate prediction of transcriptional regulatory networks is critical in providing useful information for biologists to determine what to do next. Currently, there is a substantial amount of fragmented gene regulation information described in the medical literature. However, current related text analysis methods designed to identify protein-protein interactions are not entirely suitable for finding transcriptional regulatory networks. RESULT In this article, we propose an automatic regulatory network inference method that uses bootstrapping of description patterns to predict the relationship between a TF and its TGenes. The proposed method differs from other regulatory network generators in that it makes use of both positive and negative patterns for different vector combinations in a sentence. Moreover, the positive pattern learning process can be fully automatic. Furthermore, patterns for active and passive voice sentences are learned separately. The experiments use 609 HIF-1 expert-tagged articles from PubMed as the gold standard. The results show that the proposed method can automatically generate a predicted regulatory network for a transcription factor. Our system achieves an F-measure of 72.60%. AVAILABILITY The software, training/test datasets and learned patterns are available at http://140.116. 99.138/∼hcw0901/PubMedSearch.php.
Principles and applications of ultrasound backscatter microscopy

The development of ultrasound backscatter microscopy (UBM) is described together with initial clinical and biological applications. UBM is essentially an extension of the powerful B-mode backscatter methods developed for clinical imaging in the 3-10-MHz frequency range. The development of new high sensitivity transducers in the 40-100-MHz range now permits visualization of tissue structures with resolution approaching 20 mu m and a maximum penetration of approximately 4 mm. The performance characteristics and trade-offs of these new polymer and ceramic devices are reviewed, and the implementation of high-frequency imaging systems is described. Initial clinical applications of UBM include ophthalmic, skin, and intravascular imaging. Examples of images and progress in these areas are presented. The biological application of UBM is illustrated by studies of drug uptake in living tumor spheroids. Significant increases in backscatter levels resulting from drugs targeting oxic and hypoxic cell populations are demonstrated. <<ETX>>
Ion-Sensitive Field-Effect Transistor for Biological Sensing

In recent years there has been great progress in applying FET-type biosensors for highly sensitive biological detection. Among them, the ISFET (ion-sensitive field-effect transistor) is one of the most intriguing approaches in electrical biosensing technology. Here, we review some of the main advances in this field over the past few years, explore its application prospects, and discuss the main issues, approaches, and challenges, with the aim of stimulating a broader interest in developing ISFET-based biosensors and extending their applications for reliable and sensitive analysis of various biomolecules such as DNA, proteins, enzymes, and cells.
A Non-Parametric Peak Calling Algorithm for DamID-Seq

Protein—DNA interactions play a significant role in gene regulation and expression. In order to identify transcription factor binding sites (TFBS) of double sex (DSX)—an important transcription factor in sex determination, we applied the DNA adenine methylation identification (DamID) technology to the fat body tissue of Drosophila, followed by deep sequencing (DamID-Seq). One feature of DamID-Seq data is that induced adenine methylation signals are not assured to be symmetrically distributed at TFBS, which renders the existing peak calling algorithms for ChIP-Seq, including SPP and MACS, inappropriate for DamID-Seq data. This challenged us to develop a new algorithm for peak calling. A challenge in peaking calling based on sequence data is estimating the averaged behavior of background signals. We applied a bootstrap resampling method to short sequence reads in the control (Dam only). After data quality check and mapping reads to a reference genome, the peaking calling procedure compromises the following steps: 1) reads resampling; 2) reads scaling (normalization) and computing signal-to-noise fold changes; 3) filtering; 4) Calling peaks based on a statistically significant threshold. This is a non-parametric method for peak calling (NPPC). We also used irreproducible discovery rate (IDR) analysis, as well as ChIP-Seq data to compare the peaks called by the NPPC. We identified approximately 6,000 peaks for DSX, which point to 1,225 genes related to the fat body tissue difference between female and male Drosophila. Statistical evidence from IDR analysis indicated that these peaks are reproducible across biological replicates. In addition, these peaks are comparable to those identified by use of ChIP-Seq on S2 cells, in terms of peak number, location, and peaks width.
Community long-term care services: what works and what doesn't?

To establish a context, long-term care (LTC) can be provided either through institutions or in the community; can include both formal (i.e., generally paid and often specialized) and informal (i.e., generally unpaid and often unspecialized) care; and that formal care can have either public or private funding. Within this context, a fundamental conceptual structure for addressing the topic of what works and what does not in formal community long-term care (CLTC) might be reduced to four components: • Who gets something? • What do they get? • Who pays ? • What impact does it have? Concerning who receives formal CLTC, we often have two subgroups. The first subgroup of formal CLTC users comprises those who are certified by their state officials as functionally eligible for institutional LTC. These users are often assumed to represent a type of substitution of home- and communitybased services for traditional nursing home care. This assumption of substitution persists, although for at least 25 years it has been documented that there are two or three older people with the same configuration of needs and disablements living in the community for every one person residing in a nursing home (Branch, 1976, 1977, 1980), and gerontological researchers have yet to understand clearly why the one person enters the nursing home and the other two or three do not. Those CLTC users who meet nursing home admission requirements may not represent substitution at all. The second subgroup of CLTC users comprises those whose frailty is substantial but not severe enough to qualify for state-funded nursing home care. The second subgroup is actually expanding the continuum of LTC clients.
Expression of A 2 B adenosine receptors in human lymphocytes : their role in T cell activation

Adenosine, acting outside the cell, exerts potent actions on a wide variety of physiological systems, including the nervous, cardiovascular, gastrointestinal, urogenital, respiratory, and lymphatic systems. Many of these actions are mediated via specific receptors named P 1 purinoceptors (Daly et al., 1983). From studies on the variation of adenylate cyclase activity produced by adenosine analogues, and on the rank order of potency of agonists, P 1 purinoceptors were subdivided into two classes: A1, which mediate decreases in cAMP levels, and A2, which mediate increases in cAMP levels (Van Calcker et al., 1979; Londos et al., 1980). The pharmacological characterization of the A 2 subtype in different tissues led to the finding of two different populations which were named A 2A and A2B, and had very different affinities for the agonist CGS21680. It is now becoming clear that the subtypes of adenosine receptors can be linked to a variety of signal transduction systems apart from adenylate cyclase (Stiles, 1992; Linden, 1994; Schubert et al., 1994; Fredholm, 1995). These receptor subtypes (A 1, A2A and A2B) as well as another member of the family, which was discovered more recently (A 3), have been cloned (Zhou et al., 1992; Linden et al., 1993; Salvatore et al., 1993; Tucker and Linden, 1993). All these P 1 purinoceptors belong to the superfamily of G protein-coupled receptors having seven transmembrane domains. The relevance of adenosine for the development and function of the immune system is deduced from the severe combined immunodeficiency syndrome (SCID) associated with the congenital defect of adenosine deaminase, the enzyme which degrades the nucleoside. In adenosine deaminase-deficient children, elevated levels of adenosine (and 2′-deoxyadenosine) are found in body fluids. Several mechanisms whereby adenosine deaminase deficiency may affect the development and function of lymphoid cells have been suggested but none can satisfactorily explain all the relationships found in SCID. Most of the proposed mechanisms (see Hershfield and Mitchell, 1989, for review) have rested upon the assumption that accumulation of the two physiological substrates of adenosine deaminase, adenosine and 2′-deoxyadenosine, are toxic for lymphocytes (Franco et al., 1998, and references therein). There is recent data suggesting that signaling through purinergic receptors in lymphocyte and lymphocyte precursors may contribute to the pathogenesis of adenosine deaminase-related SCID (Apasov 491 Journal of Cell Science 112, 491-502 (1999) Printed in Great Britain © The Company of Biologists Limited 1999 JCS0069
A mariner-Based Transposition System for Listeria monocytogenes

ABSTRACT In this study, we developed a new mariner-based transposition system for Listeria monocytogenes. The mariner-based system has a high rate of transposition and a low rate of plasmid retention, and transposition is very random, making it an ideal tool for high-throughput transposon mutagenesis in L. monocytogenes.