Miracle-dz/UniFAR-FTUs huggingface dataset:
Making snapshot isolation serializable

Snapshot Isolation (SI) is a multiversion concurrency control algorithm, first described in Berenson et al. [1995]. SI is attractive because it provides an isolation level that avoids many of the common concurrency anomalies, and has been implemented by Oracle and Microsoft SQL Server (with certain minor variations). SI does not guarantee serializability in all cases, but the TPC-C benchmark application [TPC-C], for example, executes under SI without serialization anomalies. All major database system products are delivered with default nonserializable isolation levels, often ones that encounter serialization anomalies more commonly than SI, and we suspect that numerous isolation errors occur each day at many large sites because of this, leading to corrupt data sometimes noted in data warehouse applications. The classical justification for lower isolation levels is that applications can be run under such levels to improve efficiency when they can be shown not to result in serious errors, but little or no guidance has been offered to application programmers and DBAs by vendors as to how to avoid such errors. This article develops a theory that characterizes when nonserializable executions of applications can occur under SI. Near the end of the article, we apply this theory to demonstrate that the TPC-C benchmark application has no serialization anomalies under SI, and then discuss how this demonstration can be generalized to other applications. We also present a discussion on how to modify the program logic of applications that are nonserializable under SI so that serializability will be guaranteed.
Proposed Classification of Cells in the Foundational Model of Anatomy

A logical and principled representation of cell types and their component parts could serve as a framework for correlating the various ontologies that are emerging in bioinformatics with a focus on cells and subcellular biological entities. In order to address this need we have extended the Foundational Model of Anatomy (FMA)1,2 from macroscopic to cellular and subcellular anatomical entities. The poster will provide a live demonstration of this implementation.
Performance Evaluation of Quantum Merging : Negative Queue Length

We study the detail of queues handling quantum communication, especially socalled quantum merging of qubits. In quantum merging, by using EPR pairs (entangled pairs of quantum particles), jobs may bring extra service capacity to the server, which can be stored in the system for future use. We will model this phenomena as queues that can have the negative queue length, and show the basic characteristics of these quantum queues.
Leaving Unemployment for Self-Employment a Discrete Duration Analysis of Determinants and Stability of Self-Employment Among Former Unemployed

The paper investigates the determinants and the success of self-employment among former unemployed. Self-employment has become an important re-employment opportunity during the last decade due to increasing subsidies. The econometric analysis is carried out using discrete hazard rate models on 14 waves of the German Socio-Economic Panel, covering the period from 1983 to 1996. I do not find any effects of unemployment duration on the transition from unemployment to selfemployment. Moreover, unemployed people entering self-employment have higher skills than the average of the unemployed population and self-employment seems to be more stable than paid-employment would have been because people face a lower risk of becoming unemployed again.
Estimating clustering coefficients and size of social networks via random walk

Online social networks have become a major force in today's society and economy. The largest of today's social networks may have hundreds of millions to more than a billion users. Such networks are too large to be downloaded or stored locally, even if terms of use and privacy policies were to permit doing so. This limitation complicates even simple computational tasks. One such task is computing the clustering coefficient of a network. Another task is to compute the network size (number of registered users) or a subpopulation size. The clustering coefficient, a classic measure of network connectivity, comes in two flavors, global and network average. In this work, we provide efficient algorithms for estimating these measures which (1) assume no prior knowledge about the network; and (2) access the network using only the publicly available interface. More precisely, this work provides three new estimation algorithms (a) the first external access algorithm for estimating the global clustering coefficient; (b) an external access algorithm that improves on the accuracy of previous network average clustering coefficient estimation algorithms; and (c) an improved external access network size estimation algorithm. The main insight offered by this work is that only a relatively small number of public interface calls are required to allow our algorithms to achieve a high accuracy estimation. Our approach is to view a social network as an undirected graph and use the public interface to retrieve a random walk. To estimate the clustering coefficient, the connectivity of each node in the random walk sequence is tested in turn. We show that the error of this estimation drops exponentially in the number of random walk steps. Another insight of this work is the fact that, although the proposed algorithms can be used to estimate the clustering coefficient of any undirected graph, they are particularly efficient on social network-like graphs. To improve the network size prior-art estimation algorithms, we count node collision one step before they actually occur. In our experiments we validate our algorithms on several publicly available social network datasets. Our results validate the theoretical claims and demonstrate the effectiveness of our algorithms.
Human Pcf11 enhances degradation of RNA polymerase II-associated nascent RNA and transcriptional termination

The poly(A) (pA) signal possesses a dual function in 3′ end processing of pre-mRNA and in transcriptional termination of RNA polymerase II (Pol II) for most eukaryotic protein-coding genes. A key protein factor in yeast and Drosophila Pol II transcriptional termination is the 3′-end processing factor, Pcf11. In vitro studies suggest that Pcf11 is capable of promoting the dissociation of Pol II elongation complexes from DNA. Moreover, several mutant alleles of yeast Pcf11 effect termination in vivo. However, functions of human Pcf11 (hPcf11) in Pol II termination have not been explored. Here we show that depletion of hPcf11 from HeLa cells reduces termination efficiency. Furthermore, we provide evidence that hPcf11 is required for the efficient degradation of the 3′ product of pA site cleavage. Finally, we show that these functions of hPcf11 require an intact pA signal.
Architectural support for synchronization-free deterministic parallel programming

We propose a novel synchronization mechanism called versioning. It dynamically establishes a deterministic order of memory accesses in parallel programs that have serial semantics, in a way that is transparent to the programmer. This order is created in a distributed manner and is enforced by monitoring memory accesses and stalling threads if necessary. Versioning gives rise to parallel programming models in which programmers need not explicitly synchronize threads and only need to specify shared data, which greatly simplifies parallel programming. However, versioning introduces overheads and thus demands architectural support. We describe versioning and the architectural support it needs. We also propose one parallel programming model that utilizes versioning and use it to parallelize 13 benchmark applications. We build an FPGA prototype of a multiprocessor system with versioning support and show that good parallel speedups are obtained. Our analysis shows minimal impact of versioning, both in terms of timing overheads and in terms of additional hardware.
Use of an interactive trivia game to increase knowledge and awareness of appropriate antibiotic use in community-dwelling older adults: a pilot survey.

OBJECTIVE To assess change in knowledge and awareness of upper respiratory-tract infections (URTIs), and appropriate antibiotic use in community-dwelling older adults. DESIGN Single group, pre- and post-test study. SETTING Two independent senior living communities in Baltimore City and Baltimore County, Maryland. PARTICIPANTS Older adults eligible to receive housing or other social services as defined by the study sites. INTERVENTION Use of an interactive trivia game to educate older adults about URTIs. A 15-item pre- and postsurvey was administered to assess change in knowledge. OUTCOME MEASURES Average change in pre- and postsurvey scores. RESULTS Thirty-two seniors participated in the game intervention, with 18 completing both surveys. There was no significant difference in the total mean pre- versus postsurvey scores. Average scores of pre- and postsurveys were 9.28 and 9.17, respectively, out of 15 points (95% confidence interval 0.65 +/- 1.414; P = 0.76). Upon review of individual survey questions, two specific areas showed a significant improvement on postsurvey scores compared with baseline. Participants showed significant improvement, however, in knowledge regarding symptoms that may require the use of an antibiotic (P = 0.02) and symptomatic management of URTI symptoms (P = 0.045). CONCLUSIONS Based on survey results, we learned more about older adults' knowledge regarding URTIs, antibiotic use, and strategies to provide education to community-dwelling geriatric adults. The game was effective in teaching older adults about symptom management and symptoms that may require an antibiotic.
Impacts of Roads, Hunting, and Habitat Alteration on Nocturnal Mammals in African Rainforests

Abstract: Nocturnal mammals are poorly studied in Central Africa, a region experiencing dramatic increases in logging, roads, and hunting activity. In the rainforests of southern Gabon, we used spotlighting surveys to estimate abundances of nocturnal mammal species and guilds at varying distances from forest roads and between hunted and unhunted treatments (comparing a 130‐km2 oil concession that was nearly free of hunting, with nearby areas outside the concession that had moderate hunting pressure). At each of 12 study sites that were evenly divided between hunted and unhunted areas, we established standardized 1‐km transects along road verges and at 50, 300, and 600 m from the road. We then repeatedly surveyed mammals at each site during 2006. Hunting had few apparent effects on this assemblage. Nevertheless, the species richness and often the abundance of nocturnal primates, smaller ungulates, and carnivores were significantly depressed within approximately 30 m of roads. Scansorial rodents increased in abundance in hunted forests, possibly in response to habitat changes caused by logging or nearby swidden farming. In multiple‐regression models many species and guilds were significantly influenced by forest‐canopy and understory cover, both of which are altered by logging and by certain abiotic variables. In general, nocturnal species, many of which are arboreal or relatively small in size (<10 kg), were less strongly influenced by hunting and more strongly affected by human‐induced changes in forest structure than were larger mammal species in our study area.
Dictionary Look-Up with One Error

LetWbe a set ofnbinary strings of lengthmeach. We are interested in designing data structures forWthat can answerd-queriesquickly; that is, given in a binary string ? , decide whether there is any member ofWwithin Hamming distancedof ? The problem, originally raised by Minsky and Papert, remains a challenge in data structure design. In this paper, we make an initial effort toward a theoretical study of the smalldcase. Our main result is a data structure that achievesO(mloglogn) query time withO(nmlogm) space for thed=1 case.
Hardware performance counters based runtime anomaly detection using SVM

The nature of ever evolving anomalies have become more sophisticated and complex in attacking the defense schemes, thereby leading to serious compromises. Existing software based techniques aim to protect a vulnerable software with another software which is also prone to compromise like obfuscation-based attacks. On the other hand, hardware performance counters offer a robust detection mechanism that is difficult to compromise since it is easier to tamper the software components than hardware features. Hence, in this paper, we propose a hardware-based monitoring method for embedded devices in detecting anomalies using carefully selected low-level hardware features. Next, a support vector machine (SVM) classifier is used to train a model that can detect anomalies based on features obtained from the selected hardware performance counters. Experimental results show that the proposed approach can achieve an accuracy of close to 100% anomaly detection rate while relying only on a single trained model. This approach can be generalized across various platforms.
A Stochastic Gradient Approach on Compressive Sensing Signal Reconstruction Based on Adaptive Filtering Framework

Based on the methodological similarity between sparse signal reconstruction and system identification, a new approach for sparse signal reconstruction in compressive sensing (CS) is proposed in this paper. This approach employs a stochastic gradient-based adaptive filtering framework, which is commonly used in system identification, to solve the sparse signal reconstruction problem. Two typical algorithms for this problem: <i>l</i> <sub>0</sub>-least mean square ( <i>l</i> <sub>0</sub>-LMS) algorithm and <i>l</i> <sub>0</sub>-exponentially forgetting window LMS (<i>l</i> <sub>0</sub>-EFWLMS) algorithm are hence introduced here. Both the algorithms utilize a zero attraction method, which has been implemented by minimizing a continuous approximation of <i>l</i> <sub>0</sub> norm of the studied signal. To improve the performances of these proposed algorithms, an <i>l</i> <sub>0</sub>-zero attraction projection (<i>l</i> <sub>0</sub> -ZAP) algorithm is also adopted, which has effectively accelerated their convergence rates, making them much faster than the other existing algorithms for this problem. Advantages of the proposed approach, such as its robustness against noise, etc., are demonstrated by numerical experiments.
Multi-Branch Vector Perturbation Precoding Design Using Lattice Reduction for MU-MIMO Systems

This paper investigates the design of vector perturbation (VP) precoding using lattice reduction (LR) based on a multi-branch (MB) strategy for multi- user multiple-input multiple-output (MU-MIMO) systems. The MB strategy constructs a group of branches for transmitting data streams according to a pre-designed ordering scheme. For each branch, an LR-aided minimum mean square error (MMSE) VP precoder is proposed and three methods are devised for the perturbation vector design. We also develop an effective scheme to design the transmit ordering patterns with appropriate structures and a suitable selection mechanism to choose the best one. Simulation results show that the proposed MB-LR-MMSE-VP algorithm achieves a better bit error rate (BER) performance than existing VP precoding schemes.
Multiplex Real-Time Reverse Transcription–Polymerase Chain Reaction for the Detection of Three Viruses Associated with Poult Enteritis Complex: Turkey Astrovirus, Turkey Coronavirus, and Turkey Reovirus

Abstract Poult enteritis complex (PEC) is an economically important disease of young turkeys characterized by diarrhea, poor weight gain, and, in some cases, high mortality. Although PEC is considered to be a polymicrobial disease, numerous viruses, including turkey coronavirus (TCV), turkey astrovirus type 2 (TAstV-2), and avian reoviruses (ARVs), have been associated with PEC-like disease. Real-time reverse transcription–polymerase chain reaction (RRT-PCR), a highly sensitive and specific detection method for viral RNA, was developed in a multiplex format for the simultaneous detection of TAstV-2 and TCV and for the detection of two genetic types of ARV. Assay sensitivity was determined using in vitro transcribed RNA and varied by target between 150 gene copies for TAstV-2 alone and 2200 gene copies for TCV when multiplexed. Virus detection was evaluated with samples collected from poults inoculated at 1 day of age with each of the viruses. Cloacal swabs and intestinal samples were obtained at 1, 2, 3, 4, 6, 9, 14, 17, and 21 days after inoculation, processed, and tested for virus detection by RRT-PCR. Cloacal swabs from TAstV-2– and TCV-infected poults were shown to have sensitivity for virus detection similar to that of intestinal samples when compared directly. ARV detection by RRT-PCR was compared with virus isolation and had similar sensitivity.
A New Strategy for the Functionalization of White Phosphorus

Research on chlorine-free conversions of P4 into organophosphorus compounds (OPCs) has a long track record, but methods that allow desirable, direct P–C bond formations have only recently emerged. These include the use of metal organyls, carbenes, carboradicals and photochemical approaches. The versatile product scope enables the preparation of both industrially relevant organophosphorus compounds, as well as a broad range of intriguing new compound classes. Herein we provide a concise overview of recent breakthroughs and outline the acquired fundamental insights to aid future developments. Manuscript: Submitted
Generation of IL-23 Producing Dendritic Cells (DCs) by Airborne Fungi Regulates Fungal Pathogenicity via the Induction of TH-17 Responses

Interleukin-17 (IL-17) producing T helper cells (TH-17) comprise a newly recognized T cell subset with an emerging role in adaptive immunity to a variety of fungi. Whether different airborne fungi trigger a common signaling pathway for TH-17 induction, and whether this ability is related to the inherent pathogenic behavior of each fungus is currently unknown. Here we show that, as opposed to primary pathogenic fungi (Histoplasma capsulatum), opportunistic fungal pathogens (Aspergillus and Rhizopus) trigger a common innate sensing pathway in human dendritic cells (DCs) that results in robust production of IL-23 and drives TH-17 responses. This response requires activation of dectin-1 by the fungal cell wall polysaccharide b-glucan that is selectively exposed during the invasive growth of opportunistic fungi. Notably, unmasking of b-glucan in the cell wall of a mutant of Histoplasma not only abrogates the pathogenicity of this fungus, but also triggers the induction of IL-23 producing DCs. Thus, b-glucan exposure in the fungal cell wall is essential for the induction of IL-23/TH-17 axis and may represent a key factor that regulates protective immunity to opportunistic but not pathogenic fungi.
Applied research of stainless steel fiber-filled acrylonitrile–butadiene–styrene copolymer composites

Composite is prepared by filling acrylonitrile–butadiene–styrene copolymer with stainless steel fiber. Its physical properties and electromagnetic shielding effectiveness are tested. When the mass percent of stainless steel fiber is 15%, shielding effectiveness of composite is 21–59 dB in frequency band of 15 MHz to 3 GHz and cylindrical shell is made of it. Experiments under radiation of X-band high power microwave and ultra-wideband electromagnetic pulse are conducted in microwave anechoic chamber while magnetic fuzes connected with electrical fire head are placed at the center of cylindrical shell. Results show good agreement with test. Coupling effect is analyzed while shell has a hole or slot of millimeter level.
A Correction to the Review Titled "Rules for Modeling Signal-Transduction Systems" by W. S. Hlavacek et al.

Formalized rules for protein-protein interactions have recently been introduced to represent the binding and enzymatic activities of proteins in cellular signaling. Rules encode an understanding of how a system works in terms of the biomolecules in the system and their possible states and interactions. A set of rules can be as easy to read as a diagrammatic interaction map, but unlike most such maps, rules have precise interpretations. Rules can be processed to automatically generate a mathematical or computational model for a system, which enables explanatory and predictive insights into the system’s behavior. Rules are independent units of a model specification that facilitate model revision. Instead of changing a large number of equations or lines of code, as may be required in the case of a conventional mathematical model, a protein interaction can be introduced or modified simply by adding or changing a single rule that represents the interaction of interest. Rules can be defined and visualized by using graphs, so no specialized training in mathematics or computer science is necessary to create models or to take advantage of the representational precision of rules. Rules can be encoded in a machine-readable format to enable electronic storage and exchange of models, as well as basic knowledge about protein-protein interactions. Here, we review the motivation for rule-based modeling; applications of the approach; and issues that arise in model specification, simulation, and testing. We also discuss rule visualization and exchange and the software available for rule-based modeling. Signaling molecules that control cellular regulation operate in complex networks of molecular interactions within the cell. Many of the individual proteins undergo multiple posttranslational modifications and can thus exist in numerous biochemically distinct states. We explore how mathematical models can cope with such complexity when intuition is insufficient to understand a regulatory scheme. We review approaches to creation of mathematical models of signaling systems with strategies that keep the models from being unwieldy but still allow them to accurately reflect biological systems. We discuss the translation of information about such signaling pathways into a computer-readable language that could allow interoperability of various models. The review has 10 figures and 155 citations and contains Web links to Web sites relevant to the various modeling efforts discussed.
Fast volume scanning approaches by X-ray-computed tomography

X-ray-computed tomography (CT) successfully underwent a transition from slice-by-slice imaging to volume imaging in the decade after 1990 due to the introduction of spiral scan modes. Later, the transition from single-slice to multislice scanning followed. With the advent of new detector technologies we are now looking forward to circular and spiral scanning using area detectors and the respective reconstruction approaches. This review treats the basic technological and algorithmic prerequisites and approaches. It goes into detail with respect to the achievable performance and image quality characteristics and discusses the range of applications. Scanning of the complete body trunk with submillimeter isotropic resolution in less than 30 s is possible today. Further extensions to new medical applications, for example, cardiac CT, but also to nonmedical applications, for example, nondestructive material testing, make CT an emerging imaging modality again.