Miracle-dz/UniFAR-FTUs huggingface dataset:
Tight Regulation of the intS Gene of the KplE1 Prophage: A New Paradigm for Integrase Gene Regulation

Temperate phages have the ability to maintain their genome in their host, a process called lysogeny. For most, passive replication of the phage genome relies on integration into the host's chromosome and becoming a prophage. Prophages remain silent in the absence of stress and replicate passively within their host genome. However, when stressful conditions occur, a prophage excises itself and resumes the viral cycle. Integration and excision of phage genomes are mediated by regulated site-specific recombination catalyzed by tyrosine and serine recombinases. In the KplE1 prophage, site-specific recombination is mediated by the IntS integrase and the TorI recombination directionality factor (RDF). We previously described a sub-family of temperate phages that is characterized by an unusual organization of the recombination module. Consequently, the attL recombination region overlaps with the integrase promoter, and the integrase and RDF genes do not share a common activated promoter upon lytic induction as in the lambda prophage. In this study, we show that the intS gene is tightly regulated by its own product as well as by the TorI RDF protein. In silico analysis revealed that overlap of the attL region with the integrase promoter is widely encountered in prophages present in prokaryotic genomes, suggesting a general occurrence of negatively autoregulated integrase genes. The prediction that these integrase genes are negatively autoregulated was biologically assessed by studying the regulation of several integrase genes from two different Escherichia coli strains. Our results suggest that the majority of tRNA-associated integrase genes in prokaryotic genomes could be autoregulated and that this might be correlated with the recombination efficiency as in KplE1. The consequences of this unprecedented regulation for excisive recombination are discussed.
Measuring and Improving the Performance of Cache-efficient Priority Queues in Dijkstra ’ s Algorithm

The priority queue is an useful data structure in computation. There currently exist many implementations of this data structure, including some that are cache-aware and some cache-oblivious. In this study, we compare the performance of several implementations of priority queues in Dijkstra’s Single Source Shortest Path algorithm. We compare high performance heaps, such as the 4ary Aligned Heap, Fast Binary Heap and Sequence Heap against in-house heap implementations, namely Buffer Heap and Auxiliary Buffer Heap, and against well-known implementations such as the textbook Binary Heap. We focus our analysis on the benefit of supporting decrease-key operations within the priority queue. Results indicate that graph density affect the relative performance of the different priority queues, and that using the Decrease-Key operation incurs unexpected performance hits. Furthermore, we will propose a parallel version of Buffer Heap which remains cache-oblivious and scales to a high level of parallelism.
Integrated Robot Task and Motion Planning in the Now

This work was supported in part by the NSF under Grant No. 1117325. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation. We also gratefully acknowledge support from ONR MURI grant N00014-09-1-1051, from AFOSR grant AOARD-104135 and from the Singapore Ministry of Education under a grant to the Singapore-MIT International Design Center. We thank Willow Garage for the use of the PR2 robot as part of the PR2 Beta Program.
PIC-based TinyOS implementation

Management of wireless sensor networks is an area of research which aims to minimise the power dissipation of such networks while maximising their functionality. TinyOS is a widely used operating system for modern wireless sensors, as its modular system is flexible yet powerful. In order to port TinyOS to a new platform, the nesC compiler must be adapted and some operating system modules must be ported. We describe the issues involved in running TinyOS on a PIC-based wireless sensor, and how the compiler must be modified to cope with the limited PIC architecture. We show that the final performance is comparable to or better than existing sensor systems for a limited set of applications, but that complex applications are likely to prove extremely difficult to implement.
Consistent detection of global predicates under a weak fault assumption

We study the problem of detecting general global predicates in distributed systems where all application processes and at most t<m monitor processes may be subject to crash faults, where m is the total number of monitor processes in the system. We introduce two new observation modalities called negotiably and discernibly (which correspond to possibly and definitely in fault-free systems) and present detection algorithms for them which work under increasingly weak fault assumptions.
Evaluating shallow and deep networks for ransomware detection and classification

Ransomware is one type of malware that covertly installs and executes a cryptovirology attack on a victims computer to demand a ransom payment for restoration of the infected resources. This kind of malware has been growing largely in recent days and causes tens of millions of dollars losses to consumers. In this paper, we evaluate shallow and deep networks for the detection and classification of ransomware. To characterize and distinguish ransomware over benign and various other families of ransomwares, we leverage the dominance of application programming interface (API) invocations. To select a best architecture for the multi-layer perceptron (MLP), we done various experiments related to network parameters and structures. All the experiments are run up to 500 epochs with a learning rate in the range [0.01-0.5]. Result obtained on our data set is more promising to distinguish ransomware not only from benign from its families too. On distinguishing the . EXE as either benign or ransomware, MLP has attained highest accuracy 1.0 and classifying the ransomware to their categories obtained highest accuracy 0.98. Moreover, MLP has performed well in detecting and classifying ransomwares in comparison to the other classical machine learning classifiers.
Collection-behavior based multi-parameter posted pricing mechanism for crowd sensing

Recently numerous sensing applications from the Internet of Things(IoT), such as traffic monitoring and noise map making, require the expensive installation cost. To handle this challenge, crowd sensing, as a new paradigm, has received extensive concerns. To achieve good service quality, incentive mechanisms are necessary to attract more users to participate in crowd sensing. However, Traditional incentive mechanisms such as the Vickrey-Clarke-Groves (VCG) mechanism and its variants, are not applicable for practical continuous crowd sensing applications, where bids cannot be solicited and only posted pricing mechanisms can be implemented. To tackle the issue, we propose a novel crowd sensing framework by applying all-pay auctions, and then design a collection-behavior based multi-parameter posted pricing mechanism by applying crowd aversion and posted pricing mechanisms. Simulation results indicate that incentive mechanisms in our proposed framework outperform the existing solution with respect to user participation and submission quality.
Who Is Still Playing Pokémon Go? A Web-Based Survey

Background Poor physical activity is one of the major health care problems in Western civilizations. Various digital gadgets aiming to increase physical activity, such as activity trackers or fitness apps, have been introduced over recent years. The newest products are serious games that incorporate real-life physical activity into their game concept. Recent studies have shown that such games increase the physical activity of their users over the short term. Objective In this study, we investigated the motivational effects of the digital game “Pokémon Go” leading to continued use or abandonment of the game. The aim of the study was to determine aspects that motivate individuals to play augmented reality exergames and how this motivation can be used to strengthen the initial interest in physical activity. Methods A total of 199 participants completed an open self-selected Web-based survey. On the basis of their self-indicated assignment to one of three predefined user groups (active, former, and nonuser of Pokémon Go), participants answered various questions regarding game experience, physical activity, motivation, and personality as measured by the Big Five Inventory. Results In total, 81 active, 56 former, and 62 nonusers of Pokémon Go were recruited. When asked about the times they perform physical activity, active users stated that they were less physically active in general than former and nonusers. However, based on a subjective rating, active users were more motivated to be physically active due to playing Pokémon Go. Motivational aspects differed for active and former users, whereas fan status was the same within both groups. Active users are more motivated by features directly related to Pokémon, such as catching all possible Pokémon and reaching higher levels, whereas former users stress the importance of general game quality, such as better augmented reality and more challenges in the game. Personality did not affect whether a person started to play Pokémon Go nor their abandonment of the game. Conclusions The results show various motivating elements that should be incorporated into augmented reality exergames based on the game Pokémon Go. We identified different user types for whom different features of the game contribute to maintained motivation or abandonment. Our results show aspects that augmented reality exergame designers should keep in mind to encourage individuals to start playing their game and facilitate long-term user engagement, resulting in a greater interest in physical activity.
Effect of Peel Rate on Interfacial Strength

Adhesives are widely used in industrial world. However, it is difficult to characterize their mechanical properties because those strongly depend on environmental and mechanical conditions such as temperature, humidity or strain rate. In this paper, we focus on the strain rate dependence of the interfacial strength and investigate the interfacial strength by peel tests under several peel rates. The results show that, in low rate case (under 10-2 mm/s), the interfacial strength was constant and, in middle rate case (10-2 to 103 mm/s), the interfacial strength increased with the peel rate. Over 103 mm/s case, the interfacial strength became lower than those in middle rate cases. From the observation of peeling front by a high speed video camera, the deformation behavior of adhesives changed with the peel rate.
Single Pass, BLAST-Like, Approximate String Matching on FPGAs

Approximate string matching is fundamental to bioinformatics, and has been the subject of numerous FPGA acceleration studies. We address issues with respect to FPGA implementations of both BLAST- and dynamic programming- (DP) based methods. Our primary contributions are two new algorithms for emulating the seeding and extension phases of BLAST. These operate in a single pass through a database at streaming rate (110 Maa/sec on a VP70 for query sizes up to 600 and 170 Maa/sec on a Virtex4 for query sizes up to 1024), and with no preprocessing other than loading the query string. Further, they use very high sensitivity with no slowdown. While current DP-based methods also operate at streaming rate, generating results can be cumbersome. We address this with a new structure for data extraction. We present results from several implementations
A new dimensionality reduction method for seabed characterization: supervised Curvilinear Component Analysis

In this paper, we present a new method for dimensionality reduction, called supervised Curvilinear Component Analysis, for the classification of sonar images task using support vector machines. Indeed it is important in many underwater applications to get tools that give automatically the kind of sediments. This method derives from the known method Curvilinear Component Analysis. It gives good results for data not highly overlapped. We have used this method after a feature extraction step based on wavelet decomposition applied to our sonar images database.
HDRE: Coverage hole detection with residual energy in wireless sensor networks

Coverage completeness is an important indicator for quality of service in wireless sensor networks (WSN). Due to limited energy and diverse working conditions, the sensor nodes have different lifetimes which often cause network holes. Most of the existing methods expose large limitation and one-sidedness because they generally consider only one aspect, either coverage rate or energy issue. This paper presents a novel method for coverage hole detection with residual energy in randomly deployed wireless sensor networks. By calculating the life expectancy of working nodes through residual energy, we make a trade-off between network repair cost and energy waste. The working nodes with short lifetime are screened out according to a proper ratio. After that, the locations of coverage holes can be determined by calculating the joint coverage probability and the evaluation criteria. Simulation result shows that compared to those traditional algorithms without consideration of energy problem, our method can effectively maintain the coverage quality of repaired WSN while enhancing the life span of WSN at the same time.
Analyses of Resected Human Brain Metastases of Breast Cancer Reveal the Association between Up-Regulation of Hexokinase 2 and Poor Prognosis

Brain metastases of breast cancer seem to be increasingin incidence as systemic therapy improves. Metastatic disease in the brain is associated with high morbidity and mortality. We present the first gene expression analysis of laser-captured epithelial cells from resected human brain metastases of breast cancer compared with unlinked primary breast tumors. The tumors were matched for histology, tumor-node-metastasis stage, and hormone receptor status. Most differentially expressed genes were down-regulated in the brain metastases, which included, surprisingly, many genes associated with metastasis. Quantitative real-time PCR analysis confirmed statistically significant differences or strong trends in the expression of six genes: BMP1, PEDF, LAMγ3, SIAH, STHMN3, and TSPD2. Hexokinase 2 (HK2) was also of interest because of its increased expression in brain metastases. HK2 is important in glucose metabolism and apoptosis. In agreement with our microarray results, HK2 levels (both mRNA and protein) were elevated in a brain metastatic derivative (231-BR) of the human breast carcinoma cell line MDA-MB-231 relative to the parental cell line (231-P) in vitro. Knockdown of HK2 expression in 231-BR cells using short hairpin RNA reduced cell proliferation when cultures were maintained in glucose-limiting conditions. Finally, HK2 expression was analyzed in a cohort of 123 resected brain metastases of breast cancer. High HK2 expression was significantly associated with poor patient survival after craniotomy (P = 0.028). The data suggest that HK2 overexpression is associated with metastasis to the brain in breast cancer and it may be a therapeutic target. (Mol Cancer Res 2009;7(9):1438–45)
Photoentrainment in blind and sighted rodent species: responses to photophase light with different wavelengths

SUMMARY Our study examined the impact of daylight (photophase) wavelength on the photoentrainment sensitivity of two species with vastly different visual systems. Social voles (Microtus socialis) and ‘blind’ mole rats (Spalax ehrenbergi) were exposed to short-wavelength (479 nm) or long-wavelength (697 nm) light at an intensity of 293 μW cm–2. Rhythms of urine production, urinary 6-sulfatoxymelatonin (6-SMT), urinary metabolites of adrenaline and cortisol, and oxygen consumption (VO2) were used as markers for the sensitivity of the photoentrainment system. Significant 24-h rhythms were detected in all variables for both species under short-wavelength light, whereas ultradian rhythms of 12- or 8-h were detected under long-wavelength light. Wavelength inversely affected 6-SMT levels in M. socialis (negative correlation) and S. ehrenbergi (positive correlation). Increased levels of stress hormone metabolites were detected in M. socialis under the long-wavelength light whereas, in S. ehrenbergi elevated levels were secreted under short-wavelength light. Long-wavelength light increased VO2 in M. socialis and decreased it in S. ehrenbergi; short-wavelength light elicited the opposite effects. Our results indicate that photophase wavelength is an integral light property for modulating photoperiodic responses in mammals, including visually challenged species. Finally, the spectral-induced differential responses between the two species potentially represent adaptive physiological flexibility in species with contrasting visual and habitat challenges.
Handling of Household Flammables by Elderly Dwelling in the Community: Executive Function and Judgment Involved in Handling Errors; The Kurihara Project

Background: Handling errors with household flammables, such as pan burning, may result in serious accidents. In the previous study, we surveyed an actual status of handling errors with household flammables in the 590 older residents in Kurihara, northern Japan. The accidents were caused by a decrease in attention/executive function and the ability to predict risks. Methods: According to results of a questionnaire regarding the “frequency of small fire accidents at home” and “the presence or absence of pan burning”, 592 elderly people were divided into 2 groups, the “low-risk group” (no small fire accident, or <1 small fire accident but the absence of pan burning in a year and the “high-risk group” (<1 small fire accident but the presence of pan burning in a year, or frequent small fire accidents). For the neurobehavioral assessments, their memory, executive function, depressive state, and judgment were evaluated using WMSR Logical Memory-I/II, Trail Making Test A/B and Digit Symbol (DS), Geriatric Depression Scale (GDS), and the question regarding “fire” in Cognitive Abilities Screening Instrument (CASI)-7, respectively. Results: The number of subjects with higher Clinical Dementia Rating (CDR) score was greater in the high-risk group compared with the low-risk group. Two-way ANCOVA using the CDR scale and risk classification as the main effect, and using age, educational level, and MMSE scores as covariant, showed that the CDR effect and risk classification were observed in Logical Memory-I/II and DS, respectively. The subjects in the high-risk group were more likely not to answer the question about “fire” in CASI -7. Conclusion: Executive function and judgment may be more likely to be involved in handling errors with household flammables, compared with memory. The finding indicated that a scale specific to the handling of household flammables should be established.
Performance of low input active aeration pile, turning pile and static pile for composting organic fertilizer.

Composting performance was carried out in low input passive aeration by using mechanical roof’s ventilation fan in comparison with turning every 7 days and static piles. The three treatments under investigation are (1) mechanical roof’s ventilation fan, (2) turning pile every seven days and (3) static pile. There were no significant differences in term of peak temperature, days to reach peak temperature, total duration which temperature above 55 oC, increasing rate and decreasing rate. The difference was the days to completion of the composting process. Treatment with mechanical roof’s ventilation fan showed the most effective composting process regarding temperature profile. It was 79.50 days in completion. Whereas slower composting processes were recorded in turning pile every 7 days and static pile. These were 111.00 and 124.00 days, respectively. Composting under mechanical roof’s ventilation fan showed significantly lower electrical conductivity (EC) than turning pile and static pile.
On the communication and streaming complexity of maximum bipartite matching

Consider the following communication problem. Alice holds a graph GA = (P,Q,EA) and Bob holds a graph GB = (P,Q,EB), where |P| = |Q| = n. Alice is allowed to send Bob a message m that depends only on the graph GA. Bob must then output a matching M ⊆ EA ∪ EB. What is the minimum message size of the message m that Alice sends to Bob that allows Bob to recover a matching of size at least (1 − e) times the maximum matching in GA ∪ GB? The minimum message length is the one-round communication complexity of approximating bipartite matching. It is easy to see that the one-round communication complexity also gives a lower bound on the space needed by a one-pass streaming algorithm to compute a (1 − e)-approximate bipartite matching. The focus of this work is to understand one-round communication complexity and one-pass streaming complexity of maximum bipartite matching. In particular, how well can one approximate these problems with linear communication and space? Prior to our work, only a 1/2-approximation was known for both these problems. In order to study these questions, we introduce the concept of an e-matching cover of a bipartite graph G, which is a sparse subgraph of the original graph that preserves the size of maximum matching between every subset of vertices to within an additive en error. We give a polynomial time construction of a 1/2-matching cover of size O(n) with some crucial additional properties, thereby showing that Alice and Bob can achieve a 2/3-approximation with a message of size O(n). While we do not provide bounds on the size of e-matching covers for e 0, a (2/3 + δ)-approximation requires a communication complexity of n1+Ω(1/log log n). We also consider the natural restrictingon of the problem in which GA and GB are only allowed to share vertices on one side of the bipartition, which is motivated by applications to one-pass streaming with vertex arrivals. We show that a 3/4-approximation can be achieved with a linear size message in this case, and this result is best possible in that super-linear space is needed to achieve any better approximation. Finally, we build on our techniques for the restricted version above to design one-pass streaming algorithm for the case when vertices on one side are known in advance, and the vertices on the other side arrive in a streaming manner together with all their incident edges. This is precisely the setting of the celebrated (1 − 1/e)-competitive randomized algorithm of Karp-Vazirani-Vazirani (KVV) for the online bipartite matching problem [12]. We present here the first deterministic one-pass streaming (1 - 1/e)-approximation algorithm using O(n) space for this setting.