Miracle-dz/UniFAR-FTUs huggingface dataset:
Inferring qualitative relations in genetic networks and metabolic pathways

MOTIVATION Inferring genetic network architecture from time series data of gene expression patterns is an important topic in bioinformatics. Although inference algorithms based on the Boolean network were proposed, the Boolean network was not sufficient as a model of a genetic network. RESULTS First, a Boolean network model with noise is proposed, together with an inference algorithm for it. Next, a qualitative network model is proposed, in which regulation rules are represented as qualitative rules and embedded in the network structure. Algorithms are also presented for inferring qualitative relations from time series data. Then, an algorithm for inferring S-systems (synergistic and saturable systems) from time series data is presented, where S-systems are based on a particular kind of nonlinear differential equation and have been applied to the analysis of various biological systems. Theoretical results are shown for Boolean networks with noises and simple qualitative networks. Computational results are shown for Boolean networks with noises and S-systems, where real data are not used because the proposed models are still conceptual and the quantity and quality of currently available data are not enough for the application of the proposed methods.
Multiple DNA sequence approximate matching

DNA matching is an important key to understanding genomes, evolution, relationships between organisms, and other concepts in genomics. Yet, comparing DNA is unlike matching typed words to a dictionary of words as there is no "true" spelling for DNA. Therefore, approximate matching algorithms must be used. There are many algorithms that can compare two DNA sequences, but when multiple sequences are to be compared, the matching becomes more difficult. Comparing multiple sequences of DNA can be performed using different known methods. These methods include dynamic programming, star alignments, tree alignments, and others, which are usually based on dynamic programming. The method proposed here is a novel method to compare all strings, not merely all strings to one, as in the star alignment method, and it does so in a different way. The proposed method, the Kaplan multiple sequence algorithm, or KMS, separates the multidimensional search area so that comparisons can be performed in parallel. This paper discusses the problem of comparing multiple sequences and introduces this new novel method to match multiple DNA strings.
A two-enqueuer queue

The question of whether all shared objects with consensus number 2 belong to Common2, the class of objects that can be implemented from two-process consensus and atomic registers, was first posed by Herlihy. In the absence of general results, several researchers have obtained implementations for restricted-concurrency versions of FIFO queue. We present the first Common2 algorithm for a queue with two enqueuers and any number of dequeuers. This algorithm is compatible with the unbounded concurrency model, and its enqueue and dequeue methods require only a constant number of steps.
Characterizing the Effects of Intermittent Faults on a Processor for Dependability Enhancement Strategy

As semiconductor technology scales into the nanometer regime, intermittent faults have become an increasing threat. This paper focuses on the effects of intermittent faults on NET versus REG on one hand and the implications for dependability strategy on the other. First, the vulnerability characteristics of representative units in OpenSPARC T2 are revealed, and in particular, the highly sensitive modules are identified. Second, an arch-level dependability enhancement strategy is proposed, showing that events such as core/strand running status and core-memory interface events can be candidates of detectable symptoms. A simple watchdog can be deployed to detect application running status (IEXE event). Then SDC (silent data corruption) rate is evaluated demonstrating its potential. Third and last, the effects of traditional protection schemes in the target CMT to intermittent faults are quantitatively studied on behalf of the contribution of each trap type, demonstrating the necessity of taking this factor into account for the strategy.
Divide and Conquer – Scalability and Variability for Adaptive Middleware

In this paper, we introduce a divide and conquer approach for the adaptation of distributed applications management by a potentially large number of interacting middleware instances. The method aims at a quick partitioning of the overall problem into smaller sub-problems that can be solved almost independently. The partitioning is found by symbolic reasoning and by applying expert knowledge that is encoded in explicit rules.
An Improved Indexing Mechanism to Index Web Documents

Owing to the dynamic nature of the web, it is difficult for search engine to find the relevant documents to serve a user query. For this purpose, search engine maintains the index of downloaded documents stored in the local repository. Whenever a query comes search engine searches the index in order to find the relevant matched results to be presented to the user. The quality of the matched result depends on the information stored in the index. The more efficient is the structure of index, more efficient the performance of search engine. Generally, inverted index are based solely on the frequency of keywords present in number of documents. In order to improve the efficiency of the search engine, an improved indexing mechanism to index the web documents is being proposed that keeps the context related information integrated with the frequency of the keyword. The structure is implemented using Trie. The implementation results on various documents show that proposed index efficiently stores the documents and search is fast.
Destabilization of α-Helical Structure in Solution Improves Bactericidal Activity of Antimicrobial Peptides: Opposite Effects on Bacterial and Viral Targets

ABSTRACT We have previously examined the mechanism of antimicrobial peptides on the outer membrane of vaccinia virus. We show here that the formulation of peptides LL37 and magainin-2B amide in polysorbate 20 (Tween 20) results in greater reductions in virus titer than formulation without detergent, and the effect is replicated by substitution of polysorbate 20 with high-ionic-strength buffer. In contrast, formulation with polysorbate 20 or high-ionic-strength buffer has the opposite effect on bactericidal activity of both peptides, resulting in lesser reductions in titer for both Gram-positive and Gram-negative bacteria. Circular dichroism spectroscopy shows that the differential action of polysorbate 20 and salt on the virucidal and bactericidal activities correlates with the α-helical content of peptide secondary structure in solution, suggesting that the virucidal and bactericidal activities are mediated through distinct mechanisms. The correlation of a defined structural feature with differential activity against a host-derived viral membrane and the membranes of both Gram-positive and Gram-negative bacteria suggests that the overall helical content in solution under physiological conditions is an important feature for consideration in the design and development of candidate peptide-based antimicrobial compounds.
Who Are the True Fans? Evidence from an Event-Related Potential Study

Fans of celebrities commonly exist in modern society. Researchers from social science have been concerned with this problem for years. Furthermore, such researchers have attempted to measure people’s involvement with celebrities in various ways. However, no study measured the degree of addiction to a specific celebrity at the neurological level. Therefore, the current study employed visually evoked event related potentials (ERPs) to examine people’s attitude toward celebrities by comparing different brain activities of fans and non-fans when they were shown a set of photos. These photos include a specific celebrity, a familiar person, a stranger and a butterfly. Furthermore, to examine the validity of the detected neural index, we also investigated the correlation between brain activity and the score of the Celebrity Attitude Scale (CAS), which was a questionnaire used to explore people’s attitude toward celebrities at behavioral level. Two groups of subjects were asked to complete an implicit task, i.e., to press a button when a picture of a butterfly appeared. Results revealed that fans showed significant positive N2 and P300 deflection when viewing the photos of their favorite celebrity, whereas in the non-fan group, the subjects only showed larger P300 amplitude as a response to the celebrity’s photos. Furthermore, a positive correlation between P300 amplitude elicited by the stimuli of a celebrity face and CAS scores was also observed. These findings indicated fan attitude to a specific celebrity can also be observed at the neurological level and suggested the potential utility of using ERP component as an index of fandom involvement.
Distortion Analysis of Differential Amplifier Ms .

The linearity of the CMOS is of major concern in the design of many analog circuits. In this paper the nonlinearity behavior of CMOS analog integrated circuits is investigated.The basic building block of analog integrated circuits such as differential amplifier with current mirror load have been chosen for harmonic distortion analysis.A mechanism to analyze the distortion of CMOS circuits in deep submicron technology that can be easily used to detect the distortion is built.The MOSFET model used for simulation is TSMC BSIM3 SPICE model from 0.13-μm CMOS process technology. HSPICE circuit simulator tool is used for distortion analysis of CMOS circuits. The MOS model used in this paper includes short-channel effects and gate-source capacitance, gate-drain capacitance, output resistance of MOS transistor. Analytical results are compared with simulation results and the influences of circuit parameters on circuit linearity are discussed.
Daily consumption of phenolics and total antioxidant capacity from fruit and vegetables in the American diet

The daily intake of total phenolics, total flavonoids and antioxidants in the American diet was estimated from the most common 34 fresh fruit and vegetables and their daily consumption data. Among 14 fruit and 20 vegetables, orange contributed the highest amount of total phenolics [117.1 mg gallic acid equivalent (GAE) person−1 day−1] and antioxidants [146.6 mg vitamin C equivalents (VCE) person−1 day−1]. Orange contributed about 26 and 25% of total phenolics and antioxidant, respectively, in the daily consumption of fruit and vegetables. Apples showed relatively high levels of total phenolics and antioxidant capacity comparable to those of oranges and their phenolics and antioxidants contribution is the second highest. Even though potatoes had lower levels of phenolics and antioxidant capacity, they were third due to the fact that their consumption is the highest (137.9 lb person−1 year−1) in the American diet. Although plums and strawberries were ranked as the group with the highest total phenolics and antioxidant capacity among 34 tested fruit and vegetables, their contributions were relatively low due to their lower daily consumption. Generally, the levels of total phenolics, total flavonoids and antioxidant capacity of fruits were higher than those of vegetables. American daily intake of phenolics, flavonoids and antioxidants from fruits and vegetables was estimated to be 450 mg GAE, 103 mg catechin equivalents and 591 mg VCE, respectively. Although we do not yet know the required minimum daily amounts of antioxidants, when we estimate the daily requirement of antioxidants, we must consider not only the antioxidant concentrations of the particular food, but also the daily intakes of the food. Copyright © 2005 Society of Chemical Industry
Supervised machine learning for grouping sketch diagram strokes

Grouping of strokes into semantically meaningful diagram elements is a difficult problem. Yet such grouping is needed if truly natural sketching is to be supported in intelligent sketch tools. Using a machine learning approach, we propose a number of new paired-stroke features for grouping and evaluate the suitability of a range of algorithms. Our evaluation shows the new features and algorithms produce promising results that are statistically better than the existing machine learning grouper.
Secure and fair auctions over ad hoc networks

The emergence of new mobile and wireless networks, with novel capabilities, offers opportunities to widen traditional internet-based applications. In this paper, we focus on a famous and widely used e-commerce application: auctions, and propose their deployment over ad hoc networks. Actually, we specify here this auction model while assuring identified crucial requirements: security and fairness. Security services are provided through threshold cryptography mechanisms whereas fairness is provided through rounds duration calculation. We prove that such a novel mobile commerce application presents advantages with regard to conventional economic models. Evaluations present optimistic results promising a realisable deployment of our auction model.
Moving objects detection for mobile mapping

Mobile mapping systems (MMS) have been widely used in fields such as intelligent transport, precision agriculture, field surveying and environment engineering. Most of the mobile mapping tasks focus on the stationary GIS (geographic information systems) objects. Moving objects such as traffics are usually viewed as contaminations, but always exist in the acquired MMS data. Detection of these moving objects is critical for MMS data post-processing and evaluation. This paper presents a robust moving objects detection algorithm for mobile mapping image sequences. The detection method is based upon optical flow fields and the detection strategy for independent motion relies on the knowledge about the camera motion which is provided by the navigation system in MMS. Through the estimation of the focus of expansion (FOE) and utilization of inconsistencies in optical flow fields, the proposed method is able to detect independently moving objects on a mobile platform. Experimentations on VISATtrade mobile mapping data have shown the effectiveness of the proposed technique.
Investigation on the Chaotic Phase Shift Keying (CPSK) system with turbo iterative coding

This paper presents the results of BER improvements in a chaotic phase shift keying (CPSK) CDMA system when turbo iterative decoding techniques are applied. The decoding technique investigated in this system is called the list bidirectional soft output (LBSO) algorithm. In particular, the method of iterative LBSO decoding based on the normalization of extrinsic information is investigated. The results achieved that CPSK-DS-CDMA system with turbo iterative LBSO decoding has much better error performance than the original CPSK system without coding. The error performance of the improved iterative LBSO decoding outperforms the improved soft output Viterbi algorithm (SOVA) decoding method.
Boromycin Kills Mycobacterial Persisters without Detectable Resistance

Boromycin is a boron-containing polyether macrolide antibiotic isolated from Streptomyces antibioticus. It was shown to be active against Gram positive bacteria and to act as an ionophore for potassium ions. The antibiotic is ineffective against Gram negative bacteria where the outer membrane appears to block access of the molecule to the cytoplasmic membrane. Here we asked whether boromycin is active against Mycobacterium tuberculosis which, similar to Gram negative bacteria, possesses an outer membrane. The results show that boromycin is a potent inhibitor of mycobacterial growth (MIC50 = 80 nM) with strong bactericidal activity against growing and non-growing drug tolerant persister bacilli. Exposure to boromycin resulted in a rapid loss of membrane potential, reduction of the intracellular ATP level and leakage of cytoplasmic protein. Consistent with boromycin acting as a potassium ionophore, addition of KCl to the medium blocked its antimycobacterial activity. In contrast to the potent antimycobacterial activities of the polyether macrolide, its cytotoxicity and haemolytic activity were low (CC50 = 30 μM, HC50 = 40 μM) with a selectivity index of more than 300. Spontaneous resistant mutants could not be isolated suggesting a mutation frequency of less than 10-9/CFU. Taken together, the results suggests that targeting mycobacterial transmembrane ion gradients may be an attractive chemotherapeutic intervention level to kill otherwise drug tolerant persister bacilli, and to slow down the development of genetic antibiotic resistance.
Computing Abstraction Hierarchies by Numerical Simulation

We present a novel method for building ABSTRIPS-style abstraction hierarchies in planning. The aim of this method is to minimize the amount of backtracking between abstraction levels. Previous approaches have determined the criticality of operator preconditions by reasoning about plans directly. Here, we adopt a simpler and faster approach where we use numerical simulation of the planning process. We demonstrate the theoretical advantages of our approach by identifying some simple properties lacking in previous approaches but possessed by our method. We demonstrate the empirical advantages of our approach by a set of four benchmark experiments using the ABTWEAK system. We compare the quality of the abstraction hierarchies generated with those built by the ALPINE and HIGHPOINT algorithms.
Geo-social recommendations based on incremental tensor reduction and local path traversal

Social networks have evolved with the combination of geographical data, into Geo-social networks (GSNs). GSNs give users the opportunity, not only to communicate with each other, but also to share images, videos, locations, and activities. The latest developments in GSNs incorporate the usage of location tracking services, such as GPS to allow users to "check in" at various locations and record their experience. In particular, users submit ratings or personal comments for their location/activity. The vast amount of data that is being generated by users with GPS devices, such as mobile phones, needs efficient methods for its effective management. In this paper, we have implemented an online prototype system, called Geo-social recommender system, where users can get recommendations on friends, locations and activities. For the friend recommendation task, we apply the FriendLink algorithm, which performs a local path traversal on the friendship network. In order to provide location/activity recommendations, we represent data by a 3-order tensor, on which latent semantic analysis and dimensionality reduction is performed using the Higher Order Singular Value Decomposition (HOSVD) technique. As more data is accumulated to the system, we use incremental solutions to update our tensor. We perform an experimental evaluation of our method with two real data sets and measure its effectiveness through recall/precision.
Vision-Enabled Node Localization in Wireless Sensor Networks

We introduce novel localization techniques for wire- less image sensor networks. Based on visual observations between the image sensor nodes or simultaneous observations of a moving object by several nodes, the proposed schemes employ simple image processing functions to obtain angular bearing information between the nodes in a neighborhood and solve for the node positions. We will first propose a technique to localize nodes relative to a coordinate system defined by two reference nodes and propagate the topology information throughout the network. In a different scheme, we consider cases where simultaneous observations from a moving target are used by several image sensors to jointly estimate the coordinates of the nodes as well as those of the target. We will also propose a technique in which the assumption of a simple motion pattern for the target allwos for a collaborative scheme for finding relative location information between the nodes. In a fourth scheme, assistance from a moving beacon knowing its location information is used to localize a network of image sensors. The proposed algorithms are based on in-node processing and local collaboration between the nodes and hence are scalable to large networks. Simulation and experimental results are provided to verify the performance of the proposed techniques.
Volumetric Energy Density of Compressed Air and Compressed Methane. Volumetric Energy

density is a combination of the potential for mechanical work, w, done by the change in pressure (P), and volume (V), and the chemical heat, q, released from burning the gas. For example, compressed air at 2,900 psi (~197 atm) has an energy density of 0.1 MJ/L calculated from PV and compressed methane (at 2,900 psi) has an energy density of 8.0 MJ/L calculated from the combination of PV and heat of combustion (Eq. 1). Estimate of Pressure Immediately After Ignition. Using the unpressurized channel volume of 1.0 mL, and our theoretically estimated temperature immediately after ignition of 2,800 o C, we calculated the maximum pressure, using the ideal gas law, to be ~1 MPa (~140 psi). Though this value is an overestimate (it does not take into account the channel volume expansion and the gas cooling, a complex calculation that is beyond the scope of this paper), we use it to illustrate the quick impulse of high pressure to use a passive valving system to control the flow of gas out of the channel after combustion and cooling.
Food Insecurity and Children’s Mental Health: A Prospective Birth Cohort Study

Food insecurity (which can be defined as inadequate access to sufficient, safe, and nutritious food that meets individuals’ dietary needs) is concurrently associated with children’s psychological difficulties. However, the predictive role of food insecurity with regard to specific types of children’s mental health symptoms has not previously been studied. We used data from the Longitudinal Study of Child Development in Québec, LSCDQ, a representative birth cohort study of children born in the Québec region, in Canada, in 1997–1998 (n = 2120). Family food insecurity was ascertained when children were 1½ and 4½ years old. Children’s mental health symptoms were assessed longitudinally using validated measures of behaviour at ages 4½, 5, 6 and 8 years. Symptom trajectory groups were estimated to identify children with persistently high levels of depression/anxiety (21.0%), aggression (26.2%), and hyperactivity/inattention (6.0%). The prevalence of food insecurity in the study was 5.9%. In sex-adjusted analyses, children from food-insecure families were disproportionately likely to experience persistent symptoms of depression/anxiety (OR: 1.79, 95% CI 1.15–2.79) and hyperactivity/inattention (OR: 3.06, 95% CI 1.68–5.55). After controlling for immigrant status, family structure, maternal age at child’s birth, family income, maternal and paternal education, prenatal tobacco exposure, maternal and paternal depression and negative parenting, only persistent hyperactivity/inattention remained associated with food insecurity (fully adjusted OR: 2.65, 95% CI 1.16–6.06). Family food insecurity predicts high levels of children’s mental health symptoms, particularly hyperactivity/inattention. Addressing food insecurity and associated problems in families could help reduce the burden of mental health problems in children and reduce social inequalities in development.