Miracle-dz/UniFAR-FTUs huggingface dataset:
Bacteroides fragilis and Escherichia coli bacteriophages in human faeces.

Some bacteriophages found in human faeces are being evaluated as possible indicators of viral contamination of water. These bacteriophages include somatic coliphages and Bacteroides fragilis phages. The aims of this study were to determine the occurrence and concentrations of somatic coliphages and Bacteroides fragilis phages in the stools of a human population residing in eastern France (n = 193). Somatic coliphages were detected in 68% of the stools at a mean concentration of 4.3 x 10(3) PFU.g-1 and Bacteroides fragilis phages were detected in 11% of the stools at a mean concentration of 7 x 10(1) PFU.g-1. Statistical analysis showed no correlation between the phage concentration and the age or sex of the human subject.
Understanding the roles of the thylakoid lumen in photosynthesis regulation

It has been known for a long time that the thylakoid lumen provides the environment for oxygen evolution, plastocyanin-mediated electron transfer, and photoprotection. More recently lumenal proteins have been revealed to play roles in numerous processes, most often linked with regulating thylakoid biogenesis and the activity and turnover of photosynthetic protein complexes, especially the photosystem II and NAD(P)H dehydrogenase-like complexes. Still, the functions of the majority of lumenal proteins in Arabidopsis thaliana are unknown. Interestingly, while the thylakoid lumen proteome of at least 80 proteins contains several large protein families, individual members of many protein families have highly divergent roles. This is indicative of evolutionary pressure leading to neofunctionalization of lumenal proteins, emphasizing the important role of the thylakoid lumen for photosynthetic electron transfer and ultimately for plant fitness. Furthermore, the involvement of anterograde and retrograde signaling networks that regulate the expression and activity of lumen proteins is increasingly pertinent. Recent studies have also highlighted the importance of thiol/disulfide modulation in controlling the functions of many lumenal proteins and photosynthetic regulation pathways.
Ecological Genomics of Anopheles gambiae Along a Latitudinal Cline: A Population-Resequencing Approach

The association between fitness-related phenotypic traits and an environmental gradient offers one of the best opportunities to study the interplay between natural selection and migration. In cases in which specific genetic variants also show such clinal patterns, it may be possible to uncover the mutations responsible for local adaptation. The malaria vector, Anopheles gambiae, is associated with a latitudinal cline in aridity in Cameroon; a large inversion on chromosome 2L of this mosquito shows large differences in frequency along this cline, with high frequencies of the inverted karyotype present in northern, more arid populations and an almost complete absence of the inverted arrangement in southern populations. Here we use a genome resequencing approach to investigate patterns of population divergence along the cline. By sequencing pools of individuals from both ends of the cline as well as in the center of the cline—where the inversion is present in intermediate frequency—we demonstrate almost complete panmixia across collinear parts of the genome and high levels of differentiation in inverted parts of the genome. Sequencing of separate pools of each inversion arrangement in the center of the cline reveals large amounts of gene flux (i.e., gene conversion and double crossovers) even within inverted regions, especially away from the inversion breakpoints. The interplay between natural selection, migration, and gene flux allows us to identify several candidate genes responsible for the match between inversion frequency and environmental variables. These results, coupled with similar conclusions from studies of clinal variation in Drosophila, point to a number of important biological functions associated with local environmental adaptation.
Spectroscopic Properties of Cool Stars in the Sloan Digital Sky Survey: An Analysis of Magnetic Activity and a Search for Subdwarfs

We present a spectroscopic analysis of nearly 8000 late-type dwarfs in the Sloan Digital Sky Survey. Using the Hα emission line as an activity indicator, we investigate the fraction of active stars as a function of spectral type and find a peak near type M8, confirming previous results. In contrast to past findings, we find that not all M7–M8 stars are active. We show that this may be a selection effect of the distance distributions of previous samples, since the active stars appear to be concentrated near the Galactic plane. We also examine the activity strength (ratio of the luminosity emitted in Hα to the bolometric luminosity) for each star and find that the mean activity strength is constant over the range M0–M5 and declines at later types. The decline begins at a slightly earlier spectral type than previously found. We explore the effect that activity has on the broadband photometric colors and find no significant differences between active and inactive stars. We also carry out a search for subdwarfs using spectroscopic metallicity indicators and find 60 subdwarf candidates. Several of these candidates are near the extreme subdwarf boundary. The spectroscopic subdwarf candidates are redder by ∼0.2 mag in g-r compared with disk dwarfs at the same r-i color.
An Integrated Approach for Agricultural Ecosystem Management

Sustainable development and growth of agriculture sector calls for improving its competitiveness through a better understanding of lands, weather and climate, and planting, especially prediction of events with increased accuracy, and systematic integration of observations and prediction into decision-making in agriculture management. In this short paper, a systematic approach based on integrated information systems (IISs) for agricultural ecosystem management is proposed. The approach involves establishing an IIS called agricultural ecosystem enterprise information system (AEEIS) that extracts data on terrain, land use, planting, and others, and integrates them for the purpose of agricultural and ecosystem management. The integration helps in generating managerial/policy alternatives in consultation not only with agricultural and ecological specialists, but also with agriculture and ecosystems management. AEEIS, a platform of enterprise information systems, includes operational database, extract transform and load, data warehouse, data mining, simulation modeling, and knowledge management for generating managerial strategies on land use, planting species/variety, and optimal coverage of plants. AEEIS is part of efforts on integrated agricultural information services that is one of the main applications of China's sustainable agricultural development plan. The short paper concludes that, for effective management of agriculture and ecosystems, a systematic approach is essential in which IISs play a crucial role.
Automated Essay Scoring by Maximizing Human-Machine Agreement

Previous approaches for automated essay scoring (AES) learn a rating model by minimizing either the classification, regression, or pairwise classification loss, depending on the learning algorithm used. In this paper, we argue that the current AES systems can be further improved by taking into account the agreement between human and machine raters. To this end, we propose a rankbased approach that utilizes listwise learning to rank algorithms for learning a rating model, where the agreement between the human and machine raters is directly incorporated into the loss function. Various linguistic and statistical features are utilized to facilitate the learning algorithms. Experiments on the publicly available English essay dataset, Automated Student Assessment Prize (ASAP), show that our proposed approach outperforms the state-of-the-art algorithms, and achieves performance comparable to professional human raters, which suggests the effectiveness of our proposed method for automated essay scoring.
The LMP2A ITAM Is Essential for Providing B Cells with Development and Survival Signals In Vivo

ABSTRACT In Epstein-Barr virus-transformed B cells, known as lymphoblastoid cell lines (LCLs), LMP2A binds the tyrosine kinases Syk and Lyn, blocking B-cell receptor (BCR) signaling and viral lytic replication. SH2 domains in Syk mediate binding to a phosphorylated immunoreceptor tyrosine-based activation motif (ITAM) in LMP2A. Mutation of the LMP2A ITAM in LCLs eliminates Syk binding and allows for full BCR signaling, thereby delineating the significance of the LMP2A-Syk interaction. In transgenic mice, LMP2A causes a developmental alteration characterized by a block in surface immunoglobulin rearrangement resulting in BCR-negative B cells. Normally B cells lacking cognate BCR are rapidly apoptosed; however, LMP2A transgenic B cells develop and survive without a BCR. When bred into the recombinase activating gene 1 null (RAG−/−) background, all LMP2A transgenic lines produce BCR-negative B cells that develop and survive in the periphery. These data indicate that LMP2A imparts developmental and survival signals to B cells in vivo. In this study, LMP2A ITAM mutant transgenic mice were generated to investigate whether the LMP2A ITAM is essential for the survival phenotype in vivo. LMP2A ITAM mutant B cells develop normally, although transgene expression is comparable to that in previously described nonmutated LMP2A transgenic B cells. Additionally, LMP2A ITAM mutant mice are unable to promote B-cell development or survival when bred into the RAG−/− background or when grown in methylcellulose containing interleukin-7. These data demonstrate that the LMP2A ITAM is required for LMP2A-mediated developmental and survival signals in vivo.
Stability analysis of cooperation system of two robot arms

In this paper we study the stability problem of a hybrid system composed of two robots, where the appropriate cooperation of robots are expected to work efficiently. The performance of system depends directly upon one main factor: the coordination movement of the robots. The stability analysis of the system results in a model of uniform Euler-Bernoulli beams with linear and non-collocated boundary feedback controller. We prove that the system is exponentially stable with suitable choice of parameters of the system. In particular, we show that the system satisfies the spectrum determine growth condition.
Object selection using a spatial language for flexible assembly

In this paper we present a new simplified natural language that makes use of spatial relations between the objects in scene to navigate an industrial robot for simple pick and place applications. Developing easy to use, intuitive interfaces is crucial to introduce robotic automation to many small medium sized enterprises (SMEs). Due to their continuously changing product lines, reprogramming costs are far more higher than installation costs. In order to hide the complexities of robot programming we propose a natural language where the use can control and jog the robot based on reference objects in the scene. We used Gaussian kernels to represent spatial regions, such as left or above. Finally we present some dialogues between the user and robot to demonstrate the usefulness of the proposed system.
Risk tolerance during conflict: Evidence from Aleppo, Syria

When war breaks out, how important are risk preferences to explaining why some individuals stay in conflict zones while others take flight? We examine risk tolerance among rebel combatants and civilians in Aleppo, Syria using a variation of the Eckel-Grossman Choice Game. Field work in Syria was conducted in 2013–14 with a total of 232 participants to include both Syrian civilians and active rebel fighters in Aleppo and Idlib Province, as well as among Syrian refugees in neighboring Turkey. Compared to Syrians in other locations, people in rebel-held territory of Aleppo, both combatants and non-combatants, are significantly more risk tolerant. We consider possible explanations for elevated risk preferences in Aleppo based on self-selection, adaptive learning, a sense of self-efficacy to affect future outcomes, conflict-related grievances, and in-group solidarity. Our analysis suggests that self-selection based on access to resources and a strong sense of self-efficacy may explain higher propensity for risk-taking. Overall, our results speak to a plausible sorting mechanism during conflict where risk averse individuals select out of conflict, while highly risk tolerant individuals are more prone to discount the inherent dangers of remaining in conflict zones. Our results provide new micro-level explanation for why some societies become mired in conflict traps involving highly risk tolerant fighting communities.
A synthesis framework based on trace and automata theory

In this paper we present a method for modeling don't cares at high-level in a form that can be used by sequential logic synthesis. Behavior is specified by a set of concurrent, interacting processes. Each process is described formally by its set of execution traces and represented by an /spl omega/-automaton. This type of specification is formally precise and allows the inclusion of don't cares by allowing multiple execution traces for a given input. Moreover, it allows us to cast the synthesis problem into a language containment problem, and to provide a formal description of these don't cares. We have developed a prototype synthesis system based on this framework, targeting the synthesis of the control portion of a circuit. Starting from a hardware description language Hardware, a specification is expressed in terms of a set of interconnected /spl omega/-automata. We demonstrate the feasibility of the approach by showing the possibility of traversing the state space of the specification automata. <<ETX>>
Nonliteral understanding of number words

Significance Human communication is rife with nonliteral language, ranging from metaphor to irony to hyperbole. How do people go so far beyond the literal meaning of an utterance to infer the speaker’s intended meaning? We present a computational model that understands hyperbolic and other nonliteral uses of number words (e.g., “That watch costs 10,000 dollars”). Our model integrates empirically measured background knowledge, principles of communication, and reasoning about communicative goals to explain the computational basis of nonliteral language understanding. This framework sheds light on the nature of communication, marking a significant advancement in the flexibility and richness of formal models of language understanding. One of the most puzzling and important facts about communication is that people do not always mean what they say; speakers often use imprecise, exaggerated, or otherwise literally false descriptions to communicate experiences and attitudes. Here, we focus on the nonliteral interpretation of number words, in particular hyperbole (interpreting unlikely numbers as exaggerated and conveying affect) and pragmatic halo (interpreting round numbers imprecisely). We provide a computational model of number interpretation as social inference regarding the communicative goal, meaning, and affective subtext of an utterance. We show that our model predicts humans’ interpretation of number words with high accuracy. Our model is the first to our knowledge to incorporate principles of communication and empirically measured background knowledge to quantitatively predict hyperbolic and pragmatic halo effects in number interpretation. This modeling framework provides a unified approach to nonliteral language understanding more generally.
Body Weight, Length and Head Circumference at Birth in a Cohort of Turkish Newborns

Objective: Intrauterine growth references are primarily useful indicators in the assessment of the general health status of newborn infants. Although Lubchenco’s references are still used in many neonatal care units, we believe that there is a need for up-to-date intrauterine growth references specific for different populations. To develop gestational age-and gender-specific national references for birth weight, birth length and head circumference. Methods: Data were collected from neonatal records of perinatology services of eleven hospitals from January to December 2009. The anthropometry of a total of 4750 singleton live births born between 28 and 41 weeks of gestation were recorded. Means and standard deviations were calculated, and percentiles for each gender and gestational week were produced using the LMS program. The results were compared with US infants and also with local data. Results: Gestational age- and gender-specific 3rd, 5th, 10th, 15th, 25th, 50th, 75th, 85th, 90th, 95th and 97th percentile values were produced. Comparison of the 10th, 50th and 90th percentile values showed that the boys were heavier and longer than the girls. Head circumference values were also higher in the boys. Proportions of small for gestational age (SGA), appropriate for gestational age (AGA) and large for gestational age (LGA) infants in the sample were 10.1%, 79.1% and 10.8%, respectively. Conclusion: These gender- and gestational age-specific references will be of use in clinical practice and also for research purposes until more comprehensive, reliable and accessible national data pertaining to the intrauterine growth of Turkish infants are produced. Conflict of interest:None declared.
A Model of Perfect Pediatric Vaccination of Dengue with Delay and Optimal Control

A delayed mathematical model of Dengue dynamical transmission between vector mosquitoes and human, incorporating a control strategy of perfect pediatric vaccination is proposed in this paper. By some analytical skills, we obtain the existence of disease-free equilibria and endemic equilibrium, the necessary conditions of global asymptotical stability about two disease-free equilibria. Further, by Pontryagin’s maximum principle, we obtain the optimal control of the disease. Finally, numerical simulations are carried out to verify the correctness of the theoretical results and feasibility of the control measure.
Design and implementation of DSP-based three-phase PFC

In this study, DSP based three phase PFC system for switching devices such as switching mode power supplies has been designed and implemented. The experimental set uses MATLAB/SIMULINK compatible eZdsp F2812 target equipped with a TI TMS320F2812 DSP. The DSP produces the driving signals by realizing control algorithm, current control and PWM modulation methods. MATLAB/SIMULINK software has been used to modeling of control algorithm, current control and PWM modulation techniques. Therefore more flexible control system has been carried out while reducing software writing time. Experimental results show that, input current of PFC system is in phase with utility voltage and its total harmonic distortion (THD) is in the range described at international standards.
Chapter 4 Games , Learning , and Assessment

Scholars from various disciplines have recently shown increasing interest in using well-designed digital games to support learning (e.g., Gee, 2003 ; Prensky, 2006 ; Shaffer, Squire, Halverson, & Gee, 2005 ; Shute, Rieber, & Van Eck, 2011 ) . A common motivation for studying games as vehicles to support learning is frustration with the current education system and a desire for alternative ways of teaching—ways that increase student engagement and yield a rich, authentic picture of the learner(s). Frustration stems from the fact that most schools in the U.S. are not adequately preparing kids for success in the twentyfi rst century (e.g., Partnership for 21st Century Skills, 2006 ) . Learning in school is still heavily geared toward the acquisition of content within a teacher-centered model, with instruction too often abstract and decontextualized and thus not suitable for this age of complexity and interconnectedness (Shute, 2007 ) . One downside of this outdated pedagogy is that other developed countries of the world are surpassing the U.S. on measures of important competencies (e.g., mathematics problem solving) as assessed by international tests such as the PISA and TIMSS (Gonzales et al., 2008 ; Howard, Paul, Marisa, & Brooke, 2010 ) . To make the problem with today’s schools clearer, consider the following scenario involving a prototypical student. Maya (13 years old) is sitting in her bedroom with two of her friends. They are playing Little Big Planet —a digital game involving sack-person characters, clever and complex problems to solve, and compelling music and graphics. The game can not only be played (for countless hours), but it also provides tools to develop one’s own levels and worlds which can then be shared
Malicious URL sequence detection using event de-noising convolutional neural network

Attackers have increased the number of infected hosts by redirecting users of compromised popular websites toward websites that exploit vulnerabilities of a browser and its plugins. To prevent damage, detecting infected hosts based on proxy logs, which are generally recorded on enterprise networks, is gaining attention rather than blacklist-based filtering because creating blacklists has become difficult due to the short lifetime of malicious domains and concealment of exploit code. Since information extracted from one URL is limited, we focus on a sequence of URLs that includes artifacts of malicious redirections. We propose a system for detecting malicious URL sequences from proxy logs with a low false positive rate. To elucidate an effective approach of malicious URL sequence detection, we compared three approaches: individual-based approach, convolutional neural network (CNN), and our newly developed event de-noising CNN (EDCNN). Our EDCNN is a new CNN to reduce the negative effect of benign URLs redirected from compromised websites included in malicious URL sequences. Our evaluation shows that the EDCNN lowers the operation cost of malware infection by reducing 47% of false alerts compared with a CNN when users access compromised websites but do not obtain exploit code due to browser fingerprinting.
Knowledge Transfer in on-Collocated Software Architecture Development : From the Perspective of Analysts and Software

Learning within software development involves the transfer of knowledge between different yet interdependent functional teams. In reality however, these teams often create islands of knowledge due mostly to indistinct flow of knowledge transfer (KT), thus fail to take advantage of the opportunity to learn from each other. Taking the non-collocated software architecture development teams as a challenge, the goal of this study is to investigate the nature of KT that occurs between the analyst and software architect teams in non-collocated software architecture development. Data are collected from semi-structured interviews with 30 respondents consisting of industrial experts ranging from analyst, software architects and project managers. We managed to gather sufficient evidence that proves KT occurs, and successfully characterize the areas of knowledge used and exchanged, the interdependency between teams, the utilization of knowledge, the medium used for KT and finally, the external conditions surrounding KT during noncollocated software architecture development. These findings are useful as they rest a good understanding of KT and its vital elements in noncollocated software architecture development for all prospective researchers and practitioners.