Miracle-dz/UniFAR-FTUs huggingface dataset:
Small Eats Big: Ecology and Diversity of Bdellovibrio and Like Organisms, and their Dynamics in Predator-Prey Interactions

The ecological role of predation is well established in the animal world. Not so in the bacterial realm where the number of known bacterial predators is small and their phylogenetic affiliations largely unknown. The best-characterized bacterial predators belong to the Bdellovibrio-Bacteriovorax group (Bdellovibrio and like organisms, the BLOs). As predation at this trophic level may be of ecological significance, there is a need to better understand the diversity and the phylogeny of bacterial predators as well as the kinetics of their interactions with their prey. Such studies could also help to develop new approaches for the control of plant and animal Gram negative pathogenic bacteria. Here, we present a short review on the ecology, diversity and the taxonomy of predatory bacteria, with an emphasis on BLOs as well as on the dynamics of the interaction between a selected strain of Bdellovibrio bacteriovorus and its Erwinia carotovora subsp. carotovora prey under high and low predator:prey ratios.
Speech processing activates visual cortex in congenitally blind humans

Neurophysiological recordings and neuroimaging data in blind and deaf animals and humans suggest that perceptual functions may be organized differently after sensory deprivation. It has been argued that neural plasticity contributes to compensatory performance in blind humans, such as faster speech processing. The present study employed functional magnetic resonance imaging (fMRI) to map language‐related brain activity in congenitally blind adults. Participants listened to sentences, with either an easy or a more difficult syntactic structure, which were either semantically meaningful or meaningless. Results show that blind adults not only activate classical left‐hemispheric perisylvian language areas during speech comprehension, as did a group of sighted adults, but that they additionally display an activation in the homologueous right‐hemispheric structures and in extrastriate and striate cortex. Both the perisylvian and occipital activity varied as a function of syntactic difficulty and semantic content. The results demonstrate that the cerebral organization of complex cognitive systems such as the language system is significantly shaped by the input available.
Differential Psychological Impact of Internet Exposure on Internet Addicts

The study explored the immediate impact of internet exposure on the mood and psychological states of internet addicts and low internet-users. Participants were given a battery of psychological tests to explore levels of internet addiction, mood, anxiety, depression, schizotypy, and autism traits. They were then given exposure to the internet for 15 min, and re-tested for mood and current anxiety. Internet addiction was associated with long-standing depression, impulsive nonconformity, and autism traits. High internet-users also showed a pronounced decrease in mood following internet use compared to the low internet-users. The immediate negative impact of exposure to the internet on the mood of internet addicts may contribute to increased usage by those individuals attempting to reduce their low mood by re-engaging rapidly in internet use.
Towards a mHealth prototype to support integrated health care for elderly in Chilean Patagonia. A Design Case.

Based on a User Centered Design (UCD) approach, this paper describes the design and first validation process of a systemic model and a paper prototype for a mobile tool to support health data registering, related to physiotherapy of institutionalized frail elderly in nursing homes in the Chilean Patagonia. Given the lack of geriatricians and caregivers in the area, the goal is to optimize time and support integrated care, through making available a set of specific information for the health team, which would allow monitoring the patient's evolution in a timely and effectively manner. The design process led to define user profiles, content and a functional specification set. A field study and rapid contextual design instruments were used to validate the model for this context, so as the first pre-functional prototype to be developed in a next stage.
Infrared Image Denoising via L1/2 Sparse Representation over Learned Dictionary

Infrared (IR) images often have low resolution and vague details, resulting in lower image quality and poor visual effect. This paper comes up with an Infrared image denoising method via L1/2 sparse representation, while simultaneously training a over-complete dictionary on its content using the K-SVD algorithm. Experiment results have shown excellent denoising ability of the proposed denoising method, which can efficiently reduce Gaussian noise while exploiting much more image texture information.
Landscape-moderated biodiversity effects of agri-environmental management: a meta-analysis

Agri-environmental management (AEM) is heralded as being key to biodiversity conservation on farmland, yet results of these schemes have been mixed, making their general utility questionable. We test with meta-analysis whether the benefits of AEM for species richness and abundance of plants and animals are determined by the surrounding landscape context. Across all studies (109 observations for species richness and 114 observations for abundance), AEM significantly increased species richness and their abundance. More specifically, we test the hypothesis that AEM benefits species richness and abundance (i.e. increases the difference between fields with and without AEM) more in simple than in complex landscapes. In croplands, species richness but not abundance was significantly enhanced in simple but not in complex landscapes. In grasslands, AEM effectively enhanced species richness and abundance regardless of landscape context. Pollinators were significantly enhanced by AEM in simple but not in complex landscapes in both croplands and grasslands. Our results highlight that the one-size-fits-all approach of many agri-environmental programmes is not an efficient way of spending the limited funds available for biodiversity conservation on farmland. Therefore, we conclude that AEM should be adapted to landscape structure and the species groups at which they are targeted.
UV Radiation and Freshwater Zooplankton: Damage, Protection and Recovery

Abstract While many laboratory and field studies show that zooplankton are negatively affected when exposed to high intensities of ultraviolet radiation (UVR), most studies also indicate that zooplankton are well adapted to cope with large variations in their UVR exposure in the pelagic zone of lakes. The response mechanisms of zooplankton are diverse and efficient and may explain the success and richness of freshwater zooplankton in optically variable waters. While no single behavioural or physiological protection mechanism seems to be superior, and while several unexplained and contradictory patterns exist in zooplankton UVR ecology, recent increases in our understanding are consistent with UVR playing an important role for zooplankton. This review examines the variability in freshwater zooplankton responses to UVR, with a focus on crustacean zooplankton (Cladocera and Copepoda). We present an overview of UVR-induced damages, and the protection and recovery mechanisms freshwater zooplankton use when exposed to UVR. We review the current knowledge of UVR impact on freshwater zooplankton at species and community levels, and discuss briefly how global change over the last three decades has influenced the UVR milieu in lakes.
Distributed neural network-based policy gradient reinforcement learning for multi-robot formations

Multi-robot learning is a challenging task not only because of large and continuous state/action spaces, but also uncertainty and partial observability during learning. This paper presents a distributed policy gradient reinforcement learning (PGRL) methodology of a multi-robot system using neural network as the function approximator. This distributed PGRL algorithm enables each robot to independently decide its policy, which is, however, affected by all the other robots. Neural network is used to generalize over continuous state space as well as discrete/continuous action spaces. A case study on leader-follower formation application is performed to demonstrate the effectiveness of the proposed learning method.
Peptide Analysis and the Bioactivity of Whey Protein Hydrolysates from Cheese Whey with Several Enzymes

The aim of this study was identifying a suitable food grade enzymes to hydrolyze whey protein concentrates (WPCs), to give the highest bioactivity. WPCs from ultrafiltration retentate were adjusted to 35% protein (WPC-35) and hydrolyzed by enzymes, alcalase, α-chymotrypsin, pepsin, protease M, protease S, and trypsin at different hydrolysis times (0, 0.5, 1, 2, 3, 4, and 5 h). These 36 types of hydrolysates were analyzed for their prominent peptides β-lactoglobulin (β-Lg) and α-lactalbumin (α-La), to identify the proteolytic activity of each enzyme. Protease S showed the highest proteolytic activity and angiotensin converting enzyme inhibitory activity of IC50, 0.099 mg/mL (91.55%) while trypsin showed the weakest effect. Antihypertensive and antioxidative peptides associated with β-Lg hydrolysates were identified in WPC-35 hydrolysates (WPH-35) that hydrolyzed by the enzymes, trypsin and protease S. WPH-35 treated with protease S in 0.5 h, responded positively to usage as a bioactive component in different applications of pharmaceutical or related industries.
Sketch-Based Crowd Modelling

The creation of complex virtual worlds has expanded from the domain of designers and animators to that of general users with no background in computer graphics. Example applications are military simulations, urban planning, landscape design, search and rescue simulations, and social media technologies such as "Second Life". In many cases the user wants to create content containing hundreds or thousands of similar objects. Modelling and placing each individual object is infeasible and new ways must be found to allow users to easily specify the distribution of a large number of objects. In this paper we introduce a sketch-based approach for crowd modelling, which is intuitive and suitable for different input devices such as mice, sketch pads, and touch screens (Windows 7). We derive design requirements by analysing real environments and by testing users' abilities to characterise crowds and collections/accumulations of objects. Based on these requirements we formulate a model-by-example approach in which users sketch a sample distribution of objects and our tool computes the complete "population" of objects over a domain specified with a sketched contour. In order to deal with different distribution patterns we first characterise the input and then use clustering and texture synthesis to replicate the characteristics over the domain. Initial results demonstrate that the tool gives plausible results for random, regular and clustered input and that it can be used in a wide variety of modelling applications.
Subband CMA Adaptive Arrays in Multipath Fading Environment

SUMMARY CMA (Constant Modulus Algorithm) adaptive arraysare considered a promising method in mobile communica-tions to mitigate multipath fading and to suppress co-chan-nel interference signals. However, since a CMA adaptivearray assumes no a priori information of the desired signal,it is difficult to separate and combine the multipath rays ofthe desired signal. Therefore, when CMA is applied, theinput signal power of the multipath rays cannot be effi-ciently utilized. Moreover, since suppressing the multipathrays requires many degrees of freedom (DOFs) of the array,the array system becomes complicated. In this paper we propose the subband CMA adaptivearray which enhances the signal correlation between themultipath rays in each subband, as such the multipathfading effect can be greatly mitigated. By using thismethod, the multipath rays of the desired signal are equal-ized and combined, whereas an interference signal withmultipath rays can be suppressed by using a single DOF. ' 2000 Scripta Technica, Electron Comm Jpn Pt 1, 83(11):43Œ54, 2000Key words: CMA adaptive array; multipath fading;co-channel interference; filter banks; blind signal process-ing.
SSI Extends SSA

Static single information (SSI) is a new compiler intermediate representation. SSI is an extension of the popular static single assignment (SSA) form. We are currently incorporating SSI into the Machine SUIF compiler infrastructure. In this paper we give results to show that SSI can be computed almost as efficiently as SSA. We also present a method for forwards and backwards sparse data flow analysis using SSI.
Notice of RetractionResearch on the evaluation of innovative firms based on innovative capability

This paper analyzes the innovative capability which plays a key role in the formation of innovative firms. Innovative capability is the essence and survival foundation of innovative firms. Hence, when one is evaluating whether a firm is innovative, innovative capability must be placed in the heart of the evaluation. On this basis, this paper proposes the evaluation criteria and evaluation system for innovative firms based on innovative capability through questionnaire investigation and factor analysis.
The Triton Branch Predictor

We describe a new branch predictor that is designed to balanc e multiple constraints—predicting branch biases versus predicting s pecific branch instance behavior. Most branch instances only require branch bias informa tion for accurate predictions while a select few require more sophisticated prediction st ructures. Our predictor uses a cache mechanism to classify branches and dynamically adjus t the balance of the predictor. On average, our predictor mispredicts 24% less often th an YAGS and 19% less often than a global perceptron predictor with the same bit budget.
Extend argumentation frameworks based on degree of attack

To capture the quantity and quality properties of attacks in argumentation process, a fuzzy argumentation framework is presented in this paper. Degree of attack is introduced into argumentation, which contributes to formalizing the internal structure of arguments. Then based on probability theory, total attack is proposed to calculate the effect of all attacks. In addition, the extensional semantics for fuzzy argumentation frameworks are explored in the same way as for extended argumentation frameworks. Finally, the application of FAF in investigation is stated.
Effects of Human Hair Additives in Compressive Strength of Asphalt Cement Mixture

This experimental study presents the effects of human hair additives in compressive strength of asphalt cement mixture as potential binder in road pavement. Human hair is strong in tension and can be used as a fibre reinforcement material. Hair Fibre (HF) is an alternate non-degradable matter is available in abundance and at a very cheap cost. It also creates environmental problem for its decompositions. This elastic property of the HF reinforced in asphalt pavement may produce better stand on traffic loading by the same fundamental mechanism of transferring the high intensity forces imparted at the surface by the wheel loads to lower levels that the subgrade can accommodate without deforming. The experiments made were asphalt mixture with human hair as the experimental group and standard asphalt mixture being the control groups. Human hair added to standard asphalt mixture with three different proportions varying from 3% to 12% by mass of with respect to bitumen. This study proves that adding cement and human hair to asphalt mixture greatly increase the strength of the mixture thus making it a good material for the construction of road pavement. Adding of both cement and human hair to asphalt mixture improves the load bearing capacity of the mixture.
Night-time neuronal activation of Cluster N in a day- and night-migrating songbird

Magnetic compass orientation in a night‐migratory songbird requires that Cluster N, a cluster of forebrain regions, is functional. Cluster N, which receives input from the eyes via the thalamofugal pathway, shows high neuronal activity in night‐migrants performing magnetic compass‐guided behaviour at night, whereas no activation is observed during the day, and covering up the birds’ eyes strongly reduces neuronal activation. These findings suggest that Cluster N processes light‐dependent magnetic compass information in night‐migrating songbirds. The aim of this study was to test if Cluster N is active during daytime migration. We used behavioural molecular mapping based on ZENK activation to investigate if Cluster N is active in the meadow pipit (Anthus pratensis), a day‐ and night‐migratory species. We found that Cluster N of meadow pipits shows high neuronal activity under dim‐light at night, but not under full room‐light conditions during the day. These data suggest that, in day‐ and night‐migratory meadow pipits, the light‐dependent magnetic compass, which requires an active Cluster N, may only be used during night‐time, whereas another magnetosensory mechanism and/or other reference system(s), like the sun or polarized light, may be used as primary orientation cues during the day.
Alteration of Enzyme Aspartate Transaminase in Goat milk related to Udder Health Status

The present experiment was conducted to study variations in milk SCC and pH, along with activity of whey enzyme Aspartate transaminase (AST) in relation to different udder health status of goats. The average values of milk SCC, pH, and AST differed significantly (P<0.01) among various udder health status of goat. The mean difference for SCC of milk showed significant (P<0.01) differences for all the comparisons varying from 6.88 to 41.88 x 105 cells/ml. The average milk pH values ranged from 6.40 ± 0.09 to 7.36 ± 0.01. The milk SCC and pH increased by 1.039 x 105 cells/ml and 0.24 respectively for each unit rise in CMT score. Similarly, the activity of AST increased by 14.04 AST U/ml for each unit rise in CMT score.
The DETER project: Advancing the science of cyber security experimentation and test

Since 2004, the DETER Cybersecurity Testbed Project has worked to create the necessary infrastructure — facilities, tools, and processes-to provide a national resource for experimentation in cyber security. The next generation of DETER envisions several conceptual advances in testbed design and experimental research methodology, targeting improved experimental validity, enhanced usability, and increased size, complexity, and diversity of experiments. This paper outlines the DETER project's status and current R&D directions.
An Approach to Using Existing Online Education Tools to Support Practical Education on MOOCs

MOOCs are popular for online education because of its convenience and excellent educational resources. At present, MOOCs just provide very limited online practical environments such as online tests, quizzes and online judge etc., but they have not provided students with some dynamic and operable online practical environments, such as interactive education tools etc. Online education tools can satisfy the needs of online practicing, mainly because of its abundance, interactivity and convenience, but MOOCs have not made full use of these online tools yet. The paper proposes an approach to using existing online education tools to support practical education on MOOCs by two enhancements: educational resources development and real-time collaborative learning. The key to the approach is operation reuse, which involves recording, optimizing and replaying user operations on existing online educations tools. Based on the approach, we develop an education platform called Smart Web Tutor. Case study is performed to analyze user experience, and the results show that our approach contributes to students' learning, especially for real-time collaborative learning. Also, some suggestions from students are inspiring to further increase the utility and user experience of our approach and education platform.
PRIOR EMISSION MODEL FOR X-RAY PLATEAU PHASE OF GAMMA-RAY BURST AFTERGLOWS

The two-component emission model to explain the plateau phase of the X-ray afterglows of gamma-ray bursts (GRBs) is proposed. One component, which is responsible for the plateau and subsequent normal decay phase of the X-ray afterglow, is the prior emission via outflow ejected from the central engine before the main burst. The other is the main outflow, which causes the prompt GRB emission and the initial steep decay phase of the X-ray afterglow. In this model, the transition from the plateau to the subsequent normal decay phase is an artifact of the choice of the zero of time. For events with distinct plateau phase, the central engine is active 103–104 s before the launch of the main outflow. According to this model, a prior emission in the X-ray and/or optical bands 103–104 s before the prompt GRB emission is possibly seen, which will be tested by near-future instruments such as Monitor of All-sky X-ray Image (MAXI), WIDe-field telescope for GRB Early Timing (WIDGET), and so on.
Tumor evolutionary directed graphs and the history of chronic lymphocytic leukemia

Cancer is a clonal evolutionary process, caused by successive accumulation of genetic alterations providing milestones of tumor initiation, progression, dissemination, and/or resistance to certain therapeutic regimes. To unravel these milestones we propose a framework, tumor evolutionary directed graphs (TEDG), which is able to characterize the history of genetic alterations by integrating longitudinal and cross-sectional genomic data. We applied TEDG to a chronic lymphocytic leukemia (CLL) cohort of 70 patients spanning 12 years and show that: (a) the evolution of CLL follows a time-ordered process represented as a global flow in TEDG that proceeds from initiating events to late events; (b) there are two distinct and mutually exclusive evolutionary paths of CLL evolution; (c) higher fitness clones are present in later stages of the disease, indicating a progressive clonal replacement with more aggressive clones. Our results suggest that TEDG may constitute an effective framework to recapitulate the evolutionary history of tumors. DOI: http://dx.doi. org/10.7554/eLife.02869. 001
After Motherhood : E ¤ ects of Maternity Leave and E ¤ ort Reallocation on Earnings

It is well documented that women with children earn less than women without children. To study this wage gap I construct a dynamic model of human capital accumulation in a setting where labor force participation is endogenous and labor supply is measured by hours and e¤ort. The model establishes relationships between optimal maternity leave duration and time and e¤ort allocations before and after the leave. I employ the model to address the key explanations found in the family gap literature: the e¤ects of career interruptions, time and energy demands of child care and selection into motherhood. Using theoretical predictions, I develop an empirical decomposition strategy to evaluate each explanation. The results suggest that the main reason for lower wages of mothers is the loss of human capital. On average, mothers do not reduce their work e¤ort. Also, I nd no evidence that the motherhood wage gap is driven by selection. Keywords: motherhood wage gap; human capital; time allocation; e¤ort allocation. JEL classi cation: C52, J22, J24, J31.
Performance analysis of multiuser receivers for large CDMA random access systems over rayleigh fading channels

The random access systems, exploiting multiuser detectors such as MMSE detector and decorrelator, over large random spreading CDMA channel subject to Rayleigh fading is investigated, under the assumption of infinite number of users, infinite spreading gain, and their ratio converging to a constant. The signal to interference ratio (SIR) is shown to converge almost surely to a constant and the bit-error rate (BER) limit is a function of the transmission probability and traffic load. The throughput and spectrum efficiency are analyzed, and confirmed by simulation results.