Miracle-dz/UniFAR-FTUs huggingface dataset:
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Reductive genome evolution in Buchnera aphidicola

We have sequenced the genome of the intracellular symbiont Buchnera aphidicola from the aphid Baizongia pistacea. This strain diverged 80–150 million years ago from the common ancestor of two previously sequenced Buchnera strains. Here, a field-collected, nonclonal sample of insects was used as source material for laboratory procedures. As a consequence, the genome assembly unveiled intrapopulational variation, consisting of ≈1,200 polymorphic sites. Comparison of the 618-kb (kbp) genome with the two other Buchnera genomes revealed a nearly perfect gene-order conservation, indicating that the onset of genomic stasis coincided closely with establishment of the symbiosis with aphids, ≈200 million years ago. Extensive genome reduction also predates the synchronous diversification of Buchnera and its host; but, at a slower rate, gene loss continues among the extant lineages. A computational study of protein folding predicts that proteins in Buchnera, as well as proteins of other intracellular bacteria, are generally characterized by smaller folding efficiency compared with proteins of free living bacteria. These and other degenerative genomic features are discussed in light of compensatory processes and theoretical predictions on the long-term evolutionary fate of symbionts like Buchnera.
Using wavelet network in nonparametric estimation

Wavelet networks are a class of neural networks consisting of wavelets. In this paper, algorithms for wavelet network construction are proposed for the purpose of nonparametric regression estimation. Particular attentions are paid to sparse training data so that problems of large dimension can be better handled. A numerical example on nonlinear system identification is presented for illustration.
Promotion of atrial fibrillation by heart failure in dogs: atrial remodeling of a different sort.

BACKGROUND Studies of atrial fibrillation (AF) due to atrial tachycardia have provided insights into the remodeling mechanisms by which "AF begets AF" but have not elucidated the substrate that initially supports AF before remodeling occurs. We studied the effects of congestive heart failure (CHF), an entity strongly associated with clinical AF, on atrial electrophysiology in the dog and compared the results with those in dogs subjected to rapid atrial pacing (RAP; 400 bpm) with a controlled ventricular rate (AV block plus ventricular pacemaker at 80 bpm). METHODS AND RESULTS CHF induced by 5 weeks of rapid ventricular pacing (220 to 240 bpm) increased the duration of AF induced by burst pacing (from 8+/-4 seconds in control dogs to 535+/-82 seconds; P<0.01), similar to the effect of 1 week of RAP (713+/-300 seconds). In contrast to RAP, CHF did not alter atrial refractory period, refractoriness heterogeneity, or conduction velocity at a cycle length of 360 ms; however, CHF dogs had a substantial increase in the heterogeneity of conduction during atrial pacing (heterogeneity index in CHF dogs, 2. 76+/-0.16 versus 1.46+/-0.10 for control and 1.51+/-0.06 for RAP dogs; P<0.01) owing to discrete regions of slow conduction. Histological examination revealed extensive interstitial fibrosis (connective tissue occupying 12.8+/-1.9% of the cross-sectional area) in CHF dogs compared with control (0.8+/-0.3%) and RAP (0. 9+/-0.2%) dogs. CONCLUSIONS Experimental CHF strongly promotes the induction of sustained AF by causing interstitial fibrosis that interferes with local conduction. The substrates of AF in CHF are very different from those of atrial tachycardia-related AF, with important potential implications for understanding, treating, and preventing AF related to CHF.
Vocational Interest Regarding Career Awareness among Adolescent Boys and Girls of Rohtak City; Haryana (India)

All young are deeply concerned about their future vocational roles. Vocation is valued by most adolescents, for its contributions to self-esteem, financial independence, and social maturity. The present study is done to find out the gender difference in the vocational interest of high school adolescents. The sample for the investigation consisted of 300 adolescents (150 boys & 150 girls) studying in 10th class. The sample was taken from six schools of Rohtak city. The standardized tool was used to measure the variable Vocational Interest Record (VIR). For analysis of data, mean, standard deviation, and t-test were computed. The results of the study revealed that the gender difference in vocational interest was seen. Results indicated that t scores on artistic, agricultural, social and household dimensions of vocational interest were significant. Significant different exists between boys and girls on above vocational areas. Girls were high on artistic, social and household jobs as compared to boys whereas boys were high on agricultural jobs.
Energy-aware thermal comfort-band maintenance scheduling under peak power constraint

Peak energy consumption has impact on upfront capital costs and hence on energy tariffs. Reducing the size of the peaks has been recognized as an important consideration in the design of efficient demand-response systems. A substantial fraction of the energy demand of buildings comes from air-conditioners, refrigerators and room-heaters. These thermostatically controlled electrical devices (TCED) maintain the temperature of the environment under its control within a desired comfort-band. Based on the insight gained by empirical observations, this paper presents a technique, which is energy-aware in scheduling TCEDs for maintaining comfort-band when peak power constraint limits the number of devices that can run at a time.
Grey Matter and White Matter Ischemic Damage is Reduced by the Competitive AMPA Receptor Antagonist, SPD 502

Protection of both grey and white matter is important for improvement in stroke outcome. In the present study the ability of a competitive α-amino-3-hydroxy-5-methyl-4-isoxazole propionic acid (AMPA) antagonist to protect axons, oligodendrocytes, and neuronal perikarya, was examined in a rodent model of transient focal cerebral ischemia. SPD 502 (8-methyl-5-(4-(N,N-dimethylsulfamoyl)phenyl)-6,7,8,9-tetrahydro-1H-pyrrolo[3,2h]-isoquinoline-2,3-dione-3-o(4-hydroxybutyricacid-2-yl)oxime) was administered as an intravenous bolus (16 mg/kg) 15 minutes before transient (3-hour) middle cerebral artery (MCA) occlusion, followed by an intravenous infusion (16 mg kg−1 hr−1) of the drug for 4 hours. Twenty-one hours after ischemia, axonal damage was reduced by 45% (P = 0.006) in the SPD 502–treated group compared with the vehicle. The anatomic extent of ischemically damaged oligodendrocytes, determined by Tau1 immunoreactivity, was reduced in the cerebral cortex by 53% (P = 0.024) in SPD 502–treated rats compared with vehicle-treated rats, but there was minimal effect in the subcortex. The volume of neuronal perikaryal damage after MCA occlusion was significantly reduced by SPD 502 in the cerebral cortex (by 68%; P = 0.005), but there was minimal change in the subcortex with drug treatment. The AMPA receptor antagonist significantly reduced the anatomic extent of lipid peroxidation (assessed as the volume of 4-hydroxynonenol immunoreactivity), and this may have contributed to its ability to protect multiple cell types in ischemia. The data demonstrate that AMPA blockade protects both grey and white matter from damage induced by transient focal ischemia.
A Bacterial Pathogen Co-opts Host Plasmin to Resist Killing by Cathelicidin Antimicrobial Peptides*

Background: Group A Streptococcus (GAS) produces streptokinase (Ska), which activates plasminogen to plasmin while binding the host enzyme to the bacterial surface. Results: Ska-activated plasmin can degrade human cathelicidin LL-37, promoting GAS resistance to the antimicrobial peptide. Conclusion: Ska contributes to GAS innate immune evasion and virulence. Significance: A human pathogen can co-opt the activity of a host protease to subvert peptide-based innate immune defense. The bacterial pathogen Group A Streptococcus (GAS) colonizes epithelial and mucosal surfaces and can cause a broad spectrum of human disease. Through the secreted plasminogen activator streptokinase (Ska), GAS activates human plasminogen into plasmin and binds it to the bacterial surface. The resulting surface plasmin protease activity has been proposed to play a role in disrupting tissue barriers, promoting invasive spread of the bacterium. We investigated whether this surface protease activity could aid the immune evasion role through degradation of the key innate antimicrobial peptide LL-37, the human cathelicidin. Cleavage products of plasmin-degraded LL-37 were analyzed by matrix-assisted laser desorption ionization mass spectrometry. Ska-deficient GAS strains were generated by targeted allelic exchange mutagenesis and confirmed to lack surface plasmin activity after growth in human plasma or media supplemented with plasminogen and fibrinogen. Loss of surface plasmin activity left GAS unable to efficiently degrade LL-37 and increased bacterial susceptibility to killing by the antimicrobial peptide. When mice infected with GAS were simultaneously treated with the plasmin inhibitor aprotinin, a significant reduction in the size of necrotic skin lesions was observed. Together these data reveal a novel immune evasion strategy of the human pathogen: co-opting the activity of a host protease to evade peptide-based innate host defenses.
Evidence for a Developmental Role for TLR4 in Learning and Memory

Toll-like receptors (TLRs) play essential roles in innate immunity and increasing evidence indicates that these receptors are expressed in neurons, astrocytes and microglia in the brain where they mediate responses to infection, stress and injury. Very little is known about the roles of TLRs in cognition. To test the hypothesis that TLR4 has a role in hippocampus-dependent spatial learning and memory, we used mice deficient for TLR4 and mice receiving chronic TLR4 antagonist infusion to the lateral ventricles in the brain. We found that developmental TLR4 deficiency enhances spatial reference memory acquisition and memory retention, impairs contextual fear-learning and enhances motor functions, traits that were correlated with CREB up-regulation in the hippocampus. TLR4 antagonist infusion into the cerebral ventricles of adult mice did not affect cognitive behavior, but instead affected anxiety responses. Our findings indicate a developmental role for TLR4 in shaping spatial reference memory, and fear learning and memory. Moreover, we show that central TLR4 inhibition using a TLR4 antagonist has no discernible physiological role in regulating spatial and contextual hippocampus-dependent cognitive behavior.
Dressing and wrapping

We prove that the validity of the recently proposed dressed, asymptotic Bethe ansatz for the planar AdS/CFT system is indeed limited at weak coupling by operator wrapping effects. This is done by comparing the Bethe ansatz predictions for the four-loop anomalous dimension of finite-spin twist-two operators to BFKL constraints from high-energy scattering amplitudes in gauge theory. We find disagreement, which means that the ansatz breaks down for length-two operators at four-loop order. Our method supplies precision tools for multiple all-loop tests of the veracity of any yet-to-be constructed set of exact spectral equations. Finally we present a conjecture for the exact four-loop anomalous dimension of the family of twist-two operators, which includes the Konishi field.
Modeling State Diagrams with And-Cross Transitions

We propose an approach to encode state diagrams with and-cross transitions. The notion of and-cross transitions is being rejected by researchers and practitioners in model-driven engineering community for reasons that include limited use-inpractice, unmanageable underlying complexity, and availability of alternative modeling solutions. In this paper, we show that and-cross transitions can be useful in practice and its underlying structural complexity can be managed for the purpose of analysis.
Neural substrates of semantic memory

Semantic memory is described as the storage of knowledge, concepts, and information that is common and relatively consistent across individuals (e.g., memory of what is a cup). These memories are stored in multiple sensorimotor modalities and cognitive systems throughout the brain (e.g., how a cup is held and manipulated, the texture of a cup's surface, its shape, its function, that is related to beverages such as coffee, and so on). Our ability to engage in purposeful interactions with our environment is dependent on the ability to understand the meaning and significance of the objects and actions around us that are stored in semantic memory. Theories of the neural basis of the semantic memory of objects have produced sophisticated models that have incorporated to varying degrees the results of cognitive and neural investigations. The models are grouped into those that are (1) cognitive models, where the neural data are used to reveal dissociations in semantic memory after a brain lesion occurs; (2) models that incorporate both cognitive and neuroanatomical information; and (3) models that use cognitive, neuroanatomic, and neurophysiological data. This review highlights the advances and issues that have emerged from these models and points to future directions that provide opportunities to extend these models. The models of object memory generally describe how category and/or feature representations encode for object memory, and the semantic operations engaged in object processing. The incorporation of data derived from multiple modalities of investigation can lead to detailed neural specifications of semantic memory organization. The addition of neurophysiological data can potentially provide further elaboration of models to include semantic neural mechanisms. Future directions should incorporate available and newly developed techniques to better inform the neural underpinning of semantic memory models. (JINS, 2007, 13, 865–880.)
Fractal Dimension: An Index to Quantify Parameters in Genetic Algorithms

— Genetic Algorithms (GAs) are direct searching methods which require little information from design space. This characteristic beside robustness of these algorithms makes them to be very popular in recent decades. On the other hand, while this method is employed, there is no guarantee to achieve optimum results. This obliged designer to run such algorithms more than one time to achieve more reliable results. There are many attempts to modify the algorithms to make them more efficient. In this paper, by application of fractal dimension (particularly, Box Counting Method), the complexity of design space are established for determination of mutation and crossover probabilities ( P m and P c ). This methodology is followed by a numerical example for more clarification. It is concluded that this modification will improve efficiency of GAs and make them to bring about more reliable results especially for design space with higher fractal dimensions.
Using Different Methods to Access the Difficult Task of Delimiting Species in a Complex Neotropical Hyperdiverse Group

The genus Rineloricaria is a Neotropical freshwater fish group with a long and problematic taxonomic history, attributed to the large number of species and the pronounced similarity among them. In the present work, taxonomic information and different molecular approaches were used to identify species boundaries and characterize independent evolutionary units. We analyzed 228 samples assembled in 53 distinct morphospecies. A general mixed yule-coalescent (GMYC) analysis indicated the existence of 70 entities, while BOLD system analyses showed the existence of 56 distinct BINs. When we used a new proposed integrative taxonomy approach, mixing the results obtained by each analysis, we identified 73 OTUs. We suggest that Rineloricaria probably has some complexity in the known species and several species not formally described yet. Our data suggested that other hyperdiverse fish groups with wide distributions can be further split into many new evolutionary taxonomic units.
Infrastructure for intrusion detection and response

Automated response to intrusions has become a major issue in defending critical systems. Because the adversary can take actions at computer speeds, systems need the capability to react without human intervention. An infrastructure that supports development of automated response systems is critically needed. This infrastructure must allow easy integration of detection and response components to enable experimentation with automated response strategies. This paper provides an overview of the intruder detection and isolation protocol (IDIP) architecture and how it supports the need for an intrusion detection and response infrastructure.
Real-time low-power task mapping in Networks-on-Chip

Many state-of-the-art approaches to power minimisation in Networks-on-Chip (NoC) are based on the reduction of the communication paths taken by packets over the interconnect. This is often done by optimising the packet routing, the allocation of tasks that produce and consume those packets, or both. In all cases, the optimisation affects the timeliness of the packets, because changes will occur in the way resources are shared at the platform cores (as tasks are reallocated) and NoC links (as packet routes are changed). In this paper, we propose an optimisation technique that is able to minimise power dissipation without sacrificing timing constraints, thus suitable to systems with hard real-time requirements. It is based on a Genetic Algorithm (GA) that evolves chromosomes representing the mapping of tasks to cores, guided by a multi-objective fitness function that combines power estimation macromodels and real-time schedulability analysis.
Mental representation and imagery in program comprehension

This paper studies the role of imagery in program comprehension. With this goal we investigated whether theories of mental models from Psychology of Programming (e.g., Pennington’s Two Stages Theory) could be expanded to account for the effect of imagery. Given the basic research in image processing, our hypothesis is that imagery would allow a quicker access to the functional (Data Flow) information of programs. Then, Visual Programming Languages should allow for quicker construction of a mental representation based on Data Flow relationships of a program than procedural languages. To test this hypothesis we ran an experiment where we accessed the mental model of C and spreadsheet programmers in different program comprehension situations. The results showed evidence that the spreadsheet programmers developed Data Flow based mental representations in all situations while C programmers seemed to access to a Control Flow based mental representation first.
Design of multi-objective UPFC employing backtracking search algorithm for enhancement of power system stability

In the arena of power system, small signal stability is one of the most important issue to be settled down. In relatively weak tie line interconnections, these low frequency oscillations are observed. Use of Flexible AC Transmission System (FACTS) devices is playing most important roles in damping out of those oscillations. Unified Power Flow Controller (UPFC), one of the key members of FACTS family is being used in long and high voltage transmission networks of modern power system. Tuning of the UPFC parameters in real time power system application is a multi-objective optimization problem. In this paper the parameters of UPFC has been optimized employing a novel optimization approach, Backtracking Search Algorithm (BSA). The efficacy of the proposed BSA tuned UPFC has been investigated by comparing the time domain simulation results with fixed gain conventional UPFC. Additionally, the Eigenvalues of optimized and conventional UPFC of the power system has also been compared.
Attack Generation for NIDS Testing Using Natural Deduction

A common way to elude a signature-based NIDS is to transform a n attack instance that the NIDS recognizes into another instance that it fails to recognize . For example, to avoid matching between the attack payload and the NIDS signature, attackers split the p ayload into several TCP packets, change it syntactically while preserving its semantics, or hide it be tween benign messages. We study attackers’ ability to find attack instances that elude a NIDS and our abil ity to recognize such instances. We observe that different instances of a given attack can be d erived from each other using simple transformations that change either the attack transport me chanism or its payload. We model these transformations as inference rules in a formal natural deduction system. Starting from an exemplary attack instance, we use an inference engine to automatically gener ate all possible instances derived from a particular collection of rules. The result is a simple yet power ful tool capable of both generating attack instances for NIDS testing and determining whether a given s equence of packets is an attack. During several testing phases using different sets of rules , our tool exposed serious vulnerabilities in Snort—a widely deployed NIDS. Attackers acquainted with th ese vulnerabilities would have been able to construct instances that elude Snort for any TCP-based at tack, any Web-CGI attack, and any attack whose signature is a certain type of regular expression.
A brief review of `little string theories'

This is a brief review of the current state of knowledge on `little string theories', which are non-gravitational theories having several string-like properties. We focus on the six-dimensional maximally supersymmetric `little string theories' and describe their definition, some of their simple properties, the motivations for studying them, the discrete lightcone quantization and holographic constructions of these theories and their behaviour at finite energy density.
Topological Observations on Multiplicative Additive Linear Logic

As an attempt to uncover the topological nature of composition of strategies in game semantics, we present a ``topological'' game for Multiplicative Additive Linear Logic without propositional variables, including cut moves. We recast the notion of (winning) strategy and the question of cut elimination in this context, and prove a cut elimination theorem. Finally, we prove soundness and completeness. The topology plays a crucial role, in particular through the fact that strategies form a sheaf.