Miracle-dz/UniFAR-FTUs huggingface dataset:
Semidefinite Programs on Sparse Random Graphs

Denote by $A$ the adjacency matrix of an Erd\H{o}s-Renyi graph with bounded average degree. We consider the problem of maximizing $\langle A-{\mathbb E}\{A\},X\rangle$ over the set of positive semidefinite matrices $X$ with diagonal entries $X_{ii}=1$. We prove that for large (bounded) average degree $\gamma$, the value of this semidefinite program (SDP) is -with high probability- $2n\sqrt{\gamma} + n\, o(\sqrt{\gamma})+ o(n)$. Our proof is based on two tools from different research areas. First, we develop a new `higher-rank' Grothendieck inequality for symmetric matrices. In the present case, our inequality implies that the value of the above SDP is arbitrarily well approximated by optimizing over rank-$k$ matrices for $k$ large but bounded. Second, we use the interpolation method from spin glass theory to approximate this problem by a second one concerning Wigner random matrices instead of sparse graphs. As an application of our results, we prove new bounds on community detection via SDP that are substantially more accurate than the state of the art.
On computing per-session performance bounds in high-speed multi-hop computer networks

We present a technique for computing upper bounds on the distribution of individual per-session performance measures such as delay and buffer occupancy for networks in which sessions may be routed over several “hops. ” Our approach is based on first stochastically bounding the distribution of the number of packets (or cells) which can be generated by each traffic source over various lengths of time and then “pushing” these bounds (which are then shown to hold over new time interval lengths at various network queues) through the network on a per-session basis. Session performance bounds can then be computed once the stochastic bounds on the arrival process have been characterized for each session at all network nodes. A numerical example is presented and the resulting distributional bounds compared with simulation as well as with a point-valued worst-case performance bound.
Antibody-resistant mutants of Borrelia burgdorferi: in vitro selection and characterization

We used polyclonal antisera and monoclonal antibodies (mAbs) to inhibit the growth of clonal populations of two strains of Borrelia burgdorferi, the Lyme disease agent, and thereby select for antibody- resistant mutants. mAbs were directed at the outer membrane proteins, OspA or OspB. Mutants resistant to the growth-inhibiting properties of the antibodies were present in the populations at frequencies ranging from 10(-5) to 10(-2). The several escape variants that were examined were of four classes. Class I mutants were resistant to all mAbs; they lacked OspA and OspB and the linear plasmid that encodes them. Two other proteins were expressed in larger amounts in class I mutants; mAbs to these proteins inhibited the mutant but not the wild-type cells. Class II mutants were resistant to some but not all mAbs; they had truncated OspA and/or OspB proteins. Class III mutants were resistant only to the selecting mAb; they had full-length Osp proteins that were not bound by the selecting antibody in Western blots. In two class III mutants resistant to different anti-OspA mAbs, missense mutations were demonstrated in the ospA genes. Class IV mutants were likewise resistant only to selecting antibody, but in this case the selecting antibody still bound in Western blots.
Pregnancy, Maternal Tobacco Smoking, and Early Age Leukemia in Brazil

Background: Cigarette smoking has been associated with acute myeloid leukemia (AML) but hypothesis on the association between maternal smoking during pregnancy and childhood leukemia remains unclear. Objectives: To investigate the association between maternal exposure to tobacco smoking during pregnancy and early age (<2 year) leukemia (EAL). Methods: A hospital-based multicenter case-control study aiming to explore EAL risk factors was carried out in Brazil during 1999–2007. Data were collected by direct interview with the biological mothers using a standardized questionnaire. The present study included 675 children (193 acute lymphoid leukemia – ALL, 59 AML and 423 controls), being the latter age frequency matched and paired by area of residence with the cases. Unconditional logistic regression was performed, and odds ratios (OR) on the association between tobacco smoking (3 months before pregnancy, during pregnancy, and 3 months after delivery) and EAL were ascertained after adjustment for selected variables (maternal age at birth and education, birth weight, infant skin color, and oral contraceptives use during pregnancy). Results: Smoking was reported by 17.5% of case mothers and 20.6% of controls. Among women who reported to have smoked 20 or more cigarettes during the index pregnancy, an adjusted OR = 5.28 (95% CI 1.40–19.95) for ALL was observed. Heavy smoking during breastfeeding yielded an adjusted risk estimate for ALL, OR = 7.78 (95% CI 1.33–45.5). No dose-response effect was observed according to smoking exposure during pregnancy and EAL. An association between secondhand smoking during pregnancy or breastfeeding was not observed. Conclusion: An association between maternal smoking and EAL in the offspring was restricted to women who have reported an intense exposure to tobacco smoke during pregnancy and breastfeeding.
Autonomous broadcast pruning in wireless ad hoc networks using coverage estimation

Purpose – The purpose of this paper is to find a practical method to minimize unnecessary rebroadcasts for ad hoc networks in a remote area.Design/methodology/approach – The authors design a theoretical coverage estimation model for autonomous broadcast pruning. To verify the effect of the model, simulations are performed to evaluate the effect of confidence level and the actual performance by using ns2 network simulator.Findings – The algorithm used to predict the coverage area of broadcasts can minimize unnecessary rebroadcasts.Originality/value – Autonomous broadcast pruning scheme based on the local prediction of a remained coverage area in the on‐going broadcast process brings us beneficial results in terms of energy savings and limited bandwidth preservation.
Future challenges

The central question addressed by the papers in this special feature lies at the core of the emerging science of sustainability. What is the decision-science needed to address sustainability issues, and how does it differ from existing decision-science? The answer is not at all obvious. Many, if not the majority, of decision scientists still take the view that sustainability changes nothing but the label placed on long-standing research questions. After all, the field of resource economics has focused on the sustainable use of renewable resources since the mid-1950s (1) and on sustainable development based on the extraction of nonrenewable resources since the mid-1970s (2). The basic insights that support both foci were developed even earlier (3), while concern over the sustainability of mineral extraction has been a recurrent theme since Jevons's 19th-century speculations on the coal question (4). Others argue, however, that we are seeing the beginning of a major change in the way the science of human use and impacts on the environment is being done. The focus on panaceas provides Ostrom and colleagues with a hook to explore these arguments.
Aetiology and prognosis of bacteraemia in Italy

A prospective multi-centre study was conducted to assess the microbiological pattern and prognostic factors of bacteraemia and their impact on clinical outcome. All patients admitted to 41 Italian hospitals over 2 months, from whom one or more clinically significant organisms were isolated from blood culture, were studied according to a standardized protocol and case definition. A total of 156 episodes of bacteraemia were identified in 20601 patients. There were 3·9 episodes of nosocomially acquired bacteraemia and 3·7 episodes of community-acquired bacteraemia per 1000 admissions. The most frequent pathogens isolated were Gram-negative bacteria (44·9%) but Gram-positive species accounted for 40·4% of episodes. Fungal infections due to Candida spp. were found in 3·8% of episodes, and multiple pathogens were recovered from 9·6% of episodes. The clinical response to bacteraemia was classified as sepsis in 90 episodes (57·7%), severe sepsis in 21 (13·5%) and septic shock in 26 (16·7%); 19 episodes (12·2%) showed no clinical response. The total in-hospital mortality was 25·0%. By multivariate logistic regression, the variables which independently predicted mortality were increasing age, the presence of septic shock, infection with Gram-positive bacteria or fungi and nosocomial acquisition.
Attention Deficit Hyperactivity Disorder: Anxiety Phenomena in Children Treated with Psychostimulant Medication for 6 Months or More

Objective: The intermediate- to long-term use of psychostimulant medication has unclear benefits on the core symptoms of attention deficit hyperactivity disorder (ADHD) and delayed onset affective symptom side effects which can mimic these core ADHD symptoms. ‘ADHD and anxiety’ has also been associated with a poor response to short-term psychostimulant medication treatment. In addition, it is unclear whether ‘ADHD and anxiety’ should be defined from the child's and/or the parent's perspective. We propose that anxiety will be increased in children with ADHD who are treated with psychostimulant medication in the intermediate- to long-term who are identified by clinicians as poor responders. Method: Twenty children with ADHD who were medicated for 6 months or more and who had ongoing core symptoms of ADHD were compared to 20 age- and IQ-matched children with ADHD who were medication-naive. Chi-squared tests were performed on the categorical dependent variables and independent t-tests on the dependent continuous variables. Results: Anxiety is significantly increased in children with ADHD treated with psychostimulant medication in the intermediate- to long-term who are noted by clinicians to have ongoing core symptoms of ADHD. This statistically significant finding is evident with both categorical and dimensional measures of anxiety from the child's perspective. Conclusions: The recognition of anxiety and its management in children with ADHD is generally poorly understood. In this particular group of children with ADHD, anxiety may be a side effect of intermediate- to long-term psychostimulant medication and/or a potential marker for a poor response to intermediate- to long-term psychostimulant medication treatment.
Target Structured Cross Language Model Refinement

The task of porting Automatic Speech Recognition (ASR) technology to many languages is hindered by a lack of transcribed acoustic data, which in turn prevents the development of accurate acoustic models necessary for the recognition task. To overcome this problem, recent research has sought to exploit the similarity of sounds across languages, and use this similarity to adapt models from one or more data rich languages for use in recognising data poor rget languages. Pronunciation variation and cross language context mismatch combine to make the task more difficult then a monolingual ASR application. In this paper, we examine the utility of recent pronunciation modelling approaches and evaluate their performance on the Indonesian and Spanish languages. Finally, we introduce a novel technique which ensures that the state distributions developed using the source language data are more closely aligned with those in the target language, thus improving classification accuracy. This technique achieved an improvement in word recognition accuracy of 19.5% absolute percentage points, when compared to standard knowledge based cross lingual mapping approach.
Hybrid-1D macroblock prediction for video compression

2009 appears to be the launching date for several activities intented to challenge the video compression standard H.264/AVC. Improvements upon H.264/AVC can be achieved either by breakthrough or incremental approaches. Due to the extreme fine tuning of H.264/AVC, the former seems tough. The latter however seems more achievable, even with the announced 50% coding efficiency improvement objective. In this highly challenging context, we propose a new scheme for macroblock partitioning and prediction. We extend the previously proposed Intra 1D scheme with a Skip 1D mode. Therefore, a macroblock is split in 1D partitions which can be predicted through two submodes in competition: Intra 1D or Skip 1D. As a second step, we further extend this scheme with an Inter 1D submode and provide the first keys to make this mode efficient. With the Intra 1D+Skip 1D scheme, an average 5.7% gain is reported compared to H.264/AVC, up to 10.1% for a given sequence. Preliminary results are also reported when the Inter 1D mode is added.
Activation of reward circuitry in human opiate addicts

The neurobiological mechanisms of opiate addictive behaviour in humans are unknown. A proposed model of addiction implicates ascending brainstem neuromodulatory systems, particularly dopamine. Using functional neuroimaging, we assessed the neural response to heroin and heroin‐related cues in established opiate addicts. We show that the effect of both heroin and heroin‐related visual cues are maximally expressed in the sites of origin of ascending midbrain neuromodulatory systems. These context‐specific midbrain activations predict responses to salient visual cues in cortical and subcortical regions implicated in reward‐related behaviour. These findings implicate common neurobiological processes underlying drug and drug‐cue‐related effects.
Cognitive Activity and Risk of Alzheimer's Disease

Recent research suggests that frequent participation in cognitively stimulating activities may reduce risk of Alzheimer's disease in old age. We review epidemiological evidence of such an association. We then consider whether cognitive activity can account for the association between higher educational and occupational attainment and reduced risk of Alzheimer's disease. Finally, we discuss the behavioral and neurobiological mechanisms that may underlie the association between cognitive activity and risk of Alzheimer's disease.
Beyond Corpus Lookup: Towards Heuristic Reasoning with Text Praveen

Both knowledge-based and text-based approaches to question answering suffer from brittleness. Text-based approaches use existing corpora like the web to answer a broad array of questions. However, most of these systems rely on corpus lookup. They have limited abilities to combine information from multiple sources, draw inferences, double check and explain answers. Knowledge-based systems can make sophisticated inferences, however, currently there exists no knowledge base that is broad enough to perform reasonably in the TREC question answering competitions. We argue that both these approaches can leverage off each other at heuristic reasoning, which is the type of reasoning underlying the human ability to make educated guesses. We focus on back of the envelope reasoning, the process of generating ballpark quantitative estimates. Starting from our previous work on a knowledge-based back of the envelope problem solver [Paritosh and Forbus, 2005], we present an analysis of how back of the envelope reasoning can be done with text.
Dose-Dependent Effects of Theta Burst rTMS on Cortical Excitability and Resting-State Connectivity of the Human Motor System

Theta burst stimulation (TBS), a specific protocol of repetitive transcranial magnetic stimulation (rTMS), induces changes in cortical excitability that last beyond stimulation. TBS-induced aftereffects, however, vary between subjects, and the mechanisms underlying these aftereffects to date remain poorly understood. Therefore, the purpose of this study was to investigate whether increasing the number of pulses of intermittent TBS (iTBS) (1) increases cortical excitability as measured by motor-evoked potentials (MEPs) and (2) alters functional connectivity measured using resting-state fMRI, in a dose-dependent manner. Sixteen healthy, human subjects received three serially applied iTBS blocks of 600 pulses over the primary motor cortex (M1 stimulation) and the parieto-occipital vertex (sham stimulation) to test for dose-dependent iTBS effects on cortical excitability and functional connectivity (four sessions in total). iTBS over M1 increased MEP amplitudes compared with sham stimulation after each stimulation block. Although the increase in MEP amplitudes did not differ between the first and second block of M1 stimulation, we observed a significant increase after three blocks (1800 pulses). Furthermore, iTBS enhanced resting-state functional connectivity between the stimulated M1 and premotor regions in both hemispheres. Functional connectivity between M1 and ipsilateral dorsal premotor cortex further increased dose-dependently after 1800 pulses of iTBS over M1. However, no correlation between changes in MEP amplitudes and functional connectivity was detected. In summary, our data show that increasing the number of iTBS stimulation blocks results in dose-dependent effects at the local level (cortical excitability) as well as at a systems level (functional connectivity) with a dose-dependent enhancement of dorsal premotor cortex-M1 connectivity.
Quantitative Trait Loci and Candidate Genes Regulating HDL Cholesterol: A Murine Chromosome Map

Objective—Summarizing the many discovered mouse and human quantitative trait loci (QTL) for high density lipoprotein (HDL) cholesterol (HDL-C) levels is important for guiding future research on the genetic regulation of HDL concentrations and for finding gene targets for upregulating HDL levels in mice and humans. Methods and Results—We summarized the 27 QTL and candidate genes associated with HDL-C concentrations in mice and plotted them on a mouse chromosome map. We also summarized the 22 human QTL for HDL-C levels and compared them with those of the mouse by comparative genomics. At least part of the mouse homologies for 18 of the 22 human HDL-C QTL were within the murine HDL-C QTL. Conclusions—Murine QTL for HDL-C levels may predict their homologous location in humans, and their underlying genes may be appropriate genes to test in humans.
Comparison of two kinds of nanomedicine for targeted gene therapy: premodified or postmodified gene delivery systems

Background The applications of ligand-polyethylene glycol (PEG)-modified nanocarriers have now emerged, as well as recognized strategies to provide the vectors with active targeting properties. In this research, premodification and postmodification were compared using the same ligand, ie, a novel conjugated mannan-containing PEG and L-α-phosphatidylethanolamine (PE). Methods Premodified and postmodified solid lipid nanoparticles were prepared and the characteristics of the two kinds of vehicles were evaluated. The modified vectors were then administered intravenously to rats and the in vivo targeting behavior of the complexes was investigated in liver macrophages. Results By carefully formulating the carriers with an optimal ratio of mannan-containing PEG-PE, postmodified vehicles displayed more efficient gene expression in rat Kupffer cells both in vitro and in vivo. Conclusion Postmodified gene carriers are superior to premodified gene vectors, although the latter is also promising for targeted gene delivery. This discovery could guide our future research.
SMT Solving for Functional Programming over Infinite Structures

We develop a simple functional programming language aimed at manipulating infinite, but first-order definable structures, such as the countably infinite clique graph or the set of all intervals with rational endpoints. Internally, such sets are represented by logical formulas that define them, and an external satisfiability modulo theories (SMT) solver is regularly run by the interpreter to check their basic properties. The language is implemented as a Haskell module.
Behavioural modelling and simulation of /spl Sigma//spl Delta/ modulators using hardware description languages

Behavioural simulation is the common alternative to the costly electrical simulation of /spl Sigma//spl Delta/ modulators (/spl Sigma//spl Delta/Ms). This paper explores the behavioural modelling and simulation of /spl Sigma//spl Delta/Ms by using hardware description languages (HDLs) and commercial behavioural simulators, as an alternative to the common special-purpose behavioural simulators. A library of building blocks, where a HDL has been used to model a complete set of circuit non-idealities, influencing the performance of /spl Sigma//spl Delta/Ms, is introduced. Three alternatives for introducing /spl Sigma//spl Delta/M topologies have been implemented. Experimental results of the simulation of a fourth-order 2-1-1 cascade multi-bit /spl Sigma//spl Delta/M are given.
Registers in the System of Semantic Relations in plWordNet

Lexicalised concepts are represented in wordnets by word-sense pairs. The strength of markedness is one of the factors which influence word use. Stylistically unmarked words are largely contextneutral. Technical terms, obsolete words, “officialese”, slangs, obscenities and so on are all marked, often strongly, and that limits their use considerably. We discuss the position of register and markedness in wordnets with respect to semantic relations, and we list typical values of register. We illustrate the discussion with the system of registers in plWordNet, the largest Polish wordnet. We present a decision tree for the assignment of marking labels, and examine the consistency of the editing decisions based on that tree.
Character recognition from trajectory by recurrent spiking neural networks

Spiking neural networks are biologically plausible and power-efficient on neuromorphic hardware, while recurrent neural networks have been proven to be efficient on time series data. However, how to use the recurrent property to improve the performance of spiking neural networks is still a problem. This paper proposes a recurrent spiking neural network for character recognition using trajectories. In the network, a new encoding method is designed, in which varying time ranges of input streams are used in different recurrent layers. This is able to improve the generalization ability of our model compared with general encoding methods. The experiments are conducted on four groups of the character data set from University of Edinburgh. The results show that our method can achieve a higher average recognition accuracy than existing methods.
Multi-scale voxel-based algorithm for UAV-derived point-clouds of complex surfaces

Point-clouds acquired using remote sensing, such as lasers or photogrammetric techniques, have grown exponentially in the last decade, providing data containing hundreds of millions of points with a density reaching hundreds of thousand points per square centimetre - when working on relatively small areas. This progress has been developed concomitantly with an increasing democratization of UAVs, in such a way that even in hardly accessible areas UAV-based photogrammetric techniques have provided researchers with detailed point-clouds. Provided those dataset, the paradigms have therefore shifted from data collection difficulties, to data processing limitations and usage. The present contribution therefore aims to provide an example of data processing using a voxel-based approach of gravel surfaces in order to derive more than the traditional surface roughness. The algorithm decomposes the surface into voxels and sub-voxels in order to determine if there are surfaces overlapping each other, showing the presence of cavities. Such dataset will then provide the necessary dataset to create metrics to improve the modelling of boundary layers dynamics in computational fluid dynamics for instance.