Miracle-dz/UniFAR-FTUs huggingface dataset:
Crime and Housing Prices

One of the most studied effects of crime is the impact that neighborhood crime has on housing values. By our count 18 studies have estimated this impact. A major drawback of these studies is that, although crime is undoubtedly endogenous in property value models, either because of simultaneity, omitted variables or measurement error, the majority of studies (12 studies) treat crime measures as exogenous independent variables. Of the limited number of studies (six studies) that do address the endogeneity of crime, the effect of crime is generally identified using questionable instruments. The purpose of our chapter is two-fold: (1) we provide the first critical review of the extensive literature that has dealt with the impact of crime on property values, and (2) we exploit a unique nine-year crime panel at the neighborhood level to estimate models that properly address the endogeneity of crime and allow us to overcome other specification errors that have plagued previous studies. Our results suggest that of the two major categories of crime (property and violent), only violent crimes exert a meaningful influence upon neighborhood housing values. A 10 per cent increase in violent crimes within a neighborhood is found to reduce housing values by as much as 6 per cent.
Collision Detection: Broad Phase Adaptation from Multi-Core to Multi-GPU Architecture

We present in this paper several contributions on the collision detection optimization centered on hardware performance. We focus on the broad phase which is the first step of the collision detection process and propose three new ways of parallelization of the wellknown ”Sweep and Prune” algorithm. We first developed a multi-core model that takes into account the number of available cores. Multi-core architecture enables us to distribute geometric computations with use of multi-threading. Critical writing section and threads idling have been minimized by introducing new data structures for each thread. Programming with directives, like OpenMP, appears to be a good compromise for code portability. We then proposed a new GPU-based algorithm also based on the ”Sweep and Prune” that has been adapted to multi-GPU architectures. Our technique is based on a spatial subdivision method used to distribute computations among GPUs. Results show that significant speed-up can be obtained by passing from 1 to 4 GPUs in a large-scale environment.
Gaussian Kullback-Leibler approximate inference

We investigate Gaussian Kullback-Leibler (G-KL) variational approximate inference techniques for Bayesian generalised linear models and various extensions. In particular we make the following novel contributions: sufficient conditions for which the G-KL objective is differentiable and convex are described; constrained parameterisations of Gaussian covariance that make G-KL methods fast and scalable are provided; the lower bound to the normalisation constant provided by G-KL methods is proven to dominate those provided by local lower bounding methods; complexity and model applicability issues of G-KL versus other Gaussian approximate inference methods are discussed. Numerical results comparing G-KL and other deterministic Gaussian approximate inference methods are presented for: robust Gaussian process regression models with either Student-t or Laplace likelihoods, large scale Bayesian binary logistic regression models, and Bayesian sparse linear models for sequential experimental design.
Importance of Sample Size for the Estimation of Repeater F Waves in Amyotrophic Lateral Sclerosis

Background:In amyotrophic lateral sclerosis (ALS), repeater F waves are increased. Accurate assessment of repeater F waves requires an adequate sample size. Methods:We studied the F waves of left ulnar nerves in ALS patients. Based on the presence or absence of pyramidal signs in the left upper limb, the ALS patients were divided into two groups: One group with pyramidal signs designated as P group and the other without pyramidal signs designated as NP group. The Index repeating neurons (RN) and Index repeater F waves (Freps) were compared among the P, NP and control groups following 20 and 100 stimuli respectively. For each group, the Index RN and Index Freps obtained from 20 and 100 stimuli were compared. Results:In the P group, the Index RN (P = 0.004) and Index Freps (P = 0.001) obtained from 100 stimuli were significantly higher than from 20 stimuli. For F waves obtained from 20 stimuli, no significant differences were identified between the P and NP groups for Index RN (P = 0.052) and Index Freps (P = 0.079); The Index RN (P < 0.001) and Index Freps (P < 0.001) of the P group were significantly higher than the control group; The Index RN (P = 0.002) of the NP group was significantly higher than the control group. For F waves obtained from 100 stimuli, the Index RN (P < 0.001) and Index Freps (P < 0.001) of the P group were significantly higher than the NP group; The Index RN (P < 0.001) and Index Freps (P < 0.001) of the P and NP groups were significantly higher than the control group. Conclusions:Increased repeater F waves reflect increased excitability of motor neuron pool and indicate upper motor neuron dysfunction in ALS. For an accurate evaluation of repeater F waves in ALS patients especially those with moderate to severe muscle atrophy, 100 stimuli would be required.
First Steps Towards a Social Comparison Model of Crowds

Modeling crowd behavior is an important challenge for cognitive modelers. Unfortunately, existing computational models are typically not tied to cognitive science theories, and are rarely evaluated against human crowd data. We investigate a general cognitive model of crowd behavior, based on Festinger’s Social Comparison Theory (SCT). We evaluate the SCT model on general pedestrian movement, and validate the model against human pedestrian behavior. The results show that SCT generates behavior more in-tune with human crowd behavior then existing non-cognitive models. Moreover, we examine the impact of the different SCT model components on the generated pedestrian behavior.
Developmental clock compromises human twin model created by embryo splitting.

STUDY QUESTION Is the quality of the human embryos generated by twinning in vitro comparable to the quality of the embryos created by fertilization? SUMMARY ANSWER Our data suggest that the human twin embryos created in vitro are unsuitable not only for clinical use but also for research purposes. WHAT IS KNOWN ALREADY Pregnancy from in vitro generated monozygotic twins by embryo splitting or twinning leads to live birth of healthy animals. Similar strategies, however, have been less successful in primates. Recent reports suggest that the splitting of human embryos might result in viable, morphologically adequate blastocysts, although the qualitative analyses of the embryos created in such a way have been very limited. STUDY DESIGN, SIZE, DURATION This study was a comparative analysis of embryos generated by twinning in vitro and the embryos created by in vitro fertilization. PARTICIPANTS/MATERIALS, SETTING, METHODS We analysed morphokinetics and developmental competence of 176 twin embryos created by splitting of 88 human embryos from either early (2-5 blastomeres, n = 43) or late (6-10 blastomeres, n = 45) cleavage stages. We compared the data with morphometrics of embryos created by in vitro fertilization and resulting in pregnancy and live birth upon single blastocyst transfer (n = 42). MAIN RESULTS AND THE ROLE OF CHANCE The morphokinetic data suggested that the human preimplantation development is subjected to a strict temporal control. Due to a 'developmental clock', the size of twin embryos was proportionate to the number of cells used for their creation. Furthermore, the first fate decision was somewhat delayed; the inner cell mass (ICM) became distinguishable later in the twin than in the normal blastocysts obtained through fertilization. If an ICM was present at all, it was small and of poor quality. The majority of the cells in the twin embryos expressed ICM and trophectoderm markers simultaneously. LIMITATIONS, REASONS FOR CAUTION We created monozygotic twins by blastomere separation from cleavage stage embryos. Embryo twinning by blastocyst bisection may circumvent limitations set by the developmental clock. WIDER IMPLICATIONS OF THE FINDINGS Taken together, our data suggest that the human twin embryos created in vitro are unsuitable not only for clinical use but also for research purposes.
Spontaneous Reperfusion after In Situ Thromboembolic Stroke in Mice

Injection of thrombin into the middle cerebral artery (MCA) of mice has been proposed as a new model of thromboembolic stroke. The present study used sequential multiparametric Magnetic Resonance Imaging (MRI), including Magnetic Resonance Angiography (MRA), Diffusion-Weighted Imaging (DWI) and Perfusion-Weighted Imaging (PWI), to document MCA occlusion, PWI-DWI mismatch, and lesion development. In the first experiment, complete MCA occlusion and reproducible hypoperfusion were obtained in 85% of animals during the first hour after stroke onset. In the second experiment, 80% of animals showed partial to complete reperfusion during a three-hour follow-up. Spontaneous reperfusion thus contributed to the variability in ischemic volume in this model. The study confirmed the value of the model for evaluating new thrombolytic treatments, but calls for extended MRI follow-up at the acute stage in therapeutic studies.
Range prediction for electric vehicles: Real-time payload detection by tire pressure monitoring

E-Mobility is facing a lot of obstacles nowadays, as for example the limits in the operating distance or the price difference between electric vehicles and vehicles with an internal combustion engine. This prevents many people from buying electric cars. Therefore, this paper presents a system to determine the payload of electric vehicles by measuring the tire pressure respectively the change of the tire pressure. The result of the measurement allows in combination with a range calculator a more detailed range prediction for automobiles (particularly for electric vehicles). The goal of this study is among others the reduction of the range anxiety of electric vehicle drivers.
Direct Interaction of GABAB Receptors with M2 Muscarinic Receptors Enhances Muscarinic Signaling

Downregulation of G-protein-coupled receptors (GPCRs) provides an important mechanism for reducing neurotransmitter signaling during sustained stimulation. Chronic stimulation of M2 muscarinic receptors (M2Rs) causes internalization of M2R and G-protein-activated inwardly rectifying potassium (GIRK) channels in neuronal PC12 cells, resulting in loss of function. Here, we show that coexpression of GABAB R2 receptors (GBR2s) rescues both surface expression and function of M2R, including M2R-induced activation of GIRKs and inhibition of cAMP production. GBR2 showed significant association with M2R at the plasma membrane but not other GPCRs (M1R, μ-opioid receptor), as detected by fluorescence resonance energy transfer measured with total internal reflection fluorescence microscopy. Unique regions of the proximal C-terminal domains of GBR2 and M2R mediate specific binding between M2R and GBR2. In the brain, GBR2, but not GBR1, biochemically coprecipitates with M2R and overlaps with M2R expression in cortical neurons. This novel heteromeric association between M2R and GBR2 provides a possible mechanism for altering muscarinic signaling in the brain and represents a previously unrecognized role for GBR2.
A climatological study of convective cloudbands in northeastern Brazil Part I : preliminary analysis

Rainfall is the most important meteorological variable in determining the climate of tropical regions such as the northeast of Brazil region (NE). This region (Fig. 1) has an area of 8,462,871 km2 and represents 18.2 per cent of the total area of Brazil. Annual average rainfall in the NE is not uniform, ranging from 1000 mm or more in the western and coastal regions to less than 400 mm in the hinterlands. The climate of the NE has been extensively studied by many researchers (e.g. Strang 1972; Ratisbona 1976; Kousky 1979; Chu 1983; Rao and Marques 1984; Rao et al. 1993) in recent decades. Aust. Met. Mag. 50 (2001) 105-113
Crystal Structure of Arp2/3 Complex

We determined a crystal structure of bovine Arp2/3 complex, an assembly of seven proteins that initiates actin polymerization in eukaryotic cells, at 2.0 angstrom resolution. Actin-related protein 2 (Arp2) and Arp3 are folded like actin, with distinctive surface features. Subunits ARPC2 p34 and ARPC4 p20 in the core of the complex associate through long carboxyl-terminal α helices and have similarly folded amino-terminal α/β domains. ARPC1 p40 is a seven-blade β propeller with an insertion that may associate with the side of an actin filament. ARPC3 p21 and ARPC5 p16 are globular α-helical subunits. We predict that WASp/Scar proteins activate Arp2/3 complex by bringing Arp2 into proximity with Arp3 for nucleation of a branch on the side of a preexisting actin filament.
Histaminergic Mechanisms for Modulation of Memory Systems

Encoding for several memory types requires neural changes and the activity of distinct regions across the brain. These areas receive broad projections originating in nuclei located in the brainstem which are capable of modulating the activity of a particular area. The histaminergic system is one of the major modulatory systems, and it regulates basic homeostatic and higher functions including arousal, circadian, and feeding rhythms, and cognition. There is now evidence that histamine can modulate learning in different types of behavioral tasks, but the exact course of modulation and its mechanisms are controversial. In the present paper we review the involvement of the histaminergic system and the effects histaminergic receptor agonists/antagonists have on the performance of tasks associated with the main memory types as well as evidence provided by studies with knockout models. Thus, we aim to summarize the possible effects histamine has on modulation of circuits involved in memory formation.
The Effects of Macro-economic Indicators on Stock Returns: Evidence from Kuwait Stock Market

The purpose of this study is to examine the impact of macroeconomic indicators (inflation, interest rate, money supply, oil prices, and unemployment rate) on Kuwait stock market. Basic indicators of Kuwait economy were analyzed using VAR model for the period from January 2001 to Dec 2010 on a monthly basis. A positive association was found between inflation, money supply and oil price in 1-month time and stock return while there is a negative relationship between interest rate in 1-month time and stock return in Kuwait stock market. There is a positive relationship between interest rate in 2-month time and stock return in Kuwait stock market and finally, there is a negative relationship between inflation, money supply and oil prices in 2-month time and stock return in Kuwait stock market.
Systematic Review on Infusion Reactions Associated with Chemotherapies and Monoclonal Antibodies for Metastatic Colorectal Cancer

Objective: The objective of this systematic review is to summarize the literature to date on the rates of infusion reactions (IR) associated with chemotherapies and monoclonal antibody (mAb) drug therapies used for the treatment of metastatic colorectal cancer (mCRC) and the associated clinical and economic impact. Methods: This study searched Medline, Medline (R) In-Process, Embase and Cochrane Library databases for studies on IRs associated with chemotherapy and mAbs in mCRC patients from 2000-2011. Results: For chemotherapy, the incidence of IRs ranged from 0-71% for all grades and 0-15% for grade 3-4. Rates of all grade IRs associated with cetuximab ranged from 7.6-33% and grade 3-4 IR rates were 0-22%. Rates of all grade IRs associated with panitumumab ranged from 0-4% and rates of grade 3-4 IRs ranged from 0-1%. The overall rate of IRs associated with bevacizumab ranged from 1.6-11%, with a rate of 0-4% for grade 3-4 IRs. A range of 50-100% of patients with grade 3-4 IRs terminated chemotherapy, and 34-100% of cetuximab patients with grade 3-4 IRs discontinued cetuximab therapy. No data were reported for bevacizumab or panitumumab. Only one study evaluated the economic impact of IRs. The study compared cetuximab administrations without an IR to those with an IR requiring resource utilization and found that mean costs were $9308 and $1725 higher for those with an IR requiring an emergency room visit or hospitalization and for those with an IR requiring outpatient treatment, respectively. Conclusions: The incidence of IRs varies among different mAbs; and IRs may cause treatment disruption and require costly medical interventions.
Assessing the Effectiveness of Corpus-Based Methods in Solving SAT Sentence Completion Questions

This paper studies different corpus-based algorithms through which to answer SAT sentence completion questions. SAT sentence completion questions assess how well different words fit into a sentence, and the ability to answer such types of questions have wide implications in optical character and speech recognition post-processing as well as word-suggestion programs. In our study, we analyze several statistical corpus-based methods through which to answer such questions, including normalized pointwise information, co-occurrence frequencies, latent semantic analysis, and the word2vec neural net implementations of continuous bag of words (CBOW) and continuous skip-gram (CSKIP) models. We find that the co-occurrence frequency method by itself has a near state-of-the-art performance with 52% correctness and that combining the co-occurrence frequency method with CBOW and CSKIP results in a state-of-the-art performance of 59%. The results of this study demonstrate that local context is a fairly strong measure in determining how well a word fits in a sentence and that exploration of non-similarity based methods may be required to further increase the ability of computers to answer such questions.
Improving Reconstituted HDL Composition for Efficient Post-Ischemic Reduction of Ischemia Reperfusion Injury

Background New evidence shows that high density lipoproteins (HDL) have protective effects beyond their role in reverse cholesterol transport. Reconstituted HDL (rHDL) offer an attractive means of clinically exploiting these novel effects including cardioprotection against ischemia reperfusion injury (IRI). However, basic rHDL composition is limited to apolipoprotein AI (apoAI) and phospholipids; addition of bioactive compound may enhance its beneficial effects. Objective The aim of this study was to investigate the role of rHDL in post-ischemic model, and to analyze the potential impact of sphingosine-1-phosphate (S1P) in rHDL formulations. Methods and Results The impact of HDL on IRI was investigated using complementary in vivo, ex vivo and in vitro IRI models. Acute post-ischemic treatment with native HDL significantly reduced infarct size and cell death in the ex vivo, isolated heart (Langendorff) model and the in vivo model (-48%, p<0.01). Treatment with rHDL of basic formulation (apoAI + phospholipids) had a non-significant impact on cell death in vitro and on the infarct size ex vivo and in vivo. In contrast, rHDL containing S1P had a highly significant, protective influence ex vivo, and in vivo (-50%, p<0.01). This impact was comparable with the effects observed with native HDL. Pro-survival signaling proteins, Akt, STAT3 and ERK1/2 were similarly activated by HDL and rHDL containing S1P both in vitro (isolated cardiomyocytes) and in vivo. Conclusion HDL afford protection against IRI in a clinically relevant model (post-ischemia). rHDL is significantly protective if supplemented with S1P. The protective impact of HDL appears to target directly the cardiomyocyte.
An International Investigation of the Association Between Societal Variables and Amount of Disclosure on Information Technology Problems : The Case of Y 2 K

The purpose of this study was to determine possible future disclosure practices related to information technology (IT) problems and the factors affecting such practices within an international accounting context. Disclosure practices related to Y2K disclosure practices was used as the central frame of reference for this study. Based on the survey of 1997/1998 fiscal-year annual reports from 1618 publicly listed firms from seventeen nations this study concluded Y2K disclosure practices varied significantly across national boundaries. It is a prediction of this study that disclosure practices on IT problems in the near to medium future will continue to vary significantly between nations. Empirical findings indicated the five societal variables (political and civil system; cultural values; type of legal system; level of economic development; and equity market) included in this study were significant determinants of the variation in the mean amount of Y2K information reported across national boundaries. Firm size, industry type and materiality of the national cost of Y2K were also associated with Y2K disclosure practices. A firm’s economic performance was not of significance. For international and national policymakers findings from this study imply a possible need to develop strategies to encourage increased disclosure on IT problems that will enable greater consistency and comparability. Finally, results from this study suggest future investigation of disclosure practices related to IT problems should drawn on socially based theoretical frameworks (such as legitimacy theory) rather than those with financial foundations.
Decision Tree as an Accelerator for Support Vector Machines

Support vector machine (SVM) is known to be a very powerful learning machine for pattern classification, of which optical character recognition (OCR) naturally falls as a branch. There are, however, a few hindrances in making an immediate application of SVM for the OCR purpose. First, to construct a well-performing SVM character recognizer has to deal with a large set of training samples (hundreds of thousands in the Chinese OCR, for example). There are two types of SVMs: linear and non-linear SVMs. Training a linear SVM is relatively inexpensive, while training a non-linear SVM is of the order np, where n is the number of training samples and p ≥ 2. Thus, the sheer size of samples has the potential of incurring a high training cost on an OCR application. Second, a normal OCR task also deals with a large number of class types. There are, for example, thousands of character class types being handled in the Chinese OCR. There are also hundreds of them being handled in the English OCR, if touched English letters are considered as separate class types from untouched letters. Since SVM training deals with one pair of class types at a time, we need to train l(l-1)/2 one-against-one (1A1) classifiers (Kerr et al. [1]) or l one-against-others (1AO) classifiers (Bottou et al. [2]), where l is the number of class types. Such a gigantic collection of classifiers not only poses a problem to the training but also to the testing of SVMs. Third, SVM training also involves a number of parameters whose values affect the generalization power of classifiers. This means that searching for optimal parameter values is necessary and it constitutes another heavy load to the SVM training. The above three factors, when put together, will demand months of computing time to complete a whole round of conventional SVM trainings, including linear and non-linear SVM trainings, and also demands an unusual amount of time in conducting a conventional online OCR task.