Miracle-dz/UniFAR-FTUs huggingface dataset:
Void Statistics in Large Galaxy Redshift Surveys: Does Halo Occupation of Field Galaxies Depend on Environment?

We use measurements of the projected galaxy correlation function wp(rp) and galaxy void statistics to test whether the galaxy content of halos of fixed mass is systematically different in low-density environments. We present new measurements of the void probability function (VPF) and underdensity probability function (UPF) from Data Release 4 of the Sloan Digital Sky Survey (SDSS), as well as new measurements from the Two-Degree Field Galaxy Redshift Survey. We compare these measurements to predictions calculated from models of the halo occupation distribution (HOD) that are constrained to match both the projected correlation function wp(rp) and the space density of galaxies . The standard implementation of the HOD assumes that galaxy occupation depends on halo mass only, and is independent of local environment. For luminosity-defined samples, we find that the standard HOD prediction is a good match to the observations, and the data exclude models in which galaxy formation efficiency is reduced in low-density environments. More remarkably, we find that the void statistics of red and blue galaxies (at L ∼ 0.4L⋆) are perfectly predicted by standard HOD models matched to the correlation function of these samples, ruling out “assembly bias” models in which galaxy color is correlated with large-scale environment at fixed halo mass. We conclude that the luminosity and color of field galaxies are determined predominantly by the mass of the halo in which they reside and have little direct dependence on the environment in which the host halo formed. In broader terms, our results show that the sizes and emptiness of voids found in the distribution of L≳ 0.2L⋆ galaxies are in excellent agreement with the predictions of a standard cosmological model with a simple connection between galaxies and dark matter halos.
THE USE OF SONIC ARTICULATION IN IDENTIFYING CORRELATION IN CAPITAL MARKET TRADING DATA

Despite intensive study, a comprehensive understanding of the structure of capital market trading data remains elusive. The one known application of audification to market price data reported in the 1990 that it was difficult to interpret the results probably because the market does not resonate according to acoustic laws. This paper reports on a technique transforming the data so it does resonate, so audification can be used as a means of identifying autocorrelation in capital market trading data. The results obtained indicate that the technique may have a wider application to other similarly structured time-series data.
Emotion Recognition and Perceived Social Support in Young People Who Offend

Young people who offend appear stuck in a cycle of adverse experiences, low levels of social support and emotional skill deficits. Yet these factors have not been extensively researched with young people who offend. The current study aimed to develop the understanding of emotion recognition ability and perceived social support in young people who offend and to explore the relationship between these variables. A total of 50 young people who offend were recruited through three Youth Offending Teams and 50 age, gender, ethnicity, socio-economic status and academically matched young people without a known offending history were recruited from a college and youth service in the same geographical area. All participants completed a demographic questionnaire, the Toronto Alexithymia Scale, a Facial Emotion Recognition Task, a Verbal Emotional Prosody Recognition Task and the Multidimensional Scale of Perceived Social Support. Failing to support the hypotheses, statistical analyses failed to show that, relative to the controls, young people who offend had significantly higher levels of alexithymia, lower levels of perceived social support or lower ability to recognise others’ emotions. However, relative to the controls, young people who offend did show significantly lower ability to recognise fear through verbal prosody. Of particular interest, looked after status, which was more commonly reported among young people who offend (38%) than controls (4%), was the predominant factor associated with all outcome variables. Thus looked after status, rather than offending status in isolation, is more associated with difficulties in identifying and describing feelings, ability to recognise others’ emotions and levels of perceived social support. In addition, significant correlations were found between (1) alexithymia and perceived social support, (2) the ability to recognise others’ emotions and perceived social support and (3) the ability to recognise emotions from facial expressions and verbal prosody. Theoretical and clinical implications of the study findings are discussed and areas for future research are suggested.
An Algorithm for Adapting RED Parameters to TCP Traffic

Random early detection (RED) can stabilize the queue within a given target range and simultaneously achieve high throughput in the routers. However, the average queue length is quite sensitive to the network scenarios and it is difficult to adapt RED parameters to the changing network traffic. This paper develops an algorithm for systematically adapting RED parameters to variable network conditions such as link capacity, round- trip time and the number of TCP flows. Simulations demonstrate that this algorithm can stabilize the queue length within a target range and maintain high link utilization in a wide variety of network traffic conditions.
Mental Health and Labour Supply : Evidence from Mexico ' s Ongoing Violent Con icts

Little is known about the monetary and non-monetary consequences of ongoing violent con icts on individuals. Using the Mexican Family Life Survey (MxFLS), this paper estimates the causal e ect of mental health (symptoms of depression/anxiety) on labour supply for working-aged men and women using measures of the ongoing drug-related violent con icts as instruments for mental health. It is argued that violent con icts deteriorate mental health and, through this, indirectly reduce individual labour supply. Exposure to violent con icts is measured both at the macro level using intentional homicide rates by region, and at the micro level indicated by the presence of armed groups in the neighbourhood. The results show a signi cant negative impact of the con icts on anxiety for men and women. Based on IV-Tobit model results, a worse mental health state decreases individual labour supply strongly and signi cantly for men. The ndings demonstrate that Mexico's population not only su ers from the violent con icts between drug-tra cking organisations by anxiety or even depression but also indirectly from less income through less work which in turn has consequences for Mexico's social development and economic growth.
SINAI at RTE-7: Integrating Personalized Page Rank Vectors into EDITS

This document describes the participation of the SINAI Research Group in the 7 challenge on Recognition of Textual Entailment (RTE). Our approach extends the promising results obtained in the last campaing into a well know framework for textual entailment recognition known as EDITS. Although the proposed solution is modest, results encourage us in the use of Personalized Page Rank as a technique for generating weighted vectors of synsets per term in texts and applying distance metrics to compute a value of lexical similarity between terms found in hypotheses and those in candidate texts.
An implementation of anger detection in speech signals

In this paper, an emotion classification system based on speech signals is presented. The classifier can identify the most common emotions, namely anger, neutral, happiness and fear. The algorithm computes a number of acoustic features which are fed into the classifier based on a pattern recognition approach. The classification system is of potential benefit for ambient intelligence in which the emotional and physical states of a person should be known to the intelligence of the environment. Using such information, the environment can better support humans in their daily activities in accordance with their preferences.
Algorithmic profiling

Traditional profilers identify where a program spends most of its resources. They do not provide information about why the program spends those resources or about how resource consumption would change for different program inputs. In this paper we introduce the idea of algorithmic profiling. While a traditional profiler determines a set of measured cost values, an algorithmic profiler determines a cost function. It does that by automatically determining the "inputs" of a program, by measuring the program's "cost" for any given input, and by inferring an empirical cost function.
THE COMPILE-AND RUN-TIME PERFORMANCE CONSIDERATIONS OF IMPLEMENTING CROSS-CUTTING CONCERNS AS ASPECTS

Aspects are frequently cited as an ideal solution to large cross-cutting concerns such as logging and first failure data capture. The flexibility of the AspectJTM language with its use of wildcards combined with a powerful runtime reflection API allows the creation of simple and extensible aspects. The paper outlines the performance implications of weaving aspects with existing programs and the relative run-time performance of woven programs in terms of throughput and scalability. This paper is an extension to our previous work [Dalton et al, 2003]; the focus is on the new developments in AspectJ technology and deeper empirical analysis.
Identification of Malicious Web Pages with Static Heuristics

Malicious web pages that launch client-side attacks on web browsers have become an increasing problem in recent years. High-interaction client honeypots are security devices that can detect these malicious web pages on a network. However, high-interaction client honeypots are both resource-intensive and known to miss attacks. This paper presents a novel classification method for detecting malicious web pages that involves inspecting the underlying static attributes of the initial HTTP response and HTML code. Because malicious web pages import exploits from remote resources and hide exploit code, static attributes characterizing these actions can be used to identify a majority of malicious web pages. Combining high-interaction client honeypots and this new classification method into a hybrid system leads to significant performance improvements.
Automatic extraction of information for catenary scene analysis

This paper presents an original system for the automatic recognition of catenary elements. Based on a bottom-up approach, our analysis is composed of two stages: the first stage provides recognition hypothesis regarding previously segmented elements, with a precision rate of 91.7 %. The second stage allows to correct some hypothesis using a Markovian model which analyzes the catenary element sequence. It allows to improve precision up to 98.1%.
Ephemeral State Assisted Discovery of Peer-to-peer Networks

In the past few years there has been an impressive number of proposals for application-specific overlays or peerto-peer networks. However the procedure to bootstrap peers in those networks has remained an under-researched topic, typically left as an implementation detail. In this paper, we first study the performance of history lists, a common decentralised bootstrap mechanism used in P2P applications. We then investigate how some lightweight network support, such as Ephemeral State, could help build a P2P application that would not depend on any centralised mechanism to discover other peers.
TCF7L2 Variation and Proliferative Diabetic Retinopathy

Proliferative diabetic retinopathy (PDR) is the most severe vision-threatening complication of diabetes. For investigation of genetic association between TCF7L2 and PDR in Caucasian type 2 diabetes mellitus (T2DM) and its functional consequences, 383 T2DM patients with PDR (T2DM-PDR) and 756 T2DM patients without diabetic retinopathy (T2DM–no DR) were genotyped with rs7903146 in TCF7L2. We found that risk allele (T) frequency of rs7903146 was significantly higher in T2DM-PDR patients (allelic P = 2.52E-04). In lymphoblastoid cells induced to undergo endoplasmic reticulum (ER) stress by treatment of tunicamycin, higher fold change of TCF7L2 and VEGFA mRNA levels were observed in rs7903146-TT cells than in rs7903146-CC cells (P = 0.02 for TCF7L2; P = 0.004 for VEGFA), suggesting that ER stress plays a role in PDR pathogenesis. Silencing TCF7L2 resulted in decreased mRNA levels of both TCF7L2 and VEGFA (P < 0.001). Retinas of oxygen-induced retinopathy mice (a model for PDR) had higher TCF7L2 and VEGFA mRNA levels than those of controls (P = 2.9E-04 for TCF7L2; P = 1.9E-07 for VEGFA). Together, data from our study show that TCF7L2-rs7903146 is associated with PDR in Caucasian T2DM and suggest that TCF7L2 promotes pathological retinal neovascularization via ER stress–dependent upregulation of VEGFA.
Consciousness, mind, and spirit: three levels of human cognition

The article elucidates three important concepts and realities that refer to cognitive phenomena and are often (mistakenly) used as synonyms: consciousness (slo. zavest), mind (slo. um), and spirit (slo. duh). They present three levels of human cognition: individual-experiential, individual-mental, and trans-individual-mental. Simply put: the concept of consciousness pertains to the waking mental life of a human being, while the concept of mind pertains to the ability and activity to consciously comprehend and understand contents and objects of human activity. I delineate three “types” of spirit: personal spirit, objective spirit, and the objectification of spirit in productions of human culture; I have doubts, however, about the existence of cosmic or super-cosmic dimensions of spirit, although some interpretations of quantum physics and modern cosmology suggest that such dimensions are possible.
Machine Learning for Map Interpretation: An Intelligent Tool for Environmental Planning

The design of a user interface integrating instruments for visual and textual representation and image interpretation is a relevant problem when developing an advisory system for environmental planning. Indeed, the user of the system needs a support to the interpretation of maps, that is, a tool that segments maps and automatically associates geometric regions on a map with those semantic labels useful for applying hints and advices suggested by the environmental planning system. In the article, we present the application of symbolic machine learning techniques to the interpretation of maps. Two inductive learning systems, namely, INDUBI/CSL and ATRE, have been used to complete the knowledge base of an expert system for environmental planning. The application described concerns the recognition of four environmental concepts that are relevant for environmental protection. The positive results obtained in two different experiments prove the strength of the adopted approach for the interpretation task.
Metabolic Enzymes from Psychrophilic Bacteria: Challenge of Adaptation to Low Temperatures in Ornithine Carbamoyltransferase from Moritellaabyssi

ABSTRACT The enzyme ornithine carbamoyltransferase (OTCase) of Moritellaabyssi (OTCaseMab), a new, strictly psychrophilic and piezophilic bacterial species, was purified. OTCaseMab displays maximal activity at rather low temperatures (23 to 25°C) compared to other cold-active enzymes and is much less thermoresistant than its homologues from Escherichiacoli or thermophilic procaryotes. In vitro the enzyme is in equilibrium between a trimeric state and a dodecameric, more stable state. The melting point and denaturation enthalpy changes for the two forms are considerably lower than the corresponding values for the dodecameric Pyrococcusfuriosus OTCase and for a thermolabile trimeric mutant thereof. OTCaseMab displays higher Km values for ornithine and carbamoyl phosphate than mesophilic and thermophilic OTCases and is only weakly inhibited by the bisubstrate analogue δ-N-phosphonoacetyl-l-ornithine (PALO). OTCaseMab differs from other, nonpsychrophilic OTCases by substitutions in the most conserved motifs, which probably contribute to the comparatively high Km values and the lower sensitivity to PALO. The Km for ornithine, however, is substantially lower at low temperatures. A survey of the catalytic efficiencies (kcat/Km) of OTCases adapted to different temperatures showed that OTCaseMab activity remains suboptimal at low temperature despite the 4.5-fold decrease in the Km value for ornithine observed when the temperature is brought from 20 to 5°C. OTCaseMab adaptation to cold indicates a trade-off between affinity and catalytic velocity, suggesting that optimization of key metabolic enzymes at low temperatures may be constrained by natural limits.
Microarray Data Analysis using Probabilistic Methods

Affymetrix microarrays are currently the most widely used microarray technology. Due to the complexity of microarray experiments, the experimental data is very noisy. Many summarization methods have been developed to provide gene expression levels from Affymetrix probe-level data. Most of the currently popular methods do not provide a measure of uncertainty for the estimated expression level of each gene. The use of probabilistic models can overcome this limitation. This thesis extends a previously developed probabilistic model, mgMOS, to obtain an improved model, multi-mgMOS. This new model provides improved accuracy and is more computationally efficient than other alternatives. It also provides a level of uncertainty associated with the measured gene expression level. This probe-level measurement error provides useful information to help in the downstream analysis of gene expression data. In order to show the advantage of the probe-level probabilistic model, the obtained uncertainty is propagated in two downstream analyses of gene expression data. One is detecting differential gene expression, another is clustering. A Bayesian hierarchical model is proposed to include probe-level measurement error into the detection of differential gene expression from replicated experiments and a standard model-based clustering method is augmented to incorporate probe-level measurement error. Due to the inclusion of the probe-level measurement error, the downstream probabilistic models become more complicated or intractable. In order to perform inference with these augmented models efficiently, various inference approximation approaches are compared in this thesis, including Maximum a Posteriori, Laplace approximation, a variational method and Markov chain Monte Carlo. Results from both benchmark data sets and a real-world data set demonstrate that the incorporation of the probe-level measurement error improves the performance of the downstream probabilistic analysis.
An approach to online asynchronous mode prevention in two-area power systems

Asynchronous modes between subsystems might lead to severe consequences, such as power system's islanding or even blackouts. In this paper, an approach to online asynchronous mode prevention algorithm in two-area power systems is presented. The algorithm determines first the Transient Stability Margin, then the minimum required quantity of generator tripping and load shedding to prevent the emerging asynchronous mode. An approach to online application of the algorithm using simultaneous signals from two PMUs at two ends of a tie line is presented. The simulation results show that the proposed algorithm can be used as an operating plan to prevent asynchronous modes in two-area power systems.
Purification, Characterization, and Heterologous Expression in Fusarium venenatum of a Novel Serine Carboxypeptidase from Aspergillus oryzae

ABSTRACT A novel serine carboxypeptidase (EC 3.4.16.1 ) was found in anAspergillus oryzae fermentation broth and was purified to homogeneity. This enzyme has a molecular weight of ca. 67,000, as determined by sodium dodecyl sulfate-polyacrylamide gel electrophoresis, and its specific activity is 21 U/mg for carbobenzoxy (Z)-Ala-Glu at pH 4.5 and 25°C. It has a ratio of bimolecular constants for Z-Ala-Lys and Z-Ala-Phe of 3.75. Optimal enzyme activity occurs at pH 4 to 4.5 and 58 to 60°C for Z-Ala-Ile. The N terminus of this carboxypeptidase is blocked. Internal fragments, obtained by cyanogen bromide digestion, were sequenced. PCR primers were then made based on the peptide sequence information, and the full-length gene sequence was obtained. An expression vector that contained the recombinant carboxypeptidase gene was used to transform aFusarium venenatum host strain. The transformed strain ofF. venenatum expressed an active recombinant carboxypeptidase. In F. venenatum, the recombinant carboxypeptidase produced two bands which had molecular weights greater than the molecular weight of the native carboxypeptidase from A. oryzae. Although the molecular weights of the native and recombinant enzymes differ, these enzymes have very similar kinetic parameters.
A positional access method for relational databases

Most commercial database management systems sort tuples of a relation by their primary keys for the purpose of supporting efficient insertions, deletions, and updates. However, primary keys are usually auto-generated integers, which bear little useful information about user data. Secondary indexes have to be created sometimes to help retrieve tuples by columns other than the primary key. Evidently, a better solution is to sort the data by columns that appear frequently in retrieval conditions. Unfortunately, this method does not work, at least not immediately, when the relation is vertically partitioned, which is a popular technique to reduce I/O overhead, since it is difficult to keep tuples of two partitions in exactly the same order unless the sorting columns are replicated, which again wastes storage space and disk bandwidth unnecessarily. In this paper, we introduce a positional access method that allows a partition to be sorted by another one but incurs little storage overhead and provide details about how to improve its performance.
Phenotypic Variability of Osteogenesis Imperfecta Type V Caused by an IFITM5 Mutation

In a large cohort of osteogenesis imperfecta type V (OI type V) patients (17 individuals from 12 families), we identified the same mutation in the 5′ untranslated region (5′UTR) of the interferon‐induced transmembrane protein 5 (IFITM5) gene by whole exome and Sanger sequencing (IFITM5 c.–14C > T) and provide a detailed description of their phenotype. This mutation leads to the creation of a novel start codon adding five residues to IFITM5 and was recently reported in several other OI type V families. The variability of the phenotype was quite large even within families. Whereas some patients presented with the typical calcification of the forearm interosseous membrane, radial head dislocation and hyperplastic callus (HPC) formation following fractures, others had only some of the typical OI type V findings. Thirteen had calcification of interosseous membranes, 14 had radial head dislocations, 10 had HPC, 9 had long bone bowing, 11 could ambulate without assistance, and 1 had mild unilateral mixed hearing loss. The bone mineral density varied greatly, even within families. Our study thus highlights the phenotypic variability of OI type V caused by the IFITM5 mutation.