Miracle-dz/UniFAR-FTUs huggingface dataset:
Scale Free Processes in Galaxy Formation

Abstract According to the ΛCDM paradigm of cosmology, galaxies form at the centers of dark matter (DM) halos. While galaxy formation involves complex baryonic physics, the formation of DM halos is governed solely by gravity and cosmology. As a result, many of their properties exhibit a near scale-free behaviour, self-similar in either halo mass, cosmic time or both. This is especially true in the Einstein-de Sitter (EdS) regime, valid at redshifts z ≳ 1, when cosmological scaling relations become particularly simple, and in the narrow mass range of normal galaxies, where the fluctuation power spectrum can be approximated by a power law. Since many galaxy properties are strongly correlated with halo mass, they tend to exhibit a self-similar behaviour as well. A partial list of self-similar properties include the mass function of DM halos, the structure of the cosmic web, the accretion/merger rate of matter onto halos, the density profiles of DM halos and their angular momentum, which eventually determines the galaxy structure. We briefly review these below, and comment on how they can be used in conjunction with simple toy models to gain insight into galaxy formation.
Predicting Metabolic Cost During Human-in-the-Loop-Optimization

Metabolic cost is a measurement of the rate of energy required to perform a task. Collecting metabolic cost data is difficult and limiting. We are interested in using human data collected during human-in-the loop optimization of exoskeleton control to predict metabolic cost. The ability to approximate human energy use during walking outside the laboratory environment will allow for more robust experimentation for exoskeletons and prosthetics.
Deep Learning For Skin Cancer Diagnosis With Hierarchical Architectures

Skin lesions are organized in a hierarchical way, which is taken into account by dermatologists when diagnosing them. However, automatic systems do not make use of this information, performing the diagnosis in a one-vs-all approach, where all types of lesions are considered. In this paper we propose to mimic the medical strategy and train a deep-learning architecture to perform a hierarchical diagnosis. Our results highlight the benefits of addressing the classification of dermoscopy images in a structured way. Additionally, we provide an extensive evaluation of criteria that must be taken into account in the development of diagnostic systems based on deep learning.
From Normal Functors to Logarithmic Space Queries

We introduce a new approach to implicit complexity in linear logic, inspired by functional database query languages and using recent developments in effective denotational semantics of polymorphism. We give the first sub-polynomial upper bound in a type system with impredicative polymorphism; adding restrictions on quantifiers yields a characterization of logarithmic space, for which extensional completeness is established via descriptive complexity.
Learner Characteristics and Syntactic and Lexical Complexity of Written Products

The purpose of this study was to search for the probable effects of learners’ characteristics on linguistic properties of their writings. Learners’ characteristics were studied via three main leaner variables; affective, cognitive, and biological variables. Extroversion/ introversion (affective), reflectivity/ impulsivity (cognitive), and gender (biological) were selected as three variables via which the learners could be categorized into different groups. The linguistic properties of the learners’ written performance were measured through Syntactic Complexity and Lexical Complexity. The participants were selected from a homogeneous group of university language learners whom were asked to write a composition. The compositions were then transcribed into available information for a computer. A computerized text analysis program (Word Smith Tools) was used to measure the linguistic properties of the written compositions. Syntactic complexity (ratio of subordination and average sentence length of the written texts) and Lexical complexity (lexical diversity and lexical density) were calculated by the program. Extroverts indicated to write in a more lexically complex way than introverts. The results showed that there was not any significant difference between reflective and impulsive learners with respect to the linguistic properties of their writings. Female and male learners also indicated no such difference with regard to the linguistic characteristics of their written performance.
Stellar populations and AGN in the bulges of SDSS galaxies

Abstract We present a new method for measuring the recent star formation history (SFH) of galaxies from their 4000Å break and Balmer absorption line strength. By making use of the whole 3750-4150Å spectral region, the method achieves a higher signal-to-noise ratio than traditional indices. The new technique is ideally suited to finding evidence for weak or old starbursts in good quality spectra, or studying post-starburst galaxies at high redshift. On application to massive, bulge dominated galaxies in the SDSS, we find clear correlations between the recent star formation history of bulges and the properties of the AGN.
Measurement of a head-related transfer function database with high spatial resolution

This paper describes a database of high spatial resolution head-related transfer functions (HRTF) measurements for 54 subjects (42 males, 12 females) and 3 dummy heads. The head-related impulse responses (HRIR) have been measured in IRCAM's anechoic chamber using the exponentional sweep sine technique and a sampling rate of 96 kHz. Microphones were positionned at the entrance of the blocked ear canal. The spatial sampling scheme is based on a Gaussian grid and includes 1680 directions with full azimuth range (0° to 360°), and elevation ranging from -51° to +86°. The angular step size is approximately 6 degrees in both dimensions. The subjects head position and orientation are tracked with an infrared optical motion capture system. The HRIR are publicly available in the standardized SOFA file format.
Understanding the Fiber-to-Yarn Conversion System Part II : Yarn Characteristics

The end product of the cotton fiber-to-yarn conversion system is a spun yarn or a staple-fiber yarn, which is suitable for making numerous end products from knit apparels to woven fabrics, from towels to sheets, and from carpets to industrial fabrics. The diversity of yarn-based products results in different views of what constitutes a yarn quality. Indeed, different textile manufacturers often express different views of yarn quality depending on the particular end product produced and the type of downstream processing used.
The effect of combined carbonation and steam curing on the microstructural evolution and mechanical properties of Portland cement concrete

The present study investigated the effect of the combined carbonation and steam curing on the physicochemical properties and CO2 uptake of the Portland cement concrete. Four different curing regimes were adopted during the initial 10 h of curing to evaluate the potential of carbonation curing as an alternative to conventional steam curing in the precast concrete industry from environmental and practical viewpoints. Four combinations of carbonation and steam curing conditions were applied as curing regimes to the samples at an early age. The test results indicated that the samples treated with the combined carbonation and steam curing exhibited higher early strength development compared to the other samples, signifying that carbonation curing can reduce the production time of precast concrete. Furthermore, the CO2 uptake capacity of the samples was calculated and found to be as high as 18% with respect to the mass of the paste samples. Hence, the simultaneous utilization of steam and CO2 for the fabrication of precast concrete members has the potential to make precast concrete greener and more costeffective.
Effect of deformation on the substructure development of two phase magnesium stannide structures

This work studied the ability of Mg-Sn alloys to be deformed under extrusion and its effect on the microstructure and mechanical properties of the alloy. Thermoelectric properties of tin rich Mg-Sn alloys was inspected and it was found that they got altered with deformation which in turn would alter the thermoelectric efficiency of these alloys.
Relative Deprivation and Resilience in Supply Networks

Dealers may experience and perceive varying levels of beneficiary exchange relations in a manufacturer’s network. Low-benefit perceiving dealers may experience relative deprivation as compared to their significant others such as better-off dealers of that manufacturer, better-off dealers of a competitor or better-off itself in previous periods, and demonstrate positive or negative reactions to that deprivation. Although manufacturer-dealer exchange (MDX) relations have been studied previously, research on relative deprivation in those relations is nonexistent. Thus, to fill this gap, this study analyzes dealers’ relative deprivation in MDX relations with perceived benefits as antecedents and reactions to deprivation as consequences. A multiple-design case approach has been conducted on two manufacturers and their dealers from the Turkish drapery industry. By analyzing dealers in MDX relations from the automotive industry, validation analyzes have been performed. This study has highlighted the importance of dealers’ relative deprivation as an issue to be handled in MDX relations. In addition, resilience of dealers appears to be an essential attribute leading to positive reactions to deprivation.
Cloning and sequence analysis of the LOC 339524 gene in Sprague-Dawley rats

We cloned the LOC339524 gene in Sprague-Dawley (SD) rats and analyzed the structure and function of the protein encoded by it. Based on the known human LOC339524 gene sequences, the full-length coding sequence of the LOC339524 gene in SD rats was cloned and amplified by the polymerase chain reaction using the complementary DNA of SD rats as a template. Bioinformatics analysis showed that the length of the cloned LOC339524 gene (GenBank accession No. KM224520) was 831 bp and it encoded a deduced protein of 276 amino acids. Sequence analysis revealed that the coded protein was identical to that produced in humans and its functional domain was located in the 138-236 amino acid fragments, a proline-rich region. Our results suggest that the encoded protein may be a significant regulator of the inflammatory response and may provide sufficient information to justify an in-depth investigation of the role of the LOC339524 gene.
On topological properties of weakly m-convex sets

The topological properties of classes of generally convex sets in multidimensional real Euclidean space $\mathbb{R}^n$, $n\ge 2$, known as $m$-convex and weakly $m$-convex, $1\le m<n$, are studied in the present work. A set of the space $\mathbb{R}^n$ is called \textbf{\emph{$m$-convex}} if for any point of the complement of the set to the whole space there is an $m$-dimensional plane passing through this point and not intersecting the set. An open set of the space is called \textbf{\emph{weakly $m$-convex}}, if for any point of the boundary of the set there exists an $m$-dimensional plane passing through this point and not intersecting the given set. A closed set of the space is called \textbf{\emph{weakly $m$-convex}} if it is approximated from the outside by a family of open weakly $m$-convex sets. These notions were proposed by Professor Yuri Zelinskii. It is known the topological classification of (weakly) $(n-1)$-convex sets in the space $\mathbb{R}^n$ with smooth boundary. Each such a set is convex, or consists of no more than two unbounded connected components, or is given by the Cartesian product $E^1\times \mathbb{R}^{n-1}$, where $E^1$ is a subset of $\mathbb{R}$. Any open $m$-convex set is obviously weakly $m$-convex. The opposite statement is wrong in general. It is established that there exist open sets in $\mathbb{R}^n$ that are weakly $(n-1)$-convex but not $(n-1)$-convex, and that such sets consist of not less than three connected components. The main results of the work are two theorems. The first of them establishes the fact that for compact weakly $(n-1)$-convex and not $(n-1)$-convex sets in the space $\mathbb{R}^n$, the same lower bound for the number of their connected components is true as in the case of open sets. In particular, the examples of open and closed weakly $(n-1)$-convex and not $(n-1)$-convex sets with three and more connected components are constructed for this purpose. And it is also proved that any compact weakly $m$-convex and not $m$-convex set of the space $\mathbb{R}^n$, $n\ge 2$, $1\le m<n$, can be approximated from the outside by a family of open weakly $m$-convex and not $m$-convex sets with the same number of connected components as the closed set has. The second theorem establishes the existence of weakly $m$-convex and not $m$-convex domains, $1\le m<n-1$, $n\ge 3$, in the spaces $\mathbb{R}^n$. First, examples of weakly $1$-convex and not $1$-convex domains $E^p\subset\mathbb{R}^p$ for any $p\ge3$, are constructed. Then, it is proved that the domain $E^p\times\mathbb{R}^{m-1}\subset\mathbb{R}^n$, $n\ge 3$, $1\le m<n-1$, is weakly $m$-convex and not $m$-convex.
Induction and identification of Stylosanthes guianensis

Stylosanthes guianensis is an elite and important forage legume species, which is extensively cultivated in tropical areas. Polyploid breeding via exposure to colchicine is a conventional and practical method to improve varieties of S. guianensis. Terminal buds of S. guianensis Reyan No.5 seedlings were treated with different concentrations of colchicine (0.00, 0.05, 0.10, 0.15, 0.20, and 0.25%) for 24, 48, and 72 h. Morphological and cytological variants were observed at a frequency of <96% among transplanted seedlings. The cytogenetic analysis of young leaf cells was conducted on all variants to identify their ploidy levels. The most efficient procedure for tetraploid production was the treatment of seedling apical buds with 20% colchicine for 48 h, with the tetraploid induction rate being 10%. This is a relatively simple and reliable method for the production of tetraploidy in S. guianensis.
Tracking of cell population from time lapse and end point confocal microscopy images with multiple hypothesis Kalman smoothing filters

This paper describes an automated visual tracking system combining time-lapse and end-point confocal microscopy to aid the interpretations of cell behaviors and interactions, with the focus on understanding the sprouting mechanism during angiogenesis. These multiple cells exhibit stochastic motion and are subjected to photobleaching and the images acquired are of low signal to noise ratio. Hence, following time-lapse imaging, high resolution end-point images are acquired. Our approach applies a probabilistic motion filter (a backward Kalman filtering followed by track smoothing) which incorporates end-point and all available time-lapse information in a mathematically consistent manner to obtain trajectory and phenotype information of multiple individual cells simultaneously. An extension of this algorithm, track smoothing with a Multiple Hypothesis Testing (MHT) data association, is proposed to improve association of multiple close contact and proliferating cells across images acquired from different time points to existing track trajectories. Our methodology was applied to tracking endothelial cell sprouting in three-dimensional micro-fluidic devices.
The Comparative Advantages of fsQCA and Regression Analysis for Moderately Large-N Analyses

This article contributes to the literature on comparative methods in the social sciences by assessing the strengths and weaknesses of regression analysis and fuzzy-set qualitative comparative analysis (fsQCA) for studies with a moderately large-n (between approximately 50 and 100). Moderately large-n studies are interesting in this respect since they allow for regression analysis as well as fsQCA analysis. These two approaches have a different epistemological foundation and thereby answer different, yet related, research questions. To illustrate the comparison of fsQCA and regression analysis empirically, I use a recent data set (n = 53) that includes data on the conditions under which governments in Western democracies increase their spending on active labor market policies (ALMPs). This comparison demonstrates that while each approach has merits and demerits, fsQCA leads to a fuller understanding of the conditions under which the outcome occurs.
Notes on generalization of proof normalization

In this paper, we provide a general setting under which results of normalization of proof trees such as, for instance, the logicality result in equational reasoning and the cut-elimination property in sequent or natural deduction calculi, can be unified and generalized. This is achieved by giving simple conditions which are sufficient to ensure that such normalization resultshold, and because syntactical, can be implemented. These conditions are based on basic properties of elementary combinations of inference rules which assure that the induced “global” proof tree transformation processes do terminate.
Cell cycle-dependent regulation of the nuclease activity of Mus 81 – Eme 1 / Mms 4

The conserved heterodimeric endonuclease Mus81– Eme1/Mms4 plays an important role in the maintenance of genomic integrity in eukaryotic cells. Here, we show that budding yeast Mus81–Mms4 is strictly regulated during the mitotic cell cycle by Cdc28 (CDK)and Cdc5 (Polo-like kinase)-dependent phosphorylation of the non-catalytic subunit Mms4. The phosphorylation of this protein occurs only after bulk DNA synthesis and before chromosome segregation, and is absolutely necessary for the function of the Mus81–Mms4 complex. Consistently, a phosphorylation-defective mms4 mutant shows highly reduced nuclease activity and increases the sensitivity of cells lacking the RecQ-helicase Sgs1 to various agents that cause DNA damage or replicative stress. The mode of regulation of Mus81–Mms4 restricts its activity to a short period of the cell cycle, thus preventing its function during chromosome replication and the negative consequences for genome stability derived from its nucleolytic action. Yet, the controlled Mus81–Mms4 activity provides a safeguard mechanism to resolve DNA intermediates that may remain after replication and require processing before
School Counselor and Teacher Collaboration to Enhance Students’ Career Development Using Project-Based Learning

We utilized a mixed-methods design to examine the experiences of 15 school counselors and 26 teachers who participated in a professional development program focused on collaboration to enhance students’ career development using project-based learning (PBL). PBL is a teaching method through which students engage in active learning by responding to a real-world challenge, problem, or question. We identified the following four themes: collaboration facilitators, collaboration challenges, classroom collaboration, and place-based collaboration. After participating in the program, teachers and school counselors reported being likely to engage with each other to incorporate career development in the classroom.
Real-Time Gait Analysis Algorithm for Patient Activity Detection to Understand and Respond to the Movements

Context: Most of the patients suffering from any neurological disorder pose ambulatory disturbance at any stage of disease which may result in falling without showing any warning sign and every patient is different from another. So there is a need to develop a mechanism to detect shaky motion. Objectives: The major objectives are: (i) To check different gait parameters in walking disorders using Shimmer platform (R). (ii) Wearing SHIMMER wireless sensors on hip, waist and chest, to check which one is the most suitable. (iii) To draw effective conclusion/results based on calibrated data in real time and offline processing in EyesWeb/Matlab.To develop an effective mechanism/algorithm for security warning and activating alarm systems. Methods: Our thesis project is related to analyze real-time gait of the patient suffering from Parkinson's disease for actively responding to the shaky movements. Based on real world data, we have developed a mechanism to monitor a real time gait analysis algorithm to detect any gait deviation. This algorithm is efficient, sensitive to detect miner deviation and not hard coded i.e. user can set Sampling Rate & Threshold values to analyze motion. Researchers can directly use this algorithm in their study without need to implement themselves. It works on pre-calculated threshold values while initial sampling rate is set to 100MHz. Results: Accelerometers putting on the chest shows high unnecessary acceleration during fall, suggest putting on waist position. Also, if a patient initiates steps with energy, his/her gait may become more stable as shown in the conscious gait. Results show that after DBS surgical procedure, the patient still experiences postural instability with fall. So it is evident to show that such patients may have reduced cognition even after surgery. Another finding is that such patients may lean left or right during turning. Conclusions: We have presented a real time gait analysis algorithm, capable of detecting the motion of the patient with PD to actively respond to the shakier motion setting threshold values. Our proposed algorithm is easy to implement, reusable and can affectively generate healthcare alarms. Additionally, this system might be used by other researchers without the need to implement by themselves. The proposed method is sensitive to detect fall therefore objectively can be used for fall risk assessment as well . The same algorithm with minor modifications can be used for seizure detection in other disorders mainly epileptic seizers to alert health providers for emergency.
Introduction to Ubit Semantic Computing

Compute science faces two basic and hardly solved problem; the first is semantic ambiguity; the second is the semantics only understandable to human, not understandable to machine. The difficulties stem from unstructured bits. Based on a new theory, called as Ubit theory, this paper introduces a new generation of semantic computing, called as Ubit Semantic Computing (USC), which can solve the problems successfully. This paper first introduces Ubit theory briefly, then explains how to eliminate semantic ambiguities of natural language, video, audio, and image; and how to make them understandable to both machine and human; then introduces how to make semantics of program and web understandable to both machine and human; making semantic translating tools no needed any more, such as compiler, interpreter, semantic analysis, web parser, domain name resolution; then introduces an integrated interface of USC, by which, anyone can access anything, from anywhere, and in anytime; at last presents an architecture of USC.