Miracle-dz/UniFAR-FTUs huggingface dataset:
The Star Formation History of NGC 1705: A Poststarburst Galaxy on the Verge of Activity

We infer the star formation history in different regions of the blue compact dwarf NGC 1705 by comparing synthetic color-magnitude diagrams with the Hubble Space Telescope optical and near-infrared photometry. We find that NGC 1705 is not a young galaxy, because its star formation commenced at least 5 Gyr ago. On the other hand, we confirm the existence of a recent burst of star formation between 15 and 10 Myr ago. We also find evidence for new strong activity, which started 3 Myr ago and is still continuing. The old population is spread across the entire galaxy, while the young and intermediate stars are more concentrated in the central regions. We derive an almost continuous star formation with variable rate and exclude the presence of long quiescent phases between the episodes during the last ≈1 Gyr. The central regions experienced an episode of star formation of ∼0.07 M⊙ yr-1 (for a Salpeter initial mass function [IMF]) 15 to 10 Myr ago. This coincides with the strong activity in the central super–star cluster. We find a rate of ∼0.3 M⊙ yr-1 for the youngest ongoing burst, which started ∼3 Myr ago. This is higher than in other dwarfs and comparable to the rate of NGC 1569. The star formation rate of earlier episodes is not especially high and falls in the range 10-3 to 10-1 M⊙ yr-1. The IMF is close to the Salpeter value or slightly steeper.
Learning Object Segmentation using a Multi Network Segment Classification Approach

In this study we propose a new strategy to perform an object segmentation using a multi neural network approach. We started extending our previously presented object detection method applying a new segment based classification strategy. The result obtained is a segmentation map post processed by a phase that exploits the GrabCut algorithm to obtain a fairly precise and sharp edges of the object of interest in a full automatic way. We tested the new strategy on a clothing commercial dataset obtaining a substantial improvement on the quality of the segmentation results compared with our previous method. The segment classification approach we propose achieves the same improvement on a subset of the Pascal VOC 2011 dataset which is a recent standard segmentation dataset, obtaining a result which is inline with the state of the art.
Transcriptomic analysis of peripheral blood mononuclear cells in rapid progressors in early HIV infection identifies a signature closely correlated with disease progression.

BACKGROUND A substantial percentage (10%-15%) of HIV-infected individuals experience a sharp decline in CD4(+) T-cell counts and progress to AIDS quickly after primary infection. Identification of biomarkers distinguishing rapid progressors (RPs) vs chronic progressors (CPs) is critical for early clinical intervention and could provide novel strategies to facilitate vaccine design and immune therapy. METHODS mRNA and microRNA (miRNA) expression profiles in the peripheral blood mononuclear cells (PBMCs) of RPs and CPs were investigated at 111 (22) days [mean (SD)] of HIV infection. The association of mRNA and miRNA expression with disease progression was examined by ROC analysis and Kaplan-Meier survival analysis. RESULTS Pathway enrichment analysis showed that genes with deregulated expression in RPs were primarily involved in apoptosis pathways. Furthermore, we found that 5 miRNAs (miR-31, -200c, -526a, -99a, and -503) in RPs were significantly decreased compared to those in CPs (P < 0.05). The decreased expression of these miRNAs was associated with a rapid disease of progression of HIV infection with a 94% predictive value as measured by the area under the curve. The upregulated predicted targets from the 5 signature miRNAs and all upregulated genes identified from mRNA microarray analysis converged to the apoptosis pathway. Moreover, overexpression of miR-31 in primary human T cells promoted their survival. CONCLUSIONS Our results have identified a distinct transcriptomic signature in PBMCs of RPs and provided novel insights to the pathogenesis of HIV infection.
A FORMAL NOTATION FOR THE RULES OF FUNCTION POINT ANALYSIS

Function Point Analysis (FPA) is a method for measuring the functional size of a software system. The rules governing FPA are laid down in the Counting Practices Manual (the CPM) by the International Function Point Users Group. This paper ◊ defines a formal notation (N) for software designs, ◊ shows that the notation N is consistent with the language of the the CPM ◊ shows that FPA can be expressed as a program (P) operating on a design expressed in N ◊ shows that the program P can be expressed in 17 steps of which 12 are algorithmic and five require human judgment. Each step of the argument is justified by reference to the the CPM. The notation N is consistent with that used by many CASE tools. The paper is designed for two classes of reader, the function points expert and the tool builder. For the function points expert it captures the mechanism of counting function points as defined in the CPM; for the tool builder it provides the detail required to start building the physical design of an interactive tool for counting function points.
User-level checkpoint and recovery for LAM/MPI

As high-performance clusters continue to grow in size and popularity, issues of fault tolerance and reliability are becoming limiting factors on application scalability. We integrated one user-level checkpointing and rollback recovery (CRR) library to LAM/MPI, a high performance implementation of the Message Passing Interface (MPI), to improve its availability. Compared with the current CRR implementation of LAM/MPI, our work supports file checkpointing and own higher portability, which can run on more platforms including IA32 and IA64 Linux. In addition, the test shows that less than 15% performance overhead is introduced by the CRR mechanism of our implementation.
Resveratrol Ameliorates the Depressive-Like Behaviors and Metabolic Abnormalities Induced by Chronic Corticosterone Injection

Chronic glucocorticoid exposure is known to cause depression and metabolic disorders. It is critical to improve abnormal metabolic status as well as depressive-like behaviors in patients with long-term glucocorticoid therapy. This study aimed to investigate the effects of resveratrol on the depressive-like behaviors and metabolic abnormalities induced by chronic corticosterone injection. Male ICR mice were administrated corticosterone (40 mg/kg) by subcutaneous injection for three weeks. Resveratrol (50 and 100 mg/kg), fluoxetine (20 mg/kg) and pioglitazone (10 mg/kg) were given by oral gavage 30 min prior to corticosterone administration. The behavioral tests showed that resveratrol significantly reversed the depressive-like behaviors induced by corticosterone, including the reduced sucrose preference and increased immobility time in the forced swimming test. Moreover, resveratrol also increased the secretion of insulin, reduced serum level of glucose and improved blood lipid profiles in corticosterone-treated mice without affecting normal mice. However, fluoxetine only reverse depressive-like behaviors, and pioglitazone only prevent the dyslipidemia induced by corticosterone. Furthermore, resveratrol and pioglitazone decreased serum level of glucagon and corticosterone. The present results indicated that resveratrol can ameliorate depressive-like behaviors and metabolic abnormalities induced by corticosterone, which suggested that the multiple effects of resveratrol could be beneficial for patients with depression and/or metabolic syndrome associated with long-term glucocorticoid therapy.
The Limits of Fiscal Policy in Current Account Adjustment

A system and method for re-attaching soft tissue to bone. In its preferred embodiment, the system comprises pin means, sleeve means, driver means, suture anchor means and suture anchor installation tool means. In use, the soft tissue is placed against the surface of the bone in its desired re-attachment position. Then the pin means is passed through the soft tissue and into the bone to securely fix the pin means (and hence the soft tissue) to the bone. Then the patient's anatomy is manipulated as needed to determine if the soft tissue has been properly positioned relative to the bone. If the soft tissue is properly positioned, the surgeon proceeds to the next step in the procedure; if not, the pin means is removed and the tissue positioning operation repeated until the soft tissue has been positioned in the desired location. Next, the sleeve means is slid telescopically over the pin means, passed through the soft tissue and then, using the driver means, drilled into the bone. Then the pin means is completely withdrawn from the bone and the soft tissue, leaving a hole in the bone. The suture anchor means is then passed down the interior of the sleeve means and into the bone, using the suture anchor installation tool means. Then the installation tool means is withdrawn from the sleeve means, leaving the suture anchor means deployed in the bone and its associated suture extending out through the sleeve means. The sleeve means is then withdrawn, and the free ends of the suture used to secure the soft tissue to the bone.
GMTC: A Generalized Commit Approach for Hybrid Mobile Environments

Mobile environments increasingly require distributed atomic transactions to support the growing diversity of financial, gaming, social networking and many other applications. The underlying mobile infrastructure is correspondingly evolving with increasingly diverse wired and wireless elements and also with increasing exposure to a variety of operational perturbations at the mobile elements and communication levels. Consequently, the challenge is not only in providing efficient nonblocking mobile commit (as a fundamental basis behind consistent mobile transactions) but to also provide efficient perturbation-resilient atomic commit in the heterogeneous mobile space. The contribution of this paper is in developing a perturbation-resilient mobile commit protocol that efficiently provides for and preserves strict atomicity for transactional applications. The protocol does not necessarily require access to the powerful communication/computation elements of the wired infrastructure during transaction execution. However, in case access to a wired network becomes possible, it then adapts to utilize this to 1) increase the resilience to network perturbations achieving higher commit rates, and 2) reduce the wireless message overhead and the blocking of transaction participants leading to higher transactions throughput. In contrast, existing solutions are often tailored either for 1) infrastructure-based mobile environments, or 2) infrastructure-less ad hoc networks. To our knowledge, there is no existing commit protocol that can adapt across diverse infrastructure communication modes. The proposed perturbation-resilient generalized mobile transaction commit (GMTC) protocol represents the first atomic commit protocol for hybrid mobile environments which 1) takes advantage of accessing infrastructures, by choosing reliable infrastructure nodes for coordination of transactions and for replication of commit data of mobile participants to tolerate network disconnections, and 2) tolerates network partitioning and delivers best-effort resultsâin terms of transaction commit rate, message complexity, and commit/abort decision time (latency)âif the access to wired infrastructure is unavailable. The protocol performance simulations (covering transaction commit rate, message complexity, and commit/abort decision time) demonstrate the effectiveness of the developed protocol in generalized mobile environments.
Almost All Learning Machines are Singular

A learning machine is called singular if its Fisher information matrix is singular. Almost all learning machines used in information processing are singular, for example, layered neural networks, normal mixtures, binomial mixtures, Bayes networks, hidden Markov models, Boltzmann machines, stochastic context-free grammars, and reduced rank regressions are singular. In singular learning machines, the likelihood function can not be approximated by any quadratic form of the parameter. Moreover, neither the distribution of the maximum likelihood estimator nor the Bayes a posteriori distribution converges to the normal distribution, even if the number of training samples tends to infinity. Therefore, the conventional statistical learning theory does not hold in singular learning machines. This paper establishes the new mathematical foundation for singular learning machines. We propose that, by using resolution of singularities, the likelihood function can be represented as the standard form, by which we can prove the asymptotic behavior of the generalization errors of the maximum likelihood method and the Bayes estimation. The result will be a base on which training algorithms of singular learning machines are devised and optimized
Marketing Orientation and Company Performance: A Comparative Study of Industrial vs. Consumer Goods Companies by

/Summary: Marketing orientation, still an intriguing concept for many, carries the pledge of superior company performance through the satisfaction of customers' needs. In this paper, drawing conclusions from an empirical investigation, the authors show that this relationship does really exist and, in the case of industrial markets , building a marketing orientation it is indeed a significant contributor to the company's performance. 3 1.
A control design method for a class of SISO switched linear systems

We consider the control design for a class of single-input si ngle-output (SISO) switched linear systems of arbitrary order. Our approach is motivated by applications in which the major design objective is to achieve similar behaviour of the closed-loop system in each system mode ensu ring stability for arbitrary switching. We study the stability of the resulting closed-loop system and exploit t he algebraic properties of a class of matrices to derive simple stability conditions for the switched system. Furth e we the implementation of the switched controller with integrators is discussed and conditions are derived to avoi d transient dynamics induced by the switching. We show that closed-loop stability and transient-free switching c an be achieved simultaneously.
Solving production scheduling with chain constraints in parallel production lines by column generation

This paper studies coil scheduling problem with chain constraints in the parallel continuous annealing production lines. The task of the problem is making schedules of the candidate coils in the inventory to minimize the total weighted completion times. In addition, some chain constraints should be satisfied, which has been determined by the practical production requirements. To solve this problem, column generation technology is adopted. And the pricing problem in column generation steps is solved by dynamic programming recursions. Branch and bound is used to obtain optimal solutions. Finally, the experiment results prove the efficiency of the algorithm.
Comparative Study on Performance of Islamic Banks and Conventional Banks in GCC region

Islamic banking is considered as alternative to conventional banking. It focuses on profit/loss and risk sharing, than interest based deposit/lending followed in conventional banking. Conventional Banking cherishes a long history while Islamic banking gained importance in last few decades. The study review and compare performance of conventional banks and Islamic banks operating in GCC region during 2005-10. The study investigates the presence, if any, of similarity in growth of chosen performance indicators of Conventional Banks and Islamic Banks in GCC region. The study selected six Islamic banks and six conventional banks. A comparative study is undertaken based performance indicators such as OER, NPR, ROA, ROE, EOA, operating expense, profit, assets, operating income, deposits and total equity. Inferences based on analysis revealed better performance of Islamic banking during the study period. Our analysis revealed that Islamic banks are more equity financed than conventional banks. ANOVA showed the presence of significant relationship in movement of selected financial indicators. Conventional banks registered growth in revenue during the period, but could not achieve improved profitability on account of higher provisions towards credit losses and impairment losses. The performance indicators were affected by financial crises as may be noted from the recessionary trends since 2007.
The pattern of c-Fos expression and its refractory period in the brain of rats and monkeys

Intense activation of neurons triggers the appearance of immediate expression genes, including c-Fos. This gene is related to various signal cascades involved in biochemical processes such as neuronal plasticity, cell growth and mitosis. Here we investigate the expression pattern and the refractory period of c-Fos in rats and monkey’s brains after stimulation with pentylenetetrazol. Rats and monkeys were sacrificed at various times after PTZ-induced seizure. Here we show that rats and monkeys already showed c-Fos expression at 0.5 h after seizure. Yet, the pattern of protein expression was longer in monkeys than rats, and also was not uniform (relative intensity) across different brain regions in monkeys as opposed to rats. In addition monkeys had a regional brain variation with regard to the temporal profile of c-Fos expression, which was not seen in rats. The refractory period after a second PTZ stimulation was also markedly different between rats and monkeys with the latter even showing a summatory effect on c-Fos expression after a second stimulation. However, assessment of c-Fos mRNA in rats indicated a post-transcriptional control mechanism underlying the duration of the refractory period. The difference in the protein expression pattern in rodents and primates characterizes a functional aspect of brain biochemistry that differs between these mammalian orders and may contribute for the more developed primate cognitive complexity as compared to rodents given c-Fos involvement in cognitive and learning tasks.
CASCADE ALGORITHMS IN WAVELET ANALYSIS

In this paper we survey some recent results on cascade algorithms. Let a be a finitely supported sequence on ZZ. The cascade operator Qa is the the linear operator on Lp(IR) (1 ≤ p ≤ ∞) given by Qaf := ∑ j∈Z a(j)f(2 · − j), f ∈ Lp(IR). The iteration scheme Qaf (n = 1, 2, . . .) is called the cascade algorithm associated with a. The Lp convergence of a cascade algorithm is characterized in terms of the p-norm joint spectral radius of two matrices associated with the corresponding mask. For the special case p = 2, convergence of a cascade algorithm is characterized in terms of the spectrum of the transition matrix associated with the mask. Then the basic theory on cascade algorithms is employed to give a unified treatment of orthogonal wavelets, biorthogonal wavelets, and fundamental refinable functions. Furthermore, we give a comprehensive review of biorthogonal wavelet bases. Our methods can be used to deal with more complicated problems such as biorthogonal wavelet bases on bounded domains. Finally, we extend our study of cascade algorithms to high dimensional spaces. † Research was supported in part by NSERC Canada under Grants # OGP 121336. §
Gendered Musical Chairs: Job Succession and Gender Segregation

Among the many sources of evidence on the phenomenon of job sex segregation is research showing that job vacancies tend to be filled by new hires who match the gender of the previous job holder. In this paper, we seek to understand how the gender composition of job vacancies is reproduced over time. Since multiple organizational processes may contribute to this pattern, this research focuses on separating the mechanisms that reproduce the gender composition of jobs. Using unique data from a retail bank, we studied the distinct steps in the hiring process for job openings produced when the previous incumbent of the job was female versus male. Our findings highlight the multifaceted nature of the processes by which gender typing of jobs is reproduced and maintained. We show that gender segregation is present at job succession not only through screeners‘ preferences but also through applicants’ self-selecting into vacancies.
Characterization and Compatibility Studies of Different Rate Retardant Polymer Loaded Microspheres by Solvent Evaporation Technique: In Vitro-In Vivo Study of Vildagliptin as a Model Drug

The present study has been performed to microencapsulate the antidiabetic drug of Vildagliptin to get sustained release of drug. The attempt of this study was to formulate and evaluate the Vildagliptin loaded microspheres by emulsion solvent evaporation technique using different polymers like Eudragit RL100, Eudragit RS100, Ethyl cellulose, and Methocel K100M. In vitro dissolution studies were carried out in 0.1 N HCl for 8 hours according to USP paddle method. The maximum and minimum drug release were observed as 92.5% and 68.5% from microspheres, respectively, after 8 hours. Release kinetics were studied in different mathematical release models to find out the linear relationship and release rate of drug. The SEM, DSC, and FTIR studies have been done to confirm good spheres and smooth surface as well as interaction along with drug and polymer. In this experiment, it is difficult to explain the exact mechanism of drug release. But the drug might be released by both diffusion and erosion as the correlation coefficient (R 2) best fitted with Korsmeyer model and release exponent (n) was 0.45–0.89. At last it can be concluded that all in vitro and in vivo experiments exhibited promising result to treat type II diabetes mellitus with Vildagliptin microspheres.
Notes on Steerable Filters

The simplest illustration of a steerable function is the first-order directional derivative of a two-dimensional Gaussian. Although we will only consider Gaussians, the principle of steerability may be extended to any differentiable function. For notational simplicity we will consider a unit-variant Gaussian and ignore the 1 p2 scaling constant: g(x; y) = e (x2+y2)=2: (1) Lets begin by considering the first-order horizontal derivative (i.e., in x) of g(x; y), given by: gx(x; y) = @g(x; y) @x = xe (x2+y2)=2: (2)
Emergence and Computability

This paper presents a discussion of the possible influence of incomputability and the incompleteness of the mathematics as a source of apparent emergence in complex systems. The suggestion is made that the analysis of complex systems as a specific instance of a complex process may be subject to inaccessible “emergence”. We discuss models of computation associated with transcending the limits of traditional Turing systems, and suggest that inquiry into complex systems in the light of the potential limitations of incomputability and incompleteness may be worthwhile.
On Service Level Measures in Stochastic Inventory Control

Abstract We consider the issue of modeling service level measures in stochastic decision making via chance constraints. More specifically we focus on service level measures in production/inventory control under stochastic demand and α service level constraints, which are constraints enforcing a prescribed non-stockout probability for the system. We introduce multiple ways of expressing these chance constraints by using conditional probability. Then we demonstrate that, when these constraints are formulated by using expressions that do not involve a conditional probability, a base stock policy is optimal for this problem only under a number of assumptions. To demonstrate this, we discuss a number of examples for simple cases in which it is possible to find better policies and we also present some analytical results. In contrast, when our novel measure involving a conditional probability is used, a base stock policy is optimal under much less restrictive assumptions, although the cost performance of the system tends to deteriorate.