Miracle-dz/UniFAR-FTUs huggingface dataset:
Near-Infrared Properties of Moderate-Redshift Galaxy Clusters: Luminosity Functions and Density Profiles

We present K-band imaging for 15 of the CNOC1 clusters. The extensive spectroscopic data set available for these clusters allows us to determine the cluster K-band luminosity function and density profile without the need for statistical background subtraction. The luminosity density and number density profiles can be described by NFW models with concentration parameters of cl = 4.28 ± 0.70 and cg = 4.13 ± 0.57, respectively. Comparing these to the dynamical mass analysis of the same clusters shows that they are similar to the cluster dark matter profile. The luminosity functions show that the evolution of K* over the redshift range 0.2 < z < 0.5 is consistent with a scenario in which the majority of stars in cluster galaxies form at high redshift (zf > 1.5) and evolve passively thereafter. The best fit for the faint-end slope of the luminosity function is α = -0.84 ± 0.08, which indicates that it does not evolve between z = 0 and 0.3. Using principal component analysis of the spectra, we classify cluster galaxies as either star-forming/recently star-forming (EM+BAL) or non-star-forming (ELL) and compute their respective luminosity functions. The faint-end slope of the ELL luminosity function is much shallower than for the EM+BAL galaxies at z = 0.3 and suggests that the number of faint ELL galaxies in clusters decreases by a factor of ~3 from z = 0 to 0.3. The redshift evolution of K* for both EM+BAL and ELL types is consistent with a passively evolving stellar population formed at high redshift. Passive evolution in both classes demonstrates that the bulk of the stellar population in all bright cluster galaxies is formed at high redshift, and subsequent transformations in morphology/color/spectral type have little effect on the total stellar mass.
Addressing Minority Student Achievement through Service Learning in a Culturally Relevant Context

Research on recreational media use among youth indicates young people of color who spend more time with media may also be at higher risk for school disengagement and low personal contentment compared to their white peers. This puts these students in a position to be even more influenced by the themes and messages that abound in pop culture, particularly music and social media. ME: MIM is a multisensory, interdisciplinary, integrated approach to teaching and learning that uses music multimedia to engage students in individual and group activities and lessons that reinforces competencies aligned with positive youth development. Song lyrics, sound recordings and music videos are used as “text” to facilitate deconstruction and discussion of the themes and messages in music and the context. Students also discuss the influence of these themes and messages on their attitudes, beliefs, and choices as it relates to their cultural group identity and individual behavior both in and out of school. ME:MIMM has been facilitated through the Challenging Horizons Program (CHP), an evidence-based, after-school and summer service-learning program for academically and behaviorally challenged students. This study examined key stakeholders’ (i.e., parents/guardians, program staff members, and school administrators) perceptions of feasibility and acceptability of ME: MIM.
Microextraction of bacterial lipid A: easy and rapid method for mass spectrometric characterization Published, JLR Papers in Press, June 1, 2005. DOI 10.1194/jlr.D500014-JLR200

Endotoxins (lipopolysaccharides) are the main components of Gram-negative bacterial outer membranes. A quick and simple way to isolate their lipid region (lipid A) directly from whole bacterial cells was devised. This method using hot ammonium-isobutyrate solvent was applied to small quantities of cells and proved to be indispensable when a rapid characterization of lipid A structure by mass spectrometry was required. Biological activities of endotoxins are directly related to the lipid A structures, which vary greatly with cell growth conditions. This method is suitable for rough- and smooth-type bacteria and very efficient for screening variations in lipid A structures. Data are acquired in a few hours and avoid the use of phenol in extraction.
Acquired Factor VIII Inhibitors: Three Cases

Acquired hemophilia A is a rare, but devastating bleeding disorder caused by spontaneous development of autoantibodies directed against coagulation factor VIII. In 40%-50% of patients it is associated with such conditions as the postpartum period, malignancy, use of medications, and autoimmune diseases; however, its cause is unknown in most cases. Acquired hemophilia A should be suspected in patients that present with a coagulation abnormality, and a negative personal and family history of bleeding. Herein we report 3 patients with acquired hemophilia A that had different underlying pathologies, clinical presentations, and therapeutic responses. Factor VIII inhibitor formation in case 1 occurred 6 months after giving birth; underlying disorders were not identified in cases 2 or 3. The bleeding phenotype in these patients’ ranged from no bleeding tendency with isolated prolongation of APTT (activated partial thromboplastin time) to severe intramuscular hematoma and hemarthrosis necessitating recombinant activated factor VII infusion and blood components transfusion. Variable responses to immunosuppressive treatment were also observed. Conflict of interest:None declared.
X-ray time lags from a pivoting power law in black holes

Most black hole candidate X-ray binaries show Fourier time lags between softer and harder X-rays. The hard photons seem to arrive up to a few ms after the soft for a given Fourier frequency of the perturbation. The energy dependence of the time lags has a roughly logarithmic behavior. Up to now most theories fail to explain the observed magnitude and Fourier frequency dependence of the lags or fail other statistical tests. We show that the time lags can arise from a simple pivoting power law model, which creates the logarithmic dependence on the photon energy at once. A pivoting power law arises naturally from jet/synchrotron models for the X-ray emission, but may also be applicable to corona models. A hint to the coherence features of the light-curves can be obtained from the power spectral density, which can be decomposed into a few broad Lorentzians that could arise from a couple of strongly damped oscillators with low quality factors below one. Using small variations of the power law index for each Lorentzian separately the lags can be derived analytically. They show the correct Fourier frequency dependence of the time lags. If one assumes variations of the power law index by ±0.2 the model can account for the observed magnitude of the time lags in Cyg X-1. The model can also be applied to TeV blazars, where a pivoting power law and hard lags have been observed directly in some cases. As a further test we calculated the cross- and auto-correlation functions for our model, which also show qualitatively the observed behavior. The auto-correlation function for higher energies has a narrower peak than at lower energies and the cross-correlation function is asymmetric but peaks nearly at zero. The coherence function for the model is in agreement with the observed data in the Fourier regime, where the model is valid.
The Three Minds Argument

Searle (1980, 2002, 2006) has long maintained a position that non-biologically based machines (including robots and digital computers), no matter how intelligently they may appear to behave, cannot achieve “intentionality” or “consciousness,” have a “mind,” and so forth. Standard replies to Searle’s argument, as commonly cited by researchers in Artificial Intelligence and related communities, are sometimes considered unsatisfactory by readers outside of such fields. One possible reason for this is that the Chinese Room Argument makes a strong appeal to some people’s intuitions regarding “understanding” and necessary conditions for consciousness. Rather than contradict any such intuitions or conditions, I present what in my view is an independent and largely compatible intuition: If Searle’s argument is sound, then surely a human placed under similar testing conditions as a non-biological machine should succeed where a machine would allegedly fail. The outcome is a new rebuttal to the Chinese Room that is ideologically independent of one’s views on the necessary and sufficient conditions for having a “mind. ”
CC chemokine CCL5 plays a central role impacting infarct size and post-infarction heart failure in mice.

AIMS The chemokine CCL5 plays a critical role as neutrophil and macrophage activator do in atherosclerosis and myocardial infarction. Thus, we investigated whether the treatment with a neutralizing monoclonal antibody (mAb) to mouse CCL5 would provide therapeutic benefit when provoking a coronary-associated ischaemic event. METHODS AND RESULTS C57Bl/6 mice were submitted to left coronary artery permanent ligature. Then, various parameters were monitored for up to 21 days. At5 min and 3 days after coronary occlusion, mice received one intravenous injection of the rat anti-mouse CCL5 mAb or isotype IgG control. Infarct size was assessed histologically and by measuring serum cardiac troponin I levels. Kinetics of CCL5 tissue expression, leucocyte infiltration, matrix metalloproteinase (MMP) levels, and collagen deposition were histologically assessed. Serum chemokine levels were measured by enzyme-linked immunosorbent assay. Cardiac function and dimensions were assessed by magnetic resonance imaging (MRI). Chronic ischaemia increased both circulating and intracardiac levels of CCL5. At 24 h, treatment with the anti-CCL5 mAb resulted in a smaller infarct size and reduced circulating levels of chemokines. This effect was associated with reduction of neutrophil and macrophage infiltration within the infarcted myocardium. After 3 days of chronic ischaemia, anti-CCL5 mAb treatment reduced cardiac MMP-9. At 7 days, collagen content was significantly lower. At 21 days, neutralizing CCL5 improved mouse survival, cardiac myocyte size, and cardiac function. CONCLUSION Treatment with anti-CCL5 mAb significantly reduced both infarct size and post-infarction heart failure in a mouse model of chronic cardiac ischaemia. Cardioprotective effects were associated with the reduction of leucocyte recruitment within infarcted hearts.
Development and Evaluation of Diclofenac Sodium Loaded-N-Trimethyl Chitosan Nanoparticles for Ophthalmic Use

The ophthalmic preparation of diclofenac sodium (DC) for relieving ocular inflammation is presently available in the market only as an eye drop solution. Due to its low occular bioavailability, it requires frequent application leading to low patients’ compliance and quality of life. This study was conducted to develop formulations of DC loaded-N-trimethyl chitosan nanoparticles (DC-TMCNs) for ophthalmic use to improve ocular biavailabiltiy of DC. DC-TMCNs varied in formulation compositions were prepared using ionic gelation technique and evaluated for their physicochemical properties, drug release, eye irritation potential, and ophthalmic absorption of diclofenac sodium. N-Trimethyl chitosan (TMC) with a 49.8% degree of quaternization was synthesized and used for DC-TMCNs production. The obtained DC-TMCNs had particle size in a range of 130–190 nm with zeta potential values of +4 to +9 mV and drug entrapment efficiencies of more than 70% depending on the content of TMC and sodium tripolyphosphate (TPP). The optimized DC-TMCNs formulation contained TMC, DC, and TPP at a weight ratio of TMC/DC/TPP = 3:1:1. Their lyophilized product reconstituted with phosphate buffer solution pH 5.5 possessed a drug release pattern that fitted within the zero-order model. The eye irritation tests showed that DC-TMCNs were safe for ophthalmic use. The in vivo ophthalmic drug absorption study performed on rabbits indicated that DC-TMCNs could improve ophthalmic bioavailability of DC. Results of this study suggested that DC-TMCNs had potential for use as an alternative to conventional DC eye drops for ophthalmic inflammation treatment.
Quantitative analysis of information security interdependency between industrial sectors

This paper employs Input-Output analysis to quantitatively analyze cross-sectoral security interdependency in terms of economic activity. Previous studies using the Inoperability Input-Output Model (IIM) have demonstrated the impact of cross-sectoral security incidents from the viewpoint of interdependency. However, the two primary limitations of these studies are that (1) they do not consider each sector's features in terms of information technology (IT) and information security (IS), and (2) they focus on the damage caused by IS incidents to sectors and do not consider the level of security interdependency itself. The author proposes a practical methodology to measure sectoral IS interdependency by introducing forward linkage and backward linkage analyses into an IIM. The methodology assesses the dependency of each sector with respect to IT and the level of IS measures. Furthermore, the paper applies the methodology to recent statistical economic data of Japanese industrial sectors and illustrates the implications of cross-sectoral security interdependency.
A Unified Framework for Low Autocorrelation Sequence Design via Majorization–Minimization

In this paper, we consider the low autocorrelation sequence design problem. We optimize a unified metric over a general constraint set. The unified metric includes the integrated sidelobe level (ISL) and the peak sidelobe level (PSL) as special cases, and the general constraint set contains the unimodular constraint, Peak-to-Average Ratio (PAR) constraint, and similarity constraint, to name a few. The optimization technique we employ is the majorization-minimization (MM) method, which is iterative and enjoys guaranteed convergence to a stationary solution. We carry out the MM method in two stages: in the majorization stage, we propose three majorizing functions: two for the unified metric and one for the ISL metric; in the minimization stage, we give closed-form solutions for algorithmic updates under different constraints. The update step can be implemented with a few Fast Fourier Transformations (FFTs) and/or Inverse FFTs (IFFTs). We also show the connections between the MM and gradient projection method under our algorithmic scheme. Numerical simulations have shown that the proposed MM-based algorithms can produce sequences with low autocorrelation and converge faster than the traditional gradient projection method and the state-of-the-art algorithms.
Impact of Disinflation on Profitability: A Data Envelopment Analysis Approach for Turkish Commercial Banks

 Abstract—Data Envelopment Analysis (DEA) analysis has been applied to the banking industry by a significant number of researchers. In this paper, the aim is to investigate the direct influence of inflation on banks' profitability. Doing so, the data of the period 1998-2003 when the inflation was relatively high is compared to the data of the period 2004-2008 when the inflation was higher. DEA's ability to evaluate several inputs and outputs at the same time and give efficiency scores to each decision making unit is used to evaluate banks' efficiencies. The results reveal which period is more profitable for commercial banks.
Adapting byte addressable memory storage to user-level file system services

Widely available distributed file systems for big data processing are implemented as user-level services since the existing file systems, which are implemented in the operating system kernel, cannot satisfy their requirements. They usually employ file systems in the kernel to persistently save their data in their local systems; thus, the kernel is always interposed for their access the storage devices. Now, next generation non-volatile memory technologies are emerging as byte addressable memory devices that can be used as high performance storage, for which the interposition of the kernel is the source of overhead. This paper proposes the adaption of memory storage to user-level file system services and the convergence of such services and memory storage. User-level file system services are connected to memory storage through the library implementation of a file system, and a library file system can directly interact with memory storage through the memory interface by mapping memory storage onto a user process address space. We implemented a library file system on Linux. The experiment results show that the the implemented library file system outperforms the existing file system in the kernel and performs 1.9x and 6.5x faster for reading and writing, respectively, for typical cases.
Structural and Parametric Evolution of Continuous-Time Recurrent Neural Networks

Neuroevolution comprehends the class of methods responsible for evolving neural network topologies and weights by means of evolutionary algorithms. Despite their good performance in several control tasks, most of these methods use variations of simple sigmoidal neurons. Recent investigations have shown the potential applicability of more realistic neuron models, opening new perspectives for the next generation of neuroevolutionary methods. This work aims to extend a recent method known as NEAT to evolve continuous-time recurrent neural networks (CTRNNs). The proposed model is compared with previous methods on a control benchmark test. Preliminary results reveal some advantages when evolving general CTRNNs over traditional models.
Coupling heterogeneous production systems by a multi-agent based cyber-physical production system

Todays increasing volatility of market demands and customer requirements are forcing industrial enterprises to realize and ensure an increased flexibility of production systems. Since current automation concepts and architectures for production systems do not provide the required flexibility sufficiently, new approaches have to be developed. This paper proposes an approach that implements the quickly evolving concept of Cyber-Physical Systems for the special case of production systems by means of software agents. A joined demonstrator of such Cyber-Physical Production System is described and used for the evaluation of the proposed multi-agent approach.
A Low-Mass Planet with a Possible Sub-Stellar-Mass Host in Microlensing Event MOA-2007-BLG-192

We report the detection of an extrasolar planet of mass ratio q ∼ 2 × 10−4 in microlensing event MOA-2007-BLG-192. The best-fit microlensing model shows both the microlensing parallax and finite source effects, and these can be combined to obtain the lens masses of M = 0.060+ 0.028−0.021 M☉ for the primary and m = 3.3+ 4.9−1.6 M⊕ for the planet. However, the observational coverage of the planetary deviation is sparse and incomplete, and the radius of the source was estimated without the benefit of a source star color measurement. As a result, the 2 σ limits on the mass ratio and finite source measurements are weak. Nevertheless, the microlensing parallax signal clearly favors a substellar mass planetary host, and the measurement of finite source effects in the light curve supports this conclusion. Adaptive optics images taken with the Very Large Telescope (VLT) NACO instrument are consistent with a lens star that is either a brown dwarf or a star at the bottom of the main sequence. Follow-up VLT and/or Hubble Space Telescope (HST) observations will either confirm that the primary is a brown dwarf or detect the low-mass lens star and enable a precise determination of its mass. In either case, the lens star, MOA-2007-BLG-192L, is the lowest mass primary known to have a companion with a planetary mass ratio, and the planet, MOA-2007-BLG-192Lb, is probably the lowest mass exoplanet found to date, aside from the lowest mass pulsar planet.
Automatic affective dimension recognition from naturalistic facial expressions based on wavelet filtering and PLS regression

Automatic affective dimension recognition from facial expression continuously in naturalistic contexts is a very challenging research topic but very important in human-computer interaction. In this paper, an automatic recognition system was proposed to predict the affective dimensions such as Arousal, Valence and Dominance continuously in naturalistic facial expression videos. Firstly, visual and vocal features are extracted from image frames and audio segments in facial expression videos. Secondly, a wavelet transform based digital filtering method is applied to remove the irrelevant noise information in the feature space. Thirdly, Partial Least Squares regression is used to predict the affective dimensions from both video and audio modalities. Finally, two modalities are combined to boost overall performance in the decision fusion process. The proposed method is tested in the fourth international Audio/Visual Emotion Recognition Challenge (AVEC2014) dataset and compared to other state-of-the-art methods in the affect recognition sub-challenge with a good performance.
A software birthmark based on weighted k-gram

A software birthmark is the invariable features of a program that can used to detect software theft. Software theft can be detected by a birthmark that can cover the whole behavior of a program. To improve the performance of k-grams of resisting semantics-preserving transformations, and also consider a birthmark should cover the whole behavior of a program. A static birthmark based on k-grams and their weights is proposed. Weight is computed by analyzing the rate of change of k-gram frequency between the original program and the transformed programs. Experimental results show that the performance of the proposed birthmark for Java applications is better than static k-gram birthmark against transformations performed by Smokescreen obfuscator, ZKM obfuscator and Jarg optimizer.
Autophagy and Non-Alcoholic Fatty Liver Disease

Autophagy, or cellular self-digestion, is a catabolic process that targets cell constituents including damaged organelles, unfolded proteins, and intracellular pathogens to lysosomes for degradation. Autophagy is crucial for development, differentiation, survival, and homeostasis. Important links between the regulation of autophagy and liver complications associated with obesity, non-alcoholic fatty liver disease (NAFLD), have been reported. The spectrum of these hepatic abnormalities extends from isolated steatosis to non-alcoholic steatohepatitis (NASH), steatofibrosis, which sometimes leads to cirrhosis, and hepatocellular carcinoma. NAFLD is one of the three main causes of cirrhosis and increases the risk of liver-related death and hepatocellular carcinoma. The pathophysiological mechanisms of the progression of a normal liver to steatosis and then more severe disease are complex and still unclear. The regulation of the autophagic flux, a dynamic response, and the knowledge of the role of autophagy in specific cells including hepatocytes, hepatic stellate cells, immune cells, and hepatic cancer cells have been extensively studied these last years. This review will provide insight into the current understanding of autophagy and its role in the evolution of the hepatic complications associated with obesity, from steatosis to hepatocellular carcinoma.