Miracle-dz/UniFAR-FTUs huggingface dataset:
Alteration in cellular fatty acid composition as a response to salt, acid, oxidative and thermal stresses in Lactobacillus helveticus.

The fundamental question in this study is concerned with whether the increase of unsaturated fatty acids in the cell membrane is a general response of certain thermotolerant strains or species when exposed to superoptimal temperatures, and in combination with other stresses, especially oxidative stress. A strain of Lactobacillus helveticus, a species widely used as a starter in the dairy industry and able to tolerate high temperature and NaCl concentrations as well as acidic conditions, was chosen for this study. Cells of strain CNBL 1156, grown in its natural medium (i.e. milk whey), were exposed for 100 min to sublethal combinations of temperature, NaCl, H(2)O(2) and pH, modulated according to a Central Composite Design. The fatty acid composition of cell lipid extract was identified by GC/MS. Polynomial equations, able to describe the individual interactive and quadratic effects of the independent variables on cell fatty acid composition, were obtained. The results and the mathematical models relative to the individual fatty acids indirectly suggest that desaturase activation or hyperinduction play an important role in the response to heat stress. In fact, the relative proportions of oleic, linoleic and palmitic acids increased with temperature in a range between 38 and 54 degrees C. The fatty acid profiles included vernolic acid (up to 37% of total fatty acids), an epoxide of linoleic acid not previously reported in microbial cells. In particular, this epoxide was present in cells exposed to low pH in combination with high temperatures and oxidative stress. In conclusion, these results provide experimental support to the hypothesis that the increase of an oxygen-consuming desaturase system, with a consequent increase in fatty acid desaturation, is a cellular response to environmental stresses able to protect the cells of this anaerobic micro-organism from toxic oxygen species and high temperatures.
Pobreza urbana, segregación residencial y mejoramiento del espacio público en la Ciudad de México

In Mexico City, as well as in other Latin American modern metropolises, huge majorities among population do not get access to income, resources and opportunities that may guarantee adequate conditions living and labor conditions. Poverty, inequality and distinct ways of social exclusion affect social cohesion. The distinct methods used to assess the extent and characteristics of poverty allow for understanding the range and features assumed by this problem. Therefore, among the goods and services offered by the city to those who live in it, this study analyses the public actions taken with the purpose of improving or building new public spaces aimed at promoting collective practices - sports, cultural and recreational areas - which may contribute to strengthen both local identity and community life. It is aimed, particularly, at retrieving the experience of Programa Comunitario de Mejoramiento Barrial (Community Program for Neighborhood Improvement), an initiative of the Federal District government, in force since 2007, that constitutes a massive and innovative participatory action which succeeded in transforming a large number of public spaces in neighborhoods, districts and shantytowns that were under conditions of urban marginalization and social degradation. This article presents two successful cases, in which the governmental support program led to changes in public spaces that contributed for promoting community participation.
Quantification of Functionalised Gold Nanoparticle-Targeted Knockdown of Gene Expression in HeLa Cells

Introduction Gene therapy continues to grow as an important area of research, primarily because of its potential in the treatment of disease. One significant area where there is a need for better understanding is in improving the efficiency of oligonucleotide delivery to the cell and indeed, following delivery, the characterization of the effects on the cell. Methods In this report, we compare different transfection reagents as delivery vehicles for gold nanoparticles functionalized with DNA oligonucleotides, and quantify their relative transfection efficiencies. The inhibitory properties of small interfering RNA (siRNA), single-stranded RNA (ssRNA) and single-stranded DNA (ssDNA) sequences targeted to human metallothionein hMT-IIa are also quantified in HeLa cells. Techniques used in this study include fluorescence and confocal microscopy, qPCR and Western analysis. Findings We show that the use of transfection reagents does significantly increase nanoparticle transfection efficiencies. Furthermore, siRNA, ssRNA and ssDNA sequences all have comparable inhibitory properties to ssDNA sequences immobilized onto gold nanoparticles. We also show that functionalized gold nanoparticles can co-localize with autophagosomes and illustrate other factors that can affect data collection and interpretation when performing studies with functionalized nanoparticles. Conclusions The desired outcome for biological knockdown studies is the efficient reduction of a specific target; which we demonstrate by using ssDNA inhibitory sequences targeted to human metallothionein IIa gene transcripts that result in the knockdown of both the mRNA transcript and the target protein.
A Hybrid Approach to Solve Cold Start Problem in Recommender Systems using Association Rules and Clustering Technique

purposes is increasing at an astonishing rate. More and more people rely on online sites for purchasing songs, apparels, books, rented movies etc. The competition between the online sites forced the web site owners to provide personalized services to their customers. So the recommender systems came into existence. Recommender systems are active information filtering systems that attempt to present to the user, information items in which the user is interested in. The websites implement recommender system feature using collaborative filtering, content based or hybrid approaches. The recommender systems also suffer from issues like cold start, sparsity and over specialization. Cold start problem is that the recommenders cannot draw inferences for users or items for which it does not have sufficient information. This paper attempts to propose a solution to the cold start problem by combining association rules and clustering technique. Comparison is done between the performance of the recommender system when association rule technique is used and the performance when association rule and clustering is combined. The experiments with the implemented system proved that accuracy can be improved when association rules and clustering is combined. An accuracy improvement of 36% was achieved by using the combination technique over the association rule technique.
Establishment of a human large cell lung tumor line (QU‐DB) with metastatic properties in athymic mice

A continuous human cell line was established from a patient with large cell anaplastic lung carcinoma. This cell line, designated QU‐DB, has been in culture for over 36 months and grows as an adherent monolayer with a doubling time of 10–12 hours. Its morphology, ultrastructure, karyotype, ability to grow in soft agar and heterotransplantability, indicate it is a large‐cell lung tumor cell line of human origin. Three cell lines were established from metastatic tumors in nude mice receiving subcutaneous injections of QU‐DB cells. The morphology and growth characteristics exhibited by these cell lines were similar to the primary cell line. Karyotypic analysis of cell lines derived from the primary tumor and a metastasis to the diaphragm were similar, but cells from a liver metastasis culture showed additional karyotypic changes. This large cell lung tumor cell line may prove useful as a model system for studies of human tumor progression and metastasis.
Person Authentication System with Quality Analysis of Multimodal Biometrics

This work is aimed at developing a multi-modal, multi-sensor based Person Authentication System (PAS) using JDL model. This research investigates the necessity of multiple sensors, multiple recognition algorithms and multiple levels of fusion and their efficiency for a Person Authentication System (PAS) with face, fingerprint and iris biometrics. Multiple modalities address the issues of non-universality encountered by unimodal systems. The PAS can be aptly addressed as ‘smart’ since several environmental factors have been considered in the design. If one sensor is not functional, others contribute to the system making it fault-tolerant. Smartness has been very tactfully administered to the processing module by employing different efficient algorithms for a given modality. Selection of the recognition algorithms is rooted on the attributes of the input. Multiplicity has been employed to establish a unanimous decision. Information fusion at various levels has been introduced. Sensor level fusion, local decision level fusion at algorithmic level and global decision level fusion provide the right inference. A multitude of decisions are fused locally to decide the weightage for the particular modality. Algorithms are tagged with weights based on their recognition accuracy. Weights are assigned to sensors based on their identification accuracy. Adaptability is incorporated by modifying the weights based on the environmental conditions. All local decisions are then combined to result in a global decision about the person. The final aggregation concludes whether ‘The Person is Authenticated or not’. Key-Words:Biometric; Image quality; Fusion; Multi-modal; Multi-sensor
Estimating the Joint Statistics of Images Using Nonparametric Windows with Application to Registration Using Mutual Information

Recently, the Non-Parametric (NP) Windows has been proposed to estimate the statistics of real 1D and 2D signals. NP Windows is accurate, because it is equivalent to sampling images at a high (infinite) resolution for an assumed interpolation model. This paper extends the proposed approach to consider joint distributions of image-pairs. Secondly, Green's Theorem is used to simplify the previous NP Windows algorithm. Finally, a resolution aware NP Windows algorithm is proposed, to improve robustness to relative scaling between an image-pair. Comparative testing of 2D image registration was performed using translation-only and affine transformations. Although more expensive than other methods, NP Windows frequently demonstrated superior performance for bias (distance between ground truth and global maximum) and frequency of convergence. Unlike other methods, the number of samples and histogram bin-size has little effect on NP Windows, and the prior selection of a kernel is not required.
Genetics of Local Adaptation in the Laboratory: Flowering Time Quantitative Trait Loci under Geographic and Seasonal Conditions in Arabidopsis

Flowering time in Arabidopsis thaliana is controlled by a large number of genes and various environmental factors, such as light and temperature. The objective of this study was to identify flowering time quantitative trait loci (QTL) under growth conditions simulating seasonal conditions from native geographic locations. Our growth chambers were set to simulate the spring conditions in Spain and Sweden, with appropriate changes in light color, intensity and day length, as well as temperature and relative humidity. Thus the Sweden-like spring conditions changed more dramatically compared to Spain-like spring conditions across the duration of our experiment. We have used these conditions to map QTL responsible for flowering time in the Kas-1/Col-gl1 recombinant inbred lines (RILs) across two replicate blocks. A linkage map from 96 RILs was established using 119 markers including 64 new SNPs markers. One major QTL, mapping to the FRIGIDA (FRI) locus, was detected on the top of chromosome 4 that showed significant gene×seasonal environment interactions. Three other minor QTL also were detected. One QTL mapping near FLOWERING LOCUS M (FLM) showed an epistatic interaction with the QTL at FRI. These QTL×environment and QTL×QTL interactions suggest that subtle ecologically relevant changes in light, temperature, and relative humidity are differentially felt by alleles controlling flowering time and may be responsible for adaptation to regional environments.
Optimal Interpolator Using a Trigonometric Polynomial le

All-digital approaches for the adjustment of timing offset in digital modems have attracted increasing attention. We recently announced a novel interpolation method which, instead of approximating the continuous-time signal with a conventional polynomial and computing the synchronized samples using a Farrow structure, uses a trigonometric polynomial. Simulation results indicate that improved performance, reduced computational delay and, in most cases, simplified hardware can be achieved. To recover a synchronized sample from existing samples, given a timing offset, we show here that we can optimize this method such that the interpolation error in the recovered sample is minimized for that specific timing offset value. Using this optimization technique, the overall interpolation error is reduced. As for the implementation, the optimal interpolator does not require additional hardware as compared to our original method.
Threshold phenomena for interference with randomly placed sensors

Assume $n$ sensors are initially placed on the half-infinite interval $[0,\infty)$ according to Poisson process with arrival rate $n. $ Let $s \ge 0$ be a given real number. We are allowed to move the sensors on the line, so as that no two sensors are placed at distance less than $s. $ When a sensor is displaced a distance equal to $|m(i)|$ the cost of movement is proportional to some (fixed) power $a>0$ of the $|m(i)|$ distance traveled. As cost measure for the displacement of the team of sensors we consider the $a$-total movement defined as the sum $M_a:=\sum_{i=1}^n |m(i)|^a,$ for some constans $a>0. $ In this paper we study tradeoffs between interference value $s$ and the expected minum $a$-total movement.
The Structural Basis of Monoclonal Antibody Alz50's Selectivity for Alzheimer's Disease Pathology*

The epitope on tau protein recognized by the monoclonal antibody Alz50 was defined through internal deletion mutagenesis and quantified by affinity measurements. The epitope is discontinuous and requires both a previously identified N-terminal segment and the microtubule binding region for efficient binding of Alz50. The interaction between these regions is consistent with an intramolecular reaction mechanism, suggesting that Alz50 binding depends on the conformation of individual tau monomers. The results suggest that tau adopts a distinct conformation when polymerized into filaments and that this conformation is recognized selectively by Alz50.
Structures of apo IRF-3 and IRF-7 DNA binding domains: effect of loop L1 on DNA binding

Interferon regulatory factors IRF-3 and IRF-7 are transcription factors essential in the activation of interferon-β (IFN-β) gene in response to viral infections. Although, both proteins recognize the same consensus IRF binding site AANNGAAA, they have distinct DNA binding preferences for sites in vivo. The X-ray structures of IRF-3 and IRF-7 DNA binding domains (DBDs) bound to IFN-β promoter elements revealed flexibility in the loops (L1–L3) and the residues that make contacts with the target sequence. To characterize the conformational changes that occur on DNA binding and how they differ between IRF family members, we have solved the X-ray structures of IRF-3 and IRF-7 DBDs in the absence of DNA. We found that loop L1, carrying the conserved histidine that interacts with the DNA minor groove, is disordered in apo IRF-3 but is ordered in apo IRF-7. This is reflected in differences in DNA binding affinities when the conserved histidine in loop L1 is mutated to alanine in the two proteins. The stability of loop L1 in IRF-7 derives from a unique combination of hydrophobic residues that pack against the protein core. Together, our data show that differences in flexibility of loop L1 are an important determinant of differential IRF-DNA binding.
Activation of ERα Signaling Differentially Modulates IFN-γ Induced HLA-Class II Expression in Breast Cancer Cells

The coordinate regulation of HLA class II (HLA-II) is controlled by the class II transactivator, CIITA, and is crucial for the development of anti-tumor immunity. HLA-II in breast carcinoma is associated with increased IFN-γ levels, reduced expression of the estrogen receptor (ER) and reduced age at diagnosis. Here, we tested the hypothesis that estradiol (E2) and ERα signaling contribute to the regulation of IFN-γ inducible HLA-II in breast cancer cells. Using a panel of established ER− and ER+ breast cancer cell lines, we showed that E2 attenuated HLA-DR in two ER+ lines (MCF-7 and BT-474), but not in T47D, while it augmented expression in ER− lines, SK-BR-3 and MDA-MB-231. To further study the mechanism(s), we used paired transfectants: ERα+ MC2 (MDA-MB-231 c10A transfected with the wild type ERα gene) and ERα− VC5 (MDA-MB-231 c10A transfected with the empty vector), treated or not with E2 and IFN-γ. HLA-II and CIITA were severely reduced in MC2 compared to VC5 and were further exacerbated by E2 treatment. Reduced expression occurred at the level of the IFN-γ inducible CIITA promoter IV. The anti-estrogen ICI 182,780 and gene silencing with ESR1 siRNA reversed the E2 inhibitory effects, signifying an antagonistic role for activated ERα on CIITA pIV activity. Moreover, STAT1 signaling, necessary for CIITA pIV activation, and selected STAT1 regulated genes were variably downregulated by E2 in transfected and endogenous ERα positive breast cancer cells, whereas STAT1 signaling was noticeably augmented in ERα− breast cancer cells. Collectively, these results imply immune escape mechanisms in ERα+ breast cancer may be facilitated through an ERα suppressive mechanism on IFN-γ signaling.
Distinguishing anxiety and depression : reexamination of the reconstructed Hamilton scales

The discriminant validities of the original and the reconstructed Hamilton anxiety and depression scales (Riskind et al., 1987) were compared in patients who had principal DSM-III-R anxiety disorders with or without one or more comorbid mood disorders. The reconstructed anxiety and depression scales that had better discriminant validity (scale intercorrelation=.61) than the original scales did (r=.78). However, the reconstructed scales shared considerable variance (about 37%), which was significantly higher than the shared variance (about 2%) reported by Risking et al. Discriminant analyses showed that the reconstructed scales did not distinguish anxiety patients with comorbid mood disorders from those without comorbid mood disorders better than the original scales did. However, the reconstructed scales eliminate item overlap, an obvious source of artifactual correlations between scores on the Hamilton anxiety and depression scales
’ s Ranking Algorithm : An Introductory Overview Joeran

Google Scholar is one of the major academic search engines but its ranking algorithm for academic articles is unknown. We performed the first steps to reverse-engineering Google Scholar’s ranking algorithm and present the results in this research-in-progress paper. The results are: Citation counts is the highest weighed factor in Google Scholar’s ranking algorithm. Therefore, highly cited articles are found significantly more often in higher positions than articles that have been cited less often. As a consequence, Google Scholar seems to be more suitable for finding standard literature than gems or articles by authors advancing a new or different view from the mainstream. However, interesting exceptions for some search queries occurred. Moreover, the occurrence of a search term in an article’s title seems to have a strong impact on the article’s ranking. The impact of search term frequencies in an article’s full text is weak. That means it makes no difference in an article’s ranking if the article contains the query terms only once or multiple times. It was further researched whether the name of an author or journal has an impact on the ranking and whether differences exist between the ranking algorithms of different search modes that Google Scholar offers. The answer in both of these cases was "yes". The results of our research may help authors to optimize their articles for Google Scholar and enable researchers to estimate the usefulness of Google Scholar with respect to their search intention and hence the need to use further academic search engines or databases. Academic Search Engines, Google Scholar, Ranking Algorithm, Research in Progress
A Novel Mobile Edge Computing-Based Architecture for Future Cellular Vehicular Networks

The evolving cellular network with centric-deployed Cloud Centers has greatly improved the mobile user experience. However, the advent of vehicular networks with a wide variety of new services and devices changes the existing cellular network landscape, and the cellular-based vehicular networks are confronted with serious challenge in terms of latency reduction and flexible service delivery. In this paper, we propose to deploy the specific server, called Mobile-Edge Computing (MEC) server, within the Radio Access Network, and allow them to connect with a set of base stations alongside roads, so as to provide flexible vehicle-related service and efficiently control the radio network. Then, the vision of MEC- assisted slicing network and a traffic scheduling policy are presented to promote network customization. As an instance of the MEC-based tailored network service, a time-predicted handover mechanism for vehicles is further developed by leveraging available road information and the enhanced capacity of the MEC server to satisfy the demand for high mobility and reliability.
Evolution of the mass function of dark matter haloes

We use a high resolutionCDM numerical simulation to calculate the mass function of dark matter haloes down to the scale of dwarf galaxies, back to a redshift of fifteen, in a 50 h −1 Mpc volume containing 80 million particles. Our low redshift results allow us to probe low σ density fluctuations significantly beyond the range of previous cosmological simulations. The Sheth and Tormen mass function provides an excellent match to all of our data except for redshifts of ten and higher, where it overpredicts halo numbers increasingly with redshift, reaching roughly 50 percent for the 10 10 − 10 11 M⊙ haloes sampled at redshift 15. Our results confirm previous findings that the simulated halo mass function can be described solely by the variance of the mass distribution, and thus has no explicit redshift dependence. We provide an empirical fit to our data that corrects for the overprediction of extremely rare objects by the Sheth and Tormen mass function. This overprediction has implications for studies that use the number densities of similarly rare objects as cosmological probes. For example, the number density of high redshift (z ≃ 6) QSOs, which are thought to be hosted by haloes at 5σ peaks in the fluctuation field, are likely to be overpredicted by at least a factor of 50%. We test the sensitivity of our results to force accuracy, starting redshift, and halo finding algorithm.
Regulation of miRNA abundance by RNA binding protein TOUGH in Arabidopsis

MicroRNAs (miRNAs) are regulators of gene expression in plants and animals. The biogenesis of miRNAs is precisely controlled to secure normal development of organisms. Here we report that TOUGH (TGH) is a component of the DCL1–HYL1–SERRATE complex that processes primary transcripts of miRNAs [i.e., primary miRNAs (pri-miRNAs)] into miRNAs in Arabidopsis. Lack of TGH impairs multiple DCL activities in vitro and reduces the accumulation of miRNAs and siRNAs in vivo. TGH is an RNA-binding protein, binds pri-miRNAs and precursor miRNAs in vivo, and contributes to pri-miRNA–HYL1 interaction. These results indicate that TGH might regulate abundance of miRNAs through promoting DCL1 cleavage efficiency and/or recruitment of pri-miRNAs.