CoMoFoD #x2014; New database for copy-move forgery detection

Due to the availability of many sophisticated image processing tools, a digital image forgery is nowadays very often used. One of the common forgery method is a copy-move forgery, where part of an image is copied to another location in the same image with the aim of hiding or adding some image content. Numerous algorithms have been proposed for a copy-move forgery detection (CMFD), but there exist only few benchmarking databases for algorithms evaluation. We developed new database for a CMFD that consist of 260 forged image sets. Every image set includes forged image, two masks and original image. Images are grouped in 5 categories according to applied manipulation: translation, rotation, scaling, combination and distortion. Also, postprocessing methods, such as JPEG compression, blurring, noise adding, color reduction etc., are applied at all forged and original images. In this paper we present database organization and content, creation of forged images, postprocessing methods, and database testing. CoMoFoD database is available at http://www.vcl.fer.hr/comofodMinistry of Science, Education and Sport, China; project numbers: 036-0361630-1635 and 036-0361630-164

Entre el Silencio y la Memoria: la existencia de Servicios de Bibliotecas para los Pueblos Originarios

This thesis, devoted to the study of the existence of library services that meet the needs of native users in Argentina, is the expression of two desires: on the one hand complete the requirement to access the degree of Bachelor of Library Science and Documentation, and another, give visibility to achieve a collective generally unknown

Entre el Silencio y la Memoria: la existencia de Servicios de Bibliotecas para los Pueblos Originarios

This thesis, devoted to the study of the existence of library services that meet the needs of native users in Argentina, is the expression of two desires: on the one hand complete the requirement to access the degree of Bachelor of Library Science and Documentation, and another, give visibility to achieve a collective generally unknown

Production of membrane proteins in yeast

Background Yeast is an important and versatile organism for studying membrane proteins. It is easy to cultivate and can perform higher eukaryote-like post-translational modifications. S. cerevisiae has a fully-sequenced genome and there are several collections of deletion strains available, whilst P. pastoris can produce very high cell densities (230 g/l). Results We have used both S. cerevisiae and P. pastoris to over-produce the following His6 and His10 carboxyl terminal fused membrane proteins. CD81 – 26 kDa tetraspanin protein (TAPA-1) that may play an important role in the regulation of lymphoma cell growth and may also act as the viral receptor for Hepatitis C-Virus. CD82 – 30 kDa tetraspanin protein that associates with CD4 or CD8 cells and delivers co-stimulatory signals for the TCR/CD3 pathway. MC4R – 37 kDa seven transmembrane G-protein coupled receptor, present on neurons in the hypothalamus region of the brain and predicted to have a role in the feast or fast signalling pathway. Adt2p – 34 kDa six transmembrane protein that catalyses the exchange of ADP and ATP across the yeast mitochondrial inner membrane. Conclusion We show that yeasts are flexible production organisms for a range of different membrane proteins. The yields are such that future structure-activity relationship studies can be initiated via reconstitution, crystallization for X-ray diffraction or NMR experiments

ADORA2A C Allele Carriers Exhibit Ergogenic Responses to Caffeine Supplementation

Caffeine’s ergogenic effects on exercise performance are generally explained by its ability to bind to adenosine receptors. ADORA2A is the gene that encodes A2A subtypes of adenosine receptors. It has been suggested that ADORA2A gene polymorphisms may be responsible for the inter-individual variations in the effects of caffeine on exercise performance. In the only study that explored the influence of variation in ADORA2A—in this case, a common polymorphism (rs5751876)—on the ergogenic effects of caffeine on exercise performance, C allele carriers were identified as “non-responders” to caffeine. To explore if C allele carriers are true “non-responders” to the ergogenic effects of caffeine, in this randomized, double-blind study, we examined the acute effects of caffeine ingestion among a sample consisting exclusively of ADORA2A C allele carriers. Twenty resistance-trained men identified as ADORA2A C allele carriers (CC/CT genotype) were tested on two occasions, following the ingestion of caffeine (3 mg/kg) and a placebo. Exercise performance was evaluated with movement velocity, power output, and muscle endurance during the bench press exercise, countermovement jump height, and power output during a Wingate test. Out of the 25 analyzed variables, caffeine was ergogenic in 21 (effect size range: 0.14 to 0.96). In conclusion, ADORA2A (rs5751876) C allele carriers exhibited ergogenic responses to caffeine ingestion, with the magnitude of improvements similar to what was previously reported in the literature among samples that were not genotype-specific. Therefore, individuals with the CT/CC genotype may still consider supplementing with caffeine for acute improvements in performance

Fairness in Algorithmic Decision Making: An Excursion Through the Lens of Causality

As virtually all aspects of our lives are increasingly impacted by algorithmic decision making systems, it is incumbent upon us as a society to ensure such systems do not become instruments of unfair discrimination on the basis of gender, race, ethnicity, religion, etc. We consider the problem of determining whether the decisions made by such systems are discriminatory, through the lens of causal models. We introduce two definitions of group fairness grounded in causality: fair on average causal effect (FACE), and fair on average causal effect on the treated (FACT). We use the Rubin-Neyman potential outcomes framework for the analysis of cause-effect relationships to robustly estimate FACE and FACT. We demonstrate the effectiveness of our proposed approach on synthetic data. Our analyses of two real-world data sets, the Adult income data set from the UCI repository (with gender as the protected attribute), and the NYC Stop and Frisk data set (with race as the protected attribute), show that the evidence of discrimination obtained by FACE and FACT, or lack thereof, is often in agreement with the findings from other studies. We further show that FACT, being somewhat more nuanced compared to FACE, can yield findings of discrimination that differ from those obtained using FACE.Comment: 7 pages, 2 figures, 2 tables.To appear in Proceedings of the International Conference on World Wide Web (WWW), 201

Altering the ribosomal subunit ratio in yeast maximizes recombinant protein yield

RIGHTS : This article is licensed under the BioMed Central licence at http://www.biomedcentral.com/about/license which is similar to the 'Creative Commons Attribution Licence'. In brief you may : copy, distribute, and display the work; make derivative works; or make commercial use of the work - under the following conditions: the original author must be given credit; for any reuse or distribution, it must be made clear to others what the license terms of this work are.Abstract Background The production of high yields of recombinant proteins is an enduring bottleneck in the post-genomic sciences that has yet to be addressed in a truly rational manner. Typically eukaryotic protein production experiments have relied on varying expression construct cassettes such as promoters and tags, or culture process parameters such as pH, temperature and aeration to enhance yields. These approaches require repeated rounds of trial-and-error optimization and cannot provide a mechanistic insight into the biology of recombinant protein production. We published an early transcriptome analysis that identified genes implicated in successful membrane protein production experiments in yeast. While there has been a subsequent explosion in such analyses in a range of production organisms, no one has yet exploited the genes identified. The aim of this study was to use the results of our previous comparative transcriptome analysis to engineer improved yeast strains and thereby gain an understanding of the mechanisms involved in high-yielding protein production hosts. Results We show that tuning BMS1 transcript levels in a doxycycline-dependent manner resulted in optimized yields of functional membrane and soluble protein targets. Online flow microcalorimetry demonstrated that there had been a substantial metabolic change to cells cultured under high-yielding conditions, and in particular that high yielding cells were more metabolically efficient. Polysome profiling showed that the key molecular event contributing to this metabolically efficient, high-yielding phenotype is a perturbation of the ratio of 60S to 40S ribosomal subunits from approximately 1:1 to 2:1, and correspondingly of 25S:18S ratios from 2:1 to 3:1. This result is consistent with the role of the gene product of BMS1 in ribosome biogenesis. Conclusion This work demonstrates the power of a rational approach to recombinant protein production by using the results of transcriptome analysis to engineer improved strains, thereby revealing the underlying biological events involved.Published versio

LiFT: A Scalable Framework for Measuring Fairness in ML Applications

Many internet applications are powered by machine learned models, which are usually trained on labeled datasets obtained through either implicit / explicit user feedback signals or human judgments. Since societal biases may be present in the generation of such datasets, it is possible for the trained models to be biased, thereby resulting in potential discrimination and harms for disadvantaged groups. Motivated by the need for understanding and addressing algorithmic bias in web-scale ML systems and the limitations of existing fairness toolkits, we present the LinkedIn Fairness Toolkit (LiFT), a framework for scalable computation of fairness metrics as part of large ML systems. We highlight the key requirements in deployed settings, and present the design of our fairness measurement system. We discuss the challenges encountered in incorporating fairness tools in practice and the lessons learned during deployment at LinkedIn. Finally, we provide open problems based on practical experience.Comment: Accepted for publication in CIKM 202

Changes in total and segmental bioelectrical resistance are correlated with whole-body and segmental changes in lean soft tissue following a resistance training intervention

Background Raw bioelectrical values can be used to assess physiological outcomes, though limited information is available concerning the relationships between changes in these values and changes in other variables of interest. Methods This investigation quantified the relationships between total and segmental changes in raw bioelectrical variables (i.e., resistance, reactance, and phase angle) and corresponding whole-body and segmental changes in independently assessed body composition. Resistance-trained females (n = 31, body mass index: 22.8 ± 2.6 kg/m2, body fat: 28 ± 6%) completed eight weeks of supervised resistance training. Before and after the intervention, body composition was assessed via dual-energy x-ray absorptiometry (GE® Lunar Prodigy), and raw bioelectrical variables were assessed via 8-point multi-frequency bioelectrical impedance analysis (Seca® mBCA 515/514) at 19 frequencies ranging from 1 to 1000 kHz. Results Lean soft tissue of the whole body (+ 3.2% [2.1, 4.4]; mean [95% confidence interval]) and each body segment (+ 2.8 to 6.3%) increased as a result of the intervention. Group-level changes in total (− 2.4% [− 5.2, 0.3]) and segmental fat mass were not statistically significant. Significant decreases in total resistance (− 2.1% [− 3.7, − 0.6] at 50 kHz) and increases in phase angle (+ 4.2% [2.5, 5.9] at 50 kHz) were observed, with minimal changes in reactance and varying changes in segmental values. Moderate to strong negative correlations (0.63 ≤ |r| ≤ 0.83, p ≤ 0.001) were found between changes in lean soft tissue and changes in resistance for the whole body, trunk, and arms. No significant correlations were identified between changes in fat mass or bone mineral content and changes in any bioelectrical variable. Conclusions Total and segmental changes in resistance were associated with corresponding total and segmental changes in lean soft tissue following a resistance training intervention, while fewer associations were identified between changes in other bioelectrical parameters (i.e., reactance and phase angle) and body composition variables (e.g., fat mass and bone mineral content). Measurement frequency and body segment appeared to influence the presence and strength relationships between bioelectrical and body composition variables. These findings suggest that researchers and practitioners utilizing bioimpedance technology may benefit from examining raw resistance values to enhance detection of physiological adaptations to exercise interventions