Government Contracts Under Argentine Law: A Comparative Law Overview

This Article will summarize Argentine law on government contracts as it exists today, with special reference to the contracts of the Federal Government. Due to the French origin of the theory and to the fact that this Article is addressed to an American readership, a tentative comparison with the main legal rules on the subject of these two countries will be offered. A discussion of the practical consequences of the application of the administrative contract doctrine, and some possible solutions to the problems created thereby will be then put forward. But first, the basic issues that this doctrine gives rise to will be defined and the French origin of the concept of contract administratif and its reception in Argentina will be explained. The analysis offered will be limited to the general substantive legal regime of Government contracts leaving aside the issues arising from the contracting procedure, i.e., the rules on competitive bidding. To the extent that this substantive regime results from laws and regulations, only those directly applicable to Government contracts shall be considered. Thus, the analysis will only deal tangentially with the impact on these contracts of the exercise of public powers granted by statutes that may affect indirectly the performance of the private contractor. Since such statutes may reach all Government contracts and not only those defined as “administrative” (unless a tautological definition is used, i.e., one that characterizes as “administrative” only those Government contracts that can be reached by laws granting regulatory or police powers to the Government), it may be argued that the issues raised by those statutes lie outside the scope of the doctrine of the administrative contract. Therefore, the issue of the conflict between the legislative powers of the State and the principle of the sanctity of the contract shall not be treated

Short and Longer-term Psychological Consequences of Operation Cast Lead: documentation from a Mental Health program in the Gaza Strip

<p>Abstract</p> <p>Background</p> <p>There is growing recognition of the psychological impact of adversity associated with armed conflict on exposed civilian populations. Yet there is a paucity of evidence on the value of mental health programs in these contexts, and of the chronology of psychological sequelae, especially in prolonged conflicts with repeated cycles of extreme violence. Here, we describe changes in the psychological profile of new patients in a mental health program after the military offensive Cast Lead, in the context of the prolonged armed conflict involving the Gaza Strip.</p> <p>Methods</p> <p>This study analyses routinely collected program data from a Médecins Sans Frontières mental health program in the Gaza Strip spanning 2007–2011. Data consist of socio-demographic as well as clinical baseline and follow-up data on new patients entering the program. Comparisons were made through Chi square and Fisher’s exact tests, univariate and multivariate logistic and linear regression.</p> <p>Results</p> <p>PTSD, depression and other anxiety disorders were the most frequent psychopathologies, with 21% having multiple diagnoses. With a median of nine sessions, clinical improvement was recorded for 83% (1122/1357), and more common for those with separation anxiety, acute and posttraumatic disorders as principal diagnosis (855/1005), compared to depression (141/183, p<0.01). Noted changes proximal to Operation Cast Lead were: a doubling in patient case load with a broader socio-economic background, shorter interval from an identified traumatic event to seeking care, and a rise in diagnoses of acute and posttraumatic stress disorders. Sustained changes included: high case load, more distal triggering events, and increase in diagnoses of other anxiety disorders (especially for children 15 years and younger) and depression (especially for patients 16 years and older).</p> <p>Conclusion</p> <p>Evolving changes in patient volume, diagnoses and recall period to triggering events suggest a lengthy and durable effect of an intensified exposure to violence in a context of prolonged conflict. Our findings suggest that mental health related humanitarian relief in protracted conflicts might need to prepare for an increase in patients with changing profiles over an extended period following an acute flare-up in violence.</p

Generative discriminative models for multivariate inference and statistical mapping in medical imaging

This paper presents a general framework for obtaining interpretable multivariate discriminative models that allow efficient statistical inference for neuroimage analysis. The framework, termed generative discriminative machine (GDM), augments discriminative models with a generative regularization term. We demonstrate that the proposed formulation can be optimized in closed form and in dual space, allowing efficient computation for high dimensional neuroimaging datasets. Furthermore, we provide an analytic estimation of the null distribution of the model parameters, which enables efficient statistical inference and p-value computation without the need for permutation testing. We compared the proposed method with both purely generative and discriminative learning methods in two large structural magnetic resonance imaging (sMRI) datasets of Alzheimer's disease (AD) (n=415) and Schizophrenia (n=853). Using the AD dataset, we demonstrated the ability of GDM to robustly handle confounding variations. Using Schizophrenia dataset, we demonstrated the ability of GDM to handle multi-site studies. Taken together, the results underline the potential of the proposed approach for neuroimaging analyses.Comment: To appear in MICCAI 2018 proceeding

Aptamers against the β-conglutin allergen: Insights into the behavior of the shortest multimeric (intra)molecular dna gquadruplex

In previous work, a 93-mer aptamer was selected against the anaphylactic allergen, β-conglutin and truncated to an 11-mer, improving the affinity by two orders of magnitude, whilst maintaining the specificity. This 11-mer was observed to fold in a G-quadruplex, and preliminary results indicated the existence of a combination of monomeric and higher-order structures. Building on this previous work, in the current study, we aimed to elucidate a deeper understanding of the structural forms of this 11-mer and the effect of the structure on its binding ability. A battery of techniques including polyacrylamide gel electrophoresis, high-performance liquid chromatography in combination with electrospray ionization time-of-flight mass spectrometry, matrix-assisted laser desorption/ionization time-of-flight, thermal binding analysis, circular dichroism and nuclear magnetic resonance were used to probe the structure of both the 11-mer and the 11-mer flanked with TT- at either the 5′ or 3′ end or at both ends. The TT-tail at the 5′ end hinders stacking effects and effectively enforces the 11-mer to maintain a monomeric form. The 11-mer and the TT- derivatives of the 11-mer were also evaluated for their ability to bind its cognate target using microscale thermophoresis and surface plasmon resonance, and biolayer interferometry confirmed the nanomolar affinity of the 11-mer. All the techniques utilized confirmed that the 11-mer was found to exist in a combination of monomeric and higher-order structures, and that independent of the structural form present, nanomolar affinity was observed

Fully Trainable and Interpretable Non-Local Sparse Models for Image Restoration

Non-local self-similarity and sparsity principles have proven to be powerful priors for natural image modeling. We propose a novel differentiable relaxation of joint sparsity that exploits both principles and leads to a general framework for image restoration which is (1) trainable end to end, (2) fully interpretable, and (3) much more compact than competing deep learning architectures. We apply this approach to denoising, jpeg deblocking, and demosaicking, and show that, with as few as 100K parameters, its performance on several standard benchmarks is on par or better than state-of-the-art methods that may have an order of magnitude or more parameters.Comment: ECCV 202

Development and validation of a computational model for steak double-sided pan cooking

The objective of this study was to develop and validate a numerical model to adequately simulate the double-sided pan cooking of beef in a domestic environment. The proposed model takes into account the heat flow from the pan to the meat and the moisture transfer, simultaneously with the meat deformation. The model considers the swelling pressure gradient caused by the shrinkage of the meat fibers and connective tissue due to the denaturation of proteins and the loss of the water holding capacity during cooking. The model results were successfully verified with experimental data of the central temperature and weight loss recorded during cooking for three degrees of doneness. The measured experimental temperatures at the center of the meat were 30 ± 3 °C (very rare), 44 ± 3 °C (rare) and 57 ± 2 °C (done) for a 19 mm steak thickness. Meanwhile, their water losses were 4 ± 2 %, 8 ± 1 % and 11 ± 2 %, respectively. The root mean squared errors of the model predictions were 2.16 °C (very rare), 3.56 °C (rare) and 4.57 °C (done) for the central temperature and 1.48 %, 2.08 % and 2.40 %, respectively for the water loss. The model also correctly predicts cooking times for steaks of different thicknesses, taking weight loss as a reference to set this time. The proposed model is postulated as a useful cooking assistance tool to estimate the optimal cooking time according to consumer preferences

Color changes in beef meat during pan cooking: kinetics, modeling and application to predict turn over time

The kinetics of heat-induced color changes in beef meat was determined and implemented in a numerical model for doublesided pan cooking of steak. The CIELab color space was used to obtain the lightness (coordinate L∗ ) and the reddish tone (coordinate a∗ ) of the cooked meat. L∗ was the CIELab coordinate that contributed the most to the change in the absolute color. Two response surfaces were found to describe the evolution with time and temperature of both color coordinates, L∗ and a∗ . The model results were successfully verified with experimental data of the two coordinates along the thickness of the meat for three degrees of cooking. The Root-Mean-Squared Errors (RMSE) for coordinate L∗ were 5.17 (very rare), 2.02 (medium rare) and 3.83 (done), and for coordinate a∗ 1.44 (very rare), 1.26 (medium rare) and 0.89 (done). The applicability of the model for practical cooking purposes was illustrated by determining the optimum turn over time to achieve a similar color profile on both sides of the meat. The turn over time depended on the desired degrees of cooking, and were comprised between one-half and two-thirds of the final cooking time, increasing from very rare cooking degree to done cooking degree

Towards domestic cooking efficiency: A case study on burger pan frying using experimental and computational results

It is well known that the use of efficient domestic cooking appliances and equipment can not only save energy, but also improve the quality of the food being prepared. This work raises the question of whether cooking procedures can also contribute to this energy efficiency. Focusing on burger pan frying, experimental data were used to develop a model able to predict cooking outcomes under different power levels supplied by an induction hob. The proposed model takes into account not only the heat consumed by water evaporation in the contact region but also the shrinkage process of the hamburger. A new formulation based on the multiplicative decomposition of the strain deformation gradient is proposed to describe the observed decoupling between weight and volume loss during the process. The model properly predicts temperature, moisture loss and shrinkage, and allows elucidation of the effects of supplying different amounts of energy on the final water content

Crimes against children: an apparently terminological knowledge representation of entities in FunGramKB

[EN] This article describes an example of the difficulties involved in the construction of a term-based satellite (or domain-specific) ontology integrated in FunGramKB –a lexico-conceptual knowledge base for the computational processing of natural language (Periñán-Pascual & Arcas-Túnez 2004, 2007, 2010a; Periñán-Pascual & Mairal-Usón 2009, 2010). The main hypothesis is that the multilevel model of FunGramKB Core Ontology can be connected to terminological satellite ontologies in order to minimize redundancy and maximize information (Periñán-Pascual & Arcas-Túnez 2010b). To this end we follow the four-phase COHERENT methodology (Periñán-Pascual & Mairal-Usón 2011): COnceptualization, HiErarchization, REmodelling and refinemeNT. In doing so, the paper furnishes substantial evidence on the structuring of a set of concepts borrowed from criminal law, an apparently terminological domain (cf. Breuker, Valente & Winkels 2005; Valente 2005; Breuker, Casanovas & Klein 2008). The Globalcrimeterm corpus has been used as an empirical foundation (Felices-Lago & Ureña-Gómez Moreno 2012, 2014). To illustrate this process, we have selected the superordinate basic concept +CRIME_00 (Alameda-Hernández & Felices-Lago 2016) and its basic and terminal subordinate concepts in the domains of organized crime and terrorism (all of them under the metaconcept #ENTITY), particularly those crimes referring predominantly to children or involving children with other vulnerable groups. The creation of specific definitions for the target concepts in this paper uses COREL (a conceptual representation language (Periñán-Pascual & Mairal-Usón 2010)) and the following upper-level conceptual path: #ENTITY> #PHYSICAL> #PROCESS> +OCCURRENCE_00> +CRIME_00. Consequently, the modelling, subsumption and hierarchisation of concepts such as $ABDUCTION_00,$CHILD_ABUSE_00, $CHILD_PORNOGRAPHY_00,$COERCE_D_00, $CHILD_TRAFFICKING_00,$MOLEST_D_00, $FORCED_LABOUR, among others, are presented.This article is based on research carried out within the framework of the Project FFI2014-53788-C3-1-P, which is funded by the Spanish Ministry of Economy and Competitiveness, and entitled: Development of a virtual laboratory for natural language processing from a functional paradigm. It is also based on the previous Project code no. FFI2010-15983: Development of a subontology in a multilingual context (English, Spanish and Italian): Using FunGramKB in the field of international cooperation in criminal matters: Terrorism and organised crime”.Alameda Hernández, Á.; Felices Lago, Á. (2017). Crimes against children: an apparently terminological knowledge representation of entities in FunGramKB. Journal of Computer-Assisted Linguistic Research. 1(1):1-19. https://doi.org/10.4995/jclr.2017.7785SWORD1191

Altered Skeletal Muscle Lipase Expression and Activity Contribute to Insulin Resistance in Humans

International audienceOBJECTIVE: Insulin resistance is associated with elevated content of skeletal muscle lipids, including triacylglycerols (TAGs) and diacylglycerols (DAGs). DAGs are by-products of lipolysis consecutive to TAG hydrolysis by adipose triglyceride lipase (ATGL) and are subsequently hydrolyzed by hormone-sensitive lipase (HSL). We hypothesized that an imbalance of ATGL relative to HSL (expression or activity) may contribute to DAG accumulation and insulin resistance. RESEARCH DESIGN AND METHODS: We first measured lipase expression in vastus lateralis biopsies of young lean (n = 9), young obese (n = 9), and obese-matched type 2 diabetic (n = 8) subjects. We next investigated in vitro in human primary myotubes the impact of altered lipase expression/activity on lipid content and insulin signaling. RESULTS: Muscle ATGL protein was negatively associated with whole-body insulin sensitivity in our population (r = -0.55, P = 0.005), whereas muscle HSL protein was reduced in obese subjects. We next showed that adenovirus-mediated ATGL overexpression in human primary myotubes induced DAG and ceramide accumulation. ATGL overexpression reduced insulin-stimulated glycogen synthesis (-30%, P < 0.05) and disrupted insulin signaling at Ser1101 of the insulin receptor substrate-1 and downstream Akt activation at Ser473. These defects were fully rescued by nonselective protein kinase C inhibition or concomitant HSL overexpression to restore a proper lipolytic balance. We show that selective HSL inhibition induces DAG accumulation and insulin resistance. CONCLUSIONS: Altogether, the data indicate that altered ATGL and HSL expression in skeletal muscle could promote DAG accumulation and disrupt insulin signaling and action. Targeting skeletal muscle lipases may constitute an interesting strategy to improve insulin sensitivity in obesity and type 2 diabetes