Costs and Returns from Milk Production in El Vigia Area in the State of Merida, Venezuela, 1969

An analysis of costs and receipts associated with the production of manufacturing milk in El Vigia area of Venezuela was the focus of this study. A personal interview survey of a sample of dairy farm operators was conducted. Averages for costs, receipts, and net returns were calculated by size groups . Tabular analysis was used to study relationships between size and other factors and net return. Net return per cow was positive on the average, but the study indicated a general need for improved levels of production. Size of operation and capital investment were two factors found to be associated with higher net returns

Malicious Hardware & Its Effects on Industry

In recent years advancements have been made in computer hardware security to circumnavigate the threat of malicious hardware. Threats come in several forms during the development and overall life cycle of computer hardware and I aim to highlight those key points. I will illustrate the various ways in which attackers exploit flaws in a chip design, or how malicious parties take advantage of the many steps required to design and fabricate hardware. Due to these exploits, the industry and consumers have suffered damages in the form of financial loss, physical harm, breaches of personal data, and a multitude of other problems. Many are under the impression that such damages and attacks are only carried out at a software level. Because of this, flaws in chip design, fabrication, and the large scale of transistors on chips have often been overlooked as a means of exploitation. However, as is the trend in cyberattacks when one door is locked attackers look to gain an entrance with any possible means. Fortunately, strides have been made in closing those doors, however now that malicious attackers have been made aware of these openings the aim is to mitigate or even abolish the damage that has been dealt

Accretion disks around black holes in modified strong gravity

Stellar-mass black holes offer what is perhaps the best scenario to test theories of gravity in the strong-field regime. In particular, f(R) theories, which have been widely discuss in a cosmological context, can be constrained through realistic astrophysical models of phenomena around black holes. We aim at building radiative models of thin accretion disks for both Schwarzschild and Kerr black holes in f(R) gravity. We study particle motion in f(R)-Schwarzschild and Kerr space-times. We present the spectral energy distribution of the accretion disk around constant Ricci scalar f(R) black holes, and constrain specific f(R) prescriptions using features of these systems. A precise determination of both the spin and accretion rate onto black holes along with X-ray observations of their thermal spectrum might allow to identify deviations of gravity from General Relativity. We use recent data on the high-mass X-ray binary Cygnus X-1 to restrict the values of the parameters of a class of f(R) models.Comment: 16 pages, 20 figures, accepted for publication in Astronomy & Astrophysic

Intramyocardial gene silencing by interfering RNA

RNAi is a widely used methodology for gene silencing. The action mechanism of siRNA molecules has been well studiedin recent years, and the technique has been optimized in terms of safety and effectiveness. Cardiovascular diseases havea high incidence in the current population, and despite of the extensive research, safe and efficient therapeutics have notyet been found, which is reflected by 17.1 million people who die each year for this cause. In this context, siRNAs arebeing considered a therapeutic tool to regulate the expression of genes involved in the generation of these pathologies.The efficacy of siRNAs entry to cardiomyocytes, the safety of the delivery process and the degree of silencing achievedare main aspects before consider it as a cardiovascular disease therapy. Presently, we will give a brief outline of thecurrent understanding of the RNAi mechanism and the delivery system to the heart. We describe the use of lentivirus fora functional silencing of cardiac proteins in the study of a pathophysiological process, the slow force response to cardiacstretch.Fil: Brea, María Soledad. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - la Plata. Centro de Investigaciones Cardiovasculares ; ArgentinaFil: Morgan, Patricio Eduardo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - la Plata. Centro de Investigaciones Cardiovasculares ; ArgentinaFil: Perez, Nestor Gustavo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - la Plata. Centro de Investigaciones Cardiovasculares ; Argentin

Data to science with AI and human-in-the-loop

AI has the potential to accelerate scientific discovery by enabling scientists to analyze vast datasets more efficiently than traditional methods. For example, this thesis considers the detection of star clusters in high-resolution images of galaxies taken from space telescopes, as well as studying bird migration from RADAR images. In these applications, the goal is to make measurements to answer scientific questions, such as how the star formation rate is affected by mass, or how the phenology of bird migration is influenced by climate change. However, current computer vision systems are far from perfect for conducting these measurements directly. They may perform poorly when training data is limited, might introduce bias, and do not offer the statistical guarantees that scientists desire. This thesis addresses these challenges in three ways. First, we consider transfer learning to hyperspectral domains. The shape of the data, i.e., having more than three channels, restricts the use of pre-trained networks trained on color images. We design and investigate lightweight adapters that can be plugged into a pre-trained network to make it compatible with hyperspectral domains. Adapters allow for better generalization when training data is limited in various image classification tasks. Second, we explore how unlabeled data in a domain can be used to bootstrap a pre-trained network. We investigate the role of self-supervised learning in training networks for star cluster classification in astronomical images. Third, we address the scenario when a model is available but unreliable. This may be due to the task\u27s difficulty or the model being deployed on out-of-domain data where performance cannot be guaranteed. We develop human-in-the-loop techniques that incorporate human vetting of model outputs to produce estimates with statistical guarantees. We ground these approaches in applications in astronomy, ecology, and climate where data is heterogeneous and has different measurement needs. Manual measurements pose challenges due to the required domain expertise and the scale of the data being analyzed. We apply ideas from this thesis to develop StarcNet, a deep learning model capable of classifying star clusters in Hubble images. It achieves a level of human agreement comparable to existing catalogs and produces similar scientific conclusions, such as age/mass or frequency/mass distributions in galaxies with existing catalogs. In collaboration with others, we use the model to automatically analyze sources from the M101 galaxy and conduct preliminary studies on the near-infrared bands of the NGC4449 galaxy. In ecology, we study the behavior of roosting birds using weather radars. Weather radars around the globe continuously scan the airspace and are sensitive enough to detect flying animals. However, the sheer volume of data makes manual analysis impractical. We have designed an AI-assisted system capable of extracting research-grade roost annotations from radar data. This system combines ideas from adapter design to develop an accurate spatio-temporal roost detector with a human-in-the-loop vetting system that produces estimates with statistical guarantees. In collaboration with others, we use this framework to quantify long-term phenological patterns of aerial insectivores such as swallow and martin roosts. These analyses represent one of the most comprehensive long-term, broad-scale examinations of avian aerial insectivore species responding to environmental change. Lastly, we consider the estimation of damaged buildings from satellite imagery on regions struck by a natural disaster. During disaster response, aid organizations aim to quickly count damaged buildings in satellite images to plan relief missions, but pre-trained building and damage detectors often perform poorly due to domain shifts. In such cases, there is a need for human-in-the-loop approaches that can accurately count with minimal human effort. We propose techniques for counting over multiple spatial or temporal regions using a small amount of screening. We conclude by discussing how AI and humans can collaborate to tackle various measurement tasks and outlining the future challenges associated with deploying AI in scientific research

On the essence and ontology of systems

In the first part of this research, publications were reviewed from 1968 to 2019, with the aim of observing how the definition of system has evolved, since it was established by Ludwig Von Bertalanffy. From this review it is concluded that this definition has not changed in essence, all the researchers consulted use concepts similar to those of Bertalanffy, when they propose a definition of system. However, according to the specific field of work, the authors add their own characteristics.Bertalanffy's definition and all that have been derived from it postulate that a system is a conglomerate of interacting components. But after a brief reasoning it is concluded that everything in our universe meets that definition. A system is an atom, a cell, a chair, a galaxy, or the universe as a whole. So systems theory would be the theory of everything, which is too broad and imprecise.Vagueness and imprecision have been eliminated when the concept of system has been applied to specific fields of knowledge and human activity and in each of them characteristics have been added that define more specifically the systems that are relevant to certain technical or scientific specialties. However, this has caused that many concepts developed in one field cannot be extended or used in others.In this work, a system definition is established that allows us to clearly and precisely describe what these entities are and distinguish them from other concepts and entities. In this way it has been possible to characterize what a system is, using concepts that are applicable to any of the types of systems that can be found in our known world: natural systems, man-made systems and social systems

An analysis of a regular black hole interior model

We analyze the thermodynamical properties of the regular static and spherically symmetric black hole interior model presented by Mboyne and Kazanas. Equations for the thermodynamical quantities valid for an arbitrary density profile are deduced, and from them we show that the model is thermodynamically unstable. Evidence is also presented pointing to its dynamical instability. The gravitational entropy of this solution based on the Weyl curvature conjecture is calculated, following the recipe given by Rudjord, Gr$\varnothing$n and Sigbj$\varnothing$rn, and it is shown to have the expected behavior.Comment: 22 pages, 17 figures, accepted for publication in International Journal of Theoretical Physic

Cardiac mineralocorticoid receptor and the Na+/H+ exchanger: Spilling the beans.

Current evidence reveals that cardiac mineralocorticoid receptor (MR) activation following myocardial stretch plays an important physiological role in adapting developed force to sudden changes in hemodynamic conditions. Its underlying mechanism involves a previously unknown nongenomic effect of the MR that triggers redox-mediated Na+/H+ exchanger (NHE1) activation, intracellular Na+ accumulation, and a consequent increase in Ca2+ transient amplitude through reverse Na+/Ca2+ exchange. However, clinical evidence assigns a detrimental role to MR activation in the pathogenesis of severe cardiac diseases such as congestive heart failure. This mini review is meant to present and briefly discuss some recent discoveries about locally triggered cardiac MR signals with the objective of shedding some light on its physiological but potentially pathological consequences in the heart.Fil: Ennis, Irene Lucia. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Centro de Investigaciones Cardiovasculares "Dr. Horacio Eugenio Cingolani". Universidad Nacional de La Plata. Facultad de Ciencias Médicas. Centro de Investigaciones Cardiovasculares "Dr. Horacio Eugenio Cingolani"; ArgentinaFil: Perez, Nestor Gustavo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Centro de Investigaciones Cardiovasculares "Dr. Horacio Eugenio Cingolani". Universidad Nacional de La Plata. Facultad de Ciencias Médicas. Centro de Investigaciones Cardiovasculares "Dr. Horacio Eugenio Cingolani"; Argentin