Study of Bagasse Pulps to Obtain Corrugated Medium

Bagasse was used as raw material to pulp various NSSC, Soda and Kraft liquors and evaluated as corrugating medium. A new pulping procedure with the M & K Digester was developed in order to reach maximum temperature at the shortest practical time. It was found that a 10% Active Alkali at 5% Sulfidity and an NSSC liquor at pH 10 with 15% SO2 on pulp gave suitable strength properties. The NSSC cook gave a higher yield but a pulp with more shives. Keywords: Bagasse, Kraft, Soda, neutral sulfite semichemical, corrugating mediu

Variety, Competition, and Population in Economic Growth: Theory and Empirics

We provide aggregate macroeconomic evidence on how, in the long-run, a diverse degree of production-complexity may affect not only the rate of economic growth, but also the correlation between the latter, population growth and the monopolistic (intermediate) markups. For a sample of OECD economies, we find that the losses due to more complexity in production are lower than the corresponding specialization gains. According to our theoretical model, this implies that the impact of population change on economic growth is slightly positive. Using a Finite Mixture Model, we also classify the countries in the sample and verify for each cluster the impact that the population growth rate and the intermediate sector's markups exert on the 5-year average real GDP growth rate

Variety, Competition, and Population in Economic Growth : Theory and Empirics

We provide aggregate macroeconomic evidence on how, in the long-run, a diverse degree of complexity in production may affect not only the rate of economic growth, but also the correlation between the latter, population growth and the monopolistic (intermediate) markups. For a sample of OECD countries, we find that the impact of population change on economic growth is slightly positive. According to our the- oretical model, this implies that the losses due to more complexity in production are lower than the corresponding specialization gains. Using a Finite Mixture Model, we also classify the countries in the sample and verify for each cluster the impact that the population growth rate and the intermediate sector\u2019s markups exert on the 5-year average real GDP growth rate

Preliminary tests on a wireless sensor network for pervasive dust monitoring in construction sites

One of the critical aspects in health and safety is the control of fine particle emissions from demolition and construction activities. Such exposure is very often the cause of professional illnesses causing a relevant economic burden for welfare and insurance institutions, besides harming workers. Hence this paper performs a feasibility study of a realtime control system of fine particle concentration on construction sites. It was conceived as a ZigbeeTM based wireless, pervasive and non-invasive system, which is easy to deploy over the site and relatively cheap. Dust sensors were interfaced with the system and calibrated in the laboratory. The prototype is described in detail and tested under controlled and real conditions, in order to determine its potential for application. The prototype was shown to be an excellent tool to support health and safety inspectors, to provide in real-time a broad map of dust concentration over the whole extension of the site, provided that calibration coefficients are worked out for the various types of dust which can be encountered on the site

Training of YOLO Neural Network for the Detection of Fire Emergency Assets

Building assets surveys are cost and time demanding and the majority of current methods still rely on manual procedures. New technologies could be used to support this task. The exploitation of Artificial Intelligence (AI) for the automatic interpretation of data is spreading throughout various application fields. However, a challenge with AI is the very large number of training images required for robustly detect and classify each object class. This paper details the procedure and parameters used for the training of a custom YOLO neural network for the recognition of fire emergency assets. The minimum number of pictures for obtaining good recognition performances and the image augmentation process have been investigated. In the end, it was found that fire extinguishers and emergency signs are reasonably detected and their position inside the pictures accurately evaluated. The use case proposed in this paper for the use of custom YOLO is the retrieval of as-is information for existing buildings. The trained neural networks are part of a system that makes use of Augmented Reality devices for capturing pictures and for visualizing the results directly on site

Development of a Digital Twin Model for Real-Time Assessment of Collisione Hazards

The AEC industry is nowadays one of the most hazardous industries in the world. The construction sector employees about 7% of the world’s work force but is responsible for 30-40% of fatalities. As statistics demonstrate, interferences between workers-on-foot and moving vehicles have caused several injuries and fatalities over the years. Despite safety organizational measures, passive safety devices imposed by regulations and efforts from training procedures, scarce improvements have been recorded. Recent research studies propose technology driven approaches as the key solutions to integrate standard health and safety management practices. This is motivated by the evidence that the dynamics of complex systems can hardly be predicted; rather a proactive approach to health and safety is more effective. Current technologies installed on construction equipment can usually react according to a strict logic, such as sending proximity alerts when workers and equipment are too close. Nevertheless, these approaches barely do make informed decisions in real-time, e.g. including the level of reactiveness of the endangered worker. In similar circumstances a digital twin of the construction site, updated by real-time data from sensors and enriched by artificial intelligence, can pro-actively support activities, forecasting dangerous scenarios on the base of several factors. In this paper a laboratory mock-up has been assumed as the test case, supported by a game engine, which is able to replicates the job site for the execution of bored piles. In such a scenario populated by an avatar of a sensor-equipped worker and a virtual driller, a Bayesian network, implemented within the game engine and fed in runtime by sensor data, works out collision probability in real-time in order to send warnings and avoid fatal accidents

Estimation of Tidal Volume during Exercise Stress Test from Wearable-Device Measures of Heart Rate and Breathing Rate

Tidal volume (TV), defined as the amount of air that moves in or out of the lungs with each respiratory cycle, is important in evaluating the respiratory function. Although TV can be reliably measured in laboratory settings, this information is hardly obtainable under everyday living conditions. Under such conditions, wearable devices could provide valuable support to monitor vital signs, such as heart rate (HR) and breathing rate (BR). The aim of this study was to develop a model to estimate TV from wearable-device measures of HR and BR during exercise. HR and BR were acquired through the Zephyr Bioharness 3.0 wearable device in nine subjects performing incremental cycling tests. For each subject, TV during exercise was obtained with a metabolic cart (Cosmed). A stepwise regression algorithm was used to create the model using as possible predictors HR, BR, age, and body mass index; the model was then validated using a leave-one-subject-out cross-validation procedure. The performance of the model was evaluated using the explained variance (R-2), obtaining values ranging from 0.65 to 0.72. The proposed model is a valid method for TV estimation with wearable devices and can be considered not subject-specific and not instrumentation-specific

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Praga quarentenária, a traça da maçã (Cydia pomonella) é responsável por entraves comerciais que extrapolam os danos diretos à produtividade. Mesmo restrito a algumas áreas urbanas do Sul do Brasil, o inseto exige monitoramento rigoroso e sua erradicação é uma busca necessária para que o país possa manter e conquistar novos mercados na exportação de frutas.bitstream/item/200929/1/14208-2012-p.30-e-32.pd

Genotypic Characterization of Non-O157 Shiga Toxin–Producing Escherichia coli in Beef Abattoirs of Argentina

The non-O157 Shiga toxin-producing Escherichia coli (STEC) contamination in carcasses and feces of 811 bovines in nine beef abattoirs from Argentina was analyzed during a period of 17 months. The feces of 181 (22.3%) bovines were positive for non-O157 STEC, while 73 (9.0%) of the carcasses showed non-O157 STEC contamination. Non-O157 STEC strains isolated from feces (227) and carcasses (80) were characterized. The main serotypes identified were O178:H19, O8:H19, O130:H11, and O113:H21, all of which have produced sporadic cases of hemolytic-uremic syndrome in Argentina and worldwide. Twenty-two (7.2%) strains carried a fully virulent stx/eae/ehxA genotype. Among them, strains of serotypes O103:[H2], O145:NM, and O111:NM represented 4.8% of the isolates. XbaI pulsed-field gel electrophoresis pattern analysis showed 234 different patterns, with 76 strains grouped in 30 clusters. Nine of the clusters grouped strains isolated from feces and from carcasses of the same or different bovines in a lot, while three clusters were comprised of strains distributed in more than one abattoir. Patterns AREXSX01.0157, AREXBX01.0015, and AREXPX01.0013 were identified as 100% compatible with the patterns of one strain isolated from a hemolytic-uremic syndrome case and two strains previously isolated from beef medallions, included in the Argentine PulseNet Database. In this survey, 4.8% (39 of 811) of the bovine carcasses appeared to be contaminated with non- O157 STEC strains potentially capable of producing sporadic human disease, and a lower proportion (0.25%) with strains able to produce outbreaks of severe disease.Fil: Masana, Marcelo. Instituto Nacional de Tecnología Agropecuaria. Centro de Investigación de Agroindustria. Instituto de Tecnología de Alimentos; ArgentinaFil: D´Astek, B. A.. Dirección Nacional de Instituto de Investigación. Administración Nacional de Laboratorio e Instituto de Salud “Dr. C. G. Malbrán”; ArgentinaFil: Palladino, Pablo Martín. Instituto Nacional de Tecnología Agropecuaria. Centro de Investigación de Agroindustria. Instituto de Tecnología de Alimentos; ArgentinaFil: Galli, Lucía. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico CONICET- La Plata. Instituto de Genética Veterinaria "Ing. Fernando Noel Dulout". Universidad Nacional de La Plata. Facultad de Ciencias Veterinarias. Instituto de Genética Veterinaria; Argentina. Dirección Nacional de Institutos de Investigación. Administración Nacional de Laboratorios e Institutos de Salud. Instituto Nacional de Enfermedades Infecciosas; ArgentinaFil: del Castillo, Lourdes Leonor. Instituto Nacional de Tecnología Agropecuaria. Centro de Investigación de Agroindustria. Instituto de Tecnología de Alimentos; ArgentinaFil: Carbonari, Claudia Carolina. Dirección Nacional de Institutos de Investigación. Administración Nacional de Laboratorios e Institutos de Salud. Instituto Nacional de Enfermedades Infecciosas; ArgentinaFil: Leotta, Gerardo Anibal. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico CONICET- La Plata. Instituto de Genética Veterinaria "Ing. Fernando Noel Dulout". Universidad Nacional de La Plata. Facultad de Ciencias Veterinarias. Instituto de Genética Veterinaria; Argentina. Dirección Nacional de Institutos de Investigación. Administración Nacional de Laboratorios e Institutos de Salud. Instituto Nacional de Enfermedades Infecciosas; ArgentinaFil: Vilacoba, Elisabet. Dirección Nacional de Institutos de Investigación. Administración Nacional de Laboratorios e Institutos de Salud. Instituto Nacional de Enfermedades Infecciosas; ArgentinaFil: Irino, K.. Instituto Adolfo Lutz. Seção de Bacteriologia; BrasilFil: Rivas, M.. Dirección Nacional de Institutos de Investigación. Administración Nacional de Laboratorios e Institutos de Salud. Instituto Nacional de Enfermedades Infecciosas; Argentin

Tools and Methods for Human Robot Collaboration: Case Studies at i-LABS

The collaboration among humans and machines is one of the most relevant topics in the Industry 4.0 paradigm. Collaborative robotics owes part of the enormous impact it has had in small and medium size enterprises to its innate vocation for close cooperation between human operators and robots. The i-Labs laboratory, which is introduced in this paper, developed some case studies in this sense involving different technologies at different abstraction levels to analyse the feasibility of human-robot interaction in common, yet challenging, application scenarios. The ergonomics of the processes, safety of operators, as well as effectiveness of the cooperation are some of the aspects under investigation with the main objective of drawing to these issues the attention from industries who could benefit from them