Intel (Brazil)

Purpose The purpose of this paper is to propose a minimum set of indicators to be measured by industrial companies to represent the triple bottom line (TBL) approach. Design/methodology/approach The research is both descriptive and quantitative. Three hypotheses establish associations among the degrees of use of TBL indicators and their different degrees of use in firms. The authors used confirmatory factor analysis (CFA) to validate the scale and structural equation modelling to represent the final measurement model. The survey gathered 149 industrial companies. Findings The results pointed out that there are positive associations among the degree of use of environmental indicators and social indicators, economic, environmental and social indicators have different degrees of use in firms, a positive association between the degree of use of environmental and social indicators and the use of economic indicators was not confirmed. The findings suggest how to measure sustainable performance for industrial companies and highlight the differences in the degree of use for the three dimensions of TBL. Research limitations/implications The limitations refer to the non-probabilistic sample, applied in a specific context, industrial companies. Practical implications This set of indicators is intended to be used by industrial companies as a reliable instrument to sustainable performance assessment of the current stage of the TBL deployment and provide alternative approaches to address specific issues related to the environmental, social and economic sustainability. Social implications The results offer tangible results for measuring and reporting firm’s social and environmental performance. Originality/value This paper intends to offer an integrated and consistent way of measuring sustainability in industrial companies.

Abstract Lignocellulose is the most abundant renewable material on Earth and the primary component of agricultural wastes such as sugarcane bagasse and wheat straw. It consists of a composite material made of cellulose, hemicellulose, and lignin. Cellulose and hemicellulose can be broken down into monomers by a set of appropriate enzymes, and the resulting monomers may be used to produce a variety of fuels or chemicals through either biological or chemical routes. However, the high production cost of these lignocellulose‐degrading enzymes remains a major challenge for the use of lignocellulosic biomass as raw material. In this context, this article reviews techno‐economic analyses concerning the production of cellulases and other lignocellulose‐degrading enzymes published over the last two decades. The major characteristics of each enzyme production process are described, underscoring the similarities and differences across the various process designs. Moreover, the enzyme production costs derived from these process designs and their composition in terms of raw materials, capital‐related factors, utilities, labor costs, etc., are compared. First, this analysis reveals that most techno‐economic evaluations in the literature address either cellulase production by submerged culture with Trichoderma reesei or enzyme production by solid‐state culture with filamentous fungi. Second, this analysis shows wide cost variations across process designs but it indicates that raw materials and capital‐related costs are generally the main drivers of the enzyme production cost. Furthermore, this assessment corroborates the importance of process parameters, such as product yield, production titer, and volumetric productivity, in the process economics of enzyme production. © 2020 Society of Chemical Industry and John Wiley & Sons, Ltd

BACKGROUND: Physicians´ lack of knowledge contributes to underuse of insulin and poor glycemic control in adults with diabetes mellitus (DM). Traditional continuing medical education have limited efficacy, and new approaches are required. OBJECTIVE: We report the design of a trial to assess the educational efficacy of InsuOnline, a game for education of primary care physicians (PCPs). The goal of InsuOnline was to improve appropriate initiation and adjustment of insulin for the treatment of DM. InsuOnline was designed to be educationally adequate, self-motivating, and attractive. METHODS: A multidisciplinary team of endocrinologists, experts in medical education, and programmers, was assembled for the design and development of InsuOnline. Currently, we are conducting usability and playability tests, with PCPs and medical students playing the game on a desktop computer. Adjustments will be made based on these results. An unblinded randomized controlled trial with PCPs who work in the city of Londrina, Brazil, will be conducted to assess the educational validity of InsuOnline on the Web. In this trial, 64 PCPs will play InsuOnline, and 64 PCPs will undergo traditional instructional activities (lecture and group discussion). Knowledge on how to initiate and adjust insulin will be assessed by a Web-based multiple choice questionnaire, and attitudes regarding diabetes/insulin will be assessed by Diabetes Attitude Scale 3 at 3 time points-before, immediately after, and 6 months after the intervention. Subjects´ general impressions on the interventions will be assessed by a questionnaire. Software logs will be reviewed. RESULTS: To our knowledge, this is the first research with the aim of assessing the educational efficacy of a computer game for teaching PCPs about insulin therapy in DM. We describe the development criteria used for creating InsuOnline. Evaluation of the game using a randomized controlled trial design will be done in future studies. CONCLUSIONS: We demonstrated that the design and development of a game for PCPs education on insulin is possible with a multidisciplinary team. InsuOnline can be an attractive option for large-scale continuous medical education to help improving PCPs´ knowledge on insulin therapy and potentially improving DM patients´ care. TRIAL REGISTRATION: Clinicaltrials.gov: NCT01759953; http://clinicaltrials.gov/show/NCT01759953 (Archived by WebCite at http://www.webcitation.org/6Dq8Vc7a6).

Abstract. We provide here an overview of, and a summary of results arising from, an extensive experimental campaign (the Spread F Experiment, or SpreadFEx) performed from September to November 2005, with primary measurements in Brazil. The motivation was to define the potential role of neutral atmosphere dynamics, specifically gravity wave motions propagating upward from the lower atmosphere, in seeding Rayleigh-Taylor instability (RTI) and plasma bubbles extending to higher altitudes. Campaign measurements focused on the Brazilian sector and included ground-based optical, radar, digisonde, and GPS measurements at a number of fixed and temporary sites. Related data on convection and plasma bubble structures were also collected by GOES 12, and the GUVI instrument aboard the TIMED satellite. Initial results of our SpreadFEx analyses are described separately by Fritts et al. (2009). Further analyses of these data provide additional evidence of 1) gravity wave (GW) activity near the mesopause apparently linked to deep convection predominantly to the west of our measurement sites, 2) small-scale GWs largely confined to lower altitudes, 3) larger-scale GWs apparently penetrating to much higher altitudes, 4) substantial GW amplitudes implied by digisonde electron densities, and 5) apparent influences of these perturbations in the lower F-region on the formation of equatorial spread F, RTI, and plasma bubbles extending to much higher altitudes. Other efforts with SpreadFEx data have also yielded 6) the occurrence, locations, and scales of deep convection, 7) the spatial and temporal evolutions of plasma bubbles, 8) 2-D (height-resolved) structures in electron density fluctuations and equatorial spread F at lower altitudes and plasma bubbles above, and 9) the occurrence of substantial tidal perturbations to the large-scale wind and temperature fields extending to bottomside F-layer and higher altitudes. Collectively, our various SpreadFEx analyses suggest direct links between deep tropical convection and large GW perturbations at large spatial scales at the bottomside F-layer and their likely contributions to the excitation of RTI and plasma bubbles extending to much higher altitudes.

Hyaluronic acid (HA) is a polysaccharide of alternating d-glucuronic acid and N-acetyl-d-glucosamine residues present in the extracellular matrix of connective, epithelial, and nervous tissues. Due to its singular hydrating, rheological and adhesive properties, HA has found numerous cosmetic and medical applications. However, techno-economic analyses of high value-added bioproducts such as HA are scarce in the literature. Here, we present a techno-economic analysis of a process for producing HA using Streptococcus zooepidemicus, simulated in SuperPro Designer. In the baseline scenario, HA is produced by batch fermentation, reaching 2.5 g/L after 24 h. It is then centrifuged, diafiltered, treated with activated carbon and precipitated with isopropanol. The product is suitable for topical formulations and its production cost was estimated as 1115 $/kg. A similar scenario, based on fed-batch culture and assuming a titer of 5.0 g/L, led to a lower cost of 946 $/kg. Moreover, in two additional scenarios, 10% of the precipitated HA is diverted to the production of a highly pure and high-molecular weight HA, suitable for injectable applications. These scenarios resulted in higher capital and operating costs, but also in higher profits, because HA for injectable use has a higher selling price that more than compensates for its higher production costs.

A clinical decision support system known as Leuko has been developed for leukemia diagnosis using a naive Bayes classifier. The system is able to recognize six types of white blood cells (WBC), including a malignancy. This paper investigates the use of support vector machines (SVMs) classifiers to recognize WBC for future leukemia diagnosis. Since SVMs are originally designed for the solution of two class problems, several strategies for their extension to this multiclass task are investigated and compared. The experimental results evidence the potential of SVMs to leukemia diagnosis and indicate that a hierarchical tree-based multiclass strategy can be better suited to a future update of the Leuko system.

Project-based learning (PBL) is an active learning methodology focused on developing both soft and hard skills by solving real-world problems. In PBL, teachers act as facilitators while students take charge of their own learning. While the practice of this methodology in computing education has been growing in recent years, it still poses some challenges that need to be addressed. Integrating Scrum and Agile methodologies into PBL can be a valuable addition when teaching computing subjects to students. Therefore, this paper presents a case study of a successful implementation of PBL with Scrum, applying Agile values and principles to teach Artificial Intelligence to undergraduate students. This study contributes to the limited research on Scrum in education, as well as helps bridge the research gap in AI teaching and learning. The case study involved 30 students from an undergraduate computing program, divided into five groups, who successfully developed five different Machine Learning (ML) models to tackle the challenging real-life problem of breast cancer prediction for the Cancer Institute of the State of São Paulo. The findings of the study indicate that the students effectively utilized Scrum and Agile methodologies throughout the process and expressed satisfaction with the approach. Additionally, they developed problem-solving abilities, critical thinking and communication skills, teamwork capabilities, and gained experience in working with real-life situations and problems. The study also demonstrates that the proposed technique aligns with the foundations of the PBL approach in computing education discussed in previous literature. It serves as a valuable resource for future research on PBL implementation, by comparing similarities and differences with existing literature and discussing the strategies employed to address implementation challenges.

This article focuses on the application of artificial avolution to the synthesis of analog active filters. The main objective of this research is the achievement of a new class of systems, with advantageous features compared to conventional ones, such as lower power consumption, higher speed and more robustness to noise. The particular problem of designing the amplifier of an AM receiver is examined in this work. Genetic algorithms are employed as our evolutionary tool and two sets of experiments are described. The first set has been carried out using a single objective, the desired frequency response of the circuit. In a second set of experiments, three other objectives have been included in the system. A new multi-objective evaluation methodology was conceived for this second set of experiments. A second approach for evolving active filters, using programmable chips, is also discussed in this paper.

The COVID-19 pandemic has motivated the rapid development of numerous vaccines that have proven effective against SARS-CoV-2. Several of these successful vaccines are based on the adenoviral vector platform. The mass manufacturing of these vaccines poses great challenges, especially in the context of a pandemic where extremely large quantities must be produced quickly at an affordable cost. In this work, two baseline processes for the production of a COVID-19 adenoviral vector vaccine, B1 and P1, were designed, simulated and economically evaluated with the aid of the software SuperPro Designer. B1 used a batch cell culture viral production step, with a viral titer of 5 × 1010 viral particles (VP)/mL in both stainless-steel and disposable equipment. P1 used a perfusion cell culture viral production step, with a viral titer of 1 × 1012 VP/mL in exclusively disposable equipment. Both processes were sized to produce 400 M/yr vaccine doses. P1 led to a smaller cost per dose than B1 ($0.15 vs. $0.23) and required a much smaller capital investment ($126 M vs. $299 M). The media and facility-dependent expenses were found to be the main contributors to the operating cost. The results indicate that adenoviral vector vaccines can be practically manufactured at large scale and low cost.

Abstract A population-based household survey was performed to estimate the prevalence of IgM and IgG to SARS-CoV-2 in residents of six districts in São Paulo City, Brazil. Serum samples collected from 299 randomly-selected adults and 218 cohabitants (N=517) were tested by chemiluminescence immunoassay ten weeks after the first reported case. Weighted overall seroprevalence was 4.7% (95% CI 3.0-6.6%). The low seroprevalence suggests that most of this population could still be infected. Serial serosurveys were initiated aiming to monitor the progress of the ongoing pandemic throughout the entire city. This may help inform public health authority decisions regarding prevention and control strategies.

The bio-based production of aromatics is experiencing a renaissance with systems and synthetic biology approaches promising to deliver bio-catalysts that will reach yields, rates and titers comparable to already existing bulk bio-processes for the production of amino acids for instance. However, aromatic building blocks derived from petrochemical routes have a huge economic advantage, they are cheap, very cheap in fact. In this article, we are trying to shed light on an important aspect of biocatalyst development that is frequently overlooked when working on strain development: economic and environmental impact of the production process. We estimate the production cost and environmental impact of a microbial fermentation process depending on culture pH, carbon source and process scale. As a model molecule we use 4-hydroxy benzoic acid (pHBA), but the results are readily transferrable to other shikimate derived aromatics with similar carbon yields and production rates.

Organic acid-based bioleaching has attracted significant research interest for the recovery of rare earth elements (REEs) and other critical metals. Utilizing biologically produced leaching agents, known as biolixiviants, derived from waste materials holds great promise for enhancing the economic viability and environmental sustainability of bioleaching processes. This study focuses on the modeling and optimization of biolixiviant production using corn stover (CS), date palm clippings (DP), and nonrecyclable paper (NP). Techno-economic analysis revealed that gluconic acid production from NP is more cost-effective than that from CS and DP, with respective costs of $0.04/kg, $0.06–0.08/kg, and $0.06–0.09/kg of the biolixiviant, yielding gluconic acid concentrations of 135.39, 172.90, and 176.87 mM, respectively. Life cycle assessment demonstrated that biolixiviant production from NP exerts the lowest environmental impact compared with the other evaluated substrates. When applied to the bioleaching of a neodymium–iron–boron magnet swarf, the biolixiviant derived from NP exhibits the highest leaching efficiencies, confirming its cost and environmental competitiveness in comparison to CS and DP.

BACKGROUND: The sum of environmental and genetic factors affects the appearance and function of the skin as it ages. The identification of molecular changes that take place during skin aging provides biomarkers and possible targets for therapeutic intervention. Retinoic acid in different formulations has emerged as an alternative to prevent and repair age-related skin damage. OBJECTIVES: To understand the effects of different retinoid formulations on the expression of genes associated with biological processes that undergo changes during skin aging. METHODS: Ex-vivo skin samples were treated topically with different retinoid formulations. The modulation of biological processes associated with skin aging was measured by Reverse Transcription quantitative PCR (RT-qPCR). RESULTS: A formulation containing microencapsulated retinol and a blend of active ingredients prepared as a triple nanoemulsion provided the best results for the modulation of biological, process-related genes that are usually affected during skin aging. CONCLUSION: This association proved to be therapeutically more effective than tretinoin or microencapsulated retinol used singly.

ABSTRACT Motivation Here, we make available a second version of the BioTIME database, which compiles records of abundance estimates for species in sample events of ecological assemblages through time. The updated version expands version 1.0 of the database by doubling the number of studies and includes substantial additional curation to the taxonomic accuracy of the records, as well as the metadata. Moreover, we now provide an R package (BioTIMEr) to facilitate use of the database. Main Types of Variables Included The database is composed of one main data table containing the abundance records and 11 metadata tables. The data are organised in a hierarchy of scales where 11,989,233 records are nested in 1,603,067 sample events, from 553,253 sampling locations, which are nested in 708 studies. A study is defined as a sampling methodology applied to an assemblage for a minimum of 2 years. Spatial Location and Grain Sampling locations in BioTIME are distributed across the planet, including marine, terrestrial and freshwater realms. Spatial grain size and extent vary across studies depending on sampling methodology. We recommend gridding of sampling locations into areas of consistent size. Time Period and Grain The earliest time series in BioTIME start in 1874, and the most recent records are from 2023. Temporal grain and duration vary across studies. We recommend doing sample‐level rarefaction to ensure consistent sampling effort through time before calculating any diversity metric. Major Taxa and Level of Measurement The database includes any eukaryotic taxa, with a combined total of 56,400 taxa. Software Format csv and. SQL.

ABSTRACT The aim of this study is to verify whether the framing effects of past performance information affect the risk perception of individuals for fixed-income and variable income fund. We assess whether risk perception varies depending on how information is communicated to investors, considering the relevance of possible framing effects arising from how information is presented in investment funds’ prospectuses and reports. This study is aimed at investors (individual and institutional) and fund industry regulators, highlighting the importance of past performance presentation. This article aims to contribute to the area by investigating how investors are influenced by varying perceptions of risk and return on fixed-income and variable-income assets, depending on information presentation format. The approach used is based on a 2x2 factorial quasi-experiment, in which format (within-subject) and time horizon (between-subjects) effects are tested in a sample of 143 respondents. Our results indicate that, for investment in a variable-income fund, a monthly yield presentation format leads to higher perceived risk, and that a framing emphasizing fund value evolution leads to higher perceived returns. As for investment in a fixed-income fund, the framing that emphasizes fund value leads to both higher perceived risk and higher perceived returns. When comparing the results for the two types of investments, the risk perception was higher for variable-income than for fixed income funds. However, perceived returns were higher for fixed income than for variable-income funds due to the framing effect, although realized returns do not corroborate this perception.

Contribution: Previous studies on learning strategies suggest that Project-Based Learning (PBL) represents a promising approach to enhancing academic performance in undergraduate environments. This research contributes to advancing active learning’s state-of-the-art by presenting a case study of a higher education institution that fully embraces Project-Based Learning. Additionally, it underscores the significance of gender-related investigations, particularly in addressing the impact of different learning styles on female students in science, technology, engineering, and mathematics (STEM). Background: As the demand for improving the ways of learning rooted in traditional models has risen, universities worldwide have begun implementing PBL, characterized by its student-centered trait that prioritizes knowledge acquisition through engagement in real-world projects. Research Question: Is PBL an effective methodology for undergraduate technology students, especially concerning its impact on female undergraduates? Methodology: To accomplish this purpose, a case study was conducted at a higher education institution, where first-year students were tasked with developing a job-matching website for women pursuing STEM careers over ten weeks, with the aim of acquiring web development skills while addressing the issue of female under-representation in technology fields. Findings: The analysis of the project’s development process experienced by the thirty-four-student class, along with their outcomes, and provided feedback on the learning experience, revealed promising findings regarding the worth of PBL adoption in computing courses, particularly concerning the development of important technical and behavioral skills. Furthermore, it was possible to establish a parallel between the subject matter of the studied project and an academic environment where gender issues are also prevalent.

In open MAS it is often a problem to achieve agents' interoperability. The heterogeneity of its components turns the establishment of interaction or cooperation among them into a non trivial task, since agents may use different internal models and the decision about trust other agents is a crucial condition to the formation of agents' cooperation. In this paper we propose the use of an ontology to deal with this issue. We experiment this idea by enhancing the ART reputation model with semantic data obtained from this ontology. This data is used during interaction among heterogeneous agents when exchanging reputation values and may be used for agents that use different reputation models.

Project-based learning (PBL) is a methodology in which students learn concepts by carrying out real projects. PBL involves the direct participation of students in the prac-tical application of the contents they are learning, promoting engagement and the development of various skills that would not be acquired through passive or individual studies. This article aims to analyze the use of PBL in teaching industrial automation concepts to 43 undergraduate Computer Engineering students. The case exploited was the concept of an industrial automation system. To support this project and validate the methodology used, data from a computing college and a partner company are considered. The technology college employs an innovative teaching methodology fully based on PBL, while the partner company has proposed a real industrial automation project to be carried out by undergraduate students. The results of this research are relevant for investigating new teaching methodologies in engineering education.

Difficulties in learning to read may have a number of causes and children tend to experience on the phonological route the most common disturbance in this cognitive task. Using two sample groups of children with and without reading difficulties and their corresponding EEG signals captured during the reading processing, we describe in this work a set of techniques that investigates such disturbance by generating whole brain mappings based on the entropy of each EEG electrode and non-supervised and supervised multivariate statistical analyses. Our experimental results have clearly showed specific neural organizations well suited to interpreting the word/phrase reading processing in these children. We believe that these techniques might become an effective computational tool in helping the diagnostic process of children with learning disabilities.

Teaching programming to novices is not a trivial task due to many students misconceptions regarding programming concepts. As a result, first-year STEM students may be discouraged to learn programming, impairing essential skills required for Information Technology professionals. This article aims to investigate if Project Based Learning (PBL) is a suitable approach to Introductory Programming that contributes to let students write functional code for real-life problems. A case study was carried out with 35 first-year students during a ten-week period. The project consisted on the development of educational computer games to disseminate cancer prevention awareness, a real-life problem proposed by a Medical College. Feedback from this external stakeholder and student perceptions are presented. PBL benefits, challenges and implications for Introductory Programming are also discussed.