Machine learning algorithms are widely used for predicting the consumer response to several food products. Recent studies in the literature demonstrated that it is possible to predict the consumer ...response to fruits using the physical, chemical, and physical–chemical data of fruits as input for the machine learning algorithms. However, a myriad of machine learning algorithms exists, and there is no consensus on which algorithm is the best for this task. This work evaluates and compares the results of six of the most used machine learning algorithms, the Random Forest, the Decision Tree, the Support Vector Machine, the Multilayer Perceptron neural network, the K‐Nearest Neighbors, and the Multivariate Linear Regression, in predicting the consumers’ acceptance, expectation, and their ideal of sweetness, succulency, and acidity for three different fruits. The results demonstrated that, indeed, there is no algorithm that outperforms all others for this task. Every algorithm has its advantages and disadvantages and performs differently according to the fruit and the corresponding dataset. Therefore, it highlights the importance of carefully selecting, optimizing, and comparing several algorithms when one is interested in predicting the consumer response to fruits.
Practical applications
Fruits are mostly commercialized without a strong assurance of their quality, which is their physical–chemical and sensory aspects. The loss of control of these aspects may impact the consumer, which can acquire low‐quality products and, thus, lead to unsatisfaction. This research shows that machine learning algorithms can be employed to effectively predict the consumer's sensory response to fruits. The use of these algorithms, which are based on easy‐to‐obtain physical and physical–chemical data, can improve the quality control of fruits in the market. Therefore, fruit producers and markets can commercialize their products based on their quality, thus providing a better experience to the consumer, which, in turn, can improve their satisfaction.
The widest k -set of disjoint paths problem Ribeiro, Marco Antônio; Carvalho, Iago Augusto; Pereira, Armando Honório
R.A.I.R.O. Recherche opérationnelle,
01/2023, Volume:
57, Issue:
1
Journal Article
Peer reviewed
Open access
Finding disjoint and widest paths are key problems in telecommunication networks. In this paper, we study the Widest
k
-set of Disjoint Paths Problem (WKDPP), an
NP
-Hard optimization problem that ...considers both aspects. Given a digraph
G
= (
N
,
A
), WKDPP consists of computing
k
arc-disjoint paths between two nodes such that the sum of its minimum capacity arcs is maximized. We present three mathematical formulations for WKDPP, a symmetry-breaking inequality set, and propose two heuristic algorithms. Computational experiments compare the proposed heuristics with another from the literature to show the effectiveness of the proposed methods.
The most popular and successful way to maintain a healthy body is to have a rich and balanced diet combined with physical exercise. Since the diet dilemma was proposed, several works in the ...literature suggested calculating a diet that respects the nutritional needs of each person. In the Caloric-Restricted Diet Problem (CRDP), the goal is to find a reduced-calorie diet that meets these nutritional needs, enabling weight loss. This paper proposes an Island-Based Hybrid Evolutionary Algorithm (IBHEA) that uses a Genetic Algorithm (GA) and a Differential Evolution (DE) Algorithm with different parameters settings in different islands communicating through several migration policies to solve the CRDP. Computational experiments showed that IBHEA outperformed more than 5% compared with non-distributed and non-hybrid implementations, generating a greater variety of diets with a small calorie count.
In this paper we study the Algorithm Mean Upper (AMU), a simple 2-approximative algorithm that can be applied to any interval data min-max regret optimization problem. We perform computational ...experiments in more than one thousand instances of three min-max regret optimization problems: the Robust Shortest Path Problem; the Robust Minimum Spanning Tree Problem; and the Robust Assignment Problem. It was shown that the average relative deviation of AMU was 14% in comparison to CPLEX upper bound, being closer to the optimum than its theoretical limit.
The Caloric-Restricted Diet Problem (CRDP) aims at finding diets with a reduced caloric count that also respects the nutritional needs of an individual. Thus, it is possible to achieve weight loss ...without compromising the individual's health. However, due to the small amount of energy contained in such diets, one may not be fully satisfied after a meal. It is possible to overcome this drawback by inserting a larger amount of protein in the diet, as it was shown to be the most effective macronutrient that provides satiety. Thus, this work presents a multi-objective mathematical formulation for the CRDP that minimizes the calorie count of the diet and maximizes the number of proteins ingested. Besides that, a Generalized Differential Evolution algorithm (GDE3) is proposed to solve the resulting problem. Computational experiments are performed with both mono-objective and multi-objective CRDP and two example diets are presented. It shows that it is possible to achieve a diet with a large amount of proteins, while restricting the caloric number.
is an opportunistic pathogen primarily associated with multidrug-resistant nosocomial infections, for which polymyxins are the last-resort antibiotics. This study investigated carbapenem-resistant
...strains exhibiting an extensively drug-resistant (XDR) phenotype, including four isolates considered locally pan drug-resistant (
PDR), isolated from inpatients during an outbreak at a teaching hospital in Brazil. ApaI DNA macrorestriction followed by PFGE clustered the strains in three pulsotypes, named A to C, among carbapenem-resistant
strains. Pulsotypes A and B clustered six polymyxin-resistant
strains. MLST analysis of representative strains of pulsotypes A, B, and C showed that they belong, respectively, to sequence types ST1 (clonal complex, CC1), ST79 (CC79), and ST903. Genomic analysis of international clones ST1 and ST79 representative strains predicted a wide resistome for β-lactams, aminoglycosides, fluoroquinolones, and trimethoprim-sulfamethoxazole, with
and
genes encoding carbapenem resistance. Amino acid substitutions in PmrB (Thr232Ile or Pro170Leu) and PmrC (Arg125His) were responsible for polymyxin resistance. Although colistin MICs were all high (MIC ≥ 128 mg/L), polymyxin B MICs varied; strains with Pro170Leu substitution in PmrB had MICs > 128 mg/L, while those with Thr232Ile had lower MICs (16-64 mg/L), irrespective of the clone. Although the first identified polymyxin-resistant
strain belonged to ST79, the ST1 strains were endemic and caused the outbreak most likely due to polymyxin B use. The genome comparison of two ST1 strains from the same patient, but one susceptible and the other resistant to polymyxin, revealed mutations in 28 ORFs in addition to
. The ORF codifying an acyl-CoA dehydrogenase has gained attention due to its fatty acid breakdown and membrane fluidity involvement. However, the role of these mutations in the polymyxin resistance mechanism remains unknown. To prevent the dissemination of XDR bacteria, the hospital infection control committee implemented the patient bathing practice with a 2% chlorhexidine solution, a higher concentration than all
chlorhexidine MICs. In conclusion, we showed the emergence of polymyxin resistance due to mutations in the chromosome of the carbapenem-resistant
ST1, a high-risk global clone spreading in this hospital.
In the present study, we aimed to evaluate the therapeutic effect of Passiflora edulis fruit peel aqueous (AFA) extract as an adjuvant to insulin to confer nephroprotection against ...streptozotocin-induced diabetes. Male Wistar rats were divided into four groups based on treatment received for 60 days: diabetic (DB), control (CTL), insulin (INS), and insulin + AFA extract (INS + AFA). mRNA and protein expression levels of podocyte (nephrin, podocin, and WT1) and tubular (megalin) proteins were measured in kidney tissue specimens and urine. Biochemical parameters and kidney histopathology were also examined. Herein, the INS + AFA group showed superior glycemic control, which resulted in the reduction of urinary albumin/creatinine ratio, maintenance of baseline levels of Nphs1, Nphs2, Wt1, and Lrp2 mRNA expression, prevention of protein loss from the kidney tissue into the urinary space, along with the maintenance of glomerular basement membrane thickness, hyalinization, glomerular and tubulointerstitial fibrosis at values approximating those of the CTL group and significantly lower than those in the DB group. Therefore, these results suggest that, as an anti-diabetic agent, the AFA extract adjuvant to insulin could reduce and potentially prevent diabetic kidney disease.
Background:
The new coronavirus disease (COVID-19) has claimed thousands of lives worldwide and disrupted the health system in many countries. As the national emergency care capacity is a crucial ...part of the COVID-19 response, we evaluated the Brazilian Health Care System response preparedness against the COVID-19 pandemic.
Methods:
A retrospective and ecological study was performed with data retrieved from the Brazilian Information Technology Department of the Public Health Care System. The numbers of intensive care (ICU) and hospital beds, general or intensivist physicians, nurses, nursing technicians, physiotherapists, and ventilators from each health region were extracted. Beds per health professionals and ventilators per population rates were assessed. A health service accessibility index was created using a two-step floating catchment area (2SFCA). A spatial analysis using Getis-Ord Gi
*
was performed to identify areas lacking access to high-complexity centers (HCC).
Results:
As of February 2020, Brazil had 35,682 ICU beds, 426,388 hospital beds, and 65,411 ventilators. In addition, 17,240 new ICU beds were created in June 2020. The South and Southeast regions have the highest rates of professionals and infrastructure to attend patients with COVID-19 compared with the northern region. The north region has the lowest accessibility to ICUs.
Conclusions:
The Brazilian Health Care System is unevenly distributed across the country. The inequitable distribution of health facilities, equipment, and human resources led to inadequate preparedness to manage the COVID-19 pandemic. In addition, the ineffectiveness of public measures of the municipal and federal administrations aggravated the pandemic in Brazil.
BACKGROUNDMalaria is curable. Nonetheless, over 229 million cases of malaria were recorded in 2019, along with 409,000 deaths. Although over 42 million Brazilians are at risk of contracting malaria, ...99% percent of all malaria cases in Brazil are located in or around the Amazon rainforest. Despite declining cases and deaths, malaria remains a major public health issue in Brazil. Accurate spatiotemporal prediction of malaria propagation may enable improved resource allocation to support efforts to eradicate the disease. METHODSIn response to calls for novel research on malaria elimination strategies that suit local conditions, in this study, we propose machine learning (ML) and deep learning (DL) models to predict the probability of malaria cases in the state of Amazonas. Using a dataset of approximately 6 million records (January 2003 to December 2018), we applied k-means clustering to group cities based on their similarity of malaria incidence. We evaluated random forest, long-short term memory (LSTM) and dated recurrent unit (GRU) models and compared their performance. RESULTSThe LSTM architecture achieved better performance in clusters with less variability in the number of cases, whereas the GRU presents better results in clusters with high variability. Although Diebold-Mariano testing suggested that both the LSTM and GRU performed comparably, GRU can be trained significantly faster, which could prove advantageous in practice. CONCLUSIONSAll models showed satisfactory accuracy and strong performance in predicting new cases of malaria, and each could serve as a supplemental tool to support regional policies and strategies.
Objetivo: Analisar as evidências apresentadas nos estudos sobre a síndrome compartimental abdominal em adultos nos últimos cinco anos. Método: Trata-se de uma revisão integrativa da literatura, com ...artigos publicados nos últimos cinco anos, que procura responder a seguinte pergunta norteadora: Quais são as evidências científicas acerca do conhecimento da síndrome compartimental abdominal? Resultados e discussão: Dada a importância e potencial de gravidade do tema, encontrou-se uma baixa quantidade de estudos relacionados ao tema nos últimos anos, também foram encontradas fragilidades entre no conhecimento dos profissionais da saúde estudados e as diretrizes atuais da WSACS, há ainda uma necessidade de atualização das diretrizes voltando o olhar para a especificidade da gestação no aumento da PIA. Conclusão: Dada complexidade da SCA, assim como, a sua necessidade de associação multidisciplinar para assistência adequada, principalmente sua relação com a atuação do profissional médico e enfermeiro, há uma lacuna na produção científica atual sobre o tema, essencialmente que os estudos apontam a necessidade do conhecimento e integração de ações dos profissionais da saúde com as diretrizes atualizadas da WSACS para manejo adequado e prevenção das complicações relacionadas a SCA.
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