Primary carcinomas of the lung are vastly represented by the conventional types of adenocarcinomas or squamous cell carcinomas. However, there are other types of non-small cell carcinomas that although uncommon represent a meaningful group that often pose a problem not only in diagnosis but also in classification. Spindle and giant cell carcinomas although uncommon primary lung carcinomas are well known to occur. Important to highlight is that current criteria are rather ambiguous and likely not up to date, which renders the classification of these tumors somewhat more obscure. In addition, with the daily use of immunohistochemical stains, the classification of these tumors may also pose a different problem in the proper allocation of these tumors. Proper classification is highly important in the selection process that takes place using such material for molecular analysis. Current molecular characteristics of these tumors is limited and lacks more in-depth studies and analysis that can provide specific targets for the treatment of patients with these tumors. The current review attempts to highlight the shortcomings in the current classification and definitions of these neoplasms as well as the more current view regarding these tumors when the use of immunohistochemical stains is employed.

Cultural recovery of Mucorales from hyphae-laden tissue is poor, and the clinical implications of culture positivity are scarcely studied. Therefore, we compared clinical and histological characteristics of culture-positive and culture-negative histology-proven pulmonary mucormycosis cases among cancer patients. Histology specimens were blindly reviewed by a Thoracic Pathologist and graded on four histopathologic features: hyphal quantity, tissue necrosis, tissue invasion, and vascular invasion. Twenty cases with a corresponding fungal culture were identified; five were culture-positive, and 15 culture-negative. Although no statistically significant differences were found, culture-positive patients were more likely to exhibit a high burden of necrosis and have a high burden of hyphae but tended to have less vascular invasion than culture-negative patients. In terms of clinical characteristics, culture-positive patients were more likely to have acute myeloid leukemia (60% vs. 27%, p=0.19), a history of hematopoietic cell transplant (80% vs. 53%, p=0.31), severe lymphopenia (absolute lymphocyte count ≤500/µL, 100% vs. 73%, p=0.36), and monocytopenia (absolute monocyte count ≤100/µL, 60% vs. 20%, p=0.11). Forty-two-day all-cause mortality was comparable between culture-positive and culture-negative patients (60% and 53%, p=0.80). This pilot study represents the first comprehensive histopathological scoring method to examine the relationship between histopathologic features, culture positivity, and clinical features of pulmonary mucormycosis.

Background: During esophagogastroduodenoscopy performed with colonoscopy, gastric and duodenal erythema, erosions, and ulcerations are often observed. This investigation was designed to review the prevalence of gastroduodenal lesions in patients who underwent wireless capsule endoscopy using standard bowel cleansing preparations, but no endoscopy or sedation. Methods: A retrospective analysis was conducted on patients referred for capsule endoscopy. Records and capsule reports were reviewed for patient demographics, preparation prescribed, procedural indications, and gastroduodenal findings. Preparations studied included polyethylene glycol lavage (PEG), PEG plus bisacodyl (PEG+bis), bisacodyl (bis), oral sulfate solution (OSS) and no prep. Results: Among the 1236 records, 498 (40.3%) were men and 738 (59.7%) were women. The mean age was 57 years +/- 17.8 years SD. The percentage of patients with lesions after any bowel preparation was 52.7% for gastric lesions and 23.6% for duodenal lesions. The percentage of patients with gastroduodenal lesions was 58.3% with prep, compared to 38.2% without prep. These findings were statistically significant with RR 1.53 [1.19-1.94] (p-value=0.00004). This difference was more pronounced in the OSS group RR 1.65 [1.29-2.1] and bisacodyl groups RR 1.64 [1.25-2.15] compared to the PEG group RR 0.95 [0.7-1.3]. Conclusion: This study showed that patients undergoing wireless capsule endoscopy who received bowel preparations had a significant increase in gastric and duodenal lesions. Of the preparations studied, OSS was associated with the greater number of gastroduodenal lesions, while PEG was the least associated with lesions with an occurrence similar to the non-prep group. The clinical significance of these lesions remains undetermined.

Exercise-based cardiac rehabilitation requires patients to perform a set of certain prescribed exercises a specific number of times. Local muscular endurance (LME) exercises are an important part of the rehabilitation program. Automatic exercise recognition and repetition counting, from wearable sensor data is an important technology to enable patients to perform exercises independently in remote settings, e.g. their own home. In this paper we first report on a comparison of traditional approaches to exercise recognition and repetition counting, corresponding to supervised machine learning and peak detection from inertial sensing signals respectively, with more recent machine learning approaches, specifically Convolutional Neural Networks (CNNs). We investigated two different types of CNN: one using the AlexNet architecture, the other using time-series array. We found that the performance of CNN based approaches were better than the traditional approaches. For exercise recognition task, we found that the AlexNet based single CNN model outperformed other methods with an overall 97.18% F1-score measure. For exercise repetition counting , again the AlexNet architecture based single CNN model outperformed other methods by correctly counting repetitions in 90% of the performed exercise sets within an error of ±1. To the best of our knowledge, our approach of using a single CNN method for both recognition and repetition counting is novel. In addition to reporting our findings, we also make the dataset we created, the INSIGHT-LME dataset, publicly available to encourage further research.

Phosphorus is required by laying hens for a variety of biological functions. It is usually provided in excess, in a readily digestible inorganic form in diet formulations. However, this does not represent an efficient use of a finite resource and can result in water pollution. Plant bound phosphorus in phytate, is common in commercial poultry diets, and represents an alternate source of phosphorus, however poultry lacks the enzyme to digest it. By adding enzymes to their diets, the availability of this phytate-bound phosphorus can be increased allowing for the reduced inclusion of inorganic P in the diet formulation. Therefore, this study was conducted to examine the effect of a natural enzyme complex that contains phytase and xylanase in layer diets. Novogen Brown Classic layers (n=314) were fed one of two diets: (T1) control diet or (T2) control diet plus a natural mixed-enzyme product with both, phytase and xylanase. Experimental diets were provided for 12 days after which the excreta from each pen were collected for an additional three days to determine total retention and ileal digestibility of phosphorus and gross energy. At the end of the trial the birds were euthanized, and their ileal contents were collected. Productivity parameters were also recorded over the course of the study. The amount of phosphorus detected in the excreta of the control group was significantly higher than the amount detected in the enzyme-supplemented group (P<0.05). Both phosphorus retention and phosphorus ileal digestibility were significantly higher in the enzyme-supplemented birds (P<0.001). Gross energy digestibility was significantly higher in the enzyme-supplemented birds for both the total tract and ileal samples (P<0.001). There were only numerical improvements, not significant, in the layer productivity parameters. This study showed that the enzyme supplement can improve total retention and ileal digestibility of phosphorus and gross energy in older layers.

The importance of enzymes in the poultry industry is ever increasing because they help to extract as many nutrients as possible from the raw material available and reduce environmental impacts. Therefore, an experiment was conducted to examine the effect of a natural enzyme complex (ASC) on diets low in AME, Ca and P. Ross 308 broilers (n = 900) were fed one of four diets: (1) positive control (PC) with no enzyme added (AME 12.55 MJ/kg, AVPhos 4.8 g/kg and AVCal 9.6 g/kg); (2) negative control (NC) with no enzyme added and down-specified for AME, Ca and P (AME 12.18 MJ/kg, AVPhos 3.3 g/kg, AVCal 8.1 g/kg); (3) negative control plus ASC at 200 g/t; and (4) negative control plus ASC at 400 g/t. Broiler performance, digesta viscosity, tibia mineralization and mineral content were analyzed at d 21. Between d 18 and 20, excreted DM, GE, total nitrogen, Ca, and P were analyzed. ASC at 200 g/t and 400 g/t improved the FCR (p = 0.0014) significantly when compared with that of the NC. There were no significant differences in BW or FI between the treatments. Birds fed ASC at 200 g/t and 400 g/t had significantly improved digesta viscosity (p &lt; 0.0001) compared with that of the PC and NC and had significantly higher excreted DM digestibility (p &lt; 0.01) than the NC and the PC with 400 g/t ASC. ASC inclusion significantly improved P retention (p &lt; 0.0001) compared with that in the PC. Ca retention was significantly increased by 400 g/t ASC compared with that in the PC and NC (p &lt; 0.001). AME was significantly higher (p &lt; 0.0001) for all treatments compared with that in the NC. There were no significant differences between treatments for any of the bone measurements. This study showed that feeding ASC can support the performance of broilers when fed a specification reduced in Ca, P and AME, with the greatest results being seen with the higher inclusion level of ASC.

As more end devices are getting connected, the Internet will become more congested. A variety of congestion control techniques have been developed either on transport or network layers. Active Queue Management (AQM) is a paradigm that aims at mitigating the congestion on the network layer by active buffer control to avoid overflow. However, finding the right parameters for an AQM scheme is challenging, due to the complexity and dynamics of the networks. On the other hand, the Explicit Congestion Notification (ECN) mechanism is a solution that makes visible incipient congestion on the network layer to the transport layer. In this work, we propose to exploit the ECN information to improve AQM algorithms by applying Machine Learning techniques. Our intelligent method uses an artificial neural network to predict congestion and an AQM parameter tuner based on reinforcement learning. The evaluation results show that our solution can enhance the performance of deployed AQM, using the existing TCP congestion control mechanisms.

The effects of climate change health impacts on urban health care systems and vulnerable populations are a researched topic with foundations on urban risk management, urban health methodologies, and sustainable urbanization. As climate change is a dynamic and transformative global issue the gap between adaptation and mitigation efforts and urban planning relies, among other things, in the limitations of previous studies of risk management structures tailored to the existing strategy to calculate the uncertainties and predict their influence on urban systems and subsystems. Moreover, as climate and health is a well-researched issue, it is also complex as the methodologies and strategic approach to minimize health risks of climate change is intrinsically contingent to risk methodologies and policy-making processes that are efficient with support of knowledge-based information. This paper emphasis the need for focusing on urban health risk management methods that serves to identify potential opportunities, and then manage and take action to prevent adverse health effects. It also emphasizes the probability of events and their consequences, which are measurable both qualitatively and quantitatively.

We present an open-source Star Tracker (ST) for Attitude Determination. Our implementation makes use of open source software of common usage in astronomy running on a Raspberry Pi 2 platform. The developed platform is open and available for parties interested in further development. Evaluation of the system showed that the ST is suitable for Cubesats of 2U or larger. The ST platform is capable of solving the Lost-In-Space (LIS) problem. Currently, the average accuracy reached of the algorithm is close to 5 seconds of arc with an average processing time of 75 seconds. However, a average accuracy of about 3 minutes of arc can be reached with 35 seconds in average processing time. We also describe the evaluation procedure, the found conclusions of this procedure, in particular the section of the algorithm where most of the processing time is spent and other possible source of errors not included in this study.

Agronomic traits such as biomass yield and abiotic stress tolerance are genetically complex and challenging to improve by conventional breeding strategies. Genomic selection (GS) is an alternative approach in which genome-wide markers are used to determine the genomic estimated breeding value (GEBV) of individuals in a population. In alfalfa, previous results indicated that low to moderate prediction accuracy values (<70%) were obtained in complex traits such as yield and abiotic stress resistance. There is a need to increase the prediction value in order to employ GS in breeding programs. In this paper we reviewed different statistic models and their applications in polyploid crops including alfalfa. Specifically, we used empirical data affiliated with alfalfa yield under salt stress to investigate approaches which use DNA marker importance values derived from machine learning models, and genome-wide association studies (GWAS) of marker-trait association scores based on different GWASpoly models, in weighted GBLUP analyses. This approach increased prediction accuracies from 50% to more than 80% for alfalfa yield under salt stress. This is the first report in alfalfa to use variable importance and GWAS-assisted approaches to increase the prediction accuracy of GS, thus helping to select superior alfalfa lines based on their GEBVs.

In recent times, using image-based deep learning techniques has been very useful for classifying fruits. However, mango is a particular challenge because its shelf life is directly related to the degree of maturity at the time of harvest, which is determined mainly through the visual assessment of the operators when sorting them, doing it incorrectly, coupled with the blows and compressions exposed during storage and transport, trigger the deterioration in their quality, hence the importance of this operation. In this sense, the purpose of this study focuses on designing a computational model based on Deep Learning that uses a convolutional neural network (CNN) parameterized to select mangoes according to their color tone based on their maturity stage. A dataset was established from 201 labeled images, then a CNN architecture was built, obtaining a model on which 3 criteria were evaluated: the number of convolution and grouping layers, the resolution of the input images and the number of training epochs required. As a result, an input image resolution of 32 x 32 pixels was achieved, the process included a convolution layer followed by pooling that fed another layer that processed the results and ended in an output layer with 2 neurons under the One Hot Encoding representation. The model required 20 epochs to perfect its training, achieving 96.04 % accuracy in mango image selection. This study supports the potential of CNNs in quality analysis through mango color selection, even in uncertainty scenarios.

Companion cropping involves growing two or more species together, benefiting the conservation of natural resources and improving fertilization and nutrient cycling by balancing chemical and organic sources. Studies, as in the case of tree tomato and Hass avocado, have shown a significant increase in yield compared to monocultures, highlighting the viability of this practice. In addition to their environmental benefit, companion crops offer economic advantages to producers by obtaining multiple products in a single harvest, strengthening food security and the economy of rural families. This study evaluated three levels of fertilization and interactions between fruit trees at different altitudes, observing differential behavior in the variables evaluated. The combination of cape gooseberry and blackberry showed significantly positive results, with more leaves and fewer pests, demonstrating the benefits of companion plants. A trend towards the combined use of chemical and organic fertilizers was observed, a potential strategy to reduce costs and improve crop growth. The results were shared with producers interested in implementing companion cropping, encouraging the adoption of this more sustainable and profitable agricultural practice. Companion crop agriculture represents a viable and promising strategy for a more efficient and sustainable agriculture, with both environmental and economic benefits.

Patches of Diopatra species from Brazilian sandy beaches were followed for ca. 50 years. Data were accessed from papers, gray literature, images and collections to verify time changes in the South Brazilian Bight (SBB) from 1974-2021. We modeled maximum density over time at 15 beaches, observing very high densities (&gt; 100 ind.m-2) in 1974 followed by a decrease (~ 10 ind.m-2) of three species of Diopatra until 1995 and a strong decline (1996-2002) when populations were almost regionally extinct (0-1 ind. m-2). A slight recovery (3-4 ind.m-2) occurred after 2006 for a single species, D. marinae, associated with warmer northern waters, suggesting a range shift. This pattern was associated with a) heatwaves linked to an El-Niño event (1988) and gradual SST surface warming of ca. 1 oC since 1974. The usage of Diopatra spp. as fishing bait could also be associated with such a reduction. After 2016, D. neapolitana, a likely alien species, was established in the SBB in high densities. Projections based on Species Distribution Modeling (SDM) suggest a potential of invasion in the same range of the known species of D. cuprea complex along the Brazilian coast despite that there are no signs of competition between both species.

This scoping review aims to identify the available evidence concerning the clinical and psychosocial impacts of the communication of oral potentially malignant disorders (OPMDs), and to map and analyze knowledge gaps regarding truth-telling about risk factors, malignant transformation, treatment, and follow-up approaches. Search strategy was performed using electronic databases (Medline/PubMed, Scopus, Embase, and Web of Science) and one grey literature database (Google Scholar). Studies focused on communicating the diagnosis of OPMDs and the patients' perceptions were included. Study selection and data extraction were performed by two authors in a two-phase process. Five publications were included in the qualitative analysis. Each publication involved a different study design, study population, types of OPMDs, and results on the important aspects of the professional-patient communication about the diagnosis of OPMDs. Although specific protocols on OPMDs communication have not yet been reported, there is an elevated interest on this topic since the strategies and skills on professional communication could provide better clinical outcomes to the patients. A list of recommendation strategies on how to communicate an OPMD diagnosis is proposed; however, future studies are still needed to design specific communication protocols for OPMD.

The extensive deployment of wireless infrastructure provides a low-cost way to track mobile users in indoor environment. This paper demonstrates a prototype model of an accurate and reliable room location awareness system in a real public environment, where three typical problems arise. First, a massive number of access points (APs) can be sensed leading to a high-dimensional classification problem. Second, heterogeneous devices record different received signal strength (RSS) levels due to the variations in chip-set and antenna attenuation. Third, APs are not necessarily visible in every scanning cycle leading to missing data. This paper presents a probabilistic Wi-Fi fingerprinting method in a hidden Markov model (HMM) framework for mobile user tracking. Considering the spatial correlation of the signal strengths from multiple APs, a Multivariate Gaussian Mixture Model (MVGMM) is fitted to model the probability distribution of RSS measurements in each cell. Furthermore, the unseen property of invisible AP has been investigated in this research, and demonstrated the efficiency of differentiation between cells. The proposed system is able to achieve comparable localization performance. The filed test results present a reliable 97% localization room level accuracy of multiple mobile users in a real university campus WiFi network without any prior knowledge of the environment.

In the present work we present a methodology for teaching the basis of the genetic code through music composition, with the aim to combine science and arts learning. The project was carried out by 155 students, the so-called MARGA Consortium, with ages comprised between 10 and 17 years from different public schools located in the Principality of Asturias, Spain. The different groups generated 8 different music works using a short genetic sequence obtained from the human notch1 gene, receptor of mutations leading to chronic lymphocytic leukemia.

Agroecology, defined as the ecological science of food production is also as practical approach to design food production systems based on local concerted solutions that aim to promote synergy among the diversity of human and non human food systems elements. These two facets makes agroecology a good candidate for participatory research. Information technology should help using this information for the production of structured scientific knowledge. In this respect, there is a need for information technology that is adaptive to encompass the diversity of within and between systems and that provide benefit to farmers that feed it with data. We present MiCampoApp, a webapp that aims to join participatory research and certification in agroecology, with two roles, the farmer and the administrator. The idea to join participatory research for decision support with certification for market differentiation in single system is that much of the certification data harbors information for scientific research, and this incentivize data collection for the interest of the farmer and the community. The administrator create a model for data collection in order to solve a research question of interest for a communities or to produce traceability information to feed participatory guarantee system in a community. The farmer collects information using simple icons and produces traceability pages for research or certification purposes.

The aim of this study was to evaluate and compare the fracture resistance of definitive zirconia dioxide restorations obtained using a computer-aided design and manufacturing (CAD/CAM) system. Methods: Two groups of ten samples were analyzed for each material (n: 20), the first group was Zolid Gen X Amann Girrbach (ZGX) and the second group was Cercon HT Dentsply Sirona (CDS). The restorations were designed with identical parameters and milled with a CAD/CAM system. Each specimen was load tested at a speed of 0.5 mm/min with a direction parallel to the major axis of the tooth and with an initial preload of 10N until fracture using a universal testing machine (Universal/Tensile Testing Machine, Autograph AGS-X Series) equipped with a 20 kN load cell. The results obtained were recorded in Newtons (N), using software connected to the testing machine. Results: Statistically significant differences were found, and the fracture toughness of the monolithic zirconia crowns was lower in the CDS group (1744.84 ± 172.8 N), compared to the ZGX group (2387.41 ± 516 N). Conclusions: The monolithic zirconia CAD-CAM zirconia crowns showed sufficient fracture strength to be used in posterior molar and premolar zones with either material as they withstood fracture loads greater than the maximum masticatory force.

Introduction: Flow-cytometry (FC) is a powerful tool that can assist in lymphoma diagnosis in lymph node (LN) specimens. Although lymphoma diagnosis and classification are mainly based on tumor cell characteristics, surrounding cells are less employed in this process.Methods: We retrospectively investigated alterations in the ploidy status, proliferative cell fraction (PF) and the percentages of surrounding immune cells in 62 consecutive LN specimens with B-Cell Non-Hodgkin Lymphoma (B-NHL) that were submitted for FC evaluation between 2019-2022.Results: Compared with indolent B-NHLs, aggressive B-NHLs show increased DNA aneuploidy and PF, increased monocytes, immature-granulocytes, mature granulocytes, CD8⁺ T-cells, Double-Negative-T-cells and Double-Positive-T-cells, and decreased total CD45⁺ cells, total lymphocytes, CD4⁺ T-cells and CD4/CD8 ratio. Receiver operating characteristic analysis determined PF > 6.8% and immature-granulocytes > 0.9% as optimal cutoffs with highest specificity and sensitivity in differentiating aggressive and indolent B-NHLs.Conclusions: These findings further strength the diagnostic value of DNA content analysis by FC and suggest the utilization of tumor surrounding immune cells in NHL diagnosis and classification.

B chromosomes (B) are supernumerary elements found in many taxonomic groups. Most B chromosomes are rich in heterochromatin and composed of abundant repetitive sequences, especially transposable elements (TEs). Bs origin is generally linked to the A chromosome complement (A). The first report of a B chromosome in African cichlids was on Astatotilapia latifasciata, which can harbor 0, 1 or 2 B chromosomes. Classical cytogenetics studies found high TE content on the species B chromosome. In this study, we aim to understand TE composition and expression on A. latifasciata genome and its relation to the B chromosome. We use bioinformatics analysis to explore TEs genome organization and also their composition on the B chromosome. Bioinformatics findings were validated by fluorescent in situ hybridization (FISH) and real-time PCR (qPCR). A. latifasciata has a TE content similar to other cichlid fishes and several expanded elements on its B chromosome. With RNA sequencing data (RNA-seq) we showed that all major TE classes are transcribed in brain, muscle and male/female gonads. The evaluation of TE expression between B- and B+ individuals showed that few elements have differential expression among groups and expanded B elements were not highly transcribed. Putative silencing mechanisms may the acting on the B chromosome of A. latifasciata to prevent adverse consequences of repeat transcription and mobilization in the genome.

Let $\mathcal{N}$ be an arbitrary class of matroids, closed under isomorphism. For $k$ a positive integer, we say that $M \in \mathcal{N}$ is \emph{$k$-minor-irreducible} if $M$ has no minor $N \in \mathcal{N}$ such that $1\leq\left|E\left(M\right)\right|-\left|E\left(N\right)\right|\leq k $. Tutte's Wheels and Whirls Theorem establish that, up to isomorphism, there are only two families of 1-minor-irreducible matroids in the class of 3-connected matroids. More recently, Lemos classified the 3-minor-irreducibles with at least 14 elements in the class of triangle-free 3-connected matroids. Here we prove a local characterization for the 2-minor-irreducible matroids with at least 11 elements in the class of triangle-free 3-connected matroids. This local characterization is used to establish two new families of 2-minor-irreducible matroids in this class.

Membrane distillation techniques appear as one of the most promise alternative to guarantee the availability of potable water in time of scarce of this essential resource. For membrane preparation, polyvinylidene fluoride (PVDF) is preferred due to the easier synthesis procedures with respect to other fluorine based polymers. In this work, copper oxide nanoparticles (CuONPs) at different weight percent (wt.%), embedded in PVDF membranes supported on non-woven polyester fabric (NWPET) were prepared by the phase-inversion method, and characterized by spectroscopy (ATR-FTIR, Raman) and electron microscopy techniques (SEM). The PVDF deposited onto the NWPET was highly composed by its polar -phase (F()= 53 %) which was determined from the ATR-FTIR spectrum. The F() value was kept constant, in the whole range of CuONPs studied (2-10 wt.%) as was determined from the ATR-FTIR spectrum. The absence of signals corresponding to CuONPs in the ATR-FTIR spectra and the appearance of peaks at 297, 360 and 630 cm-1 in the Raman spectra of the membranes suggested that the CuONPs are preferably located in the inner of the membrane but not on its surface. The membrane morphologies were characterized by SEM. From the obtained SEM micrographs, a decrease and increase in the amount of micropores and nanopores, respectively, near to the surface and intercalated in the finger-like layer were observed. As result of the CuONPs addition, the nanopores in the sponge-like layer decrease in size. The values of water contact angle (WCA) measurements showed a trend to decrease from 94° to 80° upon the addition of CuONPs (2-10 wt.%) indicating a diminish in the hydrophobicity degree of the membranes. Apparently, the increase in the amount of nanopores near to the surface decreased the membrane roughness becoming less hydrophobic.

This research seeks to understand the impact of digital platforms on the governance of smart cities. It uses the Scaffold of Popular Participation to classify digital platforms and better understand participatory governance in cities, its benefits and complications, correlating them with the SDGs of the 2030 Agenda. It was also possible to list points of attention for the development of digitization in the public sector, including in Brazil. It concluded that the digitization of public services is in progress, pressured by the civil body for greater transparency and participation. In addition, the platforms must be guided by civil inclusion in the discussion of public policies, by the training of intelligent citizens and by sustainable guidelines that guide the themes addressed. In contrast, platforms can also facilitate deception and popular manipulation, which represents a high risk if used for this purpose.

Access to health services compromises therapeutic adherence in patients with HTN, which is a risk factor for cardiovascular disease and premature death. The aim of the research is to determine the influence of access to health services on adherence to antihypertensive treatment during the COVID-19 pandemic. We included a cross-sectional analytical study. A survey was applied to 241 hypertensive patients at the Daniel Alcides Carrión Hospital, Callao-Peru. Data were analyzed using SPSS software. Absolute and relative frequencies were reported and the chi-square test was applied with a statistical significance level of p&lt;0.05. In addition, multiple logistic regression analysis was performed using the Stepwise method. An association was found between non-adherence to treatment and health expenses (ORa: 1.9 CI 95% 1.7-2.2), not receiving care due to lack of a doctor (ORa: 2.8 CI 95% 1.5-3.2), having difficulty with schedules (ORa: 3.7 CI 95% 2. 3-5.5), fear of receiving care at the hospital (ORa: 4.5 CI 95 % 2.7-6.8), trust in health personnel (ORa: 7.5 CI 95% 2.3-10.5) and considering that the physician does not have enough knowledge (ORa: 3.1 CI 95% 2.4-7.8). Therapeutic adherence was associated with physician availability for care, difficulty with schedules, fear of being seen in the hospital, trust in health personnel, and waiting time.

Background: Polycystic ovary syndrome (PCOS) is a common endocrinopathy that is highly prevalent in women of Indian ethnicity. Clinical practice guidelines do not adequately consider ethnic-cultural differences in the care of women with PCOS. This study aimed to explore ethnic Indian women’s experiences with PCOS diagnosis and management, their concerns and it’s impact on their quality of life (QoL). Methods: Global online survey of ethnic Indian women of reproductive age living with PCOS. Results: Respondents (n=4409) had a mean age of 26.8 (SD 5.5) years and the majority were diagnosed with one or more co-morbidities (anxiety/depression being the most common). Women waited one year on average before seeking treatment following symptom onset. Irregular periods, cysts on the ovaries and excess unwanted facial hair growth were their three major concerns. Weight and emotional concerns had the greatest impact on QoL. One-third did not receive information on long-term complications, appropriate behavioral advice to improve diet or exercise, or emotional support following diagnosis. Among those who received information at diagnosis, the majority were dissatisfied. Conclusions: Ethnic Indian women wait for a considerable time before seeking medical help for PCOS, have poor QoL relating to weight and mental health and are dissatisfied with the information and support provided at diagnosis. These gaps in care should be addressed in clinical practice and future research.

The present study investigates the impact of electrode surface roughness on the electrofreezing of water. This research focuses on how the electrode roughness induced by a laser treatment affects the nucleation and growth of ice crystals under controlled electric fields. To achieve this, a series of experiments were conducted using deionized water samples placed between electrodes with varying surface roughness. The electrodes, fabricated with the Al6061 T6 alloy were structured via the Laser Shock Processing (LSP) method. For this purpose, the pulsed densities during the LSP process were varied from 900 to 2500 pulses/cm2. The increase of the pulse density was correlated to the surface structuring and to the microstructural features and average roughness of the LSP-treated Al6061 alloy. A wavy-like microstructure was induced upon the LSP treatment with average roughnesses between ~ 3.5 and 6 µm at the selected pulse densities. The results indicate that electrode roughness significantly influences the electrofreezing process. Rougher electrodes were found to lower the nucleation temperature compared to smoother ones, suggesting enhanced ice nucleation activity. The findings are attributed to the increased electric field concentration at the asperities of the rough surfaces, which may facilitate the alignment of water molecules and the formation of critical ice nuclei.

The Thermodynamic Formalism provides a rigorous mathematical framework to study quantitative and qualitative aspects of dynamical systems. At its core there is a variational principle and corresponding, in its simplest form, to the Maximum Entropy principle, used as a statistical inference procedure to represent, by specific probability measures (Gibbs measures), the collective behaviour of complex systems. This framework has found applications in different domains of scienThe Thermodynamic Formalism provides a rigorous mathematical framework to study quantitative and qualitative aspects of dynamical systems. At its core there is a variational principle and corresponding, in its simplest form, to the Maximum Entropy principle, used as a statistical inference procedure to represent, by specific probability measures (Gibbs measures), the collective behaviour of complex systems. This framework has found applications in different domains of science, in particular, has been fruitful and influential in neurosciences. In this article, we review how the Thermodynamic Formalism can be exploited in the field of theoretical neuroscience, as a conceptual and operational tool, to link the dynamics of interacting neurons and the statistics of action potentials from either experimental data or mathematical models. We comment on perspectives and open problems in theoretical neuroscience that could be addressed within this formalism.ce, in particular, has been fruitful and influential in neurosciences. In this article, we review how the Thermodynamic Formalism can be exploited in the field of theoretical neuroscience, as a conceptual and operational tool, to link the dynamics of interacting neurons and the statistics of action potentials from either experimental data or mathematical models. We comment on perspectives and open problems in theoretical neuroscience that could be addressed within this formalism.

Gliomas are solid tumors of the Central Nervous System (CNS) that originated from different glial cells. The World Health Organization (WHO) classified these tumors into four groups (I-IV) with increasing malignancy. Glioblastoma (GBM) is the most common and aggressive type of brain tumor classified as a grade IV. GBM are resistant to conventional therapies with poor prognosis after diagnosis even when the Stupp protocol that combines surgery and radiochemotherapy is applied. Nowadays, few novel therapeutic strategies have been used to improve GBM treatment, looking for higher efficiency and lower side effects, but with relatively modest results. The circadian timing system temporally organizes the physiology and behavior of most organisms and daily regulates several cellular processes in organs, tissues, and even in individual cells, including tumor cells. The potentiality of the function of the circadian clock on cancer cells modulation as a new target for novel treatments with a chronobiological basis offers a different challenge that needs to be considered in further detail. The present review will discuss state of the art regarding GBM biology, the role of the circadian clock in tumor progression, and new chrono-chemotherapeutic strategies applied for GBM treatment.

: One of the challenges facing operations management is the design, choice and imple-mentation of action plans adapted to the magnitude of the deviations of the variables of an industrial process. Making conscious and quick decisions is crucial to achieving im-provements in productivity. This will be achieved if the organization's internal and external communication model is strategically designed, considering specific cultural factors and the symmetry or asymmetry required in the communication model. However, how do we organize ourselves and through what channels do we communicate within a production process to generate Big Data that combines data from technologies and the perception, comprehension and projection of experienced humans? Our purpose is to create an operations management model that facilitates the incorporation of technology, allows a prompt response to failures, and promotes the sustainability of processes, without losing sight of its alignment with the organizational strategy. The developed model was implemented in an operations management team, following the guidelines of an action researcher methodology. This resulted in the design of an operations management model and a detailed methodology for its implementation, achieving sig-nificant improvements in the metrics of the current process, making it a success story.

Context: Business Process Automation (BPA) is adopted by organizations to improve efficiency, reduce costs, and increase overall business performance. Traditional Business Process Automation (TBPA) is one of the three approaches employed to develop a BPA. TBPA entails developing BPA in a programming language for integrating the relevant applications in the digital ecosystem to execute a given process. Process variability and practitioner unavailability encumber the requirements specification for TBPA software. Objective: This work proposes a log-based approach for TBPA software to make software more adaptable to process changes and reduce reliance on practitioners, by providing a higher alignment among business process requirements and software architecture, and employing process mining to semi-automatically discover the business process during requirements elicitation. Method: The research conducted a case study in a technology institute to assess the approach and report its results in practice. Results: The results revealed significant improvements in adaptability to business process changes and decreased the time spent with practitioners, and, efficiency in development. The approach also presented limitations, including human intervention to accurately obtain the business process, complexity to trace the process into the architecture, data privacy concerns, and risk of network traffic overload. Conclusion: This research demonstrated the effectiveness of traceability between process requirements and software architecture, as well as the use of logs and process mining. These methods made TBPA software enhanced the software adaptability to changes and minimized the reliance on practitioners during requirements elicitation respectively.

Experimental recordings of the collective activity of interacting spiking neurons exhibit random behavior and memory effects, thus the stochastic process modeling the spiking activity is expected to show some degree of time irreversibility. We use the thermodynamic formalism to build a framework, in the context of spike train statistics, to quantify the degree of irreversibility of any parametric maximum entropy measure under arbitrary constraints, and provide an explicit formula for the information entropy production of the inferred Markov maximum entropy process. We provide examples to illustrate our results and discuss the importance of time irreversibility for modeling the spike train statistics.

The megacities´ sewage creates socioeconomic dependence related to water availability in the nearby zones, especially in countries with hydric stress. The present paper studies the water balance progression of realistic scenarios from 2005 to 2050 in the Mezquital Valley, the receptor of Mexico City untreated sewage since 1886, allowing agriculture irrigation in unsustainable conditions. WEAP model calculated the water demand and supply. Validation was performed with outflows data of the Tula River and simulated three scenarios: 1st) Steady-state based on inertial growth rates, 2nd) Transient scenario concerned climate change outcomes, with minor influence in surface water and hydric stress in 2050; 3rd) Transient scenario perturbed with a planned reduction of 36% in the imported wastewater and the start-up of a massive Water Treatment Plant, allowing drip and sprinkler irrigation since 2030. In the 2005-2017 period, 59% of the agriculture depended on the flood irrigation with megacity sewage. The water balance scenarios evaluated the sectorial supply of the ground and superficial water. Drip irrigation would reduce 42% of agriculture demands, but still does not grant the downflow hydroelectric requirements, aggravated by the lack of wastewater supply since 2030. This research alerts about how present policies compromise future Valley demands.

Perfluoroalkyl and polyfluoroalkyl substances (PFAS) are persistent environmental contaminants of emerging concern, recognized for their toxicity and potential carcinogenic properties. PFAS chemicals are reported to act as endocrine disruptors through their interactions with various nuclear receptors (NRs). Despite their significant impact, comprehensive screenings and detailed analyses of PFAS binding strengths at both the orthosteric and allosteric sites of NRs are currently lacking in the literature. Our study addresses this gap by focusing on the binding interaction analysis of both common and uncommon PFAS with key nuclear receptors such as the vitamin D receptor (VDR), peroxisome proliferator-activated receptor gamma (PPARγ), pregnane X receptor (PXR), and estrogen receptor alpha (ERα). We used advanced docking simulations to screen 9,507 PFAS chemicals at the orthosteric and allosteric sites of the PPARγ, PXR, VDR, and ERα. We verified the accuracy of our docking protocol through multiple docking procedures and validations. The python code used for PFAS chemical screening is deposited in the supplementary file. Among the PFAS assessed at the orthosteric site of the VDR, 21 demonstrated similar binding affinities compared to the calcitriol, while 130 PFAS, exhibited stronger binding affinities than calcitriol. At the VDR allosteric site, where lithocholic acid (LCA) natively binds, 412 PFAS matched the binding energies of LCA, and 2,229 showed even greater binding energies. Similar testing on the PXR, PPARγ, and ERα revealed that the orthosteric site of PPARγ had 1,863 PFAS binding with a higher affinity than native ligand ET1 and 693 PFAS binding at the allosteric site with greater affinity than T35 native ligand. At the PXR orthosteric site, 650 PFAS bound with a greater affinity than native ligand 4WH, while at the allosteric site, 9,148 PFAS demonstrated a greater binding affinity than the known allosetric ligand glycerol. At the orthosteric site of ERα, 40 PFAS displayed binding with a greater affinity than the native ligand estradiol and at the allosteric site, only 8 PFAS exhibited greater binding affinity than coactivator ligand SRC-1. Further, our mixture modeling analysis indicates that PFAS can bind in various combinations with themselves and with endogenous or native ligands simultaneously, to disrupt the endocrine system and cause carcinogenic responses. These findings reveal that PFAS can interfere with nuclear receptor activity by displacing endogenous or native ligands by binding to the orthosteric and allosteric sites. This study elucidates the mechanisms through which PFAS exert their endocrine-disrupting effects, potentially leading to more targeted environmental regulations and therapeutic strategies. Importantly, this study is the first to explore the binding of PFAS at allosteric sites and to model PFAS mixtures at nuclear receptors. Given the high concentration and persistence of PFAS in humans, this study called for the urgent need for further research into the carcinogenic mechanisms of PFAS and the development of intervention strategies that target nuclear receptors. Our ongoing studies extend these findings by further investigating the interactions of PFAS and co-exposed chemicals with nuclear receptors. These investigations are supported by experimental verification, which will enhance our understanding of PFAS broad effects and aid in the design of effective mitigation strategies.

Soarinho Alkaline Intrusion, southeastern Brazil, makes part of the Serra do Mar Igneous Province, and it is composed of alkali feldspar syenite, alkali feldspar trachyte, quartz syenite, and mon-zonite. Geochemical and geochronological analysis of the Soarinho were compared with data from its neighbors Rio Bonito and Tanguá. Zircon U-Pb Laser Ablation ages show that Soarinho is youngest than Rio Bonito and Tanguá. Ages obtained from the monzonite (60 ± 2 Ma), alkali feldspar syenite (58 ± 2 Ma), and quartz syenite (58 ± 2 Ma) are indistinguishable within error. Petrographic and geochemical data show a clear contrast among Soarinho, Rio Bonito, Tanguá, and Lu-Hf isotopic data for the three alkaline intrusions (all negative), point to some similarities in their sources. The data suggest an enriched mantle source for Soarinho; however, an older con-tinental crust contribution cannot be discarded.

Human keratinocytes and melanoma can stick together to form clusters after eight days in co-culture. As in dynamic system concepts, one can consider cluster formation as the system attractor, cell seeding as the initial condition, and density change over time as a path within the basin of attraction. Herein, Cellular Automata, which is a class of Agent-Based Models, and Boolean Networks are discrete modeling methods used in population dynamics such that running the dynamics of cellular automata backward reveals an underlying network in terms of basin of attraction, also known as global dynamics. Thus, we hypothesize that one can estimate the local dynamic of an agent-based model from the basin of attraction of a boolean network. Here, we propose an approach to estimating these agent-based model rules, which consists of comparing the density states within each state transition and reaching a consensus among state transitions belonging to a basin of attraction of a boolean network. The objectives of this study are: (1) to infer a boolean network from the co-culture growth curve; (2) to estimate the rules of agent-based models; and (3) to implement spatial dynamics simulations. The binarization of the growth curve shows high population density after four days; the estimated agent-based model rules were compatible with cell proliferation and migration in agreement with literature, so we had to propose individual rules for survival and death. Spatial dynamics shows that (1) keratinocytes exhibit a higher density in neighborhoods where melanoma is present; (2) the chance of keratinocyte migration increases until the fourth day, then decreases, and the probability of survival increases substantially after four days; and (3) cells with low proliferation capacity die and free space for those with high ones. Our approach suggests that the attractor state of cell co-culture is induced mainly by an increase in keratinocyte migration and survival. Our approach has the potential to offer valuable clues about microenvironmental interactions or configurations that drive population dynamics.

Background: Nutrient supplements are widely used for type 2 diabetes (T2D) yet evidence-based guidance for clinicians is lacking. Methods: We searched the four electronic databases from November 2015–December 2021. The most recent, most comprehensive, high-ranked systematic reviews, meta-analyses and/or umbrella reviews of randomised controlled trials in adults with T2D were included. Data were extracted on study characteristics, aggregate outcome measures per group (glycemic control, measures of insulin sensitivity and secretion), adverse events, and GRADE assessments. Quality was assessed using AMSTAR-2. Results: Twelve meta-analyses and one umbrella review were included. There was very low certainty evidence that chromium, Vitamin C and omega-3 polyunsaturated fatty acids (-3 PUFAs) were superior to placebo for the primary outcome of HbA1c (MD -0.54%, -0.54% and ES -0.27 respectively). Probiotics were superior to placebo for HbA1c (WMD -0.43%). There was very low certainty evidence that Vitamin D was superior to placebo for lowering HbA1c in trials of <6 months (MD -0.17%). Magnesium, zinc, Vitamin C, probiotics and polyphenols were superior to placebo for FBG. Vitamin D was superior to placebo for insulin resistance. Data on safety was limited. Conclusions: Future research should identify who may benefit from nutrient supplementation, safety, and optimal regimens and formulations.

During the last decades, the production systems have developed different strategies to increase their competitiveness in the global market. In a manufacturing and services systems, Lean Manufacturing has been consolidated through the correct implementation of its tools. The present paper presents a case study developed in a Food Packer company where a Simulation Model was considered as an alternative to reduce the waste time generated by the poor distribution of operations and transportation areas for a product within the factory. As a matter of fact, the company has detected problems on the layout distribution that prevents to fulfill the market demand. In addition, the principal aim was to create a simulation model to test different hypothetical scenarios and alternative designs for the layout distribution without modifying its facilities. Moreover, the implemented methodology was based on classical models of simulation projects and a compendium of the manufacturing systems optimization by simulation process used during the last ten years. Also, a mathematic model supported by the Promodel ® simulation software was developed considering the company characteristics; along with the model development, it was possible to compare the production system performance from the percentage of used locations, the percentage of resources utilization, the number of finished products, and the level of Work in Process (WIP). Finally, the verification and validation stages were performed before running the scenarios in the real production area. The results generated by the implementation of the project represent an increase of 68% in the production capacity and a reduction of 5% in the WIP. In addition, both outcomes are associated with the resources management, which were reassigned to other production areas.

The performance of 5 forecasting models was investigated for predicting nursery mortality using the master table built for 3,242 groups of pigs (~ 13 million animals) and 42 variables, which concerned the pre-weaning phase of production and conditions at placement in growing sites. After training and testing each model’s performance through cross-validation, the model with the best overall prediction results was the Support Vector Machine model in terms of Root Mean Squared Error (RMSE=0.406), Mean Absolute Error (MAE=0.284), and Coefficient of Determination (R2=0.731). Subsequently, the forecasting performance of the SVM model was tested on a new dataset containing 72 new groups, simulating ongoing and near real-time forecasting analysis. Despite a decrease in R2 values on the new dataset (R2=0.554), the model demonstrated high accuracy (77.78%) for predicting groups with high (5&gt;%) or low (5&lt;%) nursery mortality. This study demonstrated the capability of forecasting models to predict the nursery mortality of commercial groups of pigs using pre-weaning information and stocking conditions variables collected post-placement in nursery sites.

Abstract: Chemical burns are one of the most dangerous and aggressive types of burns as they can cause significant tissue damage, leading to pain, inflammation, necrosis, and scarring. We present a burn case report associated with the use of Acellular Dermal Matrix (MatriDerm® MedSkin Solution Dr. Suwelack AG, Billerbeck, Germany) for the reconstruction of a Hallux after the patient was mistakenly administered intramuscular Nitric Acid at another institution. The patient presented with a third degree burn that compromised the medial aspect of the hallux’s skin, the distal phalanx and nail bed. Early debridement was performed, and Negative Pressure Wound Therapy (NPWT VAC, 3M, US) was used to preserve and promote tissue viability. Eight days later, the patient was taken to the OR, and Acellular Dermal Matrix and split-thickness skin graft were used to reconstruct her right hallux’s defect. The patient achieved adequate clinical evolution and was discharged with complete reconstruction of the burned area. Acellular Dermal Matrix proved to be an important and viable option for reconstructive surgery after a chemical burn, and further studies are warranted to ensure its routine usage in this kind of lesions. Keywords: chemical burn, acellular matrix, hallux reconstruction, NPWT

Background: Spinal pain is highly prevalent and in Spain it produces a very high economic cost and the scientific evidence supporting treatments shows low to moderate evidence for exercise. Therefore, the aim of this study was to assess the effectiveness of a therapeutic group exercise protocol in reducing pain intensity and disability in patients with spinal pain in primary health care setting. Methods: A total sample of 149 patients who suffered from chronic non-specific spinal pain. Patients received a therapeutic exercise protocol, including exercises of auto-mobilization of the neck and lumbar regions, as well as core stabilization exercises. Pain intensity and disability were evaluated before and after the therapeutic exercise protocol. Results: Statistically significant differences (P&lt;0.05) were shown for pain intensity and disability of patients with neck and low back pain with an effect size from moderate to large. Conclusions: A therapeutic exercise protocol may provide beneficial effects on disability and pain intensity in patients with chronic non-specific spinal pain, including neck and low back pain conditions. Clinicians should consider the use of self-administered exercise protocols, demonstrate great effectiveness, and be less costly.

While deforestation rates decline globally they are rising in the Western Amazon. Artisanal-scale gold mining (ASGM) is a large cause of this deforestation and brings with it extensive environmental, social, governance, and public health impacts, including large carbon emissions and mercury pollution. Underlying ASGM is a broad network of factors that influence its growth, distribution, and practices such as poverty, flows of legal and illegal capital, conflicting governance, and global economic trends. Despite its central role in land use and land cover change in the Western Amazon and the severity of its social and environmental impacts, it is relatively poorly studied. While ASGM in Southeastern Peru has been quantified previously, doing so is difficult due to the heterogeneous nature of the resulting landscape. Using a novel approach to classify mining that relies on a fusion of CLASlite and the Global Forest Change dataset, two Landsat-based deforestation detection tools, we sought to quantify ASGM-caused deforestation in the period 1984–2017 in the southern Peruvian Amazon and examine trends in the geography, methods, and impacts of ASGM across that time. We identify nearly 100,000 ha of deforestation due to ASGM in the 34-year study period, an increase of 21% compared to previous estimates. Further, we find that 10% of that deforestation occurred in 2017, the highest annual amount of deforestation in the study period, with 53% occurring since 2011. Finally, we demonstrate that not all mining is created equal by examining key patterns and changes in ASGM activity and techniques through time and space. We discuss their connections with, and impacts on, socio-economic factors, such as land tenure, infrastructure, international markets, governance efforts, and social and environmental impacts.

A Robust Optimization framework with original concepts and fundamentals also admitting a fusion of ideals from relative regret models and static robust optimization, containing conservatism concepts is disclosed. The algorithm uses a fine-tune strategy to tune the model so the robustness and a target ideality can be mutually achieved with a specified risk. The framework comprises original concepts, a mathematical approach and an algorithm. The statistical treatment of the data with the original concepts from the framework make it able to make short, middle or long-term decision-making setting. The framework has high tractability since the algorithm forces the creation of a setting that makes a robust optimization with the specified risk. The framework can be applied in linear and nonlinear mathematical models since that the objective function is monotonic in the domain of the active convex region. Several examples are solved to best understand the framework and all results demonstrated high tractability and performance. There is a wide range of applications. Along all the text, there is a profound discussion about its philosophy, objective, original concepts, fields of application, statistical and probabilistic fundamentals.

We consider the maximum entropy Markov chain inference approach to characterize the collective statistics of neuronal spike trains, focusing on the statistical properties of the inferred model. We review large deviations techniques useful in this context to describe properties of accuracy and convergence in terms of sampling size. We use these results to study the statistical fluctuation of correlations, distinguishability and irreversibility of maximum entropy Markov chains. We illustrate these applications using simple examples where the large deviation rate function is explicitly obtained for maximum entropy models of relevance in this field.

The main challenges in oil platforms are how to define optimal setpoints and decision-making for controlling variables due to many existing dynamical production uncertainties while conceding safe operation and minimizing discharge to sea and atmosphere without killing plantwide inventory. A novel scheduling model to optimize the whole essential units of an oil platform production gathering topside and subsea variables is disclosed. A proper topside and subsea scheduling model enables and creates harmony between optimal production, supply chain, costs, and market dynamics, satisfying demands, environmental and operations constraints leading to stability. The interest of the present research lies in determining the optimal topside and subsea operational settings and decision-making, establishing maximum E&P performance and production control setpoints while predicting and manipulating reservoir lifespan and its revitalization. This objective is attained through a novel multiperiod large-scale model for the planning and operational production scheduling and model predictive control (MPC) in oil platforms complying with sustainability, profitability, platform design capacities, and offloading of oil and gas to supply chains or to pipeline exportation. The present model details heat and mass transfer, PVT, flow profiles along a planning horizon and can be used to any oil platform since comprises all the essential unit operations for oil, gas, CO₂, H₂S and water. The model maximizes the total oil production over any planning horizon. The model is versatile, and decision-making can be either linear or nonlinear but rather a MILP or LP as best choice on optimizing large-scale systems. If the model is applied with auto rescheduling on site within variable hours or minutes, it becomes a real-time optimization schedule approach. Due to its high-velocity performance and robustness, a novel multi-objective function strategy, acting as an LP generic plantwide MPC with industrial scope to maximize production while controlling the process is presented, and as an example is here used to control slug flow to avoid equipment trips and inventory instability, at the same time production is maximized. The output from the decision-making was compared to actual plant data, and the results proved compliance to the design capacity with process safety and sustainability. Comparing to official Brazil's government data for oil, the case study showed superiority to the same size platforms, like FPSOs P-75 and MV32, e.g., more than 101.5% more capacity to produce oil in beginning of campaign after first oil, and 10.5% during campaign. The present work indicates that: 1) the production of millions of barrels is being delayed or left aside; 2) not scheduling production harms the environment and diminish process safety; 3) not scheduling production can create stochastic supply chain deliveries instead of organizing it by deterministic offloading days; 4) scheduling is essential to manipulate, revitalize and monitor reservoir's pressure and content under uncertainty; 5) the oil platform can be automatic optimized by a plantwide MPC reducing human activity/dependency; 6) scheduling gives more transparency to stakeholders and contractors by forecasting business data and capability, and can design, develop or enable new businesses.

Background: Underreporting of Visceral Leishmaniasis (VL) in India remains a problem to public health controls. Effective and reliable surveillance systems are critical for monitoring disease outbreaks and public health control programs. However, in India, government surveillance systems are affected by levels of scarcity in resources and therefore, uncertainty surrounds the true incidence of asymptomatic and clinical cases, affecting morbidity and mortality rates. The State of Bihar alone contributes up to the 40\% of the worldwide VL cases. The inefficiency of surveillance systems occurs because of multiple reasons including delay in seeking health care, accessing non-authentic health care clinics, and existence of significant asymptomatic self healing infectious cases. This results in a failure of the system to adequately report true transmission rates and number of symptomatic cases that have sought medical advice (thus, high underreporting of cases). Objectives and Methods: There are several methods to estimate the extent of underreporting in the surveillance system. In this research, we use a mathematical dynamic model and two different types of data sets, namely, monthly incidence for 2003-2005 and yearly incidence from 2006-2012 from the Bihar's 21 most VL affected districts out of its 38 districts. The goals of the study are to estimate critical metrics to measure level of transmission and to evaluate the estimation process between the two data sets and 21 districts. In particularly, our focus is on (i) estimating infection transmission potential, underreporting level in incidence and proportion of self-healing cases, (ii) quantifying reproduction number of the$R_0$, and (iii) comparing underreporting incidence levels and proportion of self-healing cases between the two periods 2003-2005 and 2006-2012 and between 21 districts. Results: Our research suggests that the number of asymptomatic individuals in the population who eventually self-heal may have a significant effect on the dynamics of VL spread. The estimated mean self-healing proportion (out of all infected) is found to be $\sim 0.6$ with only 7 out of 21 affected districts having self-healing proportion less than $0.5$ for both data sets. The estimated mean underreporting level is at least $64$\% for the state of Bihar. The estimates of the basic reproduction numbers obtained are similar in magnitude for most of the districts, being in the range of (0.88, 2.79) and (0.98, 1.01) for 2003-2005 and 2006-2012, respectively. Conclusions: The estimates for the two types (monthly and yearly) of temporal data suggest that monthly data are better for estimation if less number of data points are available, however, in general, using such data set results in larger variances in parameters as compared to estimates obtained through aggregated yearly data. Estimated values of transmission related metrics are lower than those obtained from earlier analyses in the literature, and the implications of this for VL control are discussed. The spatial heterogeneity in these control metrics increases the risk of epidemics and makes the control strategies more complex.

The current design of reinforcement learning methods demands exhaustive computing. Algorithms such as Deep Q-Network achieved outstanding results in the development of the area. However, the need for thousands of parameters and training episodes is still a problem. Thus, this document proposes a comparative analysis of the Q-Learning algorithm (the inception to create Deep Q Learning) and our proposed method termed M-Learning. The comparison among algorithms using Markov decision processes with delayed reward as a general testbench framework. Firstly, a full description of the main problems related to implementing Q-Learning, mainly about its multiple parameters. Then, the foundations of our proposed heuristic with its formulation and the whole algorithm were reported in detail. Finally, the methodology chosen to compare both algorithms was to train the algorithms in the Frozen Lake environment. The experimental results and an analysis of the best solutions found that our proposed algorithm highlights the differences in the number of episodes necessary and their standard variations. The code will be available on a GitHub repository once the paper is published.

Introduction of exotic species in new areas through anthropic action is one of the major problems that can affect biodiversity. Branchiomma luctuosum is known for its highly invasive potential and the actual occurrence of species commonly associated with port activity areas is an extra evidence that this anthropogenic activity should not be underestimated. In order to develop suitable molecular markers for future studies on colonization routes and population dynamics of the invading individuals of B. luctuosum, nine highly polymorphic microsatellite loci were isolated and their polymorphism levels were evaluated. These loci showed a range of number of alleles per locus from five to ten and all loci had a high level of genetic diversity, and exhibited significant heterozygote deficiencies probably due to the presence of null alleles. Significant deviations from the Hardy-Weinberg equilibrium were detected at several loci and most of them were related to a heterozygous deficit. Heterozygous deficiency can be expected in this case due to the biology and history of this invasive species, in relation to its recent introduction in Brazilian coast and possible action of multiple introductory events.

Patients with advanced chronic liver disease (ACLD) or cirrhosis undergoing surgery have an increased risk of morbidity and mortality in contrast to the general population. Retrospective, observational study of ACLD patients to evaluate the predictive capacity of previous surgical risk scores in a European cohort of patients. ACLD was defined by the presence of thrombocytopenia <150.000/uL and splenomegaly; AST-to-Platelet Ratio Index >2; nodular liver edge by ultrasound; transient elastography >15 kPa and/or signs of portal hypertension. We assessed variables related to 90-day mortality and the discrimination and calibration of current surgical scores (Child-Pugh, MELD-Na, MRS, NSQIP, and VOCAL-Penn). Only patients with ACLD and major surgeries included in VOCAL-Penn were considered (n=512). The mortality rate at 90 days after surgery was 9.8%. Baseline disparities between H. Mar and VOCAL-Penn cohorts were identified. Etiology, obesity, or platelet count not were associated with mortality. The VOCAL-Penn showed the best discrimination (C-statistic90D= 0.876) and overall predictive capacity (Brier90D= 0.054) but calibration was not excellent in our cohort. VOCAL-Penn was suboptimal in patients with diabetes (C-statistic30D= 0.770), without signs of portal hypertension (C-statistic30D= 0.555), or with an abdominal wall (C-statistic30D= 0.608) or urgent (C-statistic180D= 0.692) surgeries. Our European cohort has shown a mortality rate after surgery similar to those described in American studies. However, some variables included in the VOCAL-Penn score were not associated with mortality, and VOCAL-Penn’s discriminative ability decreases in patients with diabetes, without signs of portal hypertension, and with abdominal wall or urgent surgeries. These results should be validated in larger multicenter and prospective studies.

Some of the most recent advances in enzymatic glycosylation processes focused on the production of important bioactive compounds have been analyzed. The applicability of different enzymes such as glycosidases, glycosyltransferases, glycophosphorylases and glycosynthases have been de-scribed around the review article considering their advantages and disadvantages of these biocat-alysts in the stereoselective and regioselective synthesis of different types of glycosylated mole-cules, phenolic and aliphatic alcohols, oligosaccharides, polysaccharides, glycoderivatives, glyco-peptides and glycoproteins with a clear focus on food and pharmaceutical chemistry. Therefore, these approaches combining the use of different catalytic systems, the improvement of tools such as immobilization technology, or chemical or genetic modification to improve the synthesization in the glycosylation process could be a very useful tool in a continuous biotechnological advance.

Water scarcity is a key challenge to global development. In Brazil, the Sao Francisco River Basin (SFB) has experienced water scarcity problems because of decreasing streamflow and increasing demands from multiple sectors. However, the drivers of decreased streamflow, particularly the potential role of surface-groundwater interaction, have not been yet investigated. Here, we assess long-term trends in baseflow, quickflow, and streamflow of the SFB during 1980–2015 and constrain the most likely drivers of observed decreases through trend analysis of precipitation (P), evapotranspiration (ET), and terrestrial water storage change (TWS). We found that over 82% of the observed decrease in streamflow can be attributed to a significant decreasing baseflow trend (< -20 m3 s-1 y-1) along the SFR with spatial agreement between decreased baseflow, increased ET, and irrigated agricultural land. We also noted a decrease in TWS across the SFB with trends exceeding -20 mm y-1. Overall, our findings indicate that decreasing groundwater contributions (i.e., baseflow) is providing the observed reduction in total SFR flow. A lack of significant P trends indicates that only P variability likely has not caused the observed baseflow reduction, mainly in the Middle and Sub-middle SFB. Therefore, groundwater and surface withdrawals may be likely a driver of water scarcity over the SFB.

Machine learning (ML) has a large capacity to learn and analyze a large volume of data. This study aimed to train different algorithms to discriminate between healthy and pathologic corneal images by evaluating digitally processed spectral-domain optical coherence tomography (SD-OCT) corneal images. A set of 22 SD-OCT images belonging to a random set of corneal pathologies was compared to 71 healthy corneas (control group). A binary classification method was applied; three approaches of ML were used. Once all images were analyzed, representative areas from every digital image were also processed and analyzed for a statistical feature comparison between healthy and pathologic corneas. The best performance was obtained from transfer learning - support vector machine (TL-SVM) (AUROC = 0.94, SPE 88%, SEN 100%) and transfer learning – random forest (TL- RF) method (AUROC = 0.92, SPE 84%, SEN 100%), followed by convolutional neural network (CNN) (AUROC = 0.84, SPE 77%, SEN 91%) and random forest (AUROC = 0.77, SPE 60%, SEN 95%). The highest diagnostic accuracy in classifying corneal images was achieved with the TL-SVM and the TL-RF models. In image classification, CNN was a strong predictor. This pilot experimental study developed a systematic mechanized system to discern pathologic from healthy corneas.

The COVID-19 pandemic period, from 2020 - 2022 had a significant impact on maternal infant health with mothers impacted more than their infants. We questioned whether there have been any lingering effects from the pandemic. We examined intermediate and long-term pandemic effects of maternal and neonatal outcomes before, during and after the COVID-19 pandemic period. We reviewed mother-infant pairs from three epochs: 1) the pre-COVID-19 period, 2) the COVID-19 pandemic period, and 3) the post-pandemic period. The Case Mix Index (CMI) for the neonates from all 3 epochs were detailed. Post-pandemic we noted a rising trend of LGA infants (10%), and an increase in SGA infants (13%). For women in 2023 we noted an increase in hypertension, preeclampsia, diabetes, and a higher BMI than the pre- pandemic period. There have also been more congenital anomalies (9%), and neonatal CMI increased in the post-pandemic period. Well after the pandemic period, maternal-infant health continues to be affected. For women, increase in hypertension and diabetes during pregnancy is concerning. For the infants, being LGA or SGA may have long-term consequences. The post-pandemic increase in infants with congenital anomalies compared to the pre-pandemic era is an area that needs ongoing review.

Background: Nursing home residents (NHRs) have special needs and may experience reduced functionality, higher sedentary behavior time (SBT) and decreased physical activity (PA). This study aimed to characterize NHRs based on SBT, PA, and functional performance (FP), and to identify associations between these factors. Methods: Cross-sectional study with 65 NHRs aged ≥60, evaluated by accelerometer (SBT, PA) and the following tests: Timed Up and Go (TUG), Short Physical Performance Battery (SPPB), Barthel Index (BI), and Mini-Mental State Examina-tion (MMSE). Health-related variables and anthropometry were assessed. The FP (TUG, SPPB, BI), SBT, PA intensities were used for K-means clustering analysis. Results: The cluster analysis identified: C1 – better FP, shorter SBT, and longer time in PA intensities; C2 - lower FP, longer SBT, and shorter time in PA. In addition, C2 were older, with lower MMSE, lower body mass index, and walking aids use. The SBT showed a negative weak correlation with BI. The moderate PA (MPA) was moderately correlated with the SPPB and strongly correlated with the TUG and BI. Conclusions: MPA is strongly associated with better FP and independence. NHRs have dif-ferent physical and cognitive profiles, which indicates the need for personalized strategies to prevent disability and increase PA.

Advances in communication technologies have made the interaction of small devices, such as smartphones, wearables, and sensors, scattered on the Internet, bringing a whole new set of complex applications with ever greater task processing needs. These Internet of Things (IoT) devices run on batteries with strict energy restrictions. They tend to offload task processing to remote servers, usually to Cloud Computing (CC) in datacenters geographically located away from the IoT device. In such a context, this work proposes a dynamic cost model to minimize energy consumption and task processing time for IoT scenarios in Mobile Edge Computing environments. Our approach allows for a detailed cost model, with an algorithm called TEMS that considers energy, time consumed during processing, the cost of data transmission, and energy in idle devices. The task scheduling chooses among Cloud or Mobile Edge Computing (MEC) server or local IoT devices to better execution time with lower cost. The simulated environment evaluation saved up to 51.6% energy consumption and improved task completion time up to 86.6%.

Biologic scaffolds have become an attractive approach for repairing the infarcted myocardium and have been shown to facilitate constructive remodeling in injured tissues. This study aimed to investigate the possible utilization of bacterial cellulose membrane patch containing cocultured cells to limit the myocardium's post-infarction pathology. Myocardial infarction was induced by ligating the left anterior descending coronary artery in 45 Wistar rats, and patches with or without cells were attached to the hearts. After one week, the animals underwent echocardiography for assessing ejection fraction and left ventricular end-diastolic and end-systolic volumes. Following the patch formation, cocultured cells retained viability of >90% over 14 days in culture. The patch was applied to the myocardial surface of the infarcted area after staying 14 days in culture. Interestingly, the bacterial cellulose membrane without cellular treatment showed higher preservation of cardiac dimensions; however, we did not observe improvement in the left ventricular ejection fraction of this group compared to coculture treated membranes. Our results demonstrated an important role for bacterial cellulose in supporting cells known to produce cardioprotective soluble factors and may thus provide effective future therapeutic outcomes for patients suffering from ischemic heart disease.

This paper presents the results of aerodynamical performance research focused on maintaining the thermal comfort and increasing the energy efficiency of a typical social housing unit located in a high-density urban area. Bioclimatic design strategies are used to develop a sustainable and economic technology in existing housing clusters in Mexico City. A full-scale prototype, built on campus facilities, was used to study the flow conditions around the design. All scaled prototypes implement similar criterion. Furthermore, a scaled prototype is evaluated within a low speed wind tunnel installation. Additionally, numerical simulations were performed at transient state based on previous physical measurements and historical local climatic conditions to determine preferable modifications.

The integration of diverse distributed generation (DG) units, encompassing both Renewable Energy Sources (RES) and non-RES technologies delves into voltage levels, current distributions, and power flows, aiming to optimize and effectively manage the distribution network. An RES-based DGs such as photovoltaic systems and wind turbines, alongside non-RES units like fuel cells and micro turbines. This study proposes a hybrid approach the Multi-Objective Genetic Algorithm - Grey Wolf Optimizer (MOGA-GWO). By merging the strengths of multi-objective genetic algorithms with the efficiency of the Grey Wolf Optimizer, this advanced algorithm seeks semi-optimal solutions for multi-objective optimization problems. The algorithm aims to improve convergence speed without compromising solution quality, offering a promising solution for optimizing the characteristics of DG and RES integration in distribution networks compared to Cuckoo Search and Simulation Annealing Techniques. Key algorithmic operations include individual representation, initialization, fitness function computation, selection, crossover, mutation, and ending conditions. The DG optimal power flow problem is explored with a focus on minimizing generation costs, improving voltage profiles, minimizing losses, enhancing reliability, integrating renewable energy, reducing environmental impact, managing congestion, and ensuring compliance with operational constraints. Beyond traditional considerations, the study emphasizes neglected objectives and constraints, such as cyber-security concerns, real-time operation, regulatory frameworks, social acceptance, lifecycle environmental impact, grid resilience, data privacy, aging infrastructure compatibility, and economic viability.

One way to increase overall natural gas engine efficiency is to transform exhaust waste heat into useful energy by means of a bottoming cycle. Organic Rankine cycle (ORC) is a promising technology to convert medium and low grade waste heat into mechanical power and electricity. This paper presents an energy and exergy analysis of three ORC-Waste heat recovery configurations by using an intermediate thermal oil circuit: Simple ORC (SORC), ORC with Recuperator (RORC) and ORC with Double Pressure (DORC), and Cyclohexane, Toluene and Acetone have been proposed as working fluids. An energy and exergy thermodynamic model is proposed to evaluate each configuration performance, while available exhaust thermal energy variation under different engine loads was determined through an experimentally validated mathematical model. Additionally, the effect of evaportating pressure on net power output , absolute thermal efficiency increase, absolute specific fuel consumption decrease, overall energy conversion efficiency, and component exergy destruction is also investigated. Results evidence an improvement in operational performance for heat recovery through RORC with Toluene at an evaporation pressure of 3.4 MPa, achieving 146.25 kW of net power output, 11.58% of overall conversion efficiency, 28.4% of ORC thermal efficiency, and an specific fuel consumption reduction of 7.67% at a 1482 rpm engine speed, a 120.2 L/min natural gas Flow, 1.784 lambda, and 1758.77 kW mechanical engine power.

Despite the best efforts in air-purification, airborne infectious diseases do and will continue to spread due to continuous emission of bioaerosols by the host/infected person. To tackle the rapid spread of airborne infectious diseases, a shift in focus from air-purification to bioaerosol disinfection/ decontamination is urgently needed. In this work, we studied a cold plasma ionizer (CPI) and electrostatic precipitator (ESP)-coupled CPI (CPI-ESP) for disinfection and cleaning of bioaerosols. Using porcine respiratory coronavirus (PRCV) and E. coli in a testing chamber, we demonstrated that CPI coupled with ESP is an effective technology for inactivating aerosolized microorganisms and microorganisms spread on surfaces. In addition, we have demonstrated the efficiency of a CPI-ESP coupled device for disinfection of naturally occurring airborne microbials in a few indoor settings (i.e., an living room, a discussion room, a schoolroom and an office) to determine the treatment duration- and human activity-dependent efficacy. To understand the disinfection mechanism, we conduced fluorescence microscopy study to reveal different degree of bacteria cell membrane damage under CPI treatment.

Despite advances in the reliability of sensory devices used by drones, the integrity of information from some devices is still considered an obstacle to ensuring successful flight plans. It is widely known that GNSS can suffer attacks or lose the signal from satellites, which can cause the drone to fail to complete its flight plan. In this context, we propose SiaN-VO, a Siamese network for visual odometry prediction. In our initial studies, this approach proved satisfactory for flights in static conditions (speed and height). Although interesting, these conditions do not reflect real flight conditions. In this sense, we have advanced our studies to propose the SiaN-VO, which fuses data from different sensors to enable displacement predictions to be made in dynamic flight conditions.

Keyhole neurosurgery implies reaching a target area inside the brain through an entry point specified by the neurosurgeon. In order to avoid complications, a risk assessment procedure must be done to establish the minimum risk trajectory from the entry point to the target area. The neurosurgeon establishes the risk values for the brain structure according to the type of intervention. The preset brain structure risk value is used to assess the risk value for each voxel of the brain. This paper proposes an improved risk assessment methodology based on the sum of N maximum risk values for each voxel. Then, risk assessment for a trajectory is done by adding the risk of all voxels that are part of the path. The safest trajectory is defined as the trajectory with the lower risk. Our proposed search trajectory methodology includes a Genetic Algorithm (GA) for finding the safest trajectories. The use of a GA drastically reduces the number of trajectories to analyze, speeding up the planning procedure. The achieved results were qualified by expert neurosurgeons as satisfactory. Our proposed method allows neurosurgeons to calibrate the surgical planning system by allowing them to establish the risk brain structure and the risk value for each structure.

Stroke remains a major cause of death and disability in the United States and around the world. Solid safety and efficacy profiles of novel stroke therapeutics have been generated in the laboratory, but most failed in clinical trials. Investigations into the pathology and treatment of the disease remain a key research endeavor in advancing scientific understanding and clinical applications. In particular, cell-based regenerative medicine, specifically stem cells transplantation, may hold promise as stroke therapy because grafted cells and their components may recapitulate the growth and function of the neurovascular unit, which arguably represents the alpha and omega of stroke brain pathology and recovery. Recent evidence has implicated mitochondria, organelles with a central role in energy metabolism and stress response, in stroke progression. Recognizing that stem cells offer a source of healthy mitochondria, potentially transferrable into ischemic cells, may provide a new therapeutic tool. To this end, deciphering cellular and molecular processes underlying dysfunctional mitochondria may reveal innovative strategies for stroke therapy. Here, we review recent studies capturing the intimate participation of mitochondrial impairment in stroke pathology, and showcase promising methods of healthy mitochondria transfer into ischemic cells, to critically evaluate the potential of mitochondria-based stem cell therapy for stroke.

Studies on the influence of dietary components and their effects are fundamental for nutrigenomics, or the study of how nutrients can be cellular sensors, how they affect biological processes and gene expression in different tissues. Lipids are an important source of fatty acids (FA) and energy and are fundamental to biological processes and influence the regulation of transcription. Pigs are excellent model to study nutrigenomics, particularly lipid metabolism because the deposition and composition of FA in their tissues reflect the composition of FA in their diet. Recent studies show that FA supplementation is important in production systems, such as growing and finishing pigs, as it can improve the energy value of the feed, help reduce costs, improve animal welfare, and influence the nutritional value of the meat. Studies show that oleic (OA), linoleic (LA), docosahexaenoic (DHA), and eicosapentaenoic (EPA) acids are associated with the regulation of transcription in tissues such as muscle, liver, adipose tissue, and brain. Other studies indicate that EPA and DHA are associated with changes in specific signaling pathways, altering gene expression and biophysical properties of membranes. This review, therefore, focuses on the current knowledge of the effects of dietary FA on production traits and gene expression.

Any effort to combat corruption can benefit from an examination of past and projected worldwide trends. In this paper, we forecast the level of corruption in countries by integrating an artificial neural network modeling and time series analysis. The data were obtained from 113 countries from 2007 to 2017. The study is carried out at two levels: (a) global level where all countries are considered as a monolithic group; and (b) cluster level, where countries are placed into groups based on their development-related attributes. For each cluster, we use the findings from our previous study on the cluster analysis of global corruption using machine learning methods that identified the four most influential corruption factors, and we use those as independent variables. Then, using the identified influential factors, we forecast the level of corruption in each cluster using a nonlinear autoregressive recurrent neural network with exogenous inputs (NARX), an artificial neural network technique. The NARX models were developed for each cluster, with the objective function in terms of the Corruption Perceptions Index (CPI). For each model, the optimal neural network is determined by finetuning the hyperparameters. The analysis was repeated for all countries as a single group. The accuracy of the models is assessed by comparing the mean square errors (MSE) of the time series models. The results suggest that the NARX artificial neural network technique yields reliable future values of CPI globally or for each cluster of countries. This can assist policymakers and organizations in assessing the expected efficacies of their current or future corruption control policies from a global perspective as well as for groups of countries.

The unfolded band structure and optical properties of Cu-doped KCl crystals were computed by first principles within the framework of density functional theory, implemented in the ABINIT electronic structure package utilizing pseudopotential approximation and a plane-wave basis set. From a theoretical point of view, Cu substitution into pristine KCl crystals requires calculation by the supercell (SC) method. This procedure shrinks the Brillouin zone, resulting in a folded band structure that is difficult to interpret. To solve this problem and gain insight into the effect of copper ions (Cu+) on electronic properties, the band structure of SC KCl:Cu was unfolded to make a direct comparison with the band structure of the primitive cell (PC) of pristine KCl. To understand the effect of Cu substitution on optical absorption, we calculated the imaginary part of the dielectric function of KCl:Cu through a sum-over-states formalism and broke it down into different band contributions by partially making an iterated cumulative sum (ICS) of selected valence and conduction bands. Consequently, we identified those interband transitions that give rise to the absorption peaks due to the Cu+ ion. These transitions involve valence and conduction bands formed by the Cu-3d and Cu-4s electronic states

In these times, consumers mistakenly believe that the terms “expiration date” and “best before” found on packages only convey information about food safety. Consequently, a misunderstanding of these terms contributes to food waste. In this sense, the understanding and behavior of the con-sumer with respect to the two terms were evaluated; in addition, the consumer's perception of the health risks of consuming expired food was analyzed. The research was carried out with the population of the sector of Lurigancho-Chosica, Lima – Peru; sample size was 555 participants. An online survey was sent to consumers over 18 years of age, from different sociodemographic and socioeconomic conditions. In general terms, it was found that 45% (p <0.01) consider that both terms mean the same thing, this result is a problem for food safety. The 67% (p <0.05) and 45% (p <0.05) correctly defined the first and second terms, respectively; however, the behavior is not coherent with the understanding of the terms. In addition, irrational and dangerous behavior toward expired food was evidenced, i.e., they consume expired food - "expiration date", and discard expired food - "best before". Finally, the health risks they perceived from consuming expired foods of both terms were: upset stomach, vomiting, gas, intoxi-cation, and malnutrition; these perceptions are erroneous and unfounded. Sociodemographic and socioeconomic conditions influence the under-standing, behavior, and perception of health risks. Therefore, in general lines, the level of understanding of the terms was low (p<0.01), the be-havior was inappropriate toward expired food (p<0.01), and the percep-tion of the health risk of consuming expired food was incorrect (p<0.01).

In this work, we propose a method to measure planar temperature fields of fluids flow. We used a focusing schlieren technique together with a calibration procedure to fulfill such purpose. The focusing schlieren technique uses an off-axis circular illumination to reduce the depth of focus of the optical system. The calibration procedure is based on the relation of the intensity level of each pixel of a focused schlieren image to the corresponding cutoff grid position measured at the exit focal plane of the schlieren lens. The method is applied to measure planar temperature fields of the hot air issuing from a 10 mm diameter nozzle of a commercial Hot Air Gun Soldering Station Welding. Our tests are carried out at different temperature values and different planes along the radial position of the nozzle of the Hot Air Gun Soldering Station Welding. The temperature values obtained experimentally are in agreed with those obtained with a thermocouple.

Over the years, chitosan has been the subject of numerous studies and has gained significant popularity as a biomaterial due to its various characteristics, including biocompatibility, biodegradability, and bioactivity. In this work, chitosan fibres surface was modified with ursolic acid to improve their antibacterial properties by wet impregnation method. Five specimens of chitosan fibres were immersed in ursolic acid (UA) solution for varying immersion times of 1, 2, 4, 6, and 8 hours. Characterization was carried out by means of FTIR, SEM, UV-Vis spectroscopy; the results indicated an ongoing chemical reaction between chitosan and ursolic acid resulting in changes to the chemical structure. After 2 hours, the absorbance ratio remained constant; suggesting that the reaction had reached completion and the chemical structure of the sample remained stable. Antibacterial tests were performed on the resulting chitosan fibres against two bacterial strains. The fibres without ursolic acid did not exhibit any noteworthy antibacterial activity against either strain. However, the chitosan fibres modified with ursolic acid showed significant and almost strong antibacterial activity against the Gram-positive strain, S. aureus. These results suggest that chitosan fibres modified with ursolic acid could have potential applications as antibacterial materials, particularly against Gram-positive bacteria.

GIGANTEA (GI) is a gene involved in multiple biological functions, which were analysed and are partially conserved in a series of mono- and dicotyledonous plant species. The identified biological functions include control over the circadian rhythm, light signalling, cold tolerance, hormone signalling and photoperiodic flowering. The latter function is a central role of GI, as it involves a multitude of pathways, both dependent and independent of the gene CONSTANS(CO) as well as on the basis of interaction with miRNA. The complexity of gene function of GI increases due to the existence of paralogs showing changes in genome structure as well as incidences of sub- and neofunctionalization. We present an updated report of the biological function of GI, integrating late insights into its role in floral initiation, flower development and flower volatile production.

Drowsiness detection is an important task in road safety and other areas that require sustained attention. In this article, an approach to detect drowsiness in drivers is presented, focusing on the eye region, since eye fatigue is one of the first symptoms of drowsiness. The method used for the extraction of the eye region is Mediapipe, chosen for its high accuracy and robustness. Three neural networks were analyzed based on: InceptionV3, VGG16 and ResNet50V2 that implement deep learning. The database used is NITYMED, which contains videos of drivers with different levels of drowsiness. The three networks were evaluated in terms of accuracy, precision and recall in detecting drowsiness in the eye region. The results of the study show that all three convolutional neural networks have high accuracy in detecting drowsiness in the eye region. In particular, the Resnet50V2 network achieved the highest accuracy, with a rate of 99.71% on average. For better visualization of the data, the Grad-CAM technique is used, with which we get a better understanding of the performance of the algorithms in the classification process.

In this article, we show theoretically and experimentally the formation of spin-waves band gaps in a magnonic crystal that was implemented by the deposition of periodic micro-structured strips of magnetite nanoparticles. A theoretical model describing the spectra of the transmitted spin-waves bandgaps is proposed. This is achieved using a simple model based on microwave transmission line theory and considering the presence of micro-structured strips of magnetite nanoparticles on the surface. Such magnonic crystal of equally spaced micro-structured strips of magnetite nanoparticles on the surface of an yttrium iron garnet thin film has been implemented and measured. The periodic micro-structured nanoparticles are deposited on the surface of such yttrium iron garnet single-crystal film grown on a gallium-gadolinium garnet substrate via dip-coating technique. Propagation of magnetostatic surface spin-waves is studied and it is shown that the presence of such periodic structure leads to the formation of spin-wave band gaps in the transmission characteristics. The spin-wave detection has been carried out using a pair of microwave antennas and a vector network analyzer. The results show that the periodic structure formed by the magnetite strips modifies the spectra of the transmitted spin waves producing band gaps.

Background/Objectives: To compare functional vision parameters - related to the perception of movement - of children who were exposed to SARS-CoV-2 with those who had no contact with the virus in the womb, in postnatal life, or through the family context; Methods: A cross-sectional study was conducted with children aged from 0 to 24 months. An initial assessment was performed through a caregiver interview and participants were divided into four groups considering the nature of their contact with COVID-19. Functional parameters of vision were recorded and two independent blinded researchers performed their analysis. Statistical analysis was conducted using the software SPSS®. Data normality was verified by the Shapiro-Wilk test. The prevalence and the odds ratio of visual changes according to coronavirus exposure were analyzed, considering a p-value &lt; 0.05; Results: The Gestational COVID Group presented an increased risk for unstable fixation time, convergent strabismus, and looking discontinuity; the Familiar COVID Group was more inclined to look discontinuity on horizontal tracking. However, there were no statistically significant differences in the prevalence and odds ratios between the exposure and control groups; Conclusions: Children exposed to SARS-CoV-2 during pregnancy or in the family environment had a higher incidence of gaze discontinuity, as well as a higher rate of unstable fixation and convergent strabismus in those exposed during pregnancy. However, there were no statistically significant differences between the groups.

Salinity is considered as one of the most important abiotic challenges that affect crop productivity. Plant hormones, including salicylic acid (SA), are key factors in the defence signalling output triggered during plant responses against environmental stresses. We have previously reported in peach a new SA biosynthetic pathway from mandelonitrile (MD), the molecule at the hub of the cyanogenic glucoside turnover in Prunus sp. In this work, we have studied whether this new SA biosynthetic pathway is also present in plum and the possible role this pathway plays in plant plasticity under salinity, focusing on the transgenic plum line J8-1, which displays stress tolerance via an enhanced antioxidant capacity. The SA biosynthesis from MD in non-transgenic and J8-1 micropropagated plum shoots was studied by metabolomics. Then the response of J8-1 to salt stress in presence of MD or Phe (MD precursor) was assayed by measuring: chlorophyll content and fluorescence parameters, stress related hormones, levels of non-enzymatic antioxidants, the expression of two genes coding redox-related proteins, and the content of soluble nutrients. The results from in vitro assays suggest that the SA synthesis from the MD pathway demonstrated in peach is not clearly present in plum, at least under in vitro conditions. Nevertheless, in J8-1 NaCl-stressed seedlings, an increase in SA was recorded as a result of the MD treatment, suggesting that MD could be involved in the SA biosynthesis under NaCl stress conditions in plum plants. We have also shown that the plum line J8-1 was tolerant to NaCl under greenhouse conditions, and this response was somewhat different in MD-treated plants. In that regards, the MD treatment produced an increase in SA, jasmonic acid (JA) and reduced ascorbate (ASC) contents as well as in the coefficient of non-photochemical quenching (qN) and the gene expression of Non-Expressor of Pathogenesis-Related 1 (NPR1) and thioredoxin H (TrxH) under salinity conditions, suggesting a crosstalk between different signalling pathways (NPR1/Trx and SA/JA) leading to salinity tolerance in the transgenic plum line J8-1.

Background: This study aimed to investigate the effect of fascial manipulation (FM) of the deep cervical fascia (DCF) and sequential yoga poses (SYP) on pain and function in individuals with mechanical neck pain (MNP). Method: Following the predefined criteria, ninety-nine individuals with MNP were recruited, randomised and assigned to either the intervention group (IG) (n=51) or the control group (CG) (n=48). Individuals in the IG received FM (4 sessions in 4 weeks) along with the home-based SYP (4 weeks). The CG participants received the usual care (cervical mobilization and thoracic manipulation (4 sessions in 4 weeks) along with unsupervised therapeutic exercises (4 weeks). The participants underwent baseline and weekly follow-up measurements of pain using a numerical pain rating scale (NPRS) and elbow extension range of motion (EEROM) during upper limb neurodynamic test 1 (ULNT1). The baseline and the 4th session follow-up measurements of the Patient-specific Functional Scale (PSFS) and Fear-avoidance Behavior Questionnaire (FABQ) were also taken. Results: A repeated-measures ANOVA was performed. The mean differences between the IG and CG on NPRS 3rd and 4th sessions are -1.009 (p&lt; 0.05) and -1.701 (p&lt; 0.001), respectively; on EEROM in the 4th session is 20.120 (p&lt; 0.001); on FABQ during the follow-up is -5.036 (p&lt;0.001), showing a statistically significant difference, whereas on PSFS during follow-up is 0.263 (p=0.566), suggesting no significant differences in PSFS. Conclusion: FM and SYP can aid in reducing pain and fear avoidance behavior as well as improving the function and extensibility of the upper quarter region.

Carbon nanotubes (CNTs) can be considered as semi-rigid all-carbon polymers. However, unlike conventional polymers that can form 3D networks such as hydrogels or elastomers through crosslinking with each other in solution, the cylindrical carbon lattice of CNTs was not believed to be directly crosslinkable in solution until our recent discovery of UV-defluorination driven direct CNT crosslinking. In this study, we further reveal that the UV-defluorination-driven crosslinked CNTs are metastable and can decompose more readily than fluorinated or pristine CNTs upon exposure to Raman laser irradiation. Specifically, we investigate the stability of UV-defluorinated single-walled and multi-walled fluoro-nanotubes using Raman spectroscopy under controlled varying laser power. The results indicate that both the defluorinated single-walled and multi-walled CNTs are thermally less stable than pristine CNTs or untreated fluorinated CNTs, which can be attributed to the strains on the crosslinking bonds created from the curved carbon lattice of linked CNTs. This instability, particularly evident under high-power laser irradiation, leads to combustion processes ignited at relatively lower temperatures that cause an extended burned area centered on the laser spot, offering potential future applications as mechanically robust, lightweight materials with feasible post-use degradation options.

Rare Earth Elements (REE), also known as Lanthanides (Ln3+), are a group of 17 elements showing peculiar physical and chemical properties. Unlike technological applications, very little is known about the physiological role and toxicity of Ln3+ on biological systems, in particular on microorganisms (e.g., bacteria), which represent the most abundant domains on our planet. Up to now, very limited studies have been conducted due to Ln3+ precipitation with some anions commonly present in the culture media. Therefore, the development of a minimal medium is essential to allow the study of Ln3+-microbial interactions, limiting considerably the precipitation as insoluble salts. In this regard, a new minimal culture medium capable of solubilizing large amounts of Ln3+, and allowing the growth of different microbial taxa, was successfully developed. Assays have shown that the medium is capable of solubilizing Ln3+ up to 100 times more than other common culture media and allowed the growth of 63 bacteria and 5 fungi. The kinetic growth of one yeast and one gram-positive bacterium has been defined, proving to support superior growth and biomass compared to other commonly used minimal media. Moreover, the sensitivity and uptake/absorption of a Bacillus stratosphericus strain was tested, highlighting its capability to tolerate concentrations up to 10 mM of either Cerium, Gadolinium or Lanthanum and accumulate different quantities of the three.

Current antibiograms cannot discern the particular effect of a specific antibiotic when the bacteria are incubated with a mixture of antibiotics. To prove that this task is achievable, Escherichia coli strains were treated with ciprofloxacin for 45 min, immobilized on a slide and stained with SYBR Gold. In susceptible strains, the nucleoid relative surface started to decrease near the MIC, being progressively condensed as dose increased. The shrinkage level correlated with the DNA fragmentation degree. Ciprofloxacin-resistant bacilli showed no change. Additionally, E. coli strains were incubated with ampicillin for 45 min and processed similarly. The ampicillin-susceptible strain revealed intercellular DNA fragments that increased with dose, unlike the resistant strain. Co-incubation with both antibiotics revealed that ampicillin did not modify the nucleoid condensation effect of ciprofloxacin, whereas the quinolone partially decreased the background of DNA fragments induced by ampicillin. Sixty clinical isolates, with different combinations of susceptibility-resistance to each antibiotic, were co-incubated with the EUCAST breakpoints of susceptibility of ciprofloxacin and ampicillin. The morphological assay correctly categorized all the strains for each antibiotic in 60 min, demonstrating the feasible independent evaluation of a mixture of quinolone and beta-lactam. The rapid phenotypic assay may shorten the incubation times and necessary microbial mass currently required for evaluation.

Rising antimicrobial resistance (AMR) in Salmonella serotypes host-adapted to cattle is of increasing concern to the beef and dairy industry. The bulk of the existing literature focuses on AMR post-slaughter. In comparison, the understanding of AMR in Salmonella among pre-harvest cattle is still limited, particularly in Texas, which ranks top five in beef and dairy exports in the United States; inherently, the health of Texas cattle has nationwide implications for the health of the United States beef and dairy industry. In this study, long-read whole genome sequencing and bioinformatic methods were utilized to analyze antimicrobial resistance genes (ARGs) in 98 isolates from beef and dairy cattle in the Texas Panhandle. Fisher exact tests and elastic net models accounting for population structure were used to infer associations between ARGs and antimicrobial phenotypic profiles and metadata. Gene mapping was also performed to assess the role of mobile genetic elements in harboring ARGs. ARG were found to be statistically different between the type of cattle operation and Salmonella serotypes. Beef operations were statistically significantly associated with more resistance genes compared to dairy operations. Salmonella Heidelberg, followed by Salmonella Dublin isolates, were associated with the most ARGs. Additionally, specific classes of ARGs were only present within mobile genetic elements.

Making sustainable business models, especially in manufacturing, is a key approach for organizations to adopt in order to create more sustainable processes. New technologies are needed to implement new policies that can minimize the economic, environmental, and social consequences of industrial activity. Sustainable maintenance is decisive to guarantee the availability, reliability, and safety of assets, surpassing traditional maintenance policies and embracing the principles of the circular economy. The main objective of Maintenance 4.0 is to increase the lifespan and availability of the equipment by preventing unplanned downtime, reducing planned shutdowns, and improving safety. This research focuses on the integration of advanced Industry 4.0 tools with conventional monitoring and control techniques in process industries. The article suggests that while complex neural networks might provide good predictions, simpler solutions can generalize well and have lower prediction errors because they can capture the underlying relationships between variables in a specific asset better. The combination of maintenance function, Industry 4.0 tools, and advanced statistical solutions to obtain sustainable processes can facilitate organizational change and aid decision-making in equipment management. These solutions seek to reduce interruptions and expenses through the unnecessary utilization of labor and spare parts. All these considerations improve communication and data processing, resulting in improved maintenance of a hydrogen compressor in the petrochemical industry.

In the age of social media, images come from unreliable sources that may change their content to fit a narrative. Automated detection of forged images is a complex task, especially considering recent technological advances in image manipulation software. However, in the existing literature, it is possible to identify two general approaches adopted by detection methods, active and passive. Active techniques preemptively act on an image by inserting structures before any manipulation is made that can verify its authenticity. In contrast, passive methods analyze the content of an image in search of traces of manipulation. In this way, this research proposes a novel approach to image manipulation detection, combining two passive methods through neural networks, creating a generalist approach capable of detecting with greater accuracy than the methods that compose it. Furthermore, this work used a combination of four datasets available in the literature for training and evaluation. After training, the merged approach obtained an accuracy of 89.59% in the set of validation images, significantly higher than the model trained with only unaltered images, which obtained 78.64%, and the two other models trained using images with a feature selection method applied to enhance inconsistencies that obtained 68.02% for Error-Level Analysis images and 50.70% for the method using Discrete Wavelet Transform. In addition to the performance improvement, the proposed approach’s accuracy variation was lower than the other models.

Soil and Water Assessment Tool (SWAT) was used to simulate five glacierized river basins that are global in coverage and vary in climate. The river basins included the Narayani (Nepal), Vakhsh (Central Asia), Rhone (Switzerland), Mendoza (Central Andes, Argentina), and Central Dry Andes (Chile) with a total area of 85,000 km2. A modified SWAT snow algorithm was applied in order to consider spatial variation of associated snow melt /accumulation by elevation band across each subbasin. In the previous studies, melt rates varied as a function of elevation resulting from an air temperature gradient while the snow parameters were constant throughout the entire basin. A major improvement of the new snow algorithm is separating the glaciers from seasonal snow based on their characteristics. Two SWAT snow algorithms were evaluated in simulation of monthly runoff from glaciered watershed: 1) the snow parameters are lumped (i.e. constant throughout the entire basin) and 2) the snow parameters are spatially variable based on elevation band-subbasin (i.e. modified snow algorithm). Applying the distributed SWAT snow algorithm improved the model performance in simulation of monthly runoff with snow-glacial regime, so that mean RSR decreased to 0.49 from 0.55 and NSE increased to 0.75 from 0.69. Improvement of model performance was negligible in simulation of monthly runoff from the basins with monsoon runoff regime.

Extensive genome structure variation, such as copy number variations (CNVs) and presence/absence variations, is the basis for the remarkable maize genetic diversity; however, the effect of CNVs on maize herbivory defense remains largely underexplored. Here, we report that the naturally occurring duplication of the maize 9-lipoxygenase gene, ZmLOX5, leads to increased resistance of maize to herbivory by fall armyworms (FAW). Previously, we showed that ZmLOX5-derived oxylipins are required for defense against chewing insect herbivores and identified several inbred lines, including Yu796, that contained duplicated CNVs of ZmLOX5, referred to as Yu796-2×LOX5. To test whether introgression of the Yu796-2×LOX5 locus into the herbivore-susceptible B73 background that contains a single ZmLOX5 gene is a feasible approach to increase resistance, we generated a series of near-isogenic lines that contained either 2, 1 or 0 copies of the Yu796-2×LOX5 locus in the B73 background by six back crosses (BC6). Droplet digital PCR (ddPCR) confirmed the successful introgression of the Yu796-2×LOX5 locus in B73. The resulting B73-2×LOX5 inbred line displayed increased resistance against FAW associated with increased expression of ZmLOX5, increased wound-induced production of its primary oxylipin product, the α-ketol, 9-hydroxy-10-oxo-12(Z),15(Z)-octadecadienoic acid (9,10-KODA), and the downstream defense hormones regulated by this molecule, 12-oxo-phytodienoic acid (12-OPDA) and abscisic acid (ABA). Surprisingly, wound-induced JA-Ile production was not increased in B73-2×LOX5, resulting from the increased JA catabolism. Furthermore, B73-2×LOX5 displayed enhanced drought tolerance likely due to increased ABA and 12-OPDA content. Taken together, this study revealed that the duplicated CNV of ZmLOX5 quantitively contributes to maize antiherbivore defense and presents proof-of-concept evidence that the introgression of naturally occurring duplicated CNVs of a defensive gene into the productive, but susceptible, crop varieties is a feasible breeding approach for enhancing plant resistance to herbivory and tolerance to abiotic stress.

The aim of this study was to estimate the association between fear of COVID-19 and risk perception with preventive behavior in health professionals from three Latin American countries. An analytical cross-sectional study was conducted. Health professionals with on-site care in Colombia, Ecuador, Guatemala, and Peru were surveyed. Information was collected through an online self-report questionnaire. The main variables were preventive behavior as the dependent variable and fear of COVID-19 and risk perception as independent variables. Linear regression was used, and Beta coefficients and p-values were calculated. 435 health professionals were included, the majority were aged 42 years or older (45.29%, 95%CI: 40.65%-50.01%) and female (67.82%, 95%CI: 63.27%-72.05%). It was shown that the greater the fear of COVID-19, the greater the preventive behavior of COVID-19 infection (B=2.21, p=0.002 for total behavior; B=1.12, p=0.037 for additional protection at work; B=1.11, p<0.010 for hand washing). The risk perception of COVID-19 infection had a slight direct relationship with preventive behaviors (B=0.28, p=0.021 for total behavior; B=0.13, p=0.015 for hand washing), with the exception of the preventive behavior of using additional protection at work (p=0.339). We found that fear and risk perception are associated with increased practice of hand washing and use of additional protection at work. Further studies are required on the influence of working conditions, job performance and the occurrence of mental health problems in frontline personnel with regard to COVID-19.

Circular Economy involves structural changes in traditional business models and consumers’ behaviour toward recycled products. The recycling of PET products has been increasing but there is still a gap between consumption and demand for PET packaging in Brazil. In this research, the waste reduction was examined under a projective scenario to the current ecological purposes in Brazil for reducing environmental pollution. In that manner, this paper aimed to comprehend the intention to purchase recycled PET products of Brazilian consumers. With a non-probabilistic and convenience sample, the study counts 422 participants. The method employed was based on Structural Equation Modelling and Partial Least Squares, used to test the hypotheses of causality among the variables. Results showed the perception of low quality about recycled products reduced consumers’ intention to purchase. Also, the sustainability of recycled products positively influenced the intention to purchase. In addition, recycled products presented a negative impact on the perceived safety, which could influence the purchase of recycled products in Brazil. We conclude that the image that Brazilian consumers have about recycled products positively affects the intention to purchase.

A hallmark of Alzheimer’s disease (AD) are the proteinaceous aggregates formed by the amyloid-beta peptide (Aβ) that is deposited inside the brain as amyloid plaques. The accumulation of aggregated Aβ may initiate or enhance pathologic processes in AD. According to the amyloid hypothesis any agent that has the capability to inhibit Aβ aggregation and/or destroy amyloid plaques represents a potential disease modifying drug. In 2023, a humanized IgG1 monoclonal antibody (lecanemab) against the Aβ soluble protofibrils was approved by US FDA for AD therapy thus providing compelling support to the amyloid hypothesis. To acquire a deeper insight on the in vivo Aβ aggregation, various animal models, including aged herbivores and carnivores, non-human primates, transgenic rodents, fish and worms are widely exploited. This review is based on the recent data obtained using transgenic animal AD models and presents experimental verification of the critical role in Aβ aggregation seeding of the interactions between zinc ions, Aβ with the isomerized Asp7 (isoD7- Aβ) and the α4β2 nicotinic acetylcholine receptor.

Soil-borne Trichoderma spp. have been extensively studied for their biocontrol activities against pathogens and growth promotion ability with plants. However, the beneficial effect of Trichoderma on inducing resistance against insect herbivores has been considered only recently. Among diverse Trichoderma species, consistent with previous reports, we showed that root colonization by T. virens triggered induced systemic resistance (ISR) to leaf-infecting fungal pathogens. Whether T. virens induces ISR to insect pests has not been tested before. In this study, we investigated whether T. virens affects jasmonic acid (JA) biosynthesis and defense against fall armyworm (FAW) and western corn rootworm (WCR). Unexpectedly, the results showed that T. virens colonization of maize seedlings grown in autoclaved soil suppressed wound-induced production of JA, resulting in reduced resistance to FAW. Similarly, the bacterial endophyte Pseudomonas chlororaphis 30-84 suppressed systemic resistance to FAW due to reduced JA. Further comparative analyses of the systemic effects of these endophytes when applied into sterile or non-sterile field soil showed that both T. virens and P. chlororaphis 30-84 triggered ISR against hemibiotrophic fungal pathogen Colletotrichum graminicola in both soil conditions, but only suppressed resistance to FAW in sterile soil. In contrast to the effect on FAW defense, T. virens colonization of maize roots suppressed WCR larvae survival and weight gain. This is the first report suggesting the potential role of T. virens as a biocontrol agent against WCR.

Background In this study we investigated in detail the role of cannabidiol (CBD), Beta-caryophyllene (BC), or their combinations in diabetic peripheral neuropathy (DN). The key factors that contribute to DN include mitochondrial dysfunction, inflammation, and oxidative stress. Methods Briefly, Streptozotocin (STZ) (55 mg/kg) was injected intraperitoneally to induce DN in Sprague Dawley rats and performed procedures including Randall Sellito Calipers, Von Frey Aesthesiometer, hot plate, and cold plate methods to determine mechanical and thermal hyperalgesia in vivo. The blood flow to the nerves was assessed by using the Laser Doppler device. Schwann cells were exposed to high glucose (HG) at a dose of 30 mM to induce hyperglycemia and DCFDA, JC1 & Mitosox staining were done to determine mitochondrial membrane potential, reactive oxygen species and mitochondrial superoxides in-vitro. The rats were administered i.p with BC (30mg/kg), CBD (15mg/kg), or combination while Schwann cells were treated with 3.65 µM CBD, 75 µM BC, or combination to assess their role in DN amelioration. Results Our results revealed that exposure to BC and CBD diminished HG-induced hyperglycemia in Schwann cells, in part, through reducing mitochondrial membrane potential, reactive oxygen species and mitochondrial superoxides. Further, BC and CBD combination treatment in-vivo could prevent the deterioration of mitochondrial quality control system by promoting autophagy and mitochondrial biogenesis while improving blood flow. CBD and BC treatments also reduced pain hypersensitivity to hyperalgesia and allodynia with increased antioxidant and anti-inflammatory action in diabetic rats. These in vivo effects were attributed to significant upregulation of AMPK, SIRT3, Nrf2, PINK1, PARKIN, LC3B, Beclin1 and TFAM functions while downregulation of NLRP3 inflammasome, NFκB, COX2 and p62 activity was noted as determined by western blotting. Conclusion the present studies demonstrated that STZ & HG induced oxidative and nitrosative stress play a crucial role in the pathogenesis of diabetic neuropathy. We find, for the first time, that CBD and BC combination ameliorate DN via modulating the mitochondrial quality control system.

Groundwater flow and transport models are essential tools for assessing and quantifying the mi-gration of organic contaminants at polluted sites. Uncertainties in the hydrodynamic and transport parameters of the aquifer have a significant effect on model predictions. Uncertainties can be quantified with advanced sensitivity methods such as Sobol’s High Dimensional Model Reduction (HDMR) and Variogram Analysis of Response Surfaces (VARS). Here we present the application of VARS and HDMR to assess the global sensitivities of the outputs of a transient groundwater flow model of the Gállego alluvial aquifer which is located downstream the Sardas landfill in Huesca (Spain). The aquifer is subject to the tidal effects caused by the daily oscillations of the water level in the Sabiñánigo reservoir. Global sensitivities are analysed for hydraulic heads, aquifer/reservoir fluxes, groundwater Darcy velocity and hydraulic head calibration metrics. Input parameters in-clude aquifer hydraulic conductivities and specific storage, aquitard vertical hydraulic conductiv-ities, and boundary inflows and conductances. VARS, HDMR and graphical methods agree to identify the most influential parameters which for most of the outputs are the hydraulic conduc-tivities of the zones closest to the landfill, the vertical hydraulic conductivity of the most permeable zones of the aquitard, and the boundary inflow coming from the landfill. The sensitivity of heads and aquifer/reservoir fluxes with respect to specific storage change with time. The aquifer/reservoir flux when the reservoir level is high shows interactions between specific storage and aquitard conductivity. VARS and HDMR parameter rankings are similar for the most influential parameters. However, there are discrepancies for the less relevant parameters. The efficiency of VARS was demonstrated by achieving stable results with a relatively small number of simulations.

The new digital infrastructure has become an important basis for the green development of agriculture. This paper selects provincial sample data from 2006 to 2022, constructs an indicator system to measure new digital infrastructure and agricultural green total factor productivity, and explores how new digital infrastructure can promote agricultural green development. The results show that: (1) the new digital infrastructure has a significant role in promoting the green development of agriculture, and this conclusion is still valid after processing endogeneity and heteroscedasticity; (2) Technology and land factors play an intermediary role in the promotion of green agricultural development by the new digital infrastructure, that is, the new digital infrastructure helps to improve the quality and technical level of cultivated land and thus promote green agricultural development; (3) Labor force factors optimize the mediating role of technology factors, that is, the higher the quality of labor force, the stronger the role of the new digital infrastructure in promoting the green development of agriculture through the technological path; (4) The effect of new digital infrastructure on the green development of agriculture is obviously heterogeneous, and the effect is more obvious in northwest China and the regions with lower marketization level, higher environmental regulation level. This study is helpful to clarify the relationship between new digital infrastructure and agricultural green development in China, and provide corresponding policy suggestions for promoting regional agricultural green development.

The evolution and miniaturization of the technologies for processing, storage, and communication have enabled computer systems to process a high volume of information and make decisions without human intervention. Within this context, several systems architectures and models have gained prominences, such as the Internet of Things (IoT) and Smart Grids (SGs). SGs use communication protocols to exchange information, among which the Open Smart Grid Protocol (OSGP) stands out. In contrast, this protocol does not have integration support with IoT systems that use some already consolidated communication protocols, such as the Constrained Application Protocol (CoAP). Thus, this work develops the integration of the protocols OSGP and CoAP to allow the communication between conventional IoT systems and systems dedicated to SGs. Results demonstrate the effectiveness of this integration, with the minimum impact on the flow of commands and data, making possible the use of the developed CoAP-OSGP Interface for Internet of Things (COIIoT).

Plant loss in experimental plots occurs occasionally in field experiments with coffee crops. In breeding programmes, such loss can be extremely harmful, especially when the statistical analysis methods used are not consistent with the data generated in the experiments. In this study, we analysed a set of productivity data to determine whether the compensatory effect occurs in coffee crops, analyse the need for correcting the number of failures in experiments, and identify the best stand correction method to use. Productivity data from six harvests of 11 experiments with Coffea arabica plants were used. The experiments were implemented in a randomised block design, with four replications and six plants per plot. The following stand correction methods were evaluated: rule of three, Zuber [1], Vencovsky and Cruz [2]covariance of the average or ideal stands, and Cruz [3] and compared to data without correction adjustments. The most adequate correction methods were chosen based on the existence of genetic variance, selective accuracy, and progeny ordering. The compensatory effect was evident from the analysed data, with stand correction shown to be beneficial in progeny competition experiments. The covariance methods using average or ideal stands presented the best results, followed by the method proposed by Cruz [3]. The rule of three and Zuber [1] methods showed unsatisfactory results and are not recommended for stand correction in progeny competition experiments with coffee crops

The Indian meal moth, Plodia interpunctella, poses a significant threat to global agricultural products. Although pheromone-based technologies show promise for P. interpunctella management, limitations like single-sex targeting necessitate exploring complementary strategies. Vegetable-based oils represent a potential alternative, but their efficacy, sex-specificity, and interaction with sex pheromones remain unclear. To answer these questions, we first examined attraction of P. interpunctella female and male adults to ten different vegetable oils, i.e., camellia, corn, olive, peanut, rapeseed, sesame, soybean, sunflower, walnut, and a blended oil (mixture of sunflower seed, rapeseed, soybean, peanut, and sesame oils), in the semi-field conditions. Sesame, olive, and blended oils demonstrated most attractive, capturing significantly more adults compared to other oils. We then evaluated effectiveness of these three attractive oils and their combinations with P. interpunctella sex pheromone in a grain warehouse. Traps baited with these oils captured significantly more females and males compared to control traps without attractants. However, sex pheromone addition did not improve male capture and significantly reduced female capture, suggesting an inhibitory effect. Our findings highlight the potential of blended, olive, or sesame oil trap alone as alternative monitoring and trapping tools for P. interpunctella, delivering novel insights into the development of efficient integrated pest management strategies for stored products.

We present a very computationally light and fast approximation algorithm and then verify it with genetic algorithm and simulated annealing. We show that our algorithm is on par with GA and SA in terms of output produced while having a tightly bounded time complexity. Our algorithm works best when there is a strong positive correlation between the reliability of a component and its cost. We present two algorithms with the same essence. One of them is system cost bounded and the other is target reliability bounded. Our proposed algorithm works on a subsystem level redundancy instead of component level redundancy.

Aging is a complex process associated with tissue degeneration and an increased risk of age-related diseases. This study aimed to evaluate the impact of Terasen®, a nutraceutical containing standardized extracts of Euterpe oleracea, Myrciaria dubia, and purified oil of Bixa orellana and Astrocaryum aculeatum on the lifespan of Caenorhabditis elegans, a widely used model organism for aging research. The findings demonstrated that Terasen® exhibited significant antioxidant activity and influenced the feeding behavior of C. elegans, leading to a reduced pharyngeal pumping rate and a decreased number of offspring produced by treated individuals. Notably, Terasen® also displayed a remarkable ability to extend the lifespan of C. elegans. These findings suggest that Terasen® may possess promising anti-aging effects in vivo, warranting further investigation.

Dysregulation of the arsenal of cells, growth factors, cytokines, proteases, and proteins involved in wound healing (WH), could delay the healing process. Plants and plant-derived molecules (PDMs) have been used as medicines for skin wounds. This study aimed to select and evaluate the pro-healing capacity of PMDs. Thirty-three PDMs and 10 therapeutic targets (TTs) were chosen for molecular docking and PDMs: aristolochic acid (AA), α-copaene, selinenes, β-caryophyllene (BC), and BCoxide, and TTs: metalloproteinase (MMP) 3, MMP13, and tumor necrosis factor (TNF α) for molecular dynamics. The bests inhibitor was AA, but because of its toxicity, BC and BCoxide were chosen for evaluation in HaCat cells and BALB/c mice excisional model. Both compounds were not toxic, and higher percentages of lesion area closure (LAC) were induced by BC treatment (p<0.05). All mice healed; however, an initial delay of LAC was induced by 0.05, 0.1% BCoxide, 0.1% BC, and allantoin. At the end of treatment, lower numbers of mast cells, level of cellular infiltrates (except 1% BCoxide and 0.05, 0.5%BC), epidermal thickness tendency (except 0.1, 0.5% BCoxide), and higher values of SC-thickness, and collagen fibers only by 0.5% BC treatment compared with untreated control (p<0.05) were observed. Our results show that BC is a promising multitarget candidate for wound healing treatment and optimization campaigns.

The primary objective of this systematic review was to analyze the main physical agents representing risk factors for commercial aircrew, together with their consequences. The secondary objective was to identify the countries in which studies on the topic were conducted, as well as the quality of the publications available. Thirty-five articles, published between 1996 and 2020, were selected for the review, having met all inclusion criteria. The majority of studies were conducted in the United States, Germany and Finland and had moderate or low methodological quality of evidence. The main risk factors for aircrew identified in publications were exposure to abnormal air pressure, cosmic radiation, noise, and vibrations. Hypobaric pressure was explored in response to demands for studies on this agent, a factor which may lead to otic and ear barotraumas, as well as acceleration of atherosclerosis of the carotid artery. However, there is a dearth of research exploring this phenomenon.

This paper designed a new type of generator, transgenerator, that integrates the wind turbine and flywheel into one system, aiming to make the flywheel distributed energy storage (FDES) more modular and scalable than the conventional FDES. The transgenerator is a three-member dual-mechanical-port (DMP) machine with two rotating members (inner and outer rotors) and one stationary member (stator). The transgenerator-flywheel system is introduced with the system configuration, transgenerator overview, flywheel operation principle and power management strategies, and control system. Simulations are performed in MATLAB/ Simulink to verify the system viability, including control system verification and the flywheel storage performance evaluation. Results show that the inner and outer rotors can be controlled independently with accurate and fast control response, and the grid-side control works properly. The flywheel performs well with considerable charging power and storage capacity.

Reducing CO2 emissions is urgently needed to slow down the impacts of climate change. CO2 capture using an amine solution has been developed and implemented on pilot and commercial scales. However, amine scrubbing, in particular, produces a lot of degraded solvent as waste and is energy intensive. Solid sorbents have been called to overcome those drawbacks. In this work, waste biomass-derived carbon materials were developed and tested for CO2 capture and conversion. Advanced thermal chemical processes i.e. hydrothermal and pyrolysis were applied to produce materials from agri-food waste such as soybean and okara. It was found that the number of functional groups (-C=O and -OH) in activated carbon appears in the synthesized materials, implying the generation of surface oxygenated groups. Preliminary results showed that the synthesized activated carbons are obtained with good yields, and a relatively high surface area, which may be applied as CO2 adsorption materials to solve the CO2 emission problems.

The aims of this study are to measure the technical efficiency (TE) of Cambodian household’s rice production and trying to determine its main influencing factors using the stochastic frontier production function. The study utilized primary data collected from 301 rice farmers in three selected districts of Battambang by structured questionnaires. The empirical results indicated the level of household rice output varied according to differences in the efficiency of production processes. The mean TE is 0.34 which means that famers produce 34% of rice at best practice at the current level of production inputs and technology, indicates that rice output has the potential of being increased further by 66% at the same level of inputs if farmers had been technically efficient. Furthermore, between 2013-2015 TE of household’s rice production recorded -14.3% decline rate due to highly affected of drought during dry season of 2015. Moreover, evidence reveals that land, fertilizer, and pesticide are the major influencing input factors of household’s rice production, while disaster, education of household head, family size and other crops’ cultivated area are core influencing factors decreasing TE. Conversely, the main influencing factors increasing TE are irrigated area, number of plot area and sex of household head.

The aims of this study are to measure the technical efficiency (TE) of Cambodian household’s rice production and trying to determine its main influencing factors using the stochastic frontier production function. The study utilized primary data collected from 301 rice farmers in three selected districts of Battambang by structured questionnaires. The empirical results indicated the level of household rice output varied according to differences in the efficiency of the production processes. The mean TE is 0.34 which means that famers produce 34% of rice at best practice at the current level of production inputs and technology, indicates that rice output has the potential of being increased further by 66% at the same level of inputs if farmers had been technically efficient. Furthermore, between 2013-2015, TE of household’s rice production recorded -14.3% decline rate due to highly affected of drought during dry season of 2015. Moreover, evidence reveals that land, fertilizer, and pesticide are the major influencing input factors of household’s rice production, while disaster, education of household head, family size and other crops’ cultivated area are core influencing factors decreasing TE. Conversely, the main influencing factors increasing TE are irrigated area, number of plot area and sex of household head.