A study of the water quality of the Adolfo López Mateos Reservoir (ALMD) was developed through different indicators from a spatial and seasonal perspective. Variables related to the general characteristics of water quality, trophic level and ecological risk were assessed through the water Quality Index (WQI_NSF-BROWN), Trophic State Index (TSI_CARLSON) and the Ecological Risk Index (RI_HAKANSON). Using data from physical, chemical and biological parameters obtained from four sampling points in the ALMD, the water quality was assessed in each model used. The results indicated that the reservoir presents a water quality classified as “medium” (WQI_NSF-BROWN = 70), where significant variations in the concentrations of some parameters are observed. The reservoir showed a general trophic state classified as “Mesotrophic” (TSI_{GENERAL-AVERAGE} = 43.04). The ecological risk analysis achieved the best classification of the methodology, discarding contamination by heavy metals in surface waters. Through this type of applied methodologies will help as decision making tools in the dam, as well as for application in other dams in the region.

This article presents the implementation of a model to estimate the future price of commodities in the Brazilian market from time series of short-term technical evaluation. For this, data from two databases were used, one referring to the foreign market (opening values, maximum, minimum, closing, closing adjustment and volume) and the other, from the Brazilian market (the price of the day), considering commodities, sugar, cotton, corn, soybean and wheat. Subsequently, the technical indicators were calculated from the TA-Lib technical analysis library. Pearson’s correlation coefficient was applied, records with low correlation were removed, and then the database was consolidated. From the pre-processed data, Long Short-Term Memory (LSTM) recurrent neural networks were used to perform data prediction at the one and three day interval. These models were evaluated using the mean square error (MSE), obtaining results between 0.00010 and 0.00037 on test data one day ahead, and from 0.00017 to 0.00042 three days ahead. However, based on the results obtained, it was observed that the developed model obtained a promising forecasting performance for all the commodities evaluated. As a main contribution, there is the consolidation of databases that can be used in future scientific research. Furthermore, based on its interpretation, it can assist in decision making regarding the buying and selling of commodities to increase financial gains.

This paper presents the development and implementation of a machine learning model to estimate the future price of commodities in the Brazilian market from technical analysis indicators. For this, two databases were obtained regarding the commodities sugar, cotton, corn, soybean and wheat, which were submitted to the steps of data cleaning, pre-processing and subdivision. From the pre-processed data, recurrent neural networks of the long short-term memory type were used to perform the prediction of data in the interval of 1 and 3 days ahead. These models were evaluated using mean squared error, obtaining an accuracy between 0.00010 and 0.00037 on the test data for 1 day ahead and 0.00015 to 0.00041 for 3 days ahead. However, based on the results obtained, it can be stated that the developed model obtained a good prediction performance for all commodities evaluated.

The objective of this study was to identify genomic regions and genes associated with resistance to gastrointestinal nematodes in Australian Merino sheep in Uruguay, using the single-step GWAS methodology (ssGWAS), which is based on genomic estimated breeding values (GEBVs) obtained from a combination of pedigree, genomic and phenotypic data. This methodology converts GEBVs into SNP effects. Analysis included 26,638 animals with fecal egg count (FEC) records obtained in two independent parasitic cycles (FEC1 and FEC2), and 1,700 50K SNP genotypes. Comparison of genomic regions was based on genetic variances (gVar(%)) explained by non-overlapping regions of 20 SNPs. For FEC1 and FEC2, 18 and 22 genomic windows exceeded the significance threshold (gVar(%) ≥ 0.22%), respectively. The genomic regions with strong associations with FEC1 were located on chromosomes OAR 2, 6, 11, 21 and 25, and for FEC2 on OAR 5, 6 and 11. The proportion of genetic variance attributed to the top windows was 0.83% and 1.9% for FEC1 and FEC2, respectively. The 33 candidate genes shared between the two traits were subjected to enrichment analysis, revealing a marked enrichment in biological processes related to immune system functions. These results contribute to the understanding of the genetics underlying gastrointestinal parasite resistance and its implications for other productive and welfare traits in animal breeding programs.

Introduction: Colorectal cancer (CRC) is a disease of colon or rectum the part of digestive system. DNA methylation is a process of gene expression by recruiting protein which involve in gene repression, or inhibiting the binding of transcription factors to DNA. MicroRNAs (miRNAs) have been attracting major interest as potential biomarker in cancer. Hereditary nonpolyposis of colorecta cancer (HNPCC) is a type of genetic change (mutation) in a family. Our aims to do a systematic review on DNA methylation and miRNAs serve as candidate clinical biomarkers in HNPCC. Materials and methods: Electronic databases (Medline, PubMed and Scopus data bases). We searched to identify publication all over the world related colorectal cancer and miRNA. Selection was based on the design (CRC, invasive CRC, Colon or rectum, HNPCC, microRNA, circulating miRNA, non-coding RNA), 87 papers from PubMed and 15 papers from Scopus were selected all over the world. CRC, target antigens, methodologies used for detection and miRNA expression were identified and summarized. Results: A total of 96 articles were searched, 87 articles from scopus and 9 articles from PubMed. 20 duplicates removed and remain 76, 52 excluded after screened the titles and abstracts; and remain 24, 10 full texts articles were excluded with reason, and 14 identifications were included in the studies. Conclusion: The findings of this systematic review showed that DNA methylation and mircroRNA in HNCC patients as a genetic mutation or a promoter in colorectal cancer.

In this work, we propose an easy and a low cost method for the synthesis of Nitrogen-Doped Graphene NDG and its silver nanowires NW functionalization NWGN. The synthesis was performed using the improved graphene oxide method, chemical reduction of graphene oxide in the presence of caffeine as green nitrogen source and the subsequently the silver nanowires growth in the surface, by the chemical reductions salts in the presence of NG. Achieving a homogeneous growing (coating) of graphene sheets. The samples were analyzed using conventional characterization techniques: SEM-EDX, XRD, FT-IR, RAMAN, TEM, HRTEM, STEM and XPS.

The quality assurance of malaria microscopy unit was established by National Malaria Control Program, Ministry of Health (MoH) in 2009 to respond to the internal malaria microscopy validation process, in microscopy training for malaria diagnosis in the country, monitoring and supervision, and other relevant activities regarding laboratory diagnosis of malaria in Timor-Leste is described. Trained laboratory technicians who are working in the relevant unit. There are two ways of malaria microscopy validation process such as onsite validation and monthly validation after received malaria blood smear from senior analyst at the municipality level. The aim of this work is to describe the quality assurance of malaria microscopy system in Timor-Leste. The management of quality assurance service support, the importance of quality assurance of malaria microscopy, the role of quality assurance of malaria microscopy, challenge and opportunities encountered by quality assurance microscopy unit, National Health Laboratory are highlighted. Key words: Quality assurance of malaria microscopy, system, Timor-Leste.

The Church of the Company of Jesus in Quito (1605-1765) is one of the most remarkable examples of colonial religious architecture on the World Heritage List. This church has multiple constructive phases and several interventions with no clear record of the entire architectural site, including the historical mortars. A total of 14 samples of coating mortars inside the central nave were taken, with the protocols suggested by the research team and a comparative sample of the architectural group that does not have intervention. The analysis presented in this paper focuses on mineralogical characterization, semi-quantitative analysis by X-ray diffraction and scanning electron microscopy with microanalysis of the samples. The results showed the presence of volcanic aggregate lime and gypsum, used in lining mortars and joint mortars. Mineralogical and textural composition data have allowed the mortar samples to be relatively dated.

The past years have shown the widespread vulnerability of agro-food systems and rural diets to external perturbations such as wars, climate events, and pandemics. Experiencing numerous obstacles, Cuba constitutes an example of success in the transition to agroecological sustainability models. This article characterizes how processes of agricultural change, local development, and industrial degrowth have impacted food availability and dietary diversity among rural livelihoods in the municipality of Yaguajay, Sancti Spíritus, for the past forty years (1980s-2020s). It integrates findings from focus groups, repeated nutritional surveys, and interviews carried out between 2016 and 2022 among residents of the towns of Yaguajay and La Picadora. The goal is to identify effects and response strategies within agro-food systems of rural populations. Distinguishing between periods of abundance and shortage, our findings show two counterpoints: intensive sugar monocrop cultivation which resulted in high dietary variety; and economic crises in 1990s and during the last period of the pandemic, which have led to significant dietary adjustments. The article concludes underscoring the importance of comprehensive assessments of dietary strategies to elicit what agroecological transitions mean for local realities and of the value of food consumption and small-holder production experiences to understand the limits to sustainable transformations.

This mini-review discusses the development and applications of naturally derived bioconjugates from hydroxycinnamic acids, such as coumaric, sinapic, ferulic, and caffeic acids, combined with various biomaterials. These bioconjugates offer a range of benefits including antioxidant properties, UV protection, customized hydrophilic-lipophilic balance, improved safety, solubility, emolliency, biocompatibility, biodegradability, and targeted delivery for biomedical, cosmetic, and food applications. The increasing demand for sustainable and natural products in the biomedical, cosmetic, and food industries has led to the exploration of these hydroxy cinnamic acids and their derivatives. We discuss the synthesis and modification of hydroxy cinnamic acids with biomaterials such as ω-hydroxy fatty acids, castor and lesquerella oils, glycerol, isosorbides, and synthetic polyethylene glycol to form functional phenolipids for biomedical, sunscreen and skincare applications. Techniques such as encapsulation with β-cyclodextrins and modification of biopolymeric supports like polysaccharides and starch are discussed for enhancing bioavailability and solubility. The fine-tuned development of bioconjugates from hydroxycinnamic acids using glycerol to modify the hydrophilic-lipophilic balance, substitution by water-soluble carboxylic acid groups, vegetable oil-based phenolipids, polysaccharides, PEGylation provide enhanced functionalities and offers a promising avenue for creating sustainable and effective products across various applications.

Power generation using renewable technologies has become a primordial option to satisfy the energy demand all over the world, being solar concentrating technologies widely applied for this purpose. A combination of Parabolic Trough Collector with Direct Steam Generation has been considered an excellent option for power generation, due to the economic cost and complexity in the plant are reduced. The thermal evaluation of the solar power plant as well as the PTC in the DSG process is very important in viability and economic analysis. In this sense, as the main objective of this work, a numerical tool for evaluating DSG with PTC technology has been developed. The software SOLEEC is a versatile, reliable, accurate and friendly to the user for thermally evaluating a DSG with PTC technology. The user has the possibility to compare the thermal behavior of different geometrical dimensions for a PTC; and even consider different materials; in order to satisfy the demand of superheated steam by a DSG process. The software has an error less than 5% when compared with literature results and in this paper is used to evaluate a power plant in Mexico obtaining that the change to DSG proposing different PTC could reduce the solar field about 35%.

In recent years, online social media information has been subject of study in several data science fields due to its impact on users as a communication and expression channel. Data~gathered from online platforms such as Twitter has the potential to facilitate research over social phenomena based on sentiment analysis, which usually employs Natural Language Processing and Machine Learning techniques to interpret sentimental tendencies related to users opinions and make predictions about real events. Cyber attacks are not isolated from opinion subjectivity on online social networks. Various security attacks are performed by hacker activists motivated by reactions from polemic social events. In this paper, a methodology for tracking social data that can trigger cyber attacks is developed. Our main contribution lies in the monthly prediction of tweets with content related to security attacks and the incidents detected based on ℓ1 regularization.

SiOx films, frequently derived from amino silane precursors, have found several applications with high added value. Although frequently used, the deposition of coatings from Tris(dimethyl amino)silane (TDMAS) has been reported to demand considerable amounts of energy, mainly due to the difficulty of oxidizing such compound. As it is well known, Plasma-enhanced atomic layer deposition (PEALD) is able to improve the oxidation efficiency even under low process temperatures. Owing to that, PEALD can be considered as a very promising technique for the deposition of SiOx coatings. In this work, it has been investigated the deposition of silicon oxide films using TDMAS at 150°C. It has been evaluated the effect of the plasma oxidation time (6 to 18 s) and of the atmosphere composition (pure O2 or O2+Ar) on the chemical structure, elemental composition and chemical bonding state of the films. Increasing the plasma oxidation time in pure O2 resulted in larger proportion of retained C (Si-CH3) whereas N was preserved in the structure (Si-N). on the other hand, the formation of SiOx films from TDMAS is favored in shorter oxidation times in O2 + Ar plasmas.

Parkinson’s disease (PD) is a progressive neurodegenerative disease characterized by resting tremor, bradykinesia, rigidity, postural instability, that also includes non-motor symptoms such as mood dysregulation. Dopamine (DA) is the primary neurotransmitter involved in this disease, but cholinergic imbalance has also been implicated. Current intervention in PD is focused on replenishing central DA, which provides remarkable temporary symptomatic relief but does not address the neuronal loss and the progression of the disease. It has been well established that neuronal nicotinic cholinergic receptors (nAChRs) can regulate DA release and that nicotine itself may have neuroprotective effects. Recent studies have identified nAChRs in nonneuronal cell types including glial cells, where they may regulate inflammatory responses. Given the crucial role of neuroinflammation in dopaminergic degeneration, and the involvement of microglia and astrocytes in this response, glial nAChRs may provide a novel therapeutic target in prevention and/or treatment of PD. In this review, following a brief discussion of PD, we focus on the role of glial cells and specifically their nAChRs in PD pathology and/or treatment.

Background: To inform global health policies and resources planning, this paper analyzes evolving trends in physical rehabilitation needs, using data on Years Lived with Disability (YLDs) from the Global Burden of Disease Study (GBD) 2017. Methods: Secondary analysis of how YLDs from conditions amenable to physical rehabilitation have evolved from 1990 to 2017, for the world and across countries of varying income levels. Linear regression analyses were used. Results: A 66.2% growth was found in estimated YLD Counts amenable to physical rehabilitation: a significant and linear growth of more than 5.1 billion YLDs per year (99%CI: 4.8–5.4; r² = 0.99). Low-income countries more than doubled (111.5% growth) their YLD Counts amenable to physical rehabilitation since 1990. YLD Rates per 100,000 people and the percentage of YLDs amenable to physical rehabilitation also grew significantly over time, across locations (all p > 0.05). Finally, only in high-income countries Age-standardized YLD Rates significantly decreased (p < 0.01; r² = 0.86). Conclusions: Physical rehabilitation needs have been growing significantly in absolute, per-capita and in percentage of total YLDs, globally and across countries of varying income level. In absolute terms, growths were higher in lower income countries, wherein rehabilitation is under-resourced.

An enormous interest in the development of efficient protocols for cellulose extraction has been demonstrated in the last years, however, they were usually based on non-sustainable chemical and thermal approaches. In this work we describe a new and more sustainable method for cellulose extraction from eucalyptus and pine tree wood waste products exclusively performed using microwave-assisted radiation. The methodology includes 3 main steps: i) alkaline treatment; ii) bleaching I, using H2O2; and iii) bleaching II, an acidic treatment. Samples obtained in each step were characterized by Fourier-transform Infrared (FTIR) spectroscopy, powder X-ray diffraction (PXRD), thermogravimetric analysis (TGA) and differential scanning calorimetry (DSC). The results were compared with those of starting materials, with the commercially available microcrystalline cellulose and with an industrial paper pulp. Results confirmed that for both type of wood wastes, cellulose was retained during the extractions procedures and that the removal of hemicellulose was achieved at the last step as seen by the FTIR spectra and TGA curves. The developed protocol is innovative since it constitutes an easy and quick approach to extract cellulose, from eucalyptus and pine tree wood waste using mild chemical and thermal conditions, microwave irradiation, and environmentally friendly purification steps. This approach offers the possibility of a future scale-up study to potentially apply the develop protocol to the extraction of cellulose in an industrial scale.

Currently, a large part of the wells for agricultural use located in the state of Sonora are overexploited, which generates a high degree of saline intrusion and abandonment by nearby communities. In this paper the temperature effect on the final concentration of permeate water was evaluated through voltage and intel concentration variations in a batch electrodialysis reversal process (EDR), in order to identify optimal operating conditions with emphasis on the reduction of energy consumption and cost of desalinated water. Thirty-six samples were prepared: eighteen 2,000 mg/L total dissolved solids (TDS) samples and eighteen 5,000 mg/L TDS samples; brackish well water of 639 mg/L TDS and synthetic salt were mixed to obtain those concentrations. 3 different temperatures (25, 30, 35 °C) and 2 different voltages (10 and 20 V) were tested for each sample. The best salt removal occurred in the 20 V arrays, with 18.34% higher removal for 2,000 mg/L TDS experiments and 25.05% for 5,000 mg/L experiments (average between the 25 to 35 °C tests). Temperature positively affected EDR, especially in the experiments at 10 V voltage, where increasing 10 °C increased its efficiency by 10.83% and 24.69% for 2,000 and 5,000 mg/L TDS, respectively. Energy consumption was lower with increasing temperature (35 °C), as it decreased by 1.405% and 1.613% for 2,000 and 5,000 mg/L TDS concentrations, respectively (average between 10 and 20 V tests), decreasing the cost per m3 of water.

Some of the lineages of SARS-CoV-2, the new coronavirus responsible for COVID-19, exhibit higher transmissibility or partial resistance to antibody mediated neutralization and were des-ignated by WHO as Variants of Interests (VOIs) or Concern (VOCs). The aim of this study was to monitor the dissemination of VOIs and VOCs in Venezuela during a year. A 614 nt genomic fragment was sequenced for the detection of some relevant mutations of these variants. Their presence was confirmed by complete genome sequencing, with a correlation higher than 99% between both methodologies. After the previously reported introduction of the Gamma VOC since the beginning of the year 2021, the variants Alpha VOC and Lambda VOI were detected as early as March 2021, at a very low frequency. In contrast, the Mu VOI, detected in May 2021, was able to circulate throughout the country. After the detection of Delta VOC in June 2021, it be-came the predominant circulating variant. With the arrival of the Omicron VOC in December, this variant was able to displace the Delta one in less than one month. This succession of variants was accompanied by a reduction in the Cycle threshold (Ct) values, in agreement with the in-crease in transmissibility described for these variants.

Herein are reported the main pros and cons of using the conversational Artificial Intelligence (AI) called “ChatGPT” as a tool to write essays in the academic and scientific community. Also, selected mathematical and scientific problems were solved to determine the effectiveness of this platform. To this end, a systematic case study was designed and conducted to obtain data generated by the chatbot that was further analyzed. Six different topics were chosen for the essay evaluation, and the introduction section was created using this AI. Meanwhile, six mathematical problems related to integrals, z-transform, Laplace transform, and resolution of ordinary differential equations were solved. Furthermore, a scientific problem associated with the structural properties of material was also solved. After data analysis, we concluded that the conversational platform could quickly create written essays with well-structured words. Nonetheless, in almost all cases, the chatbot only used basic information to complete the introduction, and no critical writing was obtained. For the mathematical case study, we observed that under the current status of the ChatGPT, this platform has no ability or skills to solve complex equations. Thus, significant changes need to be conducted to improve the performance of ChatGPT for mathematical solutions.

Taeniid infections pose a significant threat to both animal and public health, as certain tapeworms within this group can also infect humans, potentially leading to severe health conditions. Therefore, this calls for preventive and control measures, such as regular deworming of dogs. While the efficacy of deworming has been established in developed countries, there is a paucity of reported deworming practices in rural areas of developing countries, such as Tanzania. This study aims to understand determinants for helminth treatment-seeking behavior towards control of cestodial taeniid infections in rural settings in northern Tanzania. A cross-sectional study was undertaken in agropastoral and pastoral areas of northern Tanzania. Comprehensive data from household surveys in selected sub-villages were collected to ascertain dog ownership, dog deworming practices, and the availability of dewormers. Analytical methods were employed to discern how various determinants influenced deworming practices among dog owners in these communities. Awareness of dewormers specifically formulated for dogs emerged as a pivotal factor affecting dog deworming practices. Dog owners who were informed about appropriate dog dewormers were nearly two times more likely to engage in deworming compared to those with limited knowledge (OR = 1.78, 95% CI 1.77 - 4.18, p < 0.001). A majority 32(51.6%, 95% CI: 38.7-64.3) acknowledged accessing dewormers for livestock within their wards. Praziquantel a potent dewormer on cestodes was least known to most dog owners 2(13%, 95% CI: 2.3-41.6). Praziquantel, a potent and common dewormer effective against cestodial taeniid infections, remains relatively unknown in rural areas of northern Tanzania. Therefore, more awareness on appropriate deworming agents against taeniids in dogs should be raised in rural dog-keeping communities.

The rise of antibiotic-resistant strains of clinically important pathogens is a major threat to global health security. The World Health Organization (WHO) has recognized the urgent need to develop alternative treatments to address the growing list of priority pathogens. Antimicrobial peptides (AMPs) rank among the various suggested options with proven activity and a high potential to be developed into effective agents. Many AMPs are naturally produced by living organisms and protect the host against pathogens as a part of their innate immunity. Various mechanisms associated with their antimicrobial actions include cell membrane disruption, cell wall weakening, protein synthesis inhibition, and interference in nucleic acid dynamics that can induce apoptosis and necrosis. Acinetobacter baumannii is considered a critical pathogen, and severe clinical problems have appeared with isolates resistant to current antibiotic treatments and conventional control procedures such as UV light, disinfectants, and drying. Here, we review the natural AMPs representing the primary candidates for new anti-A. baumannii drugs in a post-antibiotic era and present the use of computational tools to develop the next generation of AMPs with greater microbicidal activity and reduced toxicity.

Considering tumors from an evolucionary perspective, successive tumor cells undergo turnover in response to stressful conditions which pressures tumor cells to adapt to a new environment. Tumor cells uses parts of themselves to communicate and share biological information, known as extracellular vesicles (EV) secretion to promote their survival and “survive to each and every metabolic cost”. Tumor microenvironment (TME) is a miscellaneous of cells, factors, extracellular matrix proteins and EVs. EVs include smalls (<160nm, exosomes) and larger (100-1,000nm, microvesicles) lipid bilayer enclosed packages of biomolecules that are shed by tumors to TME. Tumor-derived extracellular vesicles transfer adaptative stress signaling to recipient cells, reprograming these cells. Heat Shock Proteins (HSP) are more prominent stress response regulators found in exosomes. HSP-loaded exosomes actively reprogram tumor and TME cells to acquire mechanisms that contribute to tumor progression and therapy resistance. The intercellular communication mediated by HSP-loaded EVs favors the escape of tumor cells from, endoplasmic reticulum (ER) stress, hypoxia, apoptosis and anti-cancer therapies. Extracellular HSPs activate and deactivate immune response, induce cell differentiation, changes vascular homeostasis, and help to augment the pre-metastatic niche formation. Here we will explore the EV mechanism of HSP transmission among TME cells and the relevance of these intercellular communications for resistance to therapies in cancer.

Sr4Al6O12SO4 samples were obtained from the compound mixture formed by a solid–state reaction of Al2O3, SrSO4, and SrCO3. Samples were compacted at 100MPa to form pellets of 1 and 4cm in diameter and were sintered at 1400°C for 4 hours. The compound was analyzed by X–ray diffraction. Static immersion and wettability tests were performed to evaluate corrosion resistance in contact with Al–Si. Corrosion tests were carried out by immersion at 800, 900, and 1000°C for 24, 50, and 100 hours, while wettability was carried out at 900, 1000, and 1100°C for 2 hours. Subsequently, the samples were prepared metallographically. Samples were analyzed by optical microscopy, scanning electron microscopy, and image analysis. In general, reaction products consisting of alumina, spinel, oxides, and sulfates were found. The contact angles obtained were 124° to 135°. It is concluded that ceramic substrate Sr4Al6O12SO4 is resistant to corrosion by Al–Si alloy, since the slight thickness of the reaction products found in the samples (100μm) considering the severe conditions of the experiment: 1000°C and 100 hours of isothermal temperature. Furthermore, it can be said that Sr4Al6O12SO4 is not wettable by Al–Si alloys.

The obtention of simple formulae for the Lebesgue constants arising in the the classical Fourier series approximation is presented. Both even and odd cases are treated enlarging Fejér result. Asymptotic formulae are also obtained.

Acute lymphoblastic leukaemia is currently treated with bacterial L-Asparaginase; however, its side effects bring up the special need for improved and efficient novel enzymes development. Previously, we obtained low anti-asparaginase antibody production and high serum enzyme half-life in mice with the P40S/S206C mutant; however, its specific activity was significantly reduced. Thus, our aim was to test single mutants, S206C and P40S, for in vitro and in vivo assays. Our results showed that the drop in specific activity was caused by P40S substitution. Besides, our single mutants were highly stable in biological environment simulation, unlike double mutant P40S/S206C. The in vitro cell viability assay demonstrated that mutant enzymes have higher cytotoxic effect than WT on T-cells derived ALL and on some solid cancer cell lines. The in vivo assays were performed in mice to identify toxicological effects, to evoke immunological response and to study the enzymes pharmacokinetics. From these tests, none of the enzymes was toxic; however, S206C evoked lower physiological changes and immune responses. In relation to pharmacokinetic profile, S206C has two-fold higher activity than WT and P40S two hours after injection. In conclusion, we present bioengineered E. coli asparaginases with high specific enzyme activity and lesser side effects.

We enhanced the agro-hydrologic VegET model to include snow accumulation and melt processes and the separation of runoff into surface runoff and deep drainage. Driven by global weather datasets and parameterized by Land Surface Phenology (LSP), the enhanced VegET model was implemented in the cloud to simulate daily soil moisture (SM), actual evapotranspiration (ETa), and runoff (R) for the conterminous United States (CONUS) and the Greater Horn of Africa (GHA). Evaluation of the VegET model with independent data showed satisfactory performance, capturing the temporal variability of SM (Pearson correlation r: 0.22–0.97), snowpack (r: 0.86–0.88), ETa (r: 0.41–0.97), and spatial variability of R (r: 0.81–0.90). Absolute magnitudes showed some biases, indicating the need of calibrating the model for water budget analysis. The seasonal Landscape Water Requirement Satisfaction Index (L-WRSI) for CONUS and GHA showed realistic depictions of drought hazard extent and severity, indicating the usefulness of the L-WRSI for the convergence of evidence toolkit used by the Famine Early Warning System Network to monitor potential food insecurity conditions in different parts of the world. Using projected weather datasets and landcover-based LSP, the VegET model can be used not only for global monitoring of drought conditions, but also for evaluating scenarios on the effect of a changing climate and land cover on agriculture and water resources.

Background and Objectives: The techniques directed to the cranial field in osteopathy are the most questioned due to the lack of scientific evidence. In osteopathic practice, manual palpation is essential and, therefore, measuring reliability is fundamental. The objective of study is to assess the reliability and validity of osteopathic treatment depending on experience. Materials and Methods: A cross-sectional study of reliability and validity was conducted. For measurements, a strain gauge was placed on the sphenobasilar synchondrosis of the skull base, and three maneuvers (lateral compression, anteroposterior compression and compression maneuver of the mastoids) were repeated 25 times each by osteopaths with different time of experience (5-10 years, 1-5 years, <1 year). Measurement averages were computed for each of the three maneuvers to verify the average effect of each group in comparison to that of the Gold Standard (GS) (>10 years of experience). Data were analyzed to check for inter- and intra-observer reliability using intra-class correlation coefficients (ICC). Results: Reliability and validity in 5-10 experience of observer 1 and observer 2 in the tree maneuvers was excellent (p<0.001) against GS. Poor or enough reproducibility and concordance were observed in osteopaths with less experience. Conclusion: Experience of osteopaths determines the efficacy of cranial maneuvers in osteopathic treatment for patients’ rehabilitation.

Objective: To map the literature pertaining to adult Person-Centered Rehabilitation (PCR).Data Sources: Following our previously published scoping review protocol, data were identified through: three major databases, snowball searches and expert consultation.Study Selection: Two independent reviewers identified English-language papers which addressed adult physical rehabilitation and met one or more of the six pre-defined inclusion categories for PCR content. Data Extraction: Two independent reviewers extracted key characteristics of included papers (e.g. aims, methods, participants). Quantitative methods (descriptive statistics, regression analysis) and qualitative content analyses were used to synthesize the results. Data synthesis: Of 5084 unique records initially screened, 145 papers were included: 111 empirical, including 11 systematic reviews. Empirical papers had data from 13498 clients and 3849 providers, in total. Yearly publications grew exponentially from 2000 to 2017 (r²= 0.65; p<0.01). Publications were unevenly distributed by countries (e.g. United States’ publications per population size was 45 times lower than New Zealand’s). Most papers focused in more than one profession, setting-type or health conditions, respectively 57.2%, 66.2%, and 60.7%. Finally, more than half of the empirical papers (53.2%) studied implementation of PCR approaches, including its effect. Conclusion: This scoping review synthesizes key characteristics and publication trends in the PCR literature, which is mainly empirical and growing exponentially over time. Stakeholders can use the identified trends, gaps, and literature map to guide further PCR research, and both clinical and organizational practices. The high prevalence of papers focused on multiple professions, settings-type, or health conditions reinforces the need for developing a transdisciplinary, trans-service model of PCR, which will be derived from a thematic analysis of this body of literature.

In a bid to resolve lingering problems in cosmology, more focus is being tilted towards cosmological models in which physical constants of nature are not necessarily real constants, but varying with cosmic time. In this paper we have study cosmology in nonlinear electrodynamics with the Newton's gravitational constant $G$ not a constant but vary in form of power-law of the scale factor of the universe. The evolution of the scale factor $a (t)$ is studied in this model which depends on nonlinear electrodynamics fine tuning term of $\alpha$. Then we check the stability of the model using the speed of sound.

Purpose: Expanded carrier screening (ECS) informs couples of their risk of having offspring affected by certain genetic conditions. Limited data exists assessing the actions and reproductive outcomes of at-risk couples (ARCs). We describe the impact of ECS on planned and actual pregnancy management in the largest sample of ARCs studied to date. Methods: Couples who elected ECS and were found to be at high risk of having a pregnancy affected by at least one of 176 genetic conditions were invited to complete a survey about their actions and pregnancy management. Results: Three hundred ninety-one ARCs completed the survey. Among those screened before becoming pregnant, 77% planned or pursued actions to avoid having affected offspring. Among those screened during pregnancy, 37% elected prenatal diagnostic testing (PNDx) for that pregnancy. In subsequent pregnancies that occurred in both the preconception and prenatal screening groups, PNDx was pursued in 29%. The decision to decline PNDx was most frequently based on the fear of procedure-related miscarriage, as well as the belief that termination would not be pursued in the event of a positive diagnosis. Conclusions: ECS results impacted couples’ reproductive decision-making and led to altered pregnancy management that effectively eliminates the risk of having affected offspring.

This work presents the mathematical framework of the Second-Order Comprehensive Adjoint Sensitivity Analysis Methodology for Response-Coupled Forward/Adjoint Linear Systems (abbreviated as “2nd-CASAM-L”), which enables the most efficient computation of exactly obtained mathematical expressions of first- and second-order sensitivities of a generic system response with respect to functions (“features”) of model parameters. Subsequently, the first- and second-order sensitivities with respect to the model’s uncertain parameters, boundaries, and internal interfaces are obtained analytically and exactly, without needing large-scale computations. Within the 2nd-FASAM-L methodology, the number of large-scale computations is proportional to the number of model features (defined as functions of model parameters), as opposed to being proportional to the number of model parameters, which are considerably more than the number of features, being incomparably more efficient and more accurate than any other methods (statistical, finite differences, etc.) for computing exact expressions of response sensitivities (of any order) with respect to the model’s features and/or primary uncertain parameters, boundaries, and internal interfaces. The application of the 2nd-CASAM-L methodology is illustrated using a simplified energy-dependent neutron transport model of fundamental significance in nuclear reactor physics.

Intersections within urban centers do not allow all citizens to move in a fluid manner. In this sense, this paper proposes a queuing network model based on Kendall's notation for the intersection of two urban streets (East 53rd Street and East 56th Street) in Panama City. A set of traffic lights operating under a fixed time scheme controls the vehicular flow at the intersection. The objective is to optimize the vehicular flow at the intersection by minimizing the waiting time of the vehicles using mathematical models, Linear Regressor Model, and simulations performed in MATLAB evaluating the waiting time experienced by the vehicles. Based on the results obtained, the optimal signal timing of the traffic lights is determined to minimize the waiting time for both streets.

Autonomous weapons systems (AWS), sometimes referred to as “killer robots”, are receiving evermore attention, both in public discourse as well as by scholars and policymakers. Much of this interest is connected with emerging ethical and legal problems linked to increasing autonomy in weapons systems, but there is a general underappreciation for the ways in which existing law might impact on these new technologies. In this paper, we argue that as AWS become more sophisticated and increasingly more capable than flesh-and-blood soldiers, it will increasingly be the case that such soldiers are “in the power” of those AWS which fight against them. This implies that such soldiers ought to be considered hors de combat, and not targeted. In arguing for this point, we draw out a broader conclusion regarding hors de combat status, namely that it must be viewed contextually, with close reference to the capabilities of combatants on both sides of any discreet engagement. Given this point, and the fact that AWS may come in many shapes and sizes, and can be made for many different missions, we argue that each particular AWS will likely need its own standard for when enemy soldiers are deemed hors de combat. We conclude by examining how these nuanced views of hors de combat status might impact on meaningful human control of AWS.

This work introduces the mathematical framework of the novel “First-Order Comprehensive Adjoint Sensitivity Analysis Methodology for Neural Ordinary Differential Equations (1st-CASAM-NODE)” which yields exact expressions for the first-order sensitivities of NODE decoder-responses to the NODE parameters, including encoder initial conditions, while enabling the most efficient computation of these sensitivities. The application of the 1st-CASAM-NODE is illustrated by using the Nordheim-Fuchs reactor dynamics/safety phenomenological model, which is representative of physical systems that would be modeled by NODE while admitting exact analytical solutions for all quantities of interest (hidden states, decoder outputs, sensitivities with respect to all parameters and initial conditions, etc.). This work also lays the foundation for the ongoing work on conceiving the “Second-Order Comprehensive Adjoint Sensitivity Analysis Methodology for Neural Ordinary Differential Equations (2nd-CASAM-NODE)” which aims at yielding exact expressions for the second-order sensitivities of NODE decoder-responses to the NODE parameters and initial conditions while enabling the most efficient computation of these sensitivities.

The role that aquatic aerosols might play in inter-ecosystem exchange in freshwater riparian environments has largely been understudied. In these environments, where freshwater streams are used both as drinking water and for treated waste disposal, water features like waterfalls, downed trees, and increased streamflow can serve as bioaerosol producers. Such water features could have an important role in the bacterial colonization of surrounding surfaces, including the riparian phyllosphere. In this study, we explore the influence of a freshwater stream’s bacterial community composition and micropollution on riparian maple leaves exposed to bioaerosols produced from the stream. Using culture-based and non-culture-based techniques, we compared phylloplane microbial communities in riparian zones, adjacent non-riparian forested zones, and the surface waters of the stream. In this system, riparian zone maple leaf surfaces had higher bacterial counts than non-riparian zone trees. Using metagenomic profiling of the 16S rRNA gene, we found that, while microbial communities on leaves in both riparian zone and forested sites were diverse, riparian zone bacterial communities were significantly more diverse. In addition, we found that riparian leaf bacterial communities shared more amplicon sequence variants (ASVs) with stream bacterial communities than forest leaves, indicating that the riparian zone phyllosphere is likely influenced by bioaerosols produced from water surfaces.

The present minireview assessed the benefits of using artificial intelligence applications in healthcare at predicting the targets of bioactive small molecules in human. Method. The tool is a tuned algorithm, with novel data in web interface. Results. We used tables to order the information of Swiss Target Prediction that allow predictions on combination of chemotherapies and probable side effects. This tool is useful to understand the molecular mechanisms underlying a given phenotype or bioactivity, to rationalize possible favorable or unfavorable side effects and to predict off-targets of known molecules as well as to clear the way for drug repurposing. Predictions are done using a ligand-based approach to compare the similarity between a query molecule and the known ligands of a large collection of protein targets. Conclusion. This study allowed us to formulate recommendations for the use of some of the chemotherapeutic agent groups in cancer patients at a low cost. It is very important and beneficial for patients that take medicine for a longer period and on whose lives depend on such treatment.

Recent discoveries have shown that enteric glial cells play an important role in different neurodegenerative disorders such as Parkinson's disease (PD), which is characterized by motor dysfunctions caused by progressive loss of dopaminergic neurons in the substance nigra pars compacta and non-motor symptoms including gastrointestinal dysfunction. In this study we observed the modulatory effects of the flavonoid rutin on enteric glia in a PD animal model. Adult male Wistar rats were submitted to stereotaxic injection with 6-hydroxydopamine or saline, treated or not with rutin (10 mg/Kg) for 14 days. Intestinal segments (ileum and colon) were collected to analyze tissue reactivity and immunohistochemistry for neurons (HUc/d) and enteric glial cells (S100b) in the myoenteric plexuses. Behavioral tests demonstrated that treatment with rutin im-proved the motor capacity of parkinsonian animals, and also improved intestinal transit without interfering with the cell population; rutin treatment modulated reactivity of the ileal musculature by muscarinic activation, reducing relaxation through the signaling pathway of nitric oxide donors, and increasing the longitudinal contractility of the colon musculature in parkinsonian animals. Rutin demonstrated modulatory activities on the enteric nervous system, bringing relevant answers about the effect of the flavonoid in this system and po-tential application for PD adjuvant treatment.

The Eurasian grapevine (Vitis vinifera L.) is the most widely grown horticultural crop in the world and is important for the economy of many countries. In the wine production chain, grape varieties play an important role as they directly influence the authenticity and classification of the product. Identifying the different grape varieties is therefore fundamental for quality control and inspection activities, as well as for regulating production. Currently, ampelography and molecular analysis are the main approaches to identifying grape varieties. However, both methods have limitations. Ampelography is subjective and prone to errors and is experiencing enormous difficulties as ampelographers are increasingly scarce. On the other hand, molecular analyses are very demanding in terms of cost and time. In this scenario, Deep Learning (DL) and Machine Learning (ML) methods have emerged as a classification alternative to deal with the scarcity of ampelographs and avoid molecular analyses. In this study, the most recent and current methods for identifying grapevine varieties using DL classification-based approaches are presented through a systematic literature review. The classification pipeline of the 31 studies found in the literature was described, highlighting its pros and cons. Most of the studies used DL-based models trained with leaf images acquired in a controlled environment at a maximum distance of 1.2 metres to classify grape varieties. In addition, there is a large gap between practical applications and the datasets used: a great lack of varieties, limited data acquired in the field and a lack of tests on plants under adverse conditions. Potential directions for improving this area of research were also presented.

In this study, four samples of recycled aggregates from construction and demolition waste of Mexico City were characterized, in order to find innovative uses for this type of materials. Gravel and sand from a recycling plant were analyzed, as well as recycled aggregates in the laboratory from demolished concrete collected in landfills. The characterization was carried out by means of XRD, chemical microanalysis (EDS), pH measurement and sieve analysis. The results reveal that the minerals present in the analyzed materials are triclinic feldspars, cristobalite and pyroxene which correspond to the natural aggregates, as well as variable amounts of calcite, product of the carbonation of the cement paste adhered to these aggregates and in a smaller proportion calcium hemicarboaluminate, rosenhanite and tobermorite. It was determined that the quality (amount of cement) of the original concrete that was recycled, has great influence on the granulometry and the chemical-mineralogical composition of the aggregates, since there will be different quantities and qualities of cement paste adhered to the aggregates of according to size. Finally the pH values measured in all samples fluctuate between 10.15 and 12.08, therefore it is suggested that these materials can be used in soil stabilization.

In this paper we describe a method which combines sentiment analysis with machine learning techniques and/or multivariate statistical analysis. By applying this methodology it is possible to classify a collection of texts into two or more groups or clusters. On the basis of a number of previously defined clusters, the novelty of the outlined approach is the use of the sentiment analysis results as input to the machine learning model or multivariate statistical analysis. Once the classifier has been obtained, we can assign a given text into one of the pre-established clusters. The groups or clusters can represent different time periods, classes of texts transcribed from different conversations, etc. The method is illustrated through an example taken from one of the two studies in which we have applied this methodology. In one of the studies, the method was used to classify press news of a volcanic eruption, while in the other study it was used to classify the conversations recorded between a chatbot with different kinds of speakers (humans or chatbots). This last study was the seminal work in which we introduced this methodology.

Institutional sustainability is a dynamic and multifaceted concept that relies on the contributions of various institutions, including the legal and the scientific system. On the other side, consumers boycotts are an expression of political consumerism by which consumers can use their market power to attain sustainability objectives. This article explores institutional trust on the legal system and trust on scientists as potential drivers for consumers’ boycotts. Using data retrieved from the European Social Survey covering twenty-five countries, the study employs binary logistic regression to assess the importance of institutional trust and other potential drivers of product boycotts in Europe. Results confirm that boycotting behaviour is affected by institutional trust, as well as other individual variables including gender, age and life-cycle effects, education, interest in politics and level of satisfaction with the political system, generalized trust, personal well-being, and consumers’ use and perceptions of information and communication technologies. The results of this study enrich the literature on consumer boycotts and have implications for policymakers involved in sustainability initiatives.

Albert Einstein, shortly after publishing his General Relativity Theory (GRT) applied it to the entire universe in a paper of 1917. Einstein assumed that such a universe was static in time and possessed a uniform distribution of matter on the largest scales, obtaining a static and finite universe of spherical spatial curvature of radius R. Although this model was refuted by Edwin Hubble's discovery of the expansion of the universe, it is still often studied as a theoretical framework for some problems, such as the twin paradox. This paper will show that Einstein's static universe model leads to a privileged frame of reference, so that any observer moving at the speed v will be able to measure speeds of light other than c depending on the direction of beam transmission. The above will refute the validity of the application to this closed and static universe of the Special Relativity Theory (SRT) proposed by Einstein in 1905 in his article . In addition, a new synchronization convention and new coordinate transformations will be deduced, the "generic" transformations, which will replace those of Lorentz. Finally, the twin paradox in this universe will be solved by making use of them.

This paper proposes a novel data processing framework dedicated to bedload monitoring in underwater environments. After calibration, by integration the total energy in the nominal bandwidth, the proposed experimental setup is able to accurately measure the mass of individual sediments hitting the aluminum plate. This require a priori knowledge of the vibration trasients in order to match a predefined dictionary. Based on unsupervised hierarchical agglomeration of complex vibration spectra, the proposed algorithms allow to accurately localize the transients corresponding to the shocks created by sediment impacts on a steel plate.

The Independent Component Analysis (ICA) has been recently introduced as a reliable alternative to identify canonical scattering mechanisms within Polarimetric Synthetic Aperture Radar (PolSAR) images. This manuscript addresses two important aspects when applying such methods on real data, namely speckle filtering and statistical classification with ICA. A novel PolSAR data processing framework is introduced by adjusting the Lee's sigma filter to the particular nature of the Touzi's polarimetric decomposition. In its current form, it allows the use of the ICA mixing matrix in the derived speckle filter. An extension of the Fromont at al. iterative segmentation is introduced, equally. This proposed framework is tested using P band airborne PolSAR data acquired for the ESA campaign TropiSAR campaign.

The paper presents the results of the theoretical and practical research on developing the infrastructure for assessment of overall risk (explosion / occupational / terrorist attack) associated with unwanted events such as major accidents that can occur at explosive storehouses for civilian use. The scientific research outlined in this article was carried out within the Nucleu Project PN 16 43 02 15 - “Research on increasing safety levels at technical facilities for storage of explosives for civil use”.

This work (in two parts) will review the recently developed predictive modeling methodology called “4th-BERRU-PM” and its applicability to energy systems as exemplified by an illustrative application to the Polyethylene-Reflected Plutonium (acronym: PERP) OECD/NEA reactor physics benchmark. The acronym 4th-BERRU-PM designates the “Fourth-Order Best-Estimate Results with Reduced Uncertainties Predictive Modeling” methodology, which yields best-estimate results with reduced uncertainties for the first fourth-order moments (mean values, covariance, skewness, and kurtosis) of the optimally predicted posterior distribution of model results and calibrated model parameters. The 4th-BERRU-PM uses the Maximum Entropy (MaxEnt) principle to incorporate fourth-order experimental and computational information, including fourth (and higher) order sensitivities of computed model responses to model parameters, thus incorporating, as particular cases, the results previously predicted by the second-order predictive modeling methodology 2nd-BERRU-PM, and vastly generalizing the results produced by extant data assimilation and data adjustment procedures. The 4th-BERRU-PM methodology encompasses the scopes of high-order sensitivity analysis (SA), uncertainty quantification (UQ), data assimilation (DA) and model calibration (MC). The application of the 4th-BERRU-PM methodology to energy systems is illustrated by means of the above-mentioned OECD/NEA reactor physics benchmark, which is modeled using the neutron transport Boltzmann equation involving 21976 imprecisely known parameters, the solution of which is representative of “large-scale computations.” The model result (“response”) of interest is the leakage of neutrons through the outer surface of this spherical benchmark, which can be computed numerically and measured experimentally. Part 1 of this work illustrates the impact of high-order sensitivities, in conjunction with parameter standard deviations of various magnitudes, on the determination of the expected value and variance of the computed response in terms of the first four moments of the distribution of the uncertain model parameters. Part 2 of this work will illustrate the capabilities of the 4th-BERRU-PM methodology for combining computational and experimental information, up to and including forth-order sensitivities and distributional moments, for producing best-estimate values for the predicted responses and model parameters while reducing their accompanying uncertainties.

The objective of this work was to evaluate the blending and grinding influence over the nutritional, sensorial and sustainable aspects of coffee. To do so, a systematic review of the literature was accomplished. The database for the selection of relevant papers was the Portal de Periódicos da Capes, with remote access via CAFe. For the elaboration of the research, a chronological criterion with period restriction was used, considering the period between 2008-2022, to access all possible works related to the theme of this work. The following terms were used: blending; grinding; coffee; nutrition-al; sensorial; sustainability. To filter the searches, the association of these terms was also used by means of links and word associations. In the terminology, the Boolean operator AND was used to interconnect the terms used. Roasting degree, grinding, and amount of each coffee species impacts the nutritional and sensorial aspects of coffee. And the determination of each blending influences the sustainability of the environment, economic and social aspects of the coffee chain.

The durability of bridge decks is a critical factor in ensuring the safety and longevity of transportation infrastructure. This article explores advanced materials and innovative techniques designed to mitigate cracking in bridge decks, a common issue that can compromise structural integrity and increase maintenance costs. It provides a comprehensive review of cutting-edge solutions such as Fiber-Reinforced Polymers (FRP), High-Performance Concrete (HPC), Ultra-High Performance Concrete (UHPC), and self-healing concrete technologies. Each material is analyzed for its ability to enhance strength, reduce permeability, and improve resistance to environmental stressors. Additionally, the article examines the role of surface treatments, sealants, and routine maintenance practices in prolonging the life of bridge decks. By synthesizing current research and practical applications, this article offers valuable insights and recommendations for engineers, contractors, and policymakers seeking to advance bridge deck durability through innovative materials and methodologies.

Humanity, culture, societal development and language issues are mutually reinforcing much as they are intricately interwoven in a non-ceasing dynamic interrelationships within the matrix defined by language standardization or development, acquisition and use that mostly take up central place as unifying and propelling forces in language discourse. Within the confines of globalization which is neither homogenization nor convergence; but the beginning of drawing on the strength of indigenous capabilities to create knowledge ecology that would enliven socio-economic and scientific development of the world in far reaching interconnectivities and relationships across every clime, issues pertaining to language development, acquisition and use become imperative. It is against this background that this paper examines the development/standardization, acquisition and use of Esan language as one of several Nigerian indigenous languages to promote scientific and technological development through knowledge creation, preservation and dissemination. The obsession of using western model and epistemological outlook to achieve appropriate scientific and technological development to the utter neglect of home grown and culturally distilled efforts were also examined. In the light of the dare consequences and the harsh conditions globalization imposes on developing nations, this paper highlights standardization and use of indigenous languages in chatting appropriate trajectory for effectual developmental efforts in fast shrinking contemporary world.

Endometrial cancer (EC) poses a significant global health challenge, with increasing prevalence in 26 of 43 countries and over 13,000 deaths projected in the United States by 2024. This rise correlates with aging populations, the obesity epidemic, and changing reproductive patterns, including delayed childbearing. Despite the early diagnosis in 67% of cases, approximately 30% of cases present with regional or distant spread, leading to nearly 20% mortality rates. Unlike many cancers, EC mortality rates are escalating, outpacing therapeutic advancements until recently. One of the reasons for this was the lack of effective therapeutic options for advanced disease until recently. The introduction of immunotherapy has marked a turning point in EC treatment, particularly benefiting patients with defects in mismatch repair proteins (dMMRs). However, dMMR status alone does not ensure a favorable response, underscoring the need for precise patient selection. This review explores the pivotal role of mismatch repair proteins in EC, emphasizing their heterogeneity, the challenges in their assessment, and their potential as predictive biomarkers.

Post-viral fatigue syndrome (PVFS) encompasses a wide range of complex neuroimmune disorders of unknown cause characterized by disabling post-exertional fatigue, myalgia and joint pain, cognitive impairments, unrefreshing sleep, autonomic dysfunction, and neuropsychiatric symptoms. It includes myalgic encephalomyelitis, also known as chronic fatigue syndrome (ME/CFS), fibromyalgia (FM), and more recently post-COVID-19 condition (Long COVID). To date, there are no definitive clinical case criteria and no FDA-approved pharmacological therapies for PVFS. Given the current lack of effective treatments, there is a need to develop novel therapeutic strategies for these disorders. Mitochondria, the cellular organelles responsible for tissue energy production, have recently garnered attention in research into PVFS due to their crucial role in cellular bioenergetic metabolism in these conditions. Accumulating literature has identified a link between mitochondrial dysfunction and low-grade systemic inflammation in ME/CFS, FM, and Long COVID. To address this issue, this article aimed to critically review the evidence relating to mitochondrial dysfunction in the pathogenesis of these disorders; in particular, to evaluate the effectiveness of coenzyme Q10 supplementation on chronic fatigue and pain symptoms as a novel therapeutic strategy for the treatment of PVFS.

The objective of this research was to evaluate the production and phytochemical quality of cucumber fruits (Cucumis sativus), in response to the foliar application of different seaweed extracts. This study was carried out under shadow mesh conditions in the autumn - winter agricultural cycle at Instituto Tecnológico de Torreón, Torreón, Coahuila. The experimental design was completely random, using six treatments with six repetitions each. The treatments evaluated were: Macrocystis pyrifera, Bryothamnion triquetrum, Ascophyllum nodosum, Grammatophora sp., Macrocystis intergrifolia, and a control treatment with inorganic fertilization. The substrate used was a mixture of sand and vermicompost. The yield, commercial quality and phytochemical compounds of the fruit were evaluated. Results showed that yield using Steiner solution (6.75 kg m⁻²) was higher than that obtained with Bryothamnion triquetrum algae (6.07 kg m⁻²). Regarding the phenolic content, the extracts surpassed the control treatment, with Macrocystis pyrifera and Macrocystis integrifolia being statistically equal, with values of 47.37 and 43.73 mg equiv. of Ac. Gallic 100 g fresh weight, respectively. The antioxidant capacity by ABTS+ and DPPH+ methods was higher using the treatment with algae Macrocystis pyrifera with 149.4 and 454.1 μM equiv Trolox/100 g fresh base, respectively. This treatment also presented the highest value of vitamin C with 5.07 mg/100 g fresh base, being 27% greater than the control treatment. Algae extracts increased the quality of the fruits by obtaining the highest antioxidant capacity, making their use a viable option to minimize the application of conventional fertilizers, thereby attenuating the effects on the environment and improving the health of the population.

In this contribution a new configuration of a DC-DC Boost and Buck-Boost converters is proposed to track sinusoidal signals exactly, with zero tracking error. The stage is conformed by two DC-DC converters connected to the same load, this is, they are not connected in cascade. To track exactly the sinusoidal reference the control scheme is base on the indirect control algorithm and the harmonic balance method. The proposed algorithm considers a second control input with the end of cancel out the second harmonic, this second harmonic is produced by the non linearity of the model and must be cancelled since there must be a single frequency in the output. The result is such that the converters can track sinusoidal signals with exactly zero error, some numerical results are presented to corroborate the proposal.

Dietzia natronolimnaea C79793-74 has emerged as a potential probiotic strain with implications for managing Crohn's disease. This study evaluates the safety profile of D. natronolimnaea C79793-74 as a probiotic sup-plement. Genotypic characterization involved a 16S rRNA gene and genomic sequencing and genome an-notation. The safety assessment included interrogation of the assembled genome for antibiotic resistance genes and virulence factors, utilizing the CARD and VFDB databases. Notably, the analysis revealed an ab-sence of antibiotic resistance or virulence factors in Dietzia natronolimnaea C79793-74. The safety and tol-erability of D. natronolimnaea C79793-74 were further investigated in an 8-week double-blind, place-bo-controlled clinical trial involving healthy adult participants. A daily dose of 5 x 109 CFU of the probiotic strain was administered. This clinical trial represents the first assessment of the safety of D. natronolimnaea C79793-74 in human subjects. Results demonstrated that participants in both the Dietzia and Placebo groups maintained clinical and hematologic markers within the normal range throughout the study. More-over, the probiotic strain was well-tolerated, with nearly all participants experiencing no severe or medium adverse events. Collectively, the comprehensive data obtained in this study support the inference that Dietzia natronolimnaea C79793-74 is safe and well-tolerated as a nutritional supplement for human con-sumption

Player’s performance in an intense sport such as basketball is known to be related to attributes like speed, agility, and power. This study presents a comparative analysis of associations between anthropometric assessment and physical performance in different age-group elite youth basketball players, while simultaneously identifying the predictors for speed and agility in these players. U14 (n=44), U15 (n=45) and U16 (n=51) players were tested for anthropometry, lower body power, speed, and agility. U16 players were found to be taller, heavier, more muscular than U14 and U15 players. Also, the U16 group showed better performance in all performance tests. Age had a significant positive correlation with countermovement (CMJ) and drop jump (DJ) performance in U14 players, and a significant negative correlation with 10m and 20m sprint times in U15 group. CMJ and DJ emerged as the most significant predictors for sprint and agility variables, respectively. Body fat percentage was found to be a significant predictor for the speed and agility tests in all age groups, but a negative lower-body power predictor. Therefore, besides all sport-specific and fitness tests, it is essential to place emphasis on the percentage of body fat when designing players’ individualized training programs, and during team selection.

Background: As noninvasive prenatal screening usage grows in the general obstetrics setting, proper patient education on the screen’s benefits and limitations is needed. Objective: Describe the use of a technology platform designed for large-scale dissemination of noninvasive prenatal screening information and results. Study Design: The technology platform functioned as follows: Patients were emailed a link to an noninvasive prenatal screening general-education video upon laboratory receipt of a test requisition. Providers were then notified upon availability of patients’ results. If noninvasive prenatal screening results were negative, the patient was sent an automated email with instructions to access results through a secure portal where she could watch tailored informational videos, request “on-demand” or scheduled genetic counseling, or decline any further services. If genetic counseling was elected, a summary of the session was sent to the ordering provider and patient upon completion. If noninvasive prenatal screening results were positive, either the ordering provider or a board-certified genetic counselor contacted the patient directly to communicate test results and provide counseling. The number and type of results issued through the platform, the number and type of genetic counseling consultations completed, and factors associated with requesting laboratory-delivered genetic counseling were tracked and analyzed for a 39-month period. Results: Over the study period, 67,122 noninvasive prenatal screening results were issued through the platform, and 4,673 patients elected genetic counseling consultations; 95.2% (n=4,450) of consultations were for patients receiving negative results. Over 70% (n= 3,370) of consultations were on-demand rather than scheduled. Median consultation time was 14 minutes for positive results and six minutes for negative results. A positive screen, advanced maternal age, family history, previous history of a pregnancy with a chromosomal abnormality, and other high-risk pregnancy were associated with the greatest odds of electing laboratory-delivered genetic counseling. Conclusions: By combining web education, automated notifications, and genetic counseling, we implemented a service that effectively facilitates results disclosure for ordering providers. These data demonstrate the capability to deliver noninvasive prenatal screening results, education, and counseling—congruent with management guidelines—to a large population, which is imperative to quality care as uptake increases.

Pseudo-nitzschia spp. blooms are a recurrent problem in many coastal areas globally imposing some significant threats to the health of human, ecosystems and economy. Monitoring programmes have been established, where feasible, to mitigate the impacts caused by Pseudo-nitzschia spp. and other harmful algae blooms. The detection of such blooms from satellite data could really provide timely information on emerging risks but the development of taxa-specific algorithms from available multispectral data is still challenged by coupled optical properties with other taxa and water constituents, availability of ground data and generalisation capabilities of algorithms. Here, we developed a new set of algorithms (PNOI) for the detection and monitoring of Pseudo-nitzschia spp. blooms over the Galician coast (NW Iberian Peninsula) from Sentinel-3 OLCI reflectances using support vector machine (SVM). Our algorithm was trained and tested with reflectance data from 260 OLCI images and 4607 Pseudo-nitzschia spp. match up data points, of which 2171 were of high quality. The performance of no bloom/bloom model in the independent test set was robust, showing values of 0.80, 0.72 and 0.79 for area under the curve (AUC), sensitivity and specificity, respectively. Similar results were obtained by our below detection limit/presence model. We also present different model thresholds based on optimisation of true skill statistic (TSS) and F1-score. PNOI outperforms linear models, while its relationship with in-situ chlorophyll-a concentrations is weak demonstrating poor correlation with the phytoplankton abundance. We showcase the importance of PNOI algorithm and OLCI sensor for monitoring the bloom evolution between the weekly ground sampling and during periods of ground data absence, such as due to Covid-19.

This paper presents a new methodology that provides the analysis of surface texture changes in areas adjacent to the volcano and its impact product of volcanic activity. To do this, algorithms from digital image processing such as the co-occurrence matrix and the wavelet transform are used. These methods are working on images taken by the Landsat satellite platform sensor 5 TM and Landsat 7 ETM + sensor, and implemented with the purpose of evaluating superficial changes that can warn of surface movements of the volcano. The results were evaluated by similarity metrics for grayscale images, and validated in two different scenarios that have the same type of eruption, but differ, essentially, in climate and vegetation. Finally, the proposed algorithm is presented, setting the parameters and constraints for implementation and use.

The process of blood coagulation, wherein circulating blood transforms into a clot in response to internal or external injury, is a critical physiological mechanism. Monitoring this coagulation process is vital to ensure that blood clotting occurs neither too rapidly nor too slowly. Anticoagulants, a category of medications designed to prevent and treat blood clots, require meticulous monitoring to optimise dosage, enhance clinical outcomes, and minimise adverse effects. This review article delves into the various stages of blood coagulation, explores commonly used anticoagulants and their targets within the coagulation enzyme system, and emphasises the electrochemical methods employed in anticoagulant testing. Electrochemical sensors for anticoagulant monitoring are categorised into two types. The first type focuses on assays measuring thrombin activity via electrochemical techniques. The second type involves modified electrode surfaces that either directly measure the redox behaviour of anticoagulants or monitor the response of standard redox probes in the presence of these drugs. The review provides a comprehensive list of different electrode compositions and their detection and quantification limits. Additionally, it discusses the potential of employing a universal calibration plot to replace individual drug-specific calibrations. The insights presented are anticipated to significantly contribute to the sensor community's efforts in this field.

Rheumatoid arthritis (RA) occurs more frequently in women than in men, and the studies that have addressed clinical and prognostic differences between sexes are scarce and have contradictory results and methodological problems. The present work aims to evaluate sex and gender-related differences in the clinical expression and prognosis of RA as well as the impact on psychosocial variables, coping behavior, and healthcare use and access. By identifying between-sex differences and gender-related outcomes in RA, it may be possible to design tailored therapeutic strategies that consider the differences and unmet needs. Being sex, together with age, the most relevant biomarker and health determinant, a so-called personalized medicine approach to RA must include clear guidance on what to do in case of differences.

In this work, an entropy-stable and well-balanced numerical scheme for a one-dimensional blood flow model is presented. Such scheme is obtained from an explicit entropy conservative flux along with a second order discretization of the source term by using centered finite differences. We prove that the scheme is entropy-stable and preserves steady-states solutions. In addition, some numerical examples are included to test the performance of the proposed scheme.

The functional and neurophysiological distinction between dorsal and ventral hippocampus affects also GABAergic inhibition. In line with his notion, ventral CA1 pyramidal cells displayed a more dynamic and effective response to inhibitory input compared to their dorsal counterparts. We posit that this difference is effected by the dorsal-ventral gradient of activin A, a member of the transforming growth factor-β family, which is increasingly recognized for its modulatory role in brain regions involved in cognitive functions and affective behavior. Lending credence to this hypothesis, we found that in slices from transgenic mice expressing a dominant-negative mutant of activin receptor IB (dnActRIB), inhibitory transmission was enhanced only in CA1 neurons of dorsal hippocampus, where basal activin A level is much higher than in ventral hippocampus. We next asked how a rise in endogenous activin A would affect GABAergic inhibition along the longitudinal axis of the hippocampus. We performed ex vivo recordings from wild type and dnActRIB mice after overnight exposure to an enriched environment (EE), which engenders a robust increase in activing A levels in both dorsal and ventral hippocampi. Compared to control mice from standard cages, the behaviorally induced surge in activin A produced a decline in ventral inhibition, an effect that was absent in slices from dnActRIB mice. Underscoring the essential role of activin in the EE-associated modulation of ventral inhibition, this effect was mimicked by acute application of recombinant activin A in control slices. In summary, both genetic and behavioral manipulations of activin receptor signaling affected the dorsal-ventral difference in synaptic inhibition, suggesting that activin A regulates the strength of GABAergic inhibition in a region-specific fashion.

Today, computer programming is an essential pillar in the education of individuals. Even though technological evolution has eased the massive need for computer programming, a systematic lit-erature review shows some problems remain with teaching computer programing. To address such issues, in this paper we propose an adapted theory, a method, and a model for teaching some knowledge objects associated with the concepts of variables, expressions, comparisons, loops, and functions in programming fundamentals in computer sciences. The main contribution of this study comprises the extension of the concept of didactic transposition to improve teaching in context; in this paper, the idea is called didactic transposition in extensa sensu. The proposal involves the development of a linguistic corpus based on syllabi, textbooks, reference manuals, and a survey applied to experts in teaching programming fundamentals based on seventy-eight universities worldwide. An adapted theory, a method, and a model for teaching programming fundamentals using computational linguistics are produced. In addition, a template is created for designing teaching practices in this regard. The proposal generates an important alternative for the devel-opment of teaching strategies where the conditions of the context are addressed as a priority; ad-ditionally, several aspects are considered for elaborating teaching strategies using computational linguistic techniques from written documents.

The latest World Atlas of Desertification represents a turning point in the diagnosis of desertification. While it forgoes desertification mapping due to the intrinsic complexity of the phenomenon and the impossibility of measuring it using a single indicator, it introduces the Convergence of Evidence paradigm, which identifies socioeconomic and biophysical variables whose behavior allows pointing out those areas prone to desertification. The Spanish National Action Program Against Desertification (PAND), back to 2008, already implemented a similar approach to identify five “desertification landscapes” within Spain using both socio-economic and climatic information. The PAND was not only pioneering but also, unfortunately, accurate. Desertification in Spain has continued to worsen and the first two decades of the 21st century have consolidated an agri-food model whose dynamics have exacerbated the desertification processes identified in the PAND. Despite its scientific value, the PAND lacked a proper action plan and was completely detached from the diagnosis. As a result the diagnosis it provided was not followed by effective actions to halt desertification in Spain. The Spanish Government's recent declaration of climate and environmental emergency requires a new strategy to combat desertification. This commitment is an excellent opportunity to update the diagnosis of the situation and, more crucially, to unify the different desertification sectoral policies and actions under a single front. We provide here elements for a roadmap to be designed around the pressures, impacts, and drivers that define today's Spanish desertification landscapes to manage them effectively and avoid their further degradation.

Materials known as Nd:YAG are crystalline materials of the cubic system made from neodymium-doped yttrium aluminum garnet, which among others, have excellent optical properties. Nd:YAG four-level laser devices are highly used in both the health and industrial sectors. In this study, a simple and inexpensive alternative to manufacturing Nd:YAG materials through solid state reactions following powder processing routes was proposed. For this, an intense mixture of the precursor materials (Al2O3 and Y2O3) was carried out, followed by the addition of neodymium atoms to improve the optical properties of the resulting material. High energy mechanical mixing of the precursor powders resulted in submicron particles, with good size distributions of the powders. The advance of YAG formation was monitored by intermediate phase formation during heat treatment through interrupted tests at different temperatures and analysis by X-ray diffraction. From this analysis, it was found that reaction for the formation of the desired YAG is completed at 1500°C. Fourier-transform infrared spectroscopy analyses determined the presence of functional groups corresponding to the YAG. Finally, the study by optical emission spectroscopy showed wavelengths in agreement with the electronic structure of the elements of the synthesized Nd:YAG.

This paper presents performed Ansys numerical simulation on WindFloat structures. It contributes to the methodology of calculation based on CFD instruments to study the movements of the waves on semi-submersible stationary structures and highlights the importance of using RAO functions. RAO numerical approach developed can be applied to design semisubmersible WindFloat structures in order to fulfill essential requirements regarding operational safety and design. Numerical methodology was designed in accordance marine loads and the I.T.T.C. recommendations. The numerical RAO results for regular wave movements include many elements for the semi-submergible structure. Close results to open sea operation can be achieved by constant improvement in numerical simulation methodologies. The work opens the way for further hydrodynamic development on irregular waves for realistic hydrodynamic and structural response of the actual semi-submersibles at sea. The results demonstrate the accuracy of RAO function approach for specific WindFloat in Jonswap spectrum.

The genus Clostridium is an important group of pathogenic and nonpathogenic Gram-positive anaerobic bacteria with sporulation capacity and wide distribution in different environments, including the gastrointestinal tract of healthy and diseased animals and humans. Among the pathogenic species of the genus, Clostridium chauvoei stands out as a histotoxic agent. It causes important myonecroses such as blackleg, a disease with high lethality and mortality, especially in young cattle, and is responsible for significant losses to livestock worldwide. The pathogenic-ity of the disease is complex and has not yet been fully elucidated. The hypotheses cover pro-cesses from the initial absorption to the transport and deposition of the agent in the affected tis-sues. The virulence factors of C. chauvoei were divided into somatic and flagellar antigens and soluble antigens/toxins, which are the main antigens involved in vaccines against blackleg in Brazil and worldwide. This review provides important information on the first and current ap-proaches to the agent C. chauvoei and its virulence factors, as well as provides a compilation of data on Brazilian studies related to blackleg.

Myalgic Encephalomyelitis, also known as Chronic Fatigue Syndrome (ME/CFS) and Long COVID are characterized by debilitating post-exertional malaise and other core symptoms related to immune dysregulation resultant from post-viral infection, including mitochondrial dysfunction, chronic neuroinflammation and gut dysbiosis. The reported associations between altered microbiota composition and cardinal symptoms of ME/CFS and Long COVID, suggesting that use of microbial preparations, such as probiotics, by restoring the homeostasis of the brain-immune-gut axis may help in the management of symptoms in both conditions. Therefore, this review aims to investigate the implications of alerted gut microbiome and assess the evidence supporting use of microbial-based preparations, including probiotics, synbiotics, postbiotics alone and/or in combination with other nutraceuticals in the management of fatigue, inflammation, as well as neuropsychiatric and gastrointestinal symptoms among patients with ME/CFS and Long COVID.

High efficiency and safety are critical factors in ensuring optimal performance and reliability of systems and equipment across various industries. Fault Monitoring (FM) techniques play a pivotal role in this regard by continuously monitoring system performance and identifying the presence of faults or abnormalities. However, traditional FM methods face limitations in fully capturing the complex interactions within a system and providing real-time monitoring capabilities. To overcome these challenges, Digital Twin (DT) technology has emerged as a promising solution to enhance existing FM practices. By creating a virtual replica or digital copy of a physical equipment or system, DT offers the potential to revolutionize fault monitoring approaches. This paper aims to explore and discuss the diverse range of predictive methods utilized in DT and their implementations in FM across industries. Furthermore, it will showcase successful implementations of DT in FM across a wide array of industries, including manufacturing, energy, transportation, and healthcare The utilization of DT in FM enables a comprehensive understanding of system behavior and performance by leveraging real-time data, advanced analytics, and machine learning algorithms. By integrating physical and virtual components, DT facilitates the monitoring and prediction of faults, providing valuable insights into the system’s health and enabling proactive maintenance and decision-making.

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.

This work continues the review and illustrative application to energy systems of the “Fourth-Order Best-Estimate Results with Reduced Uncertainties Predictive Modeling” (4th-BERRU-PM) methodology. The 4th-BERRU-PM methodology uses the Maximum Entropy (MaxEnt) principle to incorporate fourth-order experimental and computational information, in-cluding fourth (and higher) order sensitivities of computed model responses with respect to model parameters. The 4th-BERRU-PM methodology yields the fourth-order MaxEnt posterior distribution of experimentally measured and computed model responses and parameters, in the combined phase-space of model responses and parameters. The 4th-BERRU-PM methodology encompasses fourth-order sensitivity analysis (SA) and uncertainty quantification (UQ), which were reviewed in the accompanying work (Part 1), as well as fourth-order data assimilation (DA) and model calibration (MC) capabilities, which will be reviewed and illustrated in this work (Part 2). The applicability of the 4th-BERRU-PM methodology to energy systems is illustrated by using the Polyethylene-Reflected Plutonium (acronym: PERP) OECD/NEA reactor physics benchmark, which is modeled using the linear neutron transport Boltzmann equation, involving 21976 im-precisely known parameters. This benchmark is representative of “large-scale computations” such as those involved in the modeling of energy systems. The result (“response”) of interest for the PERP benchmark is the leakage of neutrons through the outer surface of this spherical benchmark, which can be computed numerically and measured experimentally. The impact of the high-order sensitivities of the response with respect to the PERP model parameters is quantified for “high-precision” parameters (2% standard deviations) and “medium-precision” parameters (5% standard deviations). Analyzing the best-estimate results with reduced uncertainties for the 1st- through 4th-order moments (mean values, covariance, skewness, and kurtosis) produced by the 4th-BERRU-PM methodology for the PERP benchmark indicates that, even for systems mod-eled by linear equations (e.g., the PERP benchmark), retaining only first-order sensitivities is insufficient for reliable predictive modeling (including SA, UQ, DA, MC). At least second-order sensitivities should be retained in order to obtain reliable predictions.

Emotion recognition is becoming very relevant in educational scenarios, since previous research has proven the strong influence of emotions on the student's engagement and motivation. There is no standard method for stating student's affect, but physiological signals have been widely used in educational contexts. Physiological signals have been proved to offer high accuracy in detecting emotions because they reflect spontaneous affect-related information, and which is fresh and do not require an additional control or interpretation. However, most proposed works use measuring equipment that limit its applicability in real-world scenarios because of their high cost and their intrusiveness. Expensive material means an economic challenge for schools and reduce the scalability of the experiments. Intrusive equipment can be uncomfortable for the students which can lead to errors in the collected data. In this work, we analyse the feasibility of developing a low-cost non-intrusive device that integrates easy-to-capture signals that guarantee high detection accuracy. The advantage of the approach also lies in using user’s centred information sources (intra-subject) in real-world situations, which provide better detection accuracy, by offering models adapted to each subject. To this end, we present an experimental study that aims to explore the potential application of Hidden Markov Models (HMM) to predict the concentration state from 4 commonly used physiological signals, namely heart rate, breath rate, skin conductance and skin temperature. We study the multi-fusion of every possible combination of these four signals and analyse their potential use in an educational context in terms of intrusiveness, cost and accuracy. Results show that a high accuracy can be achieved with three of the signals when using HMM-based intra-subject models. However, inter-subject models, which are meant to obtain subject-independent approaches for affect detection, fail at the same task. This work concludes that the implementation of a low-cost wrist-worn device for recognising relevant emotions from each student is possible and open the way to a wide range of practical applications in the context of adaptive learning systems.

Keywords: emerging pollutants; pharmaceuticals; plant uptake; soil behavior; soil remediation.

Healthcare-associated infections (HAI) worldwide includes infections by ESKAPE-E pathogens. Environmental surfaces and fomites are important components in HAI transmission dynamics, and shoe soles are vectors of HAI. Ultraviolet (UV) disinfection is an effective method to inactivate pathogenic microorganisms. In this study, we investigated whether the SANITECH UVC shoe sole decontaminator equipment that provides germicidal UVC radiation could effectively reduce this risk of different pathogens. Six standard strains and four clinical MDR strains in liquid and solid medium were exposed to a UVC System at specific concentrations at other times. Bacterial inac-tivation (growth and cultivability) was investigated using colony counts and resazurin as meta-bolic indicators. SEM was performed to assess the membrane damage. Statistically significant reduction in cell viability for all ATCCs strains occurred after 10 sec of exposure to the UVC sys-tem, except for S enterica, which only occurred at 20 sec. The cell viability of P. aeruginosa (90.9%), E. faecalis and A. baumannii (85.3%), S. enterica (82.9%), E. coli (79.2%) and S. aureus (71.9%) was re-duced considerably at 20 sec. In colony count, after 12 sec of UVC exposure, all ATCC strains showed a 100% reduction in CFU counts, except for A. baumannii, which reduced 97.7%. A sub-stantial reduction of colonies above 3 log10 was observed at 12 and 20 sec in all bacterial strains tested, except for A. baumannii ATCC 19606 (12 sec). The exposure of ATCCs bacterial strains to the UVC system for only 2 sec was able to reduce 100% in the CFU count in all ATCCs strains, S. au-reus, P. aeruginosa, E. coli, A. baumannii, E. faecalis, except the S. enterica strain which had a statis-tically significant reduction of 99.7%. In ATCC strains, there was a substantial decrease in colonies after 4 sec (sec) of exposure to the UVC system, with a reduction ranging from 3.78-4.15 log10 CFU/mL. This reduction was observed in MDR/ESKAPE-E strains within 10 sec, showing that UVC could eliminate above 3.84 log10 CFU/mL. SEM showed a reduction of pili-like appendages after UVC treatment in all strains except for E. coli (ATCC 25922). The Sanitech UVC shoe sole decontaminator equipment from Astech Co. effectively killed in vitro a series of ATCCs and MDR/ESKAPE-E bacteria of sanitary interest, commonly found in the hospital environment.

: BACKGROUND: The prevalence of smoking among students is a growing concern, particular-ly among medical students. Being associated with stress, competitiveness, and various social in-fluences, smoking can have detrimental effects on self-esteem and self-efficacy and may create a vicious cycle that may contribute to students’ well-being and academic performance out-comes.METHODS: A cross-sectional study on 456 medical students was conducted via an online survey using structured questionnaires on socio-demographic characteristics, smoking habits, nicotine dependence, self-esteem, and self-efficacy. RESULTS: The prevalence of smoking was 31.1% The scores of self-esteem and self-efficacy were positively correlated with smoking habits (W1=0.957, W2=0.975, P<0.05). Students presented rather low smoking addiction with male stu-dents having slightly higher scores than female students on self-esteem and self-efficacy, mili-tary students had higher self-esteem scores than civilians with physical activity having a posi-tive correlation with non-smoking behavior. CONCLUSION: According to our results, self-esteem and self-efficacy were slightly positively correlated with smoking habits. Furthermore, there was no statistically significant association between other social factors and smoking. Our results may develop a theoretical basis for medical students’ psychological variables studying for further implementation of university educational programs and preventive interventions em-powering students towards an overall better quality of life, addressing, among others, smoking behaviors.

A novel investigation into the structure-function relationship was undertaken to enhance understanding of the mechanism of action of the vasoactive peptide angiotensin II (AngII) using unconventional substitutions such as AIB (α-aminobutyric acid), CHA (cyclohexylalanine acid), IAP (isonipecotic acid), TOAC (2,2,6,6-tetramethylpiperidine-1-oxyl-4-amine-4-carboxylic acid) at position 3, and DMT (2,6-dimethyl-Tyrosine) at position 4. Biological potency assays were conducted on guinea pig ileum, and structural features were analyzed using circular dichroism (CD) and molecular dynamics (MD). CHA3-AngII and AIB3-AngII analogs retained some agonistic activity, whereas IAP3-AngII and TOAC3-AngII derivatives were inactive. CD results indicated low conformational flexibility for AIB3-AngII and CHA3-AngII, and greater conformational restrictions for IAP3-AngII and TOAC3-AngII, consistent with computational modeling analyses. DMT4-AngII exhibited significant agonistic activity compared to the inactive Phe4AngII. Molecular modeling suggested a potential interaction between the hydroxyl group of Tyr4 and the amide bond between positions 7 and 8. AngII showed greater conformational restriction compared to DMT4-AngII and Phe4-AngII, underscoring the importance of tyrosine at position 4.

In December 2019, the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) emerged in the province of Wuhan, China. Since then, it has spread worldwide with new mutations being reported. We performed genomic analysis to identify the changes in genetic diversity of SARS-CoV-2 between December 2019 and November 2020, and through molecular surveillance, we monitored the mutations that could be involved in viral fitness. We analyzed 2,213 complete genomes from 6 geographical regions worldwide, which were downloaded from GenBank and GISAID databases. Although SARS-CoV-2 presented low genetic diversity, there has been an increase over time, with the presence of several hotspot mutations throughout its genome. We identified 7 frequent mutations that resulted in non-synonymous substitutions (dN). Two of them, C14408T>P323L and A23403G>D614G, located in the nsp12 and Spike protein, respectively, emerged early in the pandemic and showed a considerable increase in frequency over time. Two other mutations, A1163T>I120F in nsp2 and G22992A>S477N in the Spike protein emerged recently and have spread in Oceania and Europe. Continuous molecular surveillance of SARS-CoV-2 will be necessary to detect and describe the transmission dynamics of new variants of the virus with clinical relevance. This information is important to improve programs to control the virus.

In recent years, advancements in brain science and neuroscience have significantly influenced the field of computer science, particularly in the domain of reinforcement learning (RL). Drawing insights from neurobiology and neuropsychology, researchers have leveraged these findings to develop novel mechanisms for understanding intelligent decision-making processes in the brain. Concurrently, the emergence of quantum computing has opened new frontiers in artificial intelligence, leading to the development of quantum machine learning (QML). This study introduces a novel model that integrates Quantum Spiking Neural Networks (QSNN) and Quantum Long Short-Term Memory (QLSTM) architectures, inspired by the complex workings of the human brain. Specifically designed for reinforcement learning tasks in energy-efficient environments, our approach progresses through two distinct stages mirroring sensory and memory systems. In the initial stage, analogous to the brain’s hypothalamus, low-level information is extracted to emulate sensory data processing patterns. Subsequently, resembling the hippocampus, this information is processed at a higher level, capturing and memorizing correlated patterns. We conduct a comparative analysis of our model against existing quantum models such as Quantum Neural Networks and their classical counterparts, elucidating its unique contributions. Through empirical results, we aim to underscore the effectiveness of our approach in optimizing energy consumption in practical scenarios.

Rationale: Chronic Granulomatous Disease (CGD) is a rare primary immunodeficiency. Although most mutations are linked to the X chromosome, therefore affecting males, there are autosomal recessive forms that therefore affect both sexes. Clinically it is characterized by recurrent and severe bacterial and fungal infections, with formation of granulomas, due to the inability of phagocytes to generate reactive oxygen compounds, necessary for the intracellular death of phagocytosed microorganisms. Patient concerns: We reported a 12-year-old boy with pneumonia with pneumatocele of possible staphylococcal etiology at one year of age, bilateral orchitis secondary to Salmonella with hematogenous spread, osteomyelitis due to Salmonella, gastroenteritis due to Salmonella enteritidis, liver abscesses due to Staphycococcus aureus and lymphomatoid papulosis and pyodermititis. Diagnoses: In the biochemical diagnosis, the presence of yellow dye (NBT) and absence of dark bluish black dye (formazan) was evidenced. Regarding the genetic diagnosis, the presence of the mutation in exon 10 of CYBB (OMIM 306400) (Xp21.1) that encodes the gp91phox protein was demonstrated. Interventions and outcomes: Treatment was started with trimethoprim/sulfamethoxazole 400/80 mg every 24 hours via oral, and antifungal prophylaxis with itraconazole 200 mg every 24 hours orally is added, after which he does not present serious bacterial or fungal infections, not being able to administer immunomodulatory treatment with recombinant human Interferon gamma-1b. Lessons: The clinical finding of frequent severe infections associated with granulomas, CGD should be suspected. Treatment of this primary immunodeficiency is trimethoprim/sulfamethoxazole and itraconazole. Importantly, it indicated that the mutation in exon 10 of CYBB (Xp21.1) that encodes the gp91phox might influence the pathogenesis of CGD.

Neurotoxicity is a major obstacle to the effectiveness of cisplatin (CDDP) in cancer chemotherapy. In this process, oxidative stress and inflammation are considered to be the major mechanisms involved. The aim was to study the influence of protein quantity on some oxidative parameters in brain and lung of rats treated with cisplatin and N-Acetylcysteine (NAC). Four groups of Wistar rats (6 each one) were fed with a protein diet at 7% for 15 days. Thereafter, the groups were given either a unique dose of cisplatin® 5mg/kg or Acetylcysteine® 5mg/kg as follows: group 1 (control), NaCl 0.9% vehicle; group 2, Cisplatin; group 3, NAC; and group 4, NAC + Cisplatin. The animals were sacrificed, a sample of blood were used to measure blood triglycerides and glucose. The brain and lung were used to assay lipids peroxidation (TBARS), glutathione (GSH), serotonin metabolite (5-HIAA), catalase and the activity of Ca+2, Mg+2 ATPase, using validated methods. TBARS, H2O2 and GSH decreased significantly in cortex and cerebellum/medulla oblongata of groups treated with CDDP and NAC. Total ATPase showed a significant increase in the lung and cerebellum/medulla oblongata, while 5-HIAA depicted the same tendency in cortex of the same group of animals. 5-HIAA and ATPase increase during NAC and Cisplatin administration resulted in brain protection. This effect could even be more powerful when membrane fluidity is increased; thus, proving the efficacy of combined NAC and CDDP drug therapy, which appears to be a promising strategy for future chemotherapy in malnourished patients.

A series of novel substituted isoxazolidine derivatives was synthesized through 1,3-dipolar cycloaddition reactions of α-aryl-N-methyl nitrones with various ethylene moieties, resulting in the formation of isoxazolidine derivatives. The structures of the synthesized compounds were characterized using spectroscopic methods. The [3+2] cycloaddition (32CA) reactions of α-aryl-N-methyl nitrones with diverse ethylene substituents were computed employing Density Functional Theory (DFT) at the B3LYP/6–31G(d) level, upgrading bond parameters. An investigation of the electron localization function (ELF) unveiled the zwitterionic nature of α-aryl-N-methyl nitrones, devoid of pseudoradical or carbenoid centers. Utilization of CDFT indices enabled the prediction of global electronic flux from the strongly nucleophilic α-aryl-N-methyl nitrones to the varied electrophilic ethylene functionalities. Molecular docking and molecular dynamics simulations were conducted on the isoxazolidine derivatives against the EGFR receptor (PDB: 4ZAU). In silico assessment of the synthesized isoxazolidines involved molecular docking, wherein the compound with the highest docking score was subjected to molecular dynamics simulations. Compound 11a, out of the thirty isoxazolidine derivatives, displayed the most substantial binding energy, yielding a g score of -6.57 kcal/mol. These observations highlighted the functional role of amide NH2 and NO2 in the binding process with the target protein, influencing its activity. Furthermore, prediction of ADME drug-likeness properties was performed to identify a suitable candidate.

The concept of “hyperferritinemic syndrome” defines a complex pathophysiological and clinical entity, characterized by a systemic hyperinflammatory state, generally associated with elevated levels of proinflammatory cytokines (hypercytokinemia) and high serum levels of ferritin (hyperferritinemia), traditionally recognized as an iron-binding plasma protein involved in the storage of iron in a biologically available form for different physiological cellular processes. Recent studies have shown that ferritin has other important functions as well, operating both as a proinflammatory mediator and as a immunosupressive agent, its elevated levels in the serum being detected in various conditions associated with inflammatory states, such as infectious diseases, autoimmune and autoinflammatory disorders and, in some cases, in malignancies. Catastrophic antiphospholipid syndrome (cAPS), systemic juvenile idiopathic arthritis (sJIA) and adult-onset Still’s disease (AOSD) and acquired forms of hemophagocytic lymphohistiocytosis (HLH), which includes macrophage activation syndrome (MAS), have been associated with hyperinflammatory states and dramatic elevations of serum ferritin, generating hyperferritinemic syndromes. Severe forms of coronavirus disease-2019 (COVID-19), in which MAS may frequently develop, has also been linked to the development of a hyperferritinemic syndrome. This review offers several insights into the physiological and pathophysiological roles of ferritin in several (hyper-)inflammatory diseases, but also into the causal entities, the underlying pathophysiological mechanisms, clinical manifestations and diagnostic features of somewhat obscure, yet potentially fatal pathological conditions, reunited under the concept of hyperferritinemic syndromes.

Projected future sea level rise and marine storminess is a serious threat for beaches as they induce beach flooding and erosion. Among other factors, wave runup play an important role in beach evolution and must be robustly assessed. However, little attention has been paid to the uncertainties associated to its characterization and how do they compare to other sources of uncertainty. As a first step towards this goal, we have quantified the impact of several sources of error in the estimation of wave runup on sandy beaches. Understanding what factors are more influential in the quality of the results will help to determine the main sources of uncertainty in beach flooding projections. To reach that goal, a calibrated state-of-the-art numerical modelling system has been setup for two beaches in the Mallorca islands (NW Mediterranean). The system has been forced with the best available information of nearshore incoming waves and has been validated against observations to define the benchmark quality. To determine the key factors affecting the quality of the system’s results, different systems configurations have been tested with different degrees of complexity.Our results show that using the most sophisticated modelling system with the best information on boundary conditions, bottom bathymetry, and submerged vegetation leads to a swash RMSE comparable to the standard deviation of the observed swash. We have also found that the choice of lateral boundary conditions (i.e., source of information for the incoming waves) can double the RMSE and induce large biases. Our results also show that using a simple empirical approach usually underestimates the wave runup. However, in locations with vegetated seabed there is a compensation error, and the empirical approach can lead to acceptable results if forced by nearshore waves. In addition, we have compared the error estimates obtained with uncertainties associated to projected sea level rise. Our findings suggest that the uncertainty associated with wave runup modelling should be considered in the assessment of the total uncertainty of future beach flooding, since the analysis performed indicates that this uncertainty can account for between 16% to 60% of the uncertainties linked to mean sea level projections.

This paper proposes a definition of fractional line integral, generalising the concept of fractional definite integral. The proposal replicates the properties of the classic definite integral, namely the fundamental theorem of integral calculus. It is based on the concept of fractional anti-derivative used to generalise the Barrow formula. To define the fractional line integrals the Gr\"unwald-Letnikov and Liouville directional derivatives are introduced and their properties described. The integral is defined first for broken line paths and afterwards to any regular curve

Statistical denoising techniques have been well studied, however many challenges still remain. This 9 article focuses on determining the least necessary number of significant samples in a statistical pop-10 ulation sampling, while minimizing the impact on the statistical detection of the fiber Bragg grating 11 (FBG) power spectra. This is achieved by using Bayesian decision making, small population statis-12 tics while excluding false detection. First, we investigate the impact of two-sided sliding window 13 technique applied near the cell under the test. The window size varies from 8 to 60 samples. The 14 considered maximum size of population sampling is connected with the number of wavelength 15 samples within the bandwidth of the symmetrical FBG power spectra peaks. Regarding the sym-16 metry of FBG power spectra peaks and the possible reduction of computational demands, we inves-17 tigate the impact of a one-sided sliding window. This enables to achieve less processing latency for 18 real time applications thus brings benefits to FBG-based fiber optical sensing. Both, two- and one-19 sided small population sampling techniques are then experimentally verified. Detection results are 20 analyzed in depth via calculating detection thresholds by using the small size window sliding along-21 side the waveband. From results achieved, it was found that the normality three-sigma rule does 22 not need to be followed while using the small population sampling. Experimental demonstrations 23 and analyses showed that the proposed concept of denoising and statistical threshold detection 24 based on the sliding window does not depend on the prior knowledge of probability distribution 25 functions of the FBG power spectra peaks level and background noise. We have also found that the 26 thresholds’ adaptability mainly depends on the statistical numerical characteristics of the above ad-27 ditive mixture of the FBG power spectra peaks signals and background noise.

Music perception in foetuses has been explored under different theoretical paradigms such as habituation, categorical perception, sound preferences and recall. This study investigated the temporal dimension of music perception through the habituation and sensitization paradigm. Foetuses of 41 pregnant women, mean gestational age of 34.7 weeks (±2.4), were observed during ultrasound exams. Foetuses’ reaction to two different tempos (Allegro vs Adagio) and sources (internal vs external) of music stimuli was registered by heart rate variability (HR) and motor response according to the Assessment of Preterm Infants Behaviour scale (APIB) by its factors of movement (MOV) and organization (ORG). A folkloric lullaby, sung and played live with a stringed instrument by a musician, was presented in three stages that were compared to baseline: 1) slow tempo (Adagio), 2) fast tempo (Allegro); and 3) now sung by mother at slow tempo (Adagio). Exploratory analyses showed that all factors increased from baseline to first stage. HR and ORG varied significantly among stages, with HR being the strongest factor. MOV merely detected change from baseline to first stage. ORG decreased for Allegro but increased for maternal Adagio, while HR decreased to near baseline values. ANOVA-repeated measures with gestational age as covariate showed that all measures were sensitive to first music presentation (Adagio), although only HR and ORG differed among stages. Considering estimated marginal means, adjusted for gestational age, HR presented a sensitization pattern throughout stages, but ORG kept habituating to external source and increased to maternal Adagio, suggesting foetal discrimination by sound source. We conclude that foetuses showed different behavioural and physiological responses to external versus internal sound source and musical tempo. The combined use of a behavioural scale (APIB) and HR in foetuses proved to be a valid multidimensional instrument.

This paper presents a methodology based on deep learning models and metaheuristic algorithms for the optimization of airfoils for the design of aircraft wings with large endurance. The use of AZTLI-NN (a neural network with an architecture composed of a multilayer perceptron and a variational autoencoder) is implemented for the prediction of graphs of the aerodynamic coefficients of the airfoil as a function of the angle of attack. This neural network presents good predictions of the aerodynamic coefficients, similar to the coefficients obtained with computational fluid dynamics simulations. AZTLI-NN in combination of metaheuristic algorithms and the CST profile parameterization method show excellent performance in single-objective and multi-objective profile optimization tasks.

Myotoxic phospholipases A₂ are responsible for many clinical signs in envenomation by Bothropssnakes. A new myotoxic acidic PLA₂ Asp 49 was isolated from Colombian Bothrops asper venom. It was isolated by high efficiency liquid chromatography and named BaCol PLA₂. It had a molecular weight of 14180.69 Da and an isoelectric point of 4.4. The complete sequenceobtained by cDNA cloning, with access number in the gene bank MF319968; this sequenceevidenced a mature product of 124 amino acids with Asp in 49 position. In vivoassaysin mice demonstrated profuse oedemaand myotoxicity evidenced by increase of creatinakinasa in plasma and severe and diffuse damage to the muscular fibers, further vacuolization and hyalinization necrosis of the sarcoplasm showed by histopathology with hematoxylin and eosin staining of gastrocnemius muscle. In vitro studies showed cell membrane damage without phosphatidylserine exposure, an early apoptosis hallmark. Further BaCol PLA₂ evidenced high indirect hemolytic activityand moderate anticoagulant action. The toxin showed homology with others acidic PLA₂ isolated from Bothrops venoms, including one isolated from B. asper of Costa Rica. Unlike this, BaCol PLA₂ was myotoxic.

This study introduces a sophisticated neural network structure for segmenting breast tumors. It achieves this by combining a pretrained Vision Transformer (ViT) model with a U-Net framework. The U-Net architecture, commonly employed for biomedical image segmentation, is further enhanced with Depthwise Separable Convolutional Blocks to decrease computational complexity and parameter count, resulting in better efficiency and less overfitting. The Vision Transformer, renowned for its robust feature extraction capabilities utilizing self-attention processes, efficiently captures the overall context within images, surpassing the performance of conventional convolutional networks. By using a pretrained ViT as the encoder in our U-Net model, we take advantage of its extensive feature representations acquired from extensive datasets, resulting in a major enhancement in the model’s ability to generalize and train efficiently. The suggested model has exceptional performance in segmenting breast cancers from medical images, highlighting the advantages of integrating transformer-based encoders with efficient U-Net topologies. This hybrid methodology emphasizes the capabilities of transformers in the field of medical image processing and establishes a new standard for accuracy and efficiency in activities related to tumor segmentation.

The duality is one of the most interesting properties of the Laplace and Fourier transforms associated to the integer order derivative. Here, we will generalize it for fractional derivatives and extend the results to the Mellin, Z and discrete-time Fourier transforms. The scale and nabla derivatives are used.

This article analyzes 6 probability distributions from the Generalized Pareto family, with 3, 4 and 5 parameters, with main purpose to identify other distributions from this family with applicability in flood frequency analysis compared to the distribution already used in the literature from this family such as Generalized Pareto Type II and Wakeby. This analysis is part of a larger and more complex research carried out in the Faculty of Hydrotechnics regarding the elaboration of a norm for flood frequency analysis using the linear moments method. In Romania, the standard method of parameter estimation is the method of ordinary moments, thus the transition from this method to the method of linear moments is desired. All the necessary elements for the distributions use are presented like, the probability density functions, the complementary cumulative distribution functions, the quantile functions, the exact and approximate relations for estimating parameters, for both methods of parameters estimation. All these elements are necessary for a proper transition between the two methods, especially since the use of the method of ordinary moments is done by choosing the skewness of the observed data depending on the origin of the maximum flows. A flood frequency analysis case study, using annual maximum and annual exceedance series, was carried out for the Prigor river, to numerically present the analyzed distributions. The performance of this distributions is evaluated using relative mean error, relative absolute error and linear moments diagram.

This article presents six probability distributions from the Gamma family with three parameters, for the flood frequency analysis in hydrology. The choice of the Gamma family of statistical dis-tributions was driven by its frequent use in hydrology. In the Faculty of Hydrotechnics, the im-provement of the estimation of maximum flows and including the methodological bases for the realization of a regionalization study with the linear moments method with the corrected pa-rameters was researched, being an element of novelty. The linear moments method is better than MOM because it avoids the choice of skewness depending on the origin of the flows, practiced in Romania. The L-moments method conforms to the current trend for estimating the parameters of statistical distributions. Observed data from hydrometric stations are of relatively short length, so the statistical parameters that characterize them are of a sample that requires correction. The correction of the statistical parameters is proposed, using the method of least squares based on the inverse functions of the statistical distributions expressed with the frequency factor for L-moments. All the necessary elements for their use are presented like, quantile functions, the exact and ap-proximate relations for estimating parameters and frequency factors. A flood frequency analysis case study was carried out for the Ialomita river, to verify the proposed methodology. The per-formance of this distributions is evaluated using Kiling-Gupta and Nash-Sutcliff coefficients.

Estimating the parameters of statistical distributions generally involves solving a system of nonlinear equations or a nonlinear equation, being a technical difficulty in their usual application in hydrology. This article presents improved approximations and, in some cases, new approximations for the estimation with the method of ordinary moments and the method of linear moments, which are useful for the direct calculation of the parameters, because the errors in the approximate estimation are similar to the use of iterative numerical methods. Thirteen statistical distributions of two and three parameters frequently used in hydrology are presented, for which parameter estimation was laborious. Thus, the approximate estimation of the parameters by the two methods is simple but also precise and easily applicable by hydrology researchers. The approximate forms characterized by very small errors are the result of the research conducted within the Faculty of Hydrotechnics to update the romanian normative standards in the hydrotechnical field.

The bilateral tempered fractional derivatives are introduced generalising previous works on the one-sided tempered fractional derivatives and the two-sided fractional derivatives. An analysis of the tempered Riesz potential is done and showed that it cannot be considered as a derivative.

Remote sensing datasets are increasingly being used to provide spatially explicit large scale evapotranspiration (ET) estimates. The focus of this study was to estimate and thematically map on a pixel-by-pixel basis, the actual evapotranspiration (ET_a) of the Wonji Shoa Sugarcane Estate using the Surface Energy Balance Algorithm for Land (SEBAL), Simplified Surface Energy Balance (SSEB) and Operational Simplified Surface Energy Balance (SSEBop) algorithms. The results obtained revealed that the ranges of the daily ETa estimated on January 25, February 26, September 06 and October 08, 2002 using SEBAL were 0.0 - 6.85, 0.0 – 9.36, 0.0 – 3.61, 0.0 – 6.83 mm/day; using SSEB 0.0 - 6.78, 0.0 – 7.81, 0.0 – 3.65, 0.0 – 6.46 mm/day, and SSEBop were 0.05 - 8.25, 0.0 – 8.82, 0.2 – 4.0, 0.0 – 7.40 mm/day, respectively. The Root Mean Square Error (RMSE) values between SSEB and SEBAL, SSEBop and SEBAL, and SSEB and SSEBop were 0.548, 0.548, and 0.99 for January 25, 2002; 0.739, 0.753, and 0.994 for February 26, 2002;0.847, 0.846, and 0.999 for September 06, 2002; 0.573, 0.573, and 1.00 for October 08, 2002, respectively. The standard deviation of ET_a over the sugarcane estate showed high spatio-temporal variability perhaps due to soil moisture variability and surface cover. The three algorithm results showed that well watered sugarcane fields in the mid-season growing stage of the crop had higher ET_a values compared with the other dry agricultural fields confirming that they consumptively use more water. Generally during the dry season, ET_a is limited to water surplus areas only and in wet season, ET_a was high throughout the entire sugarcane estate. The evaporation fraction (ETrF) results also followed the same pattern as the daily ET_a over the sugarcane estate. The total crop and irrigation water requirement and effective rainfall estimated using the Cropwat model were 2468.8, 2061.6 and 423.8 mm/yr for January 2001 planted and 2281.9, 1851.0 and 437.8 mm/yr for March 2001 planted sugarcanes, respectively. The mean annual ET_a estimated for the whole estate were 107 Mm³, 140 Mm³, and 178 Mm³ using SEBAL, SSEB, and SSEBop, respectively. Even though the algorithms should be validated through field observation, they have potential to be used for effective estimation of ET in the sugarcane estate.

This paper presents a novel approach to power management techniques in energy storage system (ESS) interoperability with the energy power system (EPS) by inserting a SCADA controlled directional protection relay for improving the mode switching sequence. According with latest European standards, all necessary measures for re-synchronization and reconnection for health work of the system must be taken. The proposed approach intends to improve the “interface” between storage systems and electric power grid by using a directional relay which provides interoperability improvement by automatic recognizing and differentiating the switching sequence of the mode of operation from the fault mode. Simulated results from a small scale electrical generating system are provided. The results demonstrate that the proposed power management solution is technically ideal to achieve high quality energy while retaining the stability of the power grid network. The interoperability of PHS systems integrated with the electric power grid usually leads to perturbations in terms of frequency of the generated voltage, and for improving it we designed an automatic treating and re-connecting software module. This work regards the importance of producing electricity from green and renewable energy sources, while retaining the stability and reliability of the power grid. ESS systems are widely used to help balancing of intermittent forms of load demand on the electrical power grid at specific key moments. In this article, the pumped hydro storage (PHS) technologies are proposed as an economical way to utilize smoothly the off-peak energy or surplus energy, by pumping water to a reservoir at a higher level. During peak load periods, the stored water is discharged through the reversible pump-turbine to generate electricity to meet the peak demand controlled by designed SCADA application.

Research rarely explores LGBTQ+ youth bullying in the context of culture-specific outcomes (e.g., LGBTQ+ identity development) and what can mitigate the impact of peer stressors. This study used a concurrent mixed methods design to explore how experiences of peer victimization predicted LGBTQ+ youth’s identity development (i.e., stigma sensitivity, concealment motivation, and difficult process) and whether social support and outness served as protective, moderating factors. The mixed-methods approach provides a culture-specific context via qualitative inquiry to inform whether the quantitative findings align with how youth qualitatively discuss their experience of bullying, negative outcomes, and social support. Our sample consisted of 349 LGBTQ+ youth 14-17 years old who completed a survey (quantitative sample), and a subset of 39 LGBTQ+ youth who completed a semi-structured interview (qualitative sample). Our quantitative findings indicated that greater overall peer victimization was positively related to LGBIS-revised subscales of stigma sensitivity, concealment motivation, and difficult process, where both outness and social support moderated such relations. Qualitatively, victimized youth also reported stigma sensitivity and concealment motivation, while also endorsing how being out and having a support system played a role in their experience of being victimized. These qualitative findings align with our quantitative findings that classmate support mitigated the effects of peer victimization on difficulty of coming out. Implications for practitioners and researchers are provided.

In response to the COVID-19 pandemic, and resultant cancellation of geoscience fieldwork, as well as outstanding accessibility issues inherent in conducting fieldwork, we developed a virtual geological fieldtrip (VFT) to the Huronian age deposits in the Whitefish Falls area, Ontario, Canada. This region is a geologically significant site in which many Ontario universities conduct undergraduate teaching due to the high-quality exposures. In this contribution we describe and comment on the development of this openly available resource, the motivations in doing so, the challenges faced, its pedagogical impact and relevance, as well as provide suggestions to others in the development of such resources. Our multimedia VFT combines 360° imagery, georeferenced data on integrated maps, and multi-scale imagery (aerial/drone, outcrop, and thin section images). The VFT was built using the Esri Storymaps platform, and thus offers us the opportunity to review the effectiveness of building such resources using this medium, as well as our approach to doing so. We conclude that the Esri Storymaps platform provides a sound medium for the dissemination of multimedia VFTs, but that some aspects of in-person fieldwork remain hard to replicate. Most notably, ‘hands on experience’ and specific activities such as geological mapping. In addition, while VFTs alleviate some accessibility barriers to geoscience fieldwork, substantial barriers remain that should remain the focus of both pedagogical and geoscience work.

The two major global immunisation agenda framings (Missed Opportunity for Immunisation, MOI vs Immunisation Defaulting) are interchangeably and inappropriately used in public health research and practice with flawed or misleading strategies recommended and adopted in various settings globally. This is evident in the fact that many opportunities to adopt evidence/findings from immunisation coverage research in policy are grossly missed. Ineffectiveness of inappropriate interventions from biased evidence can discourage and mislead the governance to make radical decisions by discretion. This could be the reason for the inability of low-and middle-income countries to vaccinate 80% of their children and otherwise; this also poses a global health threat to capable nations. The current guideline and information on MOI and immunisation defaulting appear insufficient and a little clarification on it would assist forerunners in immunisation to achieve measurable progress in ensuring good coverage especially in low-and middle-income countries. Consequently, this paper is aimed at addressing this issue in immunisation practice with appropriate recommendations. Optimistically, this will stimulate further discussions, streamline differences, and gear global immunisation governance on the subject matter, to achieve the target coverage by 2030 in low-and middle-income countries.

The purpose of this study is to estimate the mean transitioning probabilities from a Healthy state to malaria positive uncomplicated state or to malaria positive severe state. It also classifies the various transitioning probabilities of moving through the various states based on some baseline characteristics. Malaria test results for 2019 over a 12-month period were collected from the University of Ghana school clinic. An H-U model for the study was developed and the transition rates from the cross-sectional data are indicated. With two states Healthy (H) and Uncomplicated (U) forming a state space, there were four possible transitions. The results show that the probability of transitioning from a Healthy state to a malaria positive state is 0.03% while the probability that an individual will remain at Healthy state (H) after the test is 99.73%. It was found that if an individual is already positive and has taken medication the probability that its second test came out negative is 6.45% while the chances that it will remain positive but uncomplicated is 93.55%. The study also showed that in the long run, about 95.98% of persons who visited the student clinic with malaria symptoms recorded negative tests for malaria parasite while about 4% recorded positive for malaria. In terms of disaggregation by gender, it was realized that the number of reported negative test results were higher for females (97.08%) than for males (96.13%). However, the infection rate is higher for males (3.87%) than females (2.92%). It is recommended that in as much as the University of Ghana has two health centers (a clinic and hospital), there should be a centralized system to track students’ health so research done would not be biased.