The Zika virus (ZIKV) epidemic brought new discoveries regarding arboviruses, especially flaviviruses, as ZIKV was described as sexually and vertically transmitted. The latter shows severe consequences for the embryo/fetus, such as congenital microcephaly and deficiency of the neural system, currently known as Congenital ZIKV Syndrome (CZS). To better understand ZIKV dynamics in trophoblastic cells present in the first trimester of pregnancy (BeWo, HTR-8, and control cell HuH-7), an experiment of viral kinetics was performed for African MR766 low passage and Asian-Brazilian IEC ZIKV lineages. The results were described independently, and demonstrated that the three placental cells lines are permissive and susceptible to ZIKV. We noticed cytopathic effects that are typical in vitro viral infection in BeWo and HTR-8. Regarding kinetics, MR766lp showed peaks of viral loads in 24 and 48 hpi for all cell types tested, as well as marked cells death after peak production. On the other hand, HTR-8 lineage inoculated with ZIKV-IEC exhibited increased viral production in 144 hpi, with a peak between 24 and 96 hpi. Furthermore, IEC had peak variations of viral production for BeWo in 144 hpi. Both cells types continued alive during the process of viral replication. Considering such in vitro results, the hypothesis that maternal-fetal transmission is probably a way of virus transmission between the mother and the embryo/fetus is maintained.

We show that low quality of all 427 Brazilian SARS-CoV-2 genomes recently published in Science (1) challenges their phylogenetic inference and may lead to incorrect typing of viral strains in clades with no statistical support. Absence of basecalling quality in genome assemblies and proper phylogeny parameter estimates preclude the assessment of signal-to-noise ratio in the data, downstream analysis and conclusions.

Background: The presence of HIV residual replication markers was investigated among distinct subgroups of individuals on antiretroviral treatment (ART). Methods: One hundred sixteen patients were distributed into 5 treatment groups: first-line suppressive ART with a non-nucleoside analog reverse-transcriptase inhibitor (NNRTI) (n = 26), first-line suppressive ART with boosted protease inhibitors (PI-r) (n = 25), suppressive salvage therapy using PI-r (n = 27), suppressive salvage therapy with PI-r and raltegravir (n = 22) and virologic failure (n = 16). Episomal and total DNA quantitation was evaluated. HIV antibody and LPS quantitation was performed. Results: Episomal DNA was positive in 26% to 38% of individuals under suppressive ART, and it was higher among ART virologic failure group (p = 0.04). HIV proviral load was higher among patients with detectable episomal DNA (p = 0.01). Individuals receiving initial PI-r treatment presented lower HIV antibody (p = 0.027) and LPS (p = 0.029) levels than individuals receiving NNRTI. There was a negative correlation between episomal DNA quantitation and the duration of suppressive ART (p = 0.04), CD4+ T-cell count (p = 0.08), and CD8+ T-cell count (p = 0.07). Conclusions: Residual HIV replication has been inferred among individuals under suppressive ART according to episomal DNA detection. Residual replication may decrease with longer periods of suppressive ART and higher levels of CD4+ and CD8+ T cells. The relationship between episomal DNA and total DNA suggests there is a replenishment of the proviral reservoir. Lower antibody and LPS levels among patients with initial PI-r ART suggest these regimens may more effectively suppress HIV, more effectively decreasing HIV antigenic component.

The generation of eucalypt sawdust has increased in Uruguay with the expansion of pulp and paper industrial sites. Currently, most of this readily available feedstock is either not used or applied for producing heat and power by combustion in biomass boilers. In this work, eucalypt sawdust was subjected to steam explosion as the first step for cellulosic ethanol production within the biorefinery concept. The effect of sawdust moisture content, pretreatment temperature and residence time were evaluated, along with the influence of water washing of steam-exploded solids on enzymatic hydrolysis and fermentation yields. After steam explosion, 60% xylans and 97% acetyl groups were recovered mainly as oligomers and acetic acid in the pretreatment liquor. Eucalypt sawdust moisture content affected the enzymatic hydrolysis performance and glucan conversion efficiency. Water washing after pretreatment improved hydrolysis efficiencies and ethanol production yields by 10% with respect to the unwashed pretreated solids at the same experimental condition. The best ethanol yields were obtained using PSSF (pre-saccharification and simultaneous saccharification and fermentation) after pretreatment at 205°C for 10 min, using sawdust with an 8% moisture content. In this case, 227 L ethanol and 40 kg total xylose (including xylo-oligomers) were obtained per ton of dry eucalypt sawdust.

Different therapeutic strategies have been investigated to target and eliminate HIV-1-infected cells by using armed antibodies specific to viral proteins, with varying degrees of success. Herein, we propose a new strategy by combining photodynamic therapy (PDT) with HIV Env-targeted immunotherapy, and refer to it as HIV photoimmunotherapy (PIT). A human anti-gp41 antibody (7B2) was conjugated to two photosensitizers with different charges through different linking strategies; “Click” conjugation by using an azide-bearing porphyrin attached via a disulfide bridge linker with a drug-to-antibody ratio (DAR) of exactly 4, and “Lysine” conjugation by using phthalocyanine IRDye 700DX dye with average DARs of 2.1, 3.0 and 4.4. These photo-immunoconjugates (PICs) were compared via biochemical and immunological characterizations regarding the dosimetry, solubility, and cell targeting. Photo-induced cytotoxicity of the PICs were compared using assays for apoptosis, reactive oxygen species (ROS), photo-cytotoxicity, and confocal microscopy. Targeted phototoxicity seems to be primarily dependent on the binding of PS-antibody to the HIV antigen on the cell membrane, whilst being independent of the PS type. This is the first report of the application of PIT for HIV immunotherapy by killing HIV Env-expressing cells.

This work aimed at producing lactic acid (LA) from sugarcane bagasse after steam explosion at 195 ºC for 7.5 and 15 min. Enzymatic hydrolysis was carried out with Novozymes’ Cellic CTec3 and/or Cellic HTec3, whereas fermentation was performed with Bacillus coagulans DSM2314. Water-washing of pretreated solids before enzymatic hydrolysis improved both hydrolysis and fermentation yields. The presence of xylo-oligosaccharides (XOS) in substrate hydrolysates reduced hydrolysis efficiency, but their effect on fermentation was negligible. The presence of fermentation inhibitors in C5 streams was circumvented by adsorption on activated carbon powder with no detectable sugar losses. High carbohydrates-to-LA conversions (Yp/s) of 0.88 g·g-1 were obtained from enzymatic hydrolysates of water-washed steam-exploded materials that were produced at 195°C, 7.5 min and the use of centrifuged-but-never-washed pretreated solids decreased Yp/s by 16%. However, when the detoxified C5 stream was added at a 10% ratio, Yp/s was raised to 0.93 g·g-1 for an LA productivity of 2.55 g·L-1·h-1. Doubling the pretreatment time caused a decrease in Yp/s to 0.78 g·g-1, but LA productivity was the highest (3.20 g·L-1·h-1). For pretreatment at 195°C for 7.5 min, elimination of water washing seemed feasible, but the use of longer pretreatment times made it mandatory to eliminate fermentation inhibitors.

Zika virus (ZIKV) is a notable arbovirus with maternal, sexual, and TORCH-related transmission capabilities. After 2015, Brazil had the highest number of ZIVK-infected pregnant women who lost their babies or delivered them with Congenital ZIKV Syndrome (CZS). ZIKV infection has been linked to variations in endogenous retroviruses (ERVs) and interleukins within the placenta. ERVs, remnants of ancient viral infections integrated into the genome, include syncytin receptors crucial for placental development. Interleukins, immune response regulators, aid immune tolerance and support syncytial structure development in the placenta, where syncytin receptors facilitate vital cell-to-cell fusion events. Since ZIKV can infect trophoblast cells, we investigated the relationship between ZIKV infections and ERV and interleukin modulations. Investigating the impact of ZIKV on trophoblast cells, we examined two cell types (BeWo and HTR8) infected with ZIKV-MR766 (African) and ZIKV-IEC-Paraíba (Asia-Brazilian) using Taqman and RT2 Profiler PCR Array assays. While early ZIKV infection (24-48 hours) did not induce differential ERV and interleukin expression, future studies involving additional trophoblastic cell lineages and extended infection timelines will illuminate the dynamic interplay between ZIKV, HERVs, interleukins, and cytokines essential for placental formation and function.

The objective of the study was to apply the principles of analytical quality by design (AQbD) to the analytical method for the determination of the radiochemical purity (PQR) of the radiopharmaceutical sodium iodide 131I oral solution, by means of thin layer chromatography (TLC) with a Radio-TLC scanner, the same one that allows to evaluate the quality of the product. For the AQbD, the analytical objective profile (ATP), critical quality attributes (CQA), risk management, the method operable design region (MODR) were defined through the response surface methodology for method optimization using the MINITAB ® software, Control Strategy and the validation of the method where the parameters of selectivity, linearity, precision, robustness, detection limit, quantification limit, range and stability of the sample solution were evaluated. Under the experimental conditions, the conditions of the method were demonstrated by TLC-Scanner and optimization was carried out for an injection volume of 3 µL, radioactive concentration of 10 mCi/mL and carrier volume of 40 µL. It was statistically demonstrated that the method is selective for the 131I iodide band Rf of 0,8 and for the radiochemical impurity IO₃⁻ Rf of 0.6, linearity from 6,0 to 22.0 mCi/mL, intermediate precision with Global RSD of 0,624%, robustness with global RSD 0,101%, detection limit of 0,09 mCi/mL, quantification limit of 0.53 Ci/mL, conforming range, and stability of the sample solution evaluated over time 0, 2 and 20 hours with a global RSD of 0,362%, obtaining consistent results. The development of the method based on AQbD allowed the generation of a design space and an operational space with knowledge of all the characteristics and limitations of the method, likewise in all the operations the conformity of the tests to the acceptance criteria was verified. The validity of our method is concluded under the established conditions, suitable for use in the manufacturing process of sodium iodide 131I and application in nuclear medicine services.

In this article we propose an application of humanitarian logistics theory to build a supportive framework for economic reactivation and pandemic management based on province vulnerability against COVID-19. The main research question is: which factors are related to COVID-19 mortality between Peruvian provinces? We conduct a spatial regression analysis to explore which factors determines the differences in COVID-19 cumulative mortality rates for 189 Peruvian provinces up to December 2020. The most vulnerable provinces are characterized by having low outcomes of long-run poverty and high population density. Low poverty means a high economic activity that leads to more deaths of COVID-19. There is a lack of supply of a set of relief goods defined as Pandemic Response and Recovery Supportive Goods and Services (PRRSGS). These goods must be delivered in order to mitigate the risk associated to COVID-19. A supportive framework for economic reactivation can be built based on regression results and a delivery strategy can be discussed according to the spatial patterns that we found for mortality rates.

This study investigated different conditions for the hydrothermal co-liquefaction (co-HTL) of sugarcane bagasse and residual cooking soybean oil, with and without the presence of ethanol as a cosolvent to maximize the bio-crude yield. All co-HTL reactions were carried out in a 300 mL Parr® reactor at temperatures ranging from 200 to 300 °C. Bio-crude yields of around 95 wt.% were obtained at 300 °C using ethanol and water as solvents. The highest biochar yield (16.6 wt.%) was achieved when using only sugarcane bagasse as substrate, without the presence of soybean oil. Bio-crude samples obtained at higher temperatures (280 °C and 300 °C) using ethanol as a hydrogen donor presented higher contents of both free fatty acids and fatty acid ethyl esters. This work presents a promising process to produce high-quality bio-crude using an abundant feedstock (sugarcane bagasse) in the presence of a lipid source which could cause environmental problems if poorly handled.

The Active Distribution Networks (ADNs) are Multi-Input Multi-Output (MIMO) systems with coupled dynamics which cause interactions among the control loops of the Distributed Energy Resources (DERs). This undesired effect lead to performance degradation in the voltage control. To mitigate the effects of these unavoidable coupling, the present paper proposes a systematic design procedure based on the analysis of the interaction's sources. In details, each DER is equipped with a double loop PI to control the active and reactive powers output by the Voltage Source Converter (VSC) which connects the DER to the network's node. Furthermore, to guarantee Ancillary Services (ASs), the two loops are coupled by a simple mechanism of cooperation of the active power to voltage regulation realized by a filtered droop law. To achieve voltage regulation with reduced loop interactions, the PI parameters and the filter's pulse are designed according to a two sequential steps procedure based on the (Internal Model Control) IMC technique. Simulation studies are finally presented to demonstrate that the proposed design method achieves both reduction of the loop interaction and robust voltage control in presence of model parameter uncertainty in the MIMO model.

Abstract: COVID-19 in 2020 brought challenges to the Brazilian public health system with an emerging virus with respiratory contagion called SARS-CoV-2. There are few studies in Brazil and in some countries, on the increased incidence of certain viral respiratory infections, includ-ing H1N1 and coronavirus and their association with low levels of vitamin D, zinc and iron. The aim of this study was to demonstrate that the deficit of vitamin D, zinc and iron has an impact on the infectious process of patients with COVID-19 and to establish new forms of prevention for the worsening of COVID-19 in the human body. Data were collected from medical records and test results from patients being followed up during the treatment period for COVID-19. Patients with low blood levels of vitamin D, zinc and iron during the treatment period of COVID-19 had a higher percentage of worsening and complications requiring hospitalization in intensive care beds. The ingestion of vitamin D, zinc and iron in the treatment period of patients with COVID-19 in addition to being an immunological protector against SARS-CoV-2 and alleviating the process of worsening the disease can also act as a biomarker in cases of this disease.

Geodetic networks are essential for most geodetic, geodynamics and civil projects, such as monitoring the position and deformation of man-made structures, monitoring the crustal deformation of the Earth, establishing and maintaining a geospatial reference frame, mapping, civil engineering projects and so on. Before the installation of geodetic marks and gathering of survey data, geodetic networks need to be designed according to the pre-established quality criteria. In this study, we present a method for designing geodetic networks based on the concept of reliability. We highlight that the method discards the use of the observation vector of Gauss-Markov model. In fact, the only needs are the geometrical network configuration and the uncertainties of the observations. The aim of the proposed method is to find the optimum configuration of the geodetic control points so that the maximum influence of an outlier on the coordinates of the network is minimum. Here, the concept of Minimal Detectable Bias defines the size of the outlier and its propagation on the parameters is used to describe the external reliability. The proposed method is demonstrated by practical application of one simulated levelling network. We highlight that the method can be applied not only for geodetic network problems, but also in any branch of modern science.

Spacetime torsion is known to be highly suppressed at the end of inflation, called preheating. Of course this fact does not avoid that metric could affect the cosmic dynamos at preheating phase as was showed by Bassett et al, in the general relativity (GR) case. In this paper, is to show that a torsionful magnetogenesis in QED effective lagrangean, drives either a torsion damping or an amplification mechanism or dynamo effect, depending upon torsion chirality. The present extension of Basset et al theory yields a new magnetic field expression $B\sim{a^{(1\pm{\beta})}}$, obtained from dynamo equation in QED. Here a cosmic factor ${\beta}=g_{T}{\eta}k$ is present. In a second example we find Higgs inlationary fields in Einstein-Cartan gravity thick domain walls (DWs). Recently a moodified Einstein-Cartan gravity was given by M Shaposhnikov et al [PRL (2020)] to obtain higgs like inflatons as a portal to dark energy.

Catalytic studies for hydrogen production via steam reforming of ethanol (SRE) are essential for process optimization. Likewise, selecting the ideal support for the active phase can be critical to achieve high conversion rates during the catalytic steam reforming. In this work, copper-based catalysts were synthesized using two different supports, NaY zeolite and Nb2O5/Al2O3 mixed oxides. The materials were prepared using wet impregnation and characterized for their physicochemical properties using different analytical techniques. Differences in catalyst morphologies were readily attributed to the characteristics of the support. The Cu/NaY catalyst showed better textural properties than Cu/Nb2O5/Al2O3, resulting in a homogeneous metal dispersion over the support surface. Both catalytic systems were active in SRE, but Cu/NaY resulted in higher ethanol conversions compared to Cu/Nb2O5/Al2O3. Hence, the performance of copper-based catalysts was influenced significantly by the textural properties of the support.

Species belonging to the Bauhinia genus, usually known as "pata-de-vaca", are popularly used to treat diabetes. Among them is Bauhinia ungulata var. obtusifolia (Ducke) Vaz, whose leaves are used, as a tea, for medicinal purposes in the Amazon region. The microencapsulation of the aqueous extract of its leaves, containing phenolic compounds, using five different wall materials (maltodextrin: DE11-14, and DE4-7; β-cyclodextrin; pectin, and sodium carboxymethylcellulose) is described in this paper. The microstructure, particle size, thermal behavior, yield, and encapsulation efficiency were investigated and compared using different techniques. Using high-performance liquid chromatography, phenolics, and flavonoids were detected and quantified in the microparticles. Microparticles, obtained with yield and phenolics encapsulation efficiency ranging between 60-83 % and 35-57 %, respectively, showed a particle size distribution between 1.15 and 5.54 µm, spherical morphology, and wrinkled surface. Among them, those prepared with sodium carboxymethylcellulose and pectin proved to be thermally the most stable. They had the highest flavonoid content (23.07 and 21.73 mgRUTE/g Extract) and total antioxidant activity by both the DPPH· (376.55 and 367.86 µmolTrolox/g Extract) and ABTS·+ (1085.72 and 1062.32 µmolTrolox/ g Extract) assays. The chromatographic analyses allowed for quantification, in the microparticles, chlorogenic acid (1.67-1.98 mg/g Extract), p-coumaric acid (0.06-0.08 mg/g Extract), rutin (11.1-12.9 mg/g Extract) and isoquercitrin (0.47-0.53 mg/g Extract), compounds considered responsible for the antidiabetic property attributed to the species.

Environmental perception is a powerful tool for identifying community needs and potential within their surroundings. This study assessed tourists' environmental perception regarding solid waste and its impact on the Hurtado balneary, located in Valledupar, Colombia. From May to July 2023, the investigation delved into the environmental attitudes and behaviors of 769 balneary users by employing a combination of observation, photographic documentation, and a comprehensive 21-question online survey. The findings unveiled compelling insights: an overwhelming 98.8% of participants acknowledged the adverse effects of solid waste on the environment, with an impressive 98% demonstrating a willingness to participate in waste management efforts. Alarmingly, 42.13% exhibited limited awareness of waste management practices, reflecting a lack of public interest and commitment (41.61%). Statistically significant disparities emerged: 59% of waste items were not appropriately disposed of in designated receptacles. Reasons for this included a lack of a sense of belonging (50.2%) and inadequate environmental education (45.6%). 96% expressed the need for river conservation signage, while 59.8% had not engaged in environmental training. The implications of these results extend beyond the Hurtado balneary, potentially informing solid waste management strategies in other aquatic environments. Furthermore, this investigation aligns with three critical Sustainable Development Goals: SDG 12, emphasizing responsible consumption and production; SDG 13, addressing climate action; and SDG 15, advocating for life on land and below water. Keywords: Tourism; solid waste; surface water; environmental management.

Mycobacterium tuberculosis complex causes tuberculosis (TB), a disease that causes pulmonary inflammation but can also affect other tissues. Despite macrophages having a defined role in TB immunopathogenesis, other innate immune cells, such as neutrophils, are involved in this process. These cells have high phagocytic ability and a microbial-killing machine comprised of enzymes, antimicrobial peptides, and reactive oxygen species. In the last two decades, a new neutrophil immune response, the neutrophil extracellular traps (NETs), has been intensely researched. NETs comprise DNA associated with histones, enzymes, and antimicrobial peptides. These structures are related to antimicrobial immune response and some immuno-pathogenesis mechanisms. This mini review highlights the role of NETs in tuberculosis and how they can be helpful as a diagnostic tool and/or therapeutic target.

The use of video in education has become ubiquitous as technological developments have markedly improved the ability and facility to create, deliver and view videos. The concomitant pedagogical transformation has created a sense of urgency regarding how video may be used to advance learning. Initial reviews have suggested only limited potential for the use of video in higher education. More recently, a systematic review of studies on the effect of video use on learning in higher education, published in the prestigious Review of Educational Research, found, overall, effects to be positive. In the present paper we critique this study and provide some needed clarity to the state of research on learning via video in higher education. We reveal significant gaps in the study methodology and write-up and use a cognitive processing lens to critically assess and reanalyse study data. We found results of this study to be only applicable to learning requiring lower-level cognitive processing and conclude, consistent with prior research, learning benefits remain limited.

Parkinson’s-disease (PD) is an incurable age-related neurodegenerative disease and its global prevalence of disability and death has increased exponentially. Although motor symptoms are the characteristic manifestations of PD, the clinical spectrum also contains a wide variety of non-motor symptoms, which are the main cause of disability and determinants of the decrease in a patient's quality of life. Noteworthy in this regard is the stress on the cardiac system that is often observed in the course of PD, however its effects have not yet been adequately researched. Here, an untargeted metabolomics approach was used to assess changes in cardiac metabolism in the 6-hydroxydopamine model of PD. Beta-sitosterol, campesterol, cholesterol, monoacylglycerol, α-tocopherol, stearic acid, beta-glycerophosphoric acid, o-phosphoethanolamine, myo-inositol-1-phosphate, alanine, valine and allothreonine, are the metabolites that significantly discriminate Parkinsonian rats from sham counterparts. Upon analysis of the metabolic pathways with the aim of uncovering the main biological pathways involved in concentration patterns of cardiac metabolites, biosynthesis of both phosphatidylethanolamine and phosphatidylcholine, glucose-alanine cycle, the glutathione metabolism and plasmalogen synthesis most adequately differentiated sham and Parkinsonian rats. Our results reveal that both lipid and energy metabolism are particularly involved in changes in cardiac metabolism in PD. These results provide insight into cardiac metabolic signatures in PD and indicate potential targets for further investigation.

The study aims to explain the different effects between the multiplication, addition, division and subtraction equations. In this sense, multiplication and addition equations develop a new element or fact, meanwhile, division equations express information within the element or fact, subtraction is the selection of element or fact. Furthermore, for a multiplication and addition equation results in the new element or fact, it is necessary to depend on specific physical concepts, without extreme alteration, as it would result in the alteration of the element or fact. It is worth highlighting the importance of fixed values ​​in the equation to describe the specific nature of the element or fact. The study makes it possible to understand open equations (without solutions) in mathematics and physics, in addition to understanding existing equations. The study makes reference to the theory of obligatory necessity and the theory of differences between elements.

Corynebacterium pseudotuberculosis is a Gram-positive bacterium that causes caseous lymphadenitis, a disease that predominantly affects sheep, goat, cattle, buffalo, and horses, but has also been recognized in other animals. This bacterium generates a severe economic impact on countries producing meat. Gene expression studies using RNA-seq is one of the most commonly used techniques to perform transcriptional experiments. Computational analysis on such data through reverse-engineering algorithms leads to a better understanding of the genome-wide complexity of gene interactomes, enabling the identification of genes having the most significant functions inferred by the activated stress response pathways. In this study, we identified the influential or causal genes from four RNA-seq data-sets from different stress conditions (high iron, low iron, acid, osmosis, and PH) in C. pseudotuberculosis, using a consensus-based network inference algorithm called miRsig and identified the causal genes in the network using the miRinfluence tool, which is based on the influence diffusion model. We found that over 50\% of the genes identified as influential have some essential cellular functions in the genomes. In the strains analyzed, most of the causal genes have crucial roles or participate in processes associated with response to extracellular stresses, pathogenicity, membrane components, and essential genes. This research brings new insight into the understanding of virulence and infection by C. pseudotuberculosis.

The study presents an assertion and explanation that major and minor numerical progressions occur that depend on the representation contained in physical space. In general cases, larger numbers are multiples and smaller numbers are simple, because multiple numbers contain more numbers in many physical spaces than simple numbers. In specific cases, they depend on the statement of what the specific representation is, and different realities from general cases may occur. Also, the theory explains the change in the number of prime numbers.

Recently Palle has investigated the chiral vorticity and Cartan torsion in neutrino asymmetries. In his case he addressed this problem in Goedel s like anisotropic Einstein-Catan cosmology. In this paper we discusse how these ideas applied to sheared Bianchi types I Einstein-Cartan (EC) neutrino amisotropic cosmology, affect the handness of neutrinos in the universe. Actually here a novel concept of the chiral metric is introduced where metric functions also possess two distinct signs as in neutrino flipping or helicity. The axial anomaly equation for neutrinos in the presence of torsion and metric chirality is shown to produce left-handed neutrinos from right-handed torsion. Metric chirality is shown to be able to define how the metric would behave far away of neutrino density. Chiral flipping of the chiral neutrinos in the presence of torsion is also investigated. It is shown that when the chiral torsion is left-handed the chemical chiral potential vanishes as the universe expands.

The theory says that the first things to exist in the universe and the current moment were driven by an imperative need; that is, the intensities of the physical concept specify influence the existence of elements and facts based on the countless observations in physical spaces in relation to elements and facts. The existence of mandatory elements in space is motivated by the characteristics of the spaces that offer conditions for such an obligation. The theory states that the universe did not arise by chance; that is, the universe emerged through determination influenced by its surroundings. The objective of the study is to help explain the elements and facts of the universe from its origins to the present.

The effects of the solvent used for the active layer materials of an OLED based on TADF emitters plays a fundamental role in solution-deposited devices. This work focuses the effects on the performance of different solvents employed to fabricate a very simple two organic layer OLED based on a green TADF emitter, under the concept of host:guest matrix. From the different results of the main figures of merit, it was possible to conclude that the OLED that used toluene as solvent for the active layer reached a maximum EQE of 14%, almost the maximum already obtained for this emitter in more complex device structures. With the analysis of the charge transport processes, it was possible to establish an explanatory model for the obtained results. Through impedance spectroscopy, additional characterization about the nature of charge transport processes was carried out. With these results, it was possible to corelate the relaxation times, with the electrical properties of the active layer, and infer about the interaction between the electrical charges and the defect levels opening new possibilities to further development in the printed OLEDs.

The exponential growth of the agricultural industry in the Amazon region has brought about notable economic advancements. However, this growth has substantially cost the region’s ecosystems, manifesting in increased deforestation and biodiversity degradation within the Amazon forest. This article is dedicated to assessing the eco-efficiency of agricultural production in Amazon biome municipalities. It places particular emphasis on identifying critical determinants through the utilization of the classic Data Envelopment Analysis (DEA) model for efficiency computation, super-efficiency models for distinctive characterization, bootstrap computational techniques for robust resampling, and the Malmquist index for calculating annual eco-efficiency indices of each Decision-Making Unit (DMU). An exploration of the correlation between efficiency and meteorological attributes of the municipalities is conducted. The findings of this study reveal several significant points: 1) Eco-efficient municipalities within the Amazon Biome can serve as benchmarks for other DMUs striving to attain optimal input-output levels. 2) Most municipalities in the Amazon Biome operate closely to the productive frontier due to the prevalent technology employed in their agricultural activities. 2) The nature of the technological frontier’s return suggests that small and large DMUs possess eco-efficiency potential. 4) The current dataset does not yield conclusive evidence regarding a direct correlation between the variables. Leveraging this information, strategic pathways can be formulated to drive economic development in tandem with the sustainability of Amazon Biome municipalities. These strategies promise to foster social, economic, and environmental benefits for the populace while providing valuable insights to inform future research within this thematic domain.

We describe the development and validation of a HPLC-MS/MS method to assess the pharmacokinetics and tumour distribution of fenretinide, a synthetic retinoid chemically related to all-trans-retinoic acid, after administration of a novel oral nanoformulation of fenretinide, called bionanofenretinide (BNF). BNF was developed to overcome the major limitation of fenretinide: its poor aqueous solubility and bioavailability due to its hydrophobic nature. The method proved to be reproducible, precise, and highly accurate for the measurement of the drug and the mains metabolites. The lower limit of quantification resulted 1 ng/mL. The curve range of 1-500 ng/mL and 50-2000 ng/mL, for plasma and tumor homogenate respectively, was appropriate for the analysis, as demonstrated by the accuracy between 96.8% and 102.4% for plasma and 96.6-102.3% for tumor. The inter-days precision and accuracy determined on quality controls at 3 different levels were in ranges of 6.9%-7.5% and 99.3-101.0% and 0.96-1.91% and 102.3-105.8% for plasma and tumour, respectively.

The Theory of differences between elements explains the reasons for the differences in physical concepts between different elements, such as quantum physics and the Theory of general relativity, being explained through observations. Thus, it is possible to conclude from the observations that the differences are motivated by the reactions between the elements, by the composition of the elements, and by the influence of the spaces that promote losses and gains of characteristics; therefore, there is no general similarity between quantum physics and the general Theory of relativity. The study aims to understand the elements and their physical concepts that make up the Universe.

One of the most important problems in the presence of epidemics and pandemics is an accurate prediction and preparedness. Scholars and experts argue that future pandemics and/or epidemics are almost inevitable events and is not whether next pandemics will happen, but when a new heath emergency will emerge. Epidemiologic models for prediction of Coronavirus Disease 2019 (COVID-19) have shown many limitations because of unpredictable dynamics of the new viral agent SARS-CoV-2 in environment and society. The main goals of this study are twofold: first, the analysis of anthropogenic activities and factors that may trigger pandemic threats; second, the planning of new directions for strategies to reduce risks that a pandemic threat emerges and/or in the initial phase to reduce vast diffusion and negative impact of new viral agents that can generate hazards and problems in public health, environment and socioeconomic systems. In particular, the investigation and understanding of sources and driving factors concerning the emergence and diffusion of new pandemics have critical aspects for strategic actions of forecast, prevention and preparation of effective policy responses to cope with next pandemic crises and health emergencies. Insights here endeavor, whenever possible, to clarify these problems to increase the knowledge of the sources and factor determining the emergence of new viral agents in order to design optimal response policies to face next pandemic diseases similar to COVID-19. .

Artificial intelligence and Quantum science supports path-breaking technologies for main technological change. The investigation goal of this study is to examine their scientific and technological development to explain drivers of these disruptive technologies. Analyses of data, based on publications and patents in quantum science and artificial intelligence, with a technometric model show that that quantum science and technology has a growth rate of 1.07, artificial Intelligence ha a rate of growth of 1.37, whereas the interaction of quantum science and artificial intelligence generates a convergent technological trajectory that has an accelerated rate of growth of 1.58, higher than trends of these technologies taken individually. These findings here clarify one of the fundamental determinants of the evolution of path-breaking technologies that can support decision making of policymakers, technology analysts and R&D managers to direct R&D investments towards fruitful inter-relationships between radical technologies that foster scientific and technological change in knowledge economies.

(1) Background: Ulcerative colitis (UC) is characterized by immune system dysregulation with frequent extraintestinal manifestations, including airways involvement. Reduction in CO diffusing capacity and functional alterations in small airways have been described. The extended analysis of Fractional Exhaled Nitric Oxide (FeNO), may distinguish the sites of production and the presence of small airways inflammation being a useful, non-invasive marker for these patient’s follow up. The aim of our study was to compare PFTs, FeNO and CANO values of UC patients with different clinical disease activity and healthy subjects to reveal lung function abnormalities and the presence of subclinical airway inflammation. (2) Methods: We enrolled 42 adult outpatients with different clinical activity stages of UC (mean age 39±13 years) and a healthy control group of 41 subjects (mean age 29±3 years). C-reactive protein (CRP) and FeNO values at different flows (50,100 and 200 ml/sec) were collected. All patients performed pulmonary function tests (PFT’s) with static volumes and diffusing capacity (DLCO). (3) Results: FENO, CANO and CRP values were significantly increased in UC patients when compared with controls (p=0.02 and p<0.0001, respectively) and proportionally to the disease activity (FeNO class 3: 27.1 ppb vs class 1-2: 6.2 ppb; CANO values class 3: 8.1 ppb vs class 1-2: 2.0 ppb (p < 0.0001). TLC and DLCO were significantly reduced in UC patients compared to controls (p=0.011 and p<0.0001, respectively). (4) The results of this study show significant lung functional abnormalities in UC patients and suggest the presence of airway inflammation directly correlated with the disease activity suggesting an integrated approach in routine assessment.

Origin, mechanics and properties of the Solar System are analysed in the framework of the Complete Relativity theory (by the same author). According to Complete Relativity, everything is relative. Any apparent absolutism (notably invariance to scale of dimensional constants, absolute elementariness, invariance to time) is an illusion stemming from limits imposed by [or on] polarized observers that will inevitably lead to misinterpretation of phenomena (another illusion) occurring on non-directly observable scales or even on observable but distant scales in space or time. If everything is relative, reference frames will exist where particles are planets and where planets are living beings. Earth is, therefore, analysed here in more detail, both as a particle and, as a living evolving being (of, hypothesized, extremely introverted intelligence). The analysis confirms the postulates and hypotheses of the theory (ie. existence of discrete vertical energy levels) with a significant degree of confidence. During the analysis, some new hypotheses have emerged. These are discussed and confirmed with various degrees of confidence. To increase confidence or refute some hypotheses, experimental verification is necessary. Main conclusions that stem from my research and are further confirmed in this paper are: universes are, indeed, completely relative; Solar System is a scaled (inflated, in some interpretations) Carbon isotope with a nucleus in a condensed (bosonic) state and components in various vertically excited states; life is common everywhere, albeit extroverted complex forms are present on planetary surfaces only during planetary neurogenesis; anthropogenic climate change is only a part (trigger from one perspective) of bigger global changes; major extinction events on a surface of a planet are relative extinctions, a regular part of transformation and transfer of life in the process of planetary neurogenesis.

Count data analysis presents unique challenges due to its discrete nature, often exhibiting excessive zeros and overdispersion. To address these complexities, count models, such as Poisson regression and Negative Binomial regression, have been developed, enabling modeling and prediction of count-based phenomena. Additionally, it’s important to notice that zero inflation, a phenomenon commonly observed in count data, requires specialized techniques for robust analysis. This article provides an overview of count data and count models, explores zero inflation, introduces Likelihood Ratio Tests, and explains how the Vuong Test can be used as a model selection criteria. Furthermore, we created a Vuong Test implementation from scratch using the Python programming language. This implementation enhances the accessibility and applicability of the Vuong Test in real-world scenarios, providing a valuable contribution to the academic community, since Python didn’t have an implementation of this statistical test.

Almost fifty years after the first installations, I identify the main lessons learned from fighting drought and poverty in Africa with direct solar-powered pumps thanks to Father Bernard Verspieren and Mali Aqua Viva. Six main findings and three main recommendations emerge from the present analysis. They are of direct relevance to all Africa’s countries whose population has gone from 438 million in 1977 to 1,308 million in 2019, with about 600 million still having no access to electricity. In place of “awareness campaigns” and extraordinary courses held by international organizations, I recommend to establish national solar energy institutes whose task will include the education of solar energy professionals giving practice-oriented workshops on solar-powered drip irrigation and rainwater harvesting throughout each Africa’s country. Said education will critically include the economic and social aspects of distributed “generation” of energy and water from sunlight and rainfall.

MRI shows in-vivo the three archetypal patterns of CNS volume loss underlying progressive ataxias, namely spinal atrophy (SA), cortical cerebellar atrophy (CCA) and olivopontocerebellar atrophy (OPCA). The MRI-based CNS atrophy pattern was reviewed in 128 progressive ataxias. A CNS atrophy pattern was identified in 91 conditions: SA in Freidreich’s ataxia, CCA in 5 acquired and 72 (24 dominant, 47 recessive,1 X-linked) inherited ataxias, OPCA in Multi-System Atrophy and 12 (9 dominant, 2 recessive,1 X-linked) inherited ataxias. The MRI-based CNS atrophy pattern may be useful for genetic assessment, identification of shared cellular targets, and repurposing therapies or enlargement of drugs indications in progressive ataxias.

Software defect prediction models enable test managers to predict defect-prone modules and assist with delivering quality products. A test manager would be willing to identify the attributes that can influence defect prediction and should be able to trust the model outcomes. The objective of this research is to create software defect prediction models with a focus on interpretability. Additionally, it aims to investigate the impact of size, complexity, and other source code metrics on the prediction of software defects. This research will also assess the reliability of cross-project defect prediction. Well-known machine learning techniques such as support vector machines, k-nearest neighbors, random forest classifiers, and artificial neural networks were applied to publicly available PROMISE datasets. The interpretability of this approach has been demonstrated by SHapley Additive exPlanations (SHAP) and local interpretable model-agnostic explanations (LIME) techniques. The developed interpretable software defect prediction models showed reliability on independent and cross-project data. Finally, the results demonstrate that static code metrics can contribute to the defect prediction models, and the inclusion of explainability assists in establishing trust in the developed models.

This review deals with the functionalization of double bonds carried out in the presence of a chiral catalyst exploiting the intramolecular attack to haliranium ions by nucleophilic nitrogen of amides or carbamates prepared from achiral aminoalkenes, and the C-N bonds formation leads to highly enantioenriched non-aromatic heterocycles. A range of protocols are reported, emphasizing the synthesis of many natural and biologically active products of pharmacological interest prepared according to this methodology.

Fostering fruitful collaboration between chemistry and physics scholars, the analysis of the differences in the practical approach to single atoms in chemistry and in physics affords a number of conceptual outcomes pointing to a more balanced relationship between chemistry and physics.

Motor intention is a high-level brain function related to planning for movement. Although studies have shown that motor intentions can be decoded from brain signals before movement execution, it was unclear whether intentions relating to mental imagery of movement could be decoded. Here, we investigated whether differences in spatial and temporal patterns of brain activation were elicited by intentions to perform different types of motor imagery and whether the patterns could be used by a multivariate pattern classifier to detect such differential intentions. The results showed that it is possible to decode intentions before the onset of different types of motor imagery from functional MR signals obtained from fronto-parietal brain regions, such as the premotor cortex and posterior parietal cortex, while controlling for eye movements and for muscular activity of the hands. These results highlight the critical role played by the aforementioned brain regions in covert motor intentions. Moreover, they have substantial implications for rehabilitating patients with motor disabilities.

It's been a growing concern that many microbes are developing resistance against many antibiotics, lowering the effectiveness and progress expected from that treatment option. To overcome the re-sistance developed by microbes, metallic and non-metallic-based nanoparticle treatments are starting to present a very promising approach. Furthermore, polyurethanes are used in a wide range of biomedical applications due to their variety of physical-chemical, mechanical, and structural properties, and biotic and abiotic degradation. They are widely used in bio-imaging procedures when metallic-based filler particles are incorporated, making the final product radiopaque. It would be advantageous, however, if polyurethanes with intrinsic radiopacity could be produced in their synthesis, avoiding a series of disadvantages in the processing and final product and also presenting potential antimicrobial activities. This review’s objective was to study the radiopacifying charac-teristics of nanoparticles as well as the physical principles of radiopacity and the variety of medical applications of polyurethanes with nanoparticles. It was found in this study that the synthetization of radiopaque polyurethanes is not only possible but also that the efficiency of synthetization was improved when using atoms with high electron density as part of the back chainbone or grafted, making them great multipurpose materials.

With a relatively small population, Russia accesses huge oil, natural gas, coal and uranium resources, and hosts advanced nuclear energy, oil and natural gas industries. However, the combined effect of today’s low cost electricity generation via photovoltaic modules, water and wind turbines and similarly low cost storage in Li-ion battery and solar hydrogen obtained via water electrolysis will have a profound impact on Russia’s energy and automotive industries.

From professors overwhelmed by anxiety-driven e-mails from students, through faculty and administrative staff wasting valued time on e-mail minutia, misuse of electronic mail in the academy has become ubiquitous. After a brief overview of the unique features of e-mail communication, this study provides insight and guidelines to plan new educational activities on healthy and productive utilization of e-mail in the academy of the digital era. The overall aim is to prioritize scholarly deep work by focusing on teaching and research work, freeing working time wasted on unproductive use of e-mail.

A quantum time-dependent spectrum analysis, or simply, quantum spectral analysis (QSA) is presented in this work, and it’s based on Schrödinger’s equation. In the classical world, it is named frequency in time (FIT), which is used here as a complement of the traditional frequency-dependent spectral analysis based on Fourier theory. Besides, FIT is a metric which assesses the impact of the flanks of a signal on its frequency spectrum - not taken into account by Fourier theory and let alone in real time. Even more, and unlike all derived tools from Fourier Theory (i.e., continuous, discrete, fast, short-time, fractional and quantum Fourier Transform, as well as, Gabor) FIT has the following advantages, among others: a) compact support with excellent energy output treatment, b) low computational cost, O(N) for signals and O(N2) for images, c) it does not have phase uncertainties (i.e., indeterminate phase for a magnitude = 0) as in the case of Discrete and Fast Fourier Transform (DFT, FFT, respectively). Finally, we can apply QSA to a quantum signal, that is, to a qubit stream in order to analyze it spectrally.

Traditional population-based metaheuristic algorithms are effective in solving complex real-world problems but require careful strategy selection and parameter tuning. Parameter-less population-based optimization algorithms have gained importance due to their simplicity and efficiency. However, research on their applicability for solving large systems of nonlinear equations is still incipient. In this paper, a systematic review and detailed description of metaphor-less optimization algorithms is made, including the Jaya algorithm, the main Jaya variants for continuous optimization problems, with a focus on the Enhanced Jaya (EJAYA) algorithm, the three Rao algorithms, the best-worst-play (BWP) algorithm, and the very recent max-min-greedy-interaction (MaGI) algorithm. This paper also discusses a few previous parallelizations of the Jaya optimization algorithm, as well as recent GPU-based massively parallel implementations of the Jaya, Enhanced Jaya (EJAYA), Rao, and BWP algorithms developed by the authors. In addition, a novel GPU-accelerated version of the MaGI algorithm is proposed. The GPU-accelerated versions of the metaphor-less algorithms developed by the authors were implemented using the Julia programming language and tested primarily on GeForce RTX 3090 and NVIDIA A100 GPUs, as well as on Tesla V100S and Tesla T4 GPUs, using a set of difficult, large-scale nonlinear equation system problems. The computational experiments carried out produced quite significant speedups, which highlights the efficiency of the GPU-based versions of the metaphor-less algorithms developed for solving large-scale systems of nonlinear equations.

Resistance to therapy and disease progression are the main causes of mortality in most cancers. In particular, the development of resistance is an important limitation affecting the efficacy of therapeutic alternatives for cancer, including chemotherapy, radiotherapy, and immunotherapy. Signaling pathways are largely responsible for the mechanisms of resistance to cancer treatment and progression, and multiple myeloma is no exception. p38 mitogen-activated protein kinase (p38) is downstream of several signaling pathways specific to treatment resistance and progression. Therefore, in recent years, developing therapeutic alternatives directed at p38 MAPK has been of great interest, in order to reverse chemotherapy resistance and prevent progression. In this review, we discuss recent findings on the role of p38, including recent advances in our understanding of its expression and activity as well as its isoforms, and its possible clinical role based on the mechanisms of resistance and progression in multiple myeloma.

Forecasting streamflow accurately is essential to achieve an efficient integrated water resources management strategy and provide consistent support to water decision-makers. We present a simple, low-cost and robust approach for forecasting monthly and yearly streamflow during the hydrological year in course, applicable to headwater catchments. It combines the use of regression analysis techniques, the two-parameter Gamma continuous cumulative probability distribution function and the Monte Carlo method. It is based on a probabilistic comparison of the progression of the current hydrological year with the historic observed series. The methodology has been successfully applied to two headwater reservoirs within the Guadalquivir River Basin in southern Spain. The root-mean-square error and correlation coefficient were used to measure the accuracy of the model and the results showed good levels of reliability. The outputs are the probabilistic monthly and yearly streamflow and 80% confidence interval. Further reductions in prediction errors may be achieved from increasing the number of observed years. These risk-based predictions are of great value, especially, before the intensive irrigation campaign starts (usually in April), when Water Authorities are to take responsible management decisions about the best allocation of the available water volume between the different water users and environmental needs.

The overhead squat movement engages various bodily structures, and its interaction with three-dimensional elastic resistance along the kinetic chain approach remains insufficiently comprehended. This study aimed to describe the scapular kinematics during an overhead squat with the forearm in a supination exercise against an ER and clarify the therapeutic potential of this exercise on scapular rehabilitation. Using an electromagnetic tracking system, we recorded the three-dimensional shoulder kinematics of 19 male participants across seven humeral elevation positions. These positions were captured at 15-degree intervals, spanning from 30 to 120 degrees. The results indicated notable distinctions in scapular upward rotation [F(1,17)=6.09, p=0.024] and scapular posterior tilt [F(1,17)=6.04, p=0.025] between the phases. Furthermore, the interactions revealed significant differences in resistance and phases during humeral elevation for scapular upward/downward rotation [F(3.77,62.48)=7.99, p<0.001], scapular internal/external rotation [F(2.98, 50.64, p<0.001)], and scapular tilt [F(2.58, 43.81)=4.76, p=0.008]. The findings demonstrated that increasing resistance through elastic resistance played a pivotal role in enhancing scapular stability throughout the humerus elevation motion. This underscores the potential of the overhead squat movement as a valuable tool for both shoulder assessment and treatment.

This article presents an in-depth review of Virtual Power Plant (VPP), its organization in the energy system and its prospects in the face of the promising future of the increasing bidirectional complexity exposed in the current scenario. A new paradigm for the operations of modern power distribution and transmission systems requires greater grid flexibility that is accompanying an extensive change in the structure of electricity markets, the fruit of the development of the renewable industry and of the growing photovoltaic systems popularized, but in contrast due to the intermittent nature cause variable uncertainties in the power system. Innovative concepts like VPP are becoming a reality, establishing an efficient and effective mechanism. The objectives and components are described in a comprehensive way, and some of the most important are pointed out and presented in detail to contribute with a description of the energy systems and the implicit research needed for sustainability and resilience in the eminent energy scenario with this technology. In addition, the literature and studies of this technology already indicate a direction of this new tool as a promising solution to manage the uncertainties of the renewable energies.

Retailers must have accurate sales forecasts to operate their businesses efficiently and effectively and to remain competitive in the marketplace. Global forecasting models like RNNs can be a powerful tool for forecasting in retail settings, where multiple time series are often interrelated and influenced by a variety of external factors. By including covariates in a forecasting model, we can better capture the various factors that can influence sales in a retail setting. This can help improve the accuracy of our forecasts and enable better decision-making for inventory management, purchasing, and other operational decisions. In this study we investigate how the accuracy of global forecasting models is affected by the inclusion of different potential demand covariates. To ensure the significance of the study's findings, we used the M5 forecasting competition's openly accessible and well-established dataset. The results obtained from the DeepAR models, which were trained on various combinations of features including time, price, events, and IDs, suggest that individually only the features corresponding to IDs improve the baseline model. However, when all the features are used together, the best performance is achieved, indicating that the individual relevance of each feature is emphasized when the information is given jointly. Comparing the model with features to the model without features, there is an improvement of 1.76\% for MRMSSE and 6.47\% for MMASE.

Background: Hospital accreditation has become ubiquitous in developing countries. Although studies recognize that accreditation can improve healthcare quality, efficiency, and safety, there are doubts about how hospitals deal with conflicts caused by the different institutional logics that inhabit this process. Therefore, this study aimed to investigate how professional and market logics, as well as the conflict between institutional demands, affect compliance with hospital accreditation. Methods: To this end, we developed a multiple case study in four Brazilian hospitals through in-depth interviews with sixteen participants (managers, physicians, nurses, physiotherapist) and on-site observation by the triangulation between the analysis of the narratives and the results of the multiple correspondence analysis. The interpretation and subsequent categorization of the interviews were guided by the study's analytical categories: institutional logics (professional and market); adoption objectives (legitimacy and efficiency); strategic responses to adoption (conformity, non-conformity, and customization); nature of demands (origin in the means and in goal). Results. The data showed that when professional logic is prominent, there is a greater tendency to customize activities, as there are conflicts in the means by which activities can be developed. When market logic stands out, there is a risk of non-conformity, mainly because the focus falls exclusively on goals. Finally, the data point to the absence of conflicts between justifications related to efficiency and legitimacy. Conclusion. We conclude the study by highlighting the theoretical and practical implications of recognizing the conflict between logics, contributing to a deeper understanding of how logic influences the attention given to specific demands and, more significantly, how they affect compliance with hospital accreditation standards, expanding the body of knowledge in the area.

Recent advancements in artificial intelligence (AI) and deep learning have revolutionized the field of protein engineering, particularly in the area of de novo protein design. This review article explores the impact of AI-driven approaches on protein design, with a specific focus on the role of structure prediction neural networks, such as AlphaFold and RoseTTAFold. The article discusses the paradigm shift brought about by these networks, which have enabled the design of proteins with unique structures and functions that are not found in nature. The review covers various aspects of AI-driven protein design, including the use of protein language models to harness evolutionary information, the development of de novo protein design workflows utilizing deep learning, and the application of generative models like RFdiffusion and RoseTTAFold All-Atom. The article also highlights the successes and applications of AI-driven protein design across diverse domains, such as enzyme engineering, antibody design, and vaccine development. Additionally, the review identifies current challenges and future directions in the field, emphasizing the need to address limitations in modeling conformational dynamics and designing proteins for in vivo functionality. The article concludes by underscoring the potential of AI-driven protein design to transform various aspects of science and technology, while also acknowledging the importance of interdisciplinary collaboration and the development of robust pipelines for the validation and optimization of designed proteins. Overall, this comprehensive review serves as a valuable resource for researchers and practitioners interested in understanding the current state and future prospects of AI-driven protein design.

The objective of this work was to investigate the deacidification of bio-oils (BOs) from triglyceride-based biomass through the application of liquid-liquid extraction (LLE) in a simple stage, using methanol and water as a binary solvent and feed/solvent ratio of 1/1. For this, the effects of process parameters such as the water content present in the solvent, the content of carboxylic acids present in the bio-oil, and the extraction temperature on the deacidification process through the efficiency and distribution coefficient were evaluated, as well as the effects of such parameters on the quality of deacidified bio-oils through physical-chemical analyzes and GC-MS analysis. The results show that such process parameters significantly affect the quality of deacidified bio-oils. The ideal condition to have the highest acid removal, i.e., the highest deacidification efficiency (72.65%), is the one in which the deacidification process is performed with aqueous methanol (5% water) at 35 °C and for BOs that have a total acid number (TAN) equal to 24.38 mg KOH/g. Therefore, the process of deacidification by LLE using aqueous methanol is a promising alternative for removing carboxylic acids and other oxygenated compounds, contributing significantly to the upgrading or improving biofuels produced by catalytic thermal cracking.

The corneal epithelium (CE) is spread between two domains, the outer vascularized limbus and the avascular cornea proper. Epithelial cells undergo constant migration from the limbus to the vision-critical central cornea. Coordinated with this migration the cells undergo differentiation changes where a pool of unique stem/precursor cells at the limbus yields the mature cells that reach the corneal center. Differentiation is heralded by the expression of the corneal-specific Krt12. Processing data acquired by scRNA-Seq we found that the increase of Krt12 expression occurs in four distinct steps within the limbus plus a single continuous increase in the cornea. Differential gene analysis demonstrated that these domains reflect discreet stages of CE differentiation and yielded extensive information of the genes undergoing down or up regulation in the sequential transition from less to more differentiate conditions. The approach allowed the identification of multiple gene cohorts, including a) the genes that have maximal expression in the most primitive, Krt12-negative cell cohort, which is likely to include the stem/precursor cells; b) the sets of genes that undergo continuous increase or decrease along the whole differentiation path, and c) and the genes showing maximal positive or negative correlation with the changes in Krt12.

The theory of limited numbers says that the number is not infinite, that is, the number is limited in parts or completely. To reach a conclusion about the limited number, one must understand the meaning of mathematics and varied spaces, therefore, one must understand that mathematics and spaces interact. Mathematics has the function of describing the world precisely, where numbers represent elements or facts that rationally belong to space, and spaces have different intensities of specific physical concepts in each space; therefore, there is no infinite element or fact due to differences in the intensities of specific physical concepts in spaces that do not allow for the fact or fact in all spaces.

The theory says that number interacts with spaces based on the meaning of mathematics, this way it is possible to obtain numerical knowledge. The theory shows the possibility of using spaces relating to each other to explain the reasons why two even numbers form a pair, two odd numbers form a pair, an even and an odd number form an odd number, three odd numbers form an odd number, three even numbers form an odd number. one even, one odd and two evens form an odd, two odd and one even form a pair.

Gestational diabetes mellitus (GDM) is a common complication of pregnancy that adversely affects maternal and offspring health. A variety of risk factors, such as BMI and age, have been associated with increased risks of gestational diabetes. However, in many cases gestational diabetes occurs in healthy nulliparous women with no obvious risk factors. Emerging data suggest that the tendency to develop gestational diabetes has genetic and environmental components. Here we develop a polygenic risk score for gestational diabetes. We further investigate relationships between the genetic architecture of GDM and genetically constructed risk factors and biomarkers. Our results show that genetics can be used as an early screening tool that identifies at-risk at higher risk of GDM before its onset to propose comprehensive monitoring and preventative programs to mitigate the risks.

Large-scale integration of solar energy technologies in Rome’s built environment epitomizes the needed general adoption of distributed generation via functionalization of buildings of all size and end use across the world, to become active energy generators and no longer energy users only. This paper identifies selected technology solutions and critical policy and educational initiatives to effectively achieve within the next decade (2018-2027) the widespread uptake of decentralized solar energy systems in the built environment on a global scale.

To examine the association of sleep quality and work from home with physical inactivity (PI) in leisure time during Covid-19 pandemic. A population-based household survey was conducted in two Bra-zilian municipalities from October to December 2020. Leisure-time physical activity (PA) was self-reported, and individuals who practiced less than 150 minutes of moderate PA or 75 minutes of vigorous PA weekly were classified as PI. Sleep quality was measured using the Pittsburgh Sleep Quality Index (PSQI). WFH was assessed by: "Currently, how is your work routine regarding location? Associations were investigated using logistic regression and directed acyclic graphs (DAG) for the multivariate models. A total of 1,750 adults were interviewed, 69.1% were PI and 51.9% had poor sleep quality. Furthermore, 79.8% were not in WFH. In multivariate analysis, leisure PI was associated with poor sleep quality (OR:1.59: 95% CI: 1.02-2.48), and not being in WFH (OR:1.62: 95% CI: 1.05-2.50). When performing the combined analysis between these two factors, and who were not in WFH were four times more likely to be PI at leisure (OR=4.22;95%CI:2.05-8.65). The results indicate a high prevalence of PI, with poor quality sleep and non-WFH associated with leisure PI. These combined factors exacer-bated the occurrence of PI.

The goal of the study presented in this article is to investigate interconnection issues of the Intelligent Electrical Networks (IENs) with the existing ones, as well as the deployment of the appropriate load forecasting demand techniques. The concept of IENs has recently emerged as a potential solution to the global energy problem, due to the more flexible dispersed production units that are involved. In the same context, additional issues, such as the reduction of production-transfer-distribution costs as well as power losses are analyzed as well, via the penetration of Renewable Energy Sources (RESs). To this end, it is necessary to use appropriate advanced infrastructure, where in combination with modern telecommunication networks will make possible the full exploitation of IENs. Moreover, to make the electricity system more efficient, to avoid voltage and frequency imbalance issues and to implement optimal production and consumption planning, the Electric Load Forecast (ELF) is a vital process and plays a key role in the planning as well as in the management of electricity systems. Therefore, recent state of the art approaches in ELF methods are discussed as well.

The main objective of this study was to study the effect of occupational stress on turnover intentions, as well as whether this relationship is mediated by burnout levels and moderated by motivation. The sample of this study consisted of 603 participants, all employees of the Portuguese Tax and Customs Authority, which is part of the Ministry of Finance and belongs to the Direct State Administration. The results indicate that occupational stress (with managers, with career and remuneration and with work overload) has a positive and significant effect on turnover intentions and that this relationship is mediated by burnout. Motivation (intrinsic and identified) has a negative and significant effect on turnover intentions. Intrinsic motivation moderates the rela-tionship between occupational stress (with managers, with colleagues, with career and pay and with family problems) and turnover intentions. These results indicate that among the dimensions of occupational stress, the most critical are stress with managers, work overload and career and pay. These are factors that the Direct State Administration should be concerned about in trying to minimize their causes.

Reducing the levels of toxic chemicals that cause adverse health and environmental impacts is a challenge for the international community. There is a need of a global strategy. Indeed, too often the problems associated to the exposure of chemical substances is recognized a posteriori, in the presence of consequences already observed. The prediction of the likely effects of chemical exposure on human health is based on classical tests with animals, which are time and money consuming, may deviate from an accurate prediction towards humans, and arises ethical concerns. Regulations are now considering the adoption of in silico (or computational) methods, which can be used for prioritizing substances according to the probability to be toxic for the biosphere. Several initiatives have prioritized chemicals, typically based according to some criteria, such as chemicals which may be endocrine disruptors, or persistent, bioaccumulative, or toxic (PBT). However, these initiatives focused on a certain range of adverse properties, and covered a certain number of substances only. We applied a set of largely validated and widely used predictive methods to large collections of chemicals: (i) to about 340,000 with a defined function, and (ii) to about 6 millions, which have been synthetized. The aim of this study is to quantify the putative impact of existing and future chemicals on towards human health, ecological and environment properties. The impact on the environment is the cause of major concern. This is the case of pesticides and hazardous, which is quite expected; however, also pharmacologically active candidate compounds of natural origin may have a high level of ecotoxicity. Pesticides and hazardous are also the categories of higher concern for humans, followed by pharmaceuticals. The pesticides and the hazardous are the categories of higher concern also on the environmental point of view. The results of our analysis could be the basis for the identification of new safety rules.

Cancer is a complex and heterogeneous disease, influenced by various factors that affect its progression and response to treatment. Although histopathological diagnosis is crucial for identifying and classifying cancer, it may not accurately predict the disease's development and evolution in all cases. To address this limitation, liquid biopsy has emerged as a valuable tool, enabling a more precise and non-invasive analysis of cancer. Liquid biopsy offers the ability to detect tumor DNA fragments, circulating tumor cells, and exosomes released by cancer cells into the bloodstream. Exosomes, in particular, have attracted significant attention in cancer research due to their specific protein composition, which can provide valuable insights into the disease. The protein profile of exosomes often differs from that of normal cells, reflecting the unique molecular characteristics of cancer. Analyzing these proteins can help identify cancer-associated markers that play critical roles in tumor progression, invasion, and metastasis. Ongoing research and clinical validation are essential to advance and effectively utilize protein biomarkers in cancer. Nevertheless, their potential to improve diagnosis and treatment is highly promising. This review discuss several exosome proteins of interest in breast cancer, particularly focusing on studies conducted in mammary tissue and cell lines in humans and experimental animals. Unfortunately, the studies conducted in the canine species are scarce. This emphasis sheds light on the limited research available in this field. Additionally, we present a curated selection of studies that have explored exosomal proteins as potential biomarkers, aiming to achieve the aforementioned benefits in breast cancer diagnosis, prognosis, monitoring, and treatment.

Canine mammary tumors (CMTs) are among the most common disease in female dogs and share similarities with human breast cancer, which have placed these animals as a model of study in comparative oncology. Metabolic reprogramming is one of them and is known as a hallmark of carcinogenesis whereby cells undergo adjustments to supply the high bioenergetic and biosynthetic demands of rapidly proliferating cells. However, such alterations are also vulnerabilities that may serve as therapeutic strategies which have been tested mostly in human clinical trials, but poorly explored in CMTs. In this dedicated review, we compilated the metabolic changes described for CMTs emphasizing the metabolism of carbohydrates, amino acids, lipids, and mitochondrial function. We observed here key factors associated with the presence and aggressiveness of CMTs, such as the increase in glucose uptake followed by enhanced anaerobic glycolysis via upregulation of glycolytic enzymes, changes in glutamine catabolism due to overexpression of glutaminases, raise in fatty acid oxidation and distinct effects depending on the lipid saturation, in addition to mitochondrial DNA which is a hotspot for mutations. Therefore, more attention should be paid to this topic given that targeting metabolic fragilities could improve the outcome of CMTs.

Leishmaniasis is a complex infectious parasitic disease caused by protozoa of the genus Leishmania, belonging to a group of neglected tropical diseases. It poses significant global health challenges, particularly in socio-economically disadvantaged regions. Macrophages, as innate immune cells, play a crucial role in initiating the inflammatory response against the pathogens responsible for this disease. Macrophage polarization, the process of differentiating macrophages into pro-inflammatory (M1) or anti-inflammatory (M2) phenotypes, is essential for the immune response in leishmaniasis. The M1 phenotype is associated with resistance to Leishmania infection, while the M2 phenotype is predominant in susceptible environments. Notably, various immune cells, including T cells, play a significant role in modulating macrophage polarization by releasing cytokines that influence macrophage maturation and function. Furthermore, other immune cells can also impact macrophage polarization in a T-cell-dependent manner. Therefore, this review comprehensively examines macrophage polarization's role in leishmaniasis and other immune cells' potential involvement in this intricate process.

We propose an approach for estimating the error in depth data provided by generic 3D sensors, which are modern devices capable of generating an image (RGB data) and a depth map (distance) or other similar 2.5D structure (e.g. stereo disparity) of the scene. Our approach starts capturing images of a checkerboard pattern devised for the method. Then proceed with the construction of a dense depth map using functions that generally comes with the device SDK (based on disparity or depth). The 2D processing of RGB data is performed next to find the checkerboard corners. Clouds of corner points are finally created (in 3D), over which an RMS error estimation is computed. We come up with a multi-platform system and its verification and evaluation has been done, using the development kit of the board nVIDIA Jetson TK1 with the MS Kinects v1/v2 and the Stereolabs ZED camera. So the main contribution is the error determination procedure that does not need any data set or benchmark, thus relying only on data acquired on-the-fly. With a simple checkerboard, our approach is able to determine the error for any device. Envisioned application is on 3D reconstruction for robotic vision, with a series of 3D vision sensors embarked in robots (UAV of type quadcopter and terrestrial robots) for high-precision map construction, which can be used for sensing and monitoring.

Driven by the rapid uptake of battery electric vehicles, Li-ion power batteries are increasingly reused in stationary energy storage systems, and eventually recycled to recover all the valued components. Offering an updated global perspective, this study provides a circular economy insight on lithium-ion battery reuse and recycling.

Climate change is expected to influence cooling and heating energy demand of residential buildings and affect overall thermal comfort. Towards this end, the heating degree-day (HDD), the cooling degree-day (CDD) and the HDD+CDD were computed from an ensemble of 7 high-resolution bias-corrected simulations attained from EURO-CORDEX under RCP4.5 and RCP8.5. These three indicators were analyzed for 1971-2000 (from E-OBS) and 2011-2040 and 2041-2070, under both RCPs. Results show that the overall spatial distribution of HDD trends for the 3 time-periods points out an increase of energy demand to heat internal environments in Portugal's northern-eastern regions, most significant under RCP8.5. It is projected an increase of CDD values for both scenarios; however, statistically significant linear trends were only found for 2041-2070 under RCP4.5. The need for cooling is almost negligible for the remaining periods, though linear trend values are still considerably higher for 2041-2070 under RCP8.5. By the end of 2070, higher amplitudes for all indicators are depicted for southern Algarve and Alentejo regions, mainly under RCP8.5. For 2041-2070 the Centre and Alentejo (North and Centre) regions present major positive differences for HDD(CDD) under RCP4.5(RCP8.5), within the 5 NUTS II regions predicting higher heating(cooling) requirements for some locations.

Abstract: To compare the use of variable mechanical ventilation with conventional mechanical ventilation in porcine model of ARDS. Methods: Animals were divided into two groups (n = 6), conventional ventilation and variable ventilation with bi-oscillatory PEEP. For induction of ARDS, intravenous oleic acid was used until a P/F ratio of 200 to 300 mmHg. The animals were ventilated with pressure control, FiO2 1.0, inspiration-expiration ratio = 1:2, tidal volume 6 ml/kg with the initial respiratory rate adjusted to maintain an end tidal CO2 tension of 35 to 45 mmHg. Variable ventilation was characterized by the oscillation of PEEP from 5 to 10 cmH2O every 4 respiratory cycles, in convencional ventilation group PEEP was set from 5 cmH2O. Ventilatory, hemodynamic parameters, oxidative stress, antioxidant enzymes, Interleukin 8 (IL8) and 17-a (IL17a) and histological analyzes were evaluated; Results: The use of BiPEEP demonstrated improvement in lung compliance and PaO2 in relation to control. The levels of oxidative stress and antioxidant enzymes showed no significant difference. There was no difference in IL17a between groups. In IL8 there was a significant increase in the lung base of control in relation to BiPEEP, and a reduction in the apex of BiPEEP in relation to control. The control group showed changes in lung morphology characterized by cellular infiltrates, a thickening of the alveolar septae and atelectasis, which were attenuated in BiPEEP group; (4) Conclusions: The use of variable ventilation with bi-oscillatory level of PEEP demonstrates a potential ventilatory strategy in an experimental model of ARDS.

In a context of increasingly necessary energy transition, precise modelling of profiles for low-voltage (LV) network consumers is crucial to enhance hosting capacity. Typically, load curves for these consumers are estimated through measurement campaigns conducted by Distribution System Operators (DSO) for a representative subset of customers or through the aggregation of load curves from household appliances within a residence. With the instrumentation of smart meters becoming more common, a new approach to modelling profiles for residential customers is proposed to make the most of the measurements from these meters. The disaggregation model estimates the load profile of customers on a low-voltage network by disaggregating the load curve measured at the secondary substation level. By utilizing only the maximum power measured by Linky smart meters, along with the load curve of the secondary substation, this model can estimate the daily profile of customers. For 48 secondary substations in our dataset, the model obtained an average symmetric mean average percentage error (SMAPE) error of 4.91% in reconstructing the load curve of the secondary substation from the curves disaggregated by the model. This methodology can allow the estimation of the daily consumption behaviors of the low-voltage customers. In this way, we can safely envision solutions that enhance the grid hosting capacity.

Background: Melatonin is a potent mitochondrial, cytoprotective and antioxidant molecule with potentially strong anti-aging properties. Topical melatonin has shown to improve the clinical signs of skin aging. Melatosphere™ is a new lipid-based delivery system able to improve stability and skin penetration of melatonin when used in topical formulations. No clinical studies, using objective instrumental data, are available so far regarding the positive effect of Melatosphere™ in improving wrinkles in women with mild-to-moderate skin aging. Study Aim: We evaluate, in an open prospective, evaluator-blinded trial, the effects on skin texture of 2 months treatment with a Melatosphere™ based cream. Subjects and Methods: 15 women aged >45 years with mild to moderate facial skin aging (Glogau score ≥2) participated in the trial, after their informed consent. An ANTERA 3D computer-assisted skin analysis evaluation for the assessment of coarse and fine wrinkles of the periorbital area and melanin content was performed at baseline and after two months of treatment. An evaluator-blinded Investigator Global assessment of skin elastosis, roughness, level of dyscromia, skin dryness and presence of actinic damage was also performed at the same time points using a 4-grade score from 0 (no sign) to 3 (severe sign). Results: At baseline the mean (SD) IGA score was 8.2(1.0). After 2 months the IGA score significantly decrease to 4.2(1.4) (49% reduction) (P=0.0007). ANTERA 3D evaluations showed a significant reduction in skin coarse and fine wrinkles volume in the target area of -31% and -18%, respectively. Melanin content was reduced significantly by -17%. Conclusion: Topical melatonin carried in Melatosphere improves in the short-term signs of skin aging evaluated clinically and by ANTERA 3D device in women with mild to moderate skin aging.

Vaginal ecosystem is a unique environment where, in physiological conditions, lactobacilli dominate. However, also pathogenic microbial species, responsible of vaginitis and vaginosis, can harbor vaginal microbiota. To extend the data published by De Seta and Larsen in Pathogens (2021), here we analyzed both the anti-Candida and anti-inflammatory properties of the vaginal gel formulation, Respecta® Balance Gel (RBG), commercialized as an adjuvant to treat vaginitis and vaginosis. We evaluated its activity by an in vitro model where a monolayer of A-431 vaginal epithelial cells was infected by Candida albicans in the presence of RBG or the placebo formulation (pRBG). Specifically, we tested the RBG capacity to counteract C. albicans virulence factors as well as their anti-inflammatory properties. Our results show that, unlike the placebo, RBG reduces ,reduces, C. albicans adhesion, its capacity to form hyphae and C. albicans-induced vaginal cell damage. Interestingly, both RBG and pRBG reduce LPS-induced IL-8 secretion (being RBG the most effective) demonstrating that also the placebo retains anti-inflammatory properties. By our experimental approach we highlight the possible role of farnesol on such effects, but we would like to point out that lactic acid, polydextrose and glycogen too must be relevant in the actual application. Taken together, our results show that RBG impairs C. albicans virulence and is able to reduce the inflammation in the vaginal environment, ultimately allowing the establishment of a balanced vaginal ecosystem.

The main objective of this research was to analyze the relationship between socioeconomic and demographic indicators and the level of transparency of municipalities in the state of Maranhão. The transparency index was constructed based on the LRF and LAI and consisted of 32 items. Subsequently , for To identify which factors explain the level of transparency, a multiple linear regression was carried out, comparing the explanatory variables for the level of transparency adopted in this study. The sample consisted of municipalities in the State of Maranhão, totaling 211 municipalities, as 7 did not have a website. The results of the multiple linear regression model indicate that the IDHM, the log of total GDP, the GDP per capita and the variable log of POP explain the NT of the municipalities surveyed to the point of explain the level of transparency of the municipalities of Maranhão, only the IFDM did not show a relationship with the NT among the variables analyzed.

Using Directed Transfer Function (DTF) and Partial Directed Coherence (PDC) in their information version, this paper extends their theoretical framework to incorporate instantaneous Granger Causality (iGC)’s frequency domain description into a single unified perspective. We show that standard vector autoregressive models allow portraying iGC’s repercussions associated with Granger Connectivity where interactions mediated without delay between time series can be easily detected.

Raman spectroscopy (RS) turns out to be a promising tool for cancer di- agnosis. In particular, in the last years several studies have demonstrated how the diagnostic performances of Raman Spectroscopy can be significantly improved by employing Machine Learning (ML) algorithms for the interpre- tation of Raman-based data. In line with these findings, in this paper, we demonstrated how RS coupled with ML allowed to accurately distinguish the three grades of Chondrosarcoma and to distinguish Chondrosarcoma and a benign counterpart called Enchondroma. We obtained such results by ana- lyzing a dataset composed of a relatively small number of Raman spectra, collected in a previous study. Such spectra were acquired from micromet- ric tissue sections with a Confocal Raman Microscope. In particular, we tested the classification performances of a Support Vector Machine and a Random Forest Classifier, as representative of Machine Learning, and two versions of the Multi-Layer Perceptron, as representative of Deep Learning (DL). These models showed excellent classification performances, especially those belonging to DL, with accuracy reaching 99.7%. This outcome makes the aforementioned models a promising route for future improvements of di- agnostic devices focused on detecting bone cancerous tissues. In addition, we highlighted how the ML models studied resulted in slightly worse classifi- cation performances in comparison to DL. Alongside the diagnostic purpose, the aforementioned approach allowed to identify characteristic molecules, i. e. amino acids, nucleic acids and bioapatites, relevant for the obtainment of the final diagnostic response, through the analysis of the so-called Per- mutation Feature Importance. Permutation Feature Importance could hence represent a promising parameter for the understanding of the biochemical processes on the basis of the tumor progression. In turn, the spectral bands highlighted by Permutation Feature Importance could represent precious in- dicators in the attempt to restrict the spectral acquisition to specific Raman bands. This last objective could help to reduce the amount of experimental data needed to obtain an accurate final grading outcome, with consequent reduction of the computational cost.

Objectives We tested the hypothesis that poor adherence is associated with a greater risk of alcohol-caused mortality and morbidities within the first year of discontinuing this medication. Materials and Methods Retrospective cohort study of 3319 individuals who received Acamprosate® in the East of Scotland in a 10-year period using a health informatics approach with record linkage of dispensing data, hospital utilization (SMR) and General Register Office of Scotland (GROS) data. Primary outcome was adherence between one to six months of initiating Acamprosate® medication. Secondary outcome was all cause morbidities and mortality. Results Of the total 3319 individuals identified, good adherence index of >80% was found in 59% of those prescribed Acamprosate® after three months and 6% after six months. There were significant linear trends of poorer adherence with increased risk of alcohol-caused mortality (HR1.2), medical morbidities especially neoplasm (HR 4.1|) and poisoning (HR 1.4) and psychiatric morbidities especially stress (HR 35.1), psychotic (HR 5.6) and neurotic disorders and directly alcohol induced conditions (7.4 HR) after adjustment for other factors within a one-year period of initiation of Acamprosate® treatment. Discussion and Conclusions Further exploratory studies using this digitalized approach should be encouraged in order to capture role of compliance to Acamprosate® and other types of medication that are known to reduce relapse into alcohol dependence and its direct relationship to mortality and morbidities in this population.

Socially Responsible Investments, also referred to as ethical or sustainable investments, have experienced rapid global growth in recent years. They represent an investment approach that incorporates social, environmental, and ethical considerations into decision-making processes. Consequently, the significance of SRIs has captured the attention of academics, prompting inquiries into the impact of integrating social criteria on portfolio performance. The primary objective of this work was to conduct a comparative study of the performance between socially responsible and non-socially responsible investment funds, using funds domiciled in Portugal and Spain. Various multi-factor models, including the three-factor model of Fama and French (1992), the four-factor model of Carhart (1997), and the five-factor model of Fama and French (2015), were employed to assess performance. The sample comprised 125 investment funds, with 43 identified as socially responsible and 82 as non-socially responsible. The study's findings indicate that there are no significant differences between socially responsible funds and their conventional counterparts. The majority of funds experience performance alterations during periods of crisis compared to crisis-free periods. Additionally, when comparing non-conditional models with conditional models, an improvement in the explanatory power of the latter is observed. This suggests that the inclusion of the dummy variable enhances the quality of fit for the models.

Variability is the predisposition of the elements in systems to assume different values over time and space. In biology, the variability is basic to explain differences and development in organisms but in the fields of scientific and technological information, the effects of variability on evolutionary dynamics of disciplines and technologies are unknown. In a broad analogy with the principles of biology, the variability within research fields can be a central argument to explain trajectories in scientific development and technological evolution. The purpose of the present study is to see whether statistical evidence supports the general hypothesis that the rate of growth in technologies can be explained by the level of variability in scientific fields and with this principal goal to analyze the relation between scientific variability and rate of growth in technologies. Proposed hypothesis of scientific variability here endeavors to explain basic sources of scientific development and technological evolution to lay the foundations for a general theory. The test here is based on emerging research fields of quantum technologies: Quantum Imaging, Quantum Meteorology, Quantum Sensing and Quantum Optics. A preliminary statistical evidence seems in general to support the hypothesis stated that the rate of growth in technological fields can be explained by the level of scientific variability in research fields, measured with relative entropy index. Nonparametric correlation based on Spearman’s rho shows a positive coefficient of 0.80 of these variables; linear model of the rate of technological growth = f(scientific variability) reveals a coefficient of regression equal to 1.63 (R²=0.60). Findings here suggest a general law that scientific variability positively drives scientific development and technological evolution. In particular, a higher variability within research fields can support scientific development and a high rate of growth in technological evolution (measured with scientific and technological information). Proposed hypothesis of scientific variability is especially relevant in environments of rapid change to explain determinants and dynamics of technological change within a general theoretical framework that supports technological management and forecasting of promising innovations.

A proposed interpretation of the characteristics and causes of the variation in science dynamics for technological evolution is described. The theoretical approach focuses on variability in research topics that guide scientific and technological evolution. Statistical method verifies the proposed approach by applying entropy, measures of dispersion and variance decomposition. The statistical evidence, using data of four main research fields in quantum technologies, suggests the following empirical properties: a) the growth of heterogeneity in research topics is inversely proportional to the age of research fields: recent research fields have a higher variability between topics with uncertainty in evolutionary dynamics, whereas older research fields have a lower variability and more concentration in specific research topics with stable evolution towards clear directions; b) the nature of research fields has a systematic effects in variability guiding the evolution of technologies. The theoretical approach and findings clarify main characteristics and causes of the evolution of science and technologies considering the underlying homogeneity or heterogeneity in research topics, providing main implications to improve the scientific and technological forecasting that may support appropriate R&D investments towards promising research fields and technologies

True randomness is necessary for the security of any cryptographic protocol, including quantum key distribution (QKD). In QKD transceivers, randomness is supplied by one or more local private entropy sources of quantum origin, which can be either passive (e.g. a beam splitter) or active (e.g. an electronic quantum random number generator). In order to understand better the role of randomness in QKD we revisit the well-known "detector blinding" attack on BB84 QKD protocol, which utilizes strong light to achieve an undetectable and complete recovery of the secret key. We present two findings. First, we show that the detector blinding attack is in fact an attack on the receiver’s local entropy source. Second, based on this insight, we propose a modified receiver station and a statistical criterion which together enable robust detection of any bright-light attack and thus restore security.

Preprints are regularly cited in peer reviewed journal articles, books and conference paper. Are preprint citations somehow less important than citations to peer reviewed research papers? This study investigates citation patterns between 2017 and 2020 for preprints published in three preprint servers, one specializing in biology (bioRxiv), one in chemistry (ChemRxiv), and another hosting preprints in all disciplines (Research Square). As evaluation of scholarship continues to largely rely on citation-based metrics, this analysis and its outcomes will be useful to inform new research-based education in today’s scholarly communication.

In most world’s countries, scholarship evaluation for tenure and promotion continues to rely on conventional criteria of publications in journals of high impact factor and grant funding. Continuing to hire and promote scholars for their achievements in research and in securing research funds exposes universities at risk because students, directly and indirectly through government funds, are the main source of revenues for academic institutions, whereas talented young researchers are those who actually carry out most of the published research. Purposeful scholarship evaluation needs to include all three areas of scholarly activity: research, teaching and mentoring, and service to society. Young scholars seeking tenure and promotion benefit from the practice of open science because it provides better and more impactful results with respect to each of the three areas of scholarship.

In the digital era in which over 4 billion people regularly access the internet, the conventional process of publishing scientific articles in academic journals following peer review is undergoing profound changes. Following physics and mathematics scholars who started to publish their work on the freely accessible arXiv server in the early 1990s, researchers of all disciplines increasingly publish scientific articles in the form of freely accessible and fully citeable preprints before or in parallel to conventional submission to academic journals for peer review. The full transition to open science, I argue in this study, requires to expand the education of students and young researchers to include scholarly communication in the digital era.

Sharing the same raw material, recycling and composting are in direct conflict with incineration of municipal solid waste in combined heath and power plants. Indeed, waste-to-energy plants in regions with high recycling rates import urban waste from other countries to use otherwise unused capacity, and raise revenues. Using the case of Italy’s second largest and economically most developed region, I discuss the economic viability of municipal solid waste incineration to produce electricity and heath in the context of the increasing role of electricity production from renewable energy sources as well as of the emerging mass-scale uptake of bioplastics. Four lessons and three guidelines aimed to local authorities and policy makers emerge from the present study.

During the last 25 years the scientific community has coexisted with the most fascinating protocol due to Quantum Physics: quantum teleportation (QTele), which would have been impossible if quantum entanglement, so questioned by Einstein, did not exist. In this work, a complete architecture for the teleportation of Computational Basis States (CBS) is presented. Such CBS will represent each of the possible 24 classical bits commonly used to encode every pixel of a 3-color-channel-image (red-green-blue, or cyan-yellow-magenta). For this purpose, a couple of interfaces: classical-to-quantum (Cl2Qu) and quantum-to-classical (Qu2Cl) are presented with two versions of the teleportation protocol: standard and simplified.

During the last century, entanglement was the bone of contention between the two main pillars of Physics: General Relativity (GR) and Quantum Mechanics (QM). This began in 1935 with the Einstein-Podolsky-Rosen paradox (EPR paradox) which concluded that although Quantum Mechanics is not wrong, it is an incomplete theory to represent physical reality. In this paper it is demonstrated that some byproducts resulting from entanglement and which we will call avatars act as a hinge that link both theories making the completeness of QM clear. Moreover, a thorough analysis of the non-locality of this effect will be carried out. Besides, it is demonstrated that entanglement is an instantaneous phenomenon and that it does not require the use of a superluminal signaling for this purpose. Finally, the avatars will also appear in each wormhole resulting from an entanglement process (WREP) demonstrating that they are traversable with an equivalent path of null length which can be crossed in a null time with all that this implies in Quantum Communications.

A simplified version of the quantum teleportation protocol is presented in here. Its experimental confirmation will have deep implications for a better understanding of Quantum Entanglement with a particular projection on Quantum Communications.

On June 8 and June 9, 2017, we gave two invited lectures at the Zelinsky Institute of Organic Chemistry (ZIOC) of the Russian Academy of Sciences, Moscow. The first lecture, “Sol-Gel Catalysts: Making Green Chemistry Possible”, focused on the practical outcomes of 25 years of research on sol-gel entrapped catalysts. The second, “Chemistry for the Bioeconomy: From Discussion to Action”, offered a critical insight to the forthcoming bioeconomy. Both lectures aroused much interest in the audience and ended with a vigorous discussion lasting about one hour. An outlook is provided herein.

Solar green roofs, namely rooftops functionalized with properly selected living vegetation and photovoltaic modules, achieve an ideal symbiotic relationship in which promotion of biodiversity and onsite renewable energy production are both enhanced whereas the roof provides a wide range of environmental, health, aesthetic and economic benefits. This study provides a unified outlook of this eminent sustainable technology at the dawn of its uptake across the world, especially in polluted urban areas.

Hydroxychloroquine, a known antiviral metabolite of chloroquine, is increasingly used along with antibiotic azithromycin for the treatment of COVID-19 infection. In about one month India, the world’s largest manufacturer, delivered hydroxychloroquine for treating COVID-19 to over 50 countries. The therapy is being used across the world both for patients staying at home at the early phase of symptoms, as well as for patients hospitalized. We summarize achievements as of late April 2020, review possible modes of action and suggest avenues for the quick scale-up of production of hydroxychloroquine.

Quantum revival phenomena, wherein the wave function of a quantum system periodically returns to its initial state after evolving in time, are investigated in this study. Focusing on electrons confined within a quantum box with an impurity, both weak and strong coupling regimes are explored, revealing intricate relationships between impurity parameters and temporal dynamics. The investigation considers the influence of impurity position, impurity strength, and external factors such as aluminum concentration, temperature, and hydrostatic pressure on classical periods and revival times. Through analytical derivations and graphical analyses, the study elucidates the sensitivity of quantum revivals to these parameters, providing valuable insights into the fundamental aspects of quantum mechanics. While no specific physical applications are discussed, the findings offer implications for quantum heat engines and other quantum-based technologies, emphasizing the importance of understanding quantum revivals in confined quantum systems.

The natural distribution of stress in the femur is altered when total hip arthroplasty (THA) is performed. In fact, when a stem is inserted inside the femur, there is a variation in stress due to the difference in rigidity between the material with which the stem is made and the femur. This generates the phenomenon of stress-shielding. The aim of this study is to design an optimized prosthesis that guarantees excellent rotational stability and re-duced stress shielding. Methods: through the finite element method (FEM) the mechanical behavior of the stem subjected to the loads described by ISO 7206-4: 2010 is studied. Re-sults: Through topological optimization, there is a reduction in stress shielding in the proximal zone of 31.46%. The addition of ridges on the dorsal side of the stem also im-proves rotational stability by 27.82%. Conclusions: The decrease in stiffness that is rec-orded with the optimized stem, guarantees a greater distribution of stress on the bone. The presence of dorsal ridges also favors the corticalization of the bone as it loads the bone near the dorsal ensuring further stability. The perforated prosthesis presented in this study, shows an increase in primary stability and an improvement in rotational stability. As there is also a bone regrowth inside the prosthesis.

Integrated crop-livestock production (ILP) is an interesting alternative for more sustainable soil use. However, more studies are needed to analyze soil pore properties under ILP at the micrometer scale. Thus, this study proposes a detailed analysis of soil pore architecture at the micrometer scale in three dimensions. For this purpose, samples of an Oxisol under ILP subjected to minimum tillage (MT) and no-tillage (NT) with ryegrass as cover crop (C) and silage (S) were investigated. The soil micromorphological properties of the soil were analyzed using X-ray microtomography. The MT(C) system showed the highest values of porosity (c. 20.4%), connectivity (c. 32.8×103), volume (c. 26%), and number of pores (c. 32%) in a rod-like shape. On the other hand, the MT(S), NT(C), and NT(S) systems showed higher tortuosities (c. 2.2, c. 2.0, and c. 2.1) and lower pore connectivities (c. 8.3×103, c. 6.9×103, and c. 6.2×103), especially in S use. Ellipsoidal and rod-shaped pores predominated over spheroidal and disc-shaped pores in all treatments. The results of this study show that the use of ryegrass as a cover crop improves soil physical properties, especially in MT. For S use, the type of soil management (MT or NT) did not show any differences.

With confirmed COVID-19 cases surpassing the 8.5 million mark around the globe, there is an imperative need to deepen the efforts from the international scientific community to gain comprehensive understanding of SARS-CoV-2. Although the main clinical manifestations are associated with respiratory or intestinal symptoms, reports of specific and non-specific neurological signs and symptoms, both at presentation or during the course of the acute phase, are increasing. Approximately 25-40% of the patients present neurological symptoms. The etiology of these neurological manifestations remains obscure, and probably involves several direct pathways, not excluding the direct entry of the virus to the Central Nervous System (CNS) through the olfactory epithelium, circumventricular organs, or disrupted blood-brain barrier (BBB). Furthermore, neuroinflammation might occur in response to the strong systemic cytokine storm described for COVID-19, or due to dysregulation of the CNS angiotensin system. Descriptions of neurological manifestations in patients in the previous coronavirus (CoV) outbreaks have been numerous for the SARS-CoV and lesser for MERS-CoV. Strong evidence from patients and experimental models suggests that some human variants of CoV have the ability to reach the CNS and that neurons, astrocytes and/or microglia can be target cells for CoV. A growing body of evidence shows that astrocytes and microglia have a major role in neuroinflammation, responding to local CNS inflammation and/or to dysbalanced peripheral inflammation. This is another potential mechanism for SARS-CoV-2 damage to the CNS. In this work we will summarize the known neurological manifestations of SARS-CoV-2, SARS-CoV and MERS-CoV, explore the potential role for astrocytes and microglia in the infection and neuroinflammation, and compare them with the previously described human and animal CoV that showed neurotropism. We also propose possible underlying mechanisms by focusing on our knowledge of glia, neurons, and their dynamic intricate communication with the immune system.

In this work, the influence of catalyst reuse and reaction time on the yield and quality of organic liquid products (OLP) obtained in a cracking pilot plant at 450 °C and 1.0 atm has been systematically investigated. The distillation of OLP produced 04 (four) distilled fractions. The quality of the biofuels was certified by physical-chemical analysis, as well as FT-IR and GC-MS analysis. The experimental results showed the feasibility of applying the spent sodium carbonate twice in catalytic cracking of vegetable oils. The physical-chemical properties (density, viscosity, acid value, saponification value, and flash point) of OLP decrease as the reaction time increases. The distillation of OLP yields 62.35% (wt.), producing green-like gasoline, kerosene, and diesel fractions rich in hydrocarbons. Therefore, biofuels-like fractions produced by distillation of OLP have a great potential for replacing partially petroleum derived fuels.

Sudden unexpected death (SUD) is a fatal event that occurs in an apparently healthy subject so that such an abrupt outcome could have not been predicted. SUD - including sudden intrauterine unexplained death (SIUD), sudden neonatal unexpected death (SNUD), sudden infant death syndrome (SIDS), sudden unexpected death of the young (SUDY), sudden unexpected death in the adult (SUDA) - occurs as the first manifestation of an unknown underlying disease or within a few hours of presentation of a disease. SUD is a major unsolved, shocking form of death that occurs frequently and can happen at any time without warning. For each case of SUD, a review of clinical history data and performance of a complete autopsy, particularly focused on the study of the cardiac conduction system were carried out according to the necropsy protocol devised by the Lino Rossi Research Center, Università degli Studi di Milano, Italy. Research cases are represented by 75 SUD victims, subdivided into 15 SIUD, 15 SNUD, 15 SUDY, and 15 SUDA victims, collected and selected for this study. After the routine autopsy and clinical history analysis, the death remained unexplained and hence a diagnosis of SUD was assigned to the 75. subjects, which included45 females (60%) and 30 (40%) males, ranging in age from 27 gestational weeks to 76 years. Serial sections of the cardiac conduction system disclosed frequent congenital alterations, of the cardiac conduction system in fetuses and infants. An age-related significant difference in distribution among the 5 age-related groups was detected for the following anomalies of the conduction system: central fibrous body (CFB) islands of conduction tissue, fetal dispersion, resorptive degeneration, Mahaim fiber, CFB cartilaginous meta-hyperplasia, His bundle septation, sino-atrial node (SAN) artery fibromuscular thickening, atrio-ventricular junction hypoplasia, intramural right bundle branch, and SAN hypoplasia. The results data are useful to understand the cause of death for all SUD cases that were unexpected and would have otherwise remained unexplained, so to motivate medical examiners and pathologists to perform more in-depth studies.

Global models have been developed to tackle the challenge of forecasting sets of series that are related or share similarities, but not for heterogeneous datasets. Various methods of partitioning by relatedness have been introduced to enhance the similarities of the set, resulting in improved forecasting accuracy but often at the cost of a reduced sample size, which could be harmful. To shed light on how the relatedness between series impacts the effectiveness of global models in real-world demand forecasting problems we perform an extensive empirical study using the M5 competition dataset. We examined cross-learning scenarios driven by the product hierarchy commonly employed in retail planning, which allow global models to capture interdependencies across products and regions more effectively. Our findings show that global models outperform state-of-the-art local benchmarks by a considerable margin, indicating that they are not inherently more limited than local models and can handle unrelated time series data effectively. The accuracy of data partitioning approaches increases, as the size of the data pools and the models' complexity decrease. However, there is a trade-off between data availability and data relatedness. Smaller data pools lead to increased similarity among time series, making it easier to capture cross-product and cross-region dependencies, but this comes at the cost of a reduced sample, which may not be beneficial. Finally, it's worth noting that the successful implementation of global models for heterogeneous datasets can significantly impact forecasting practice.

Unmanned Aerial Vehicles (UAVs) in particular multirotors are becoming the {\it de facto} tool for aerial sensing and remote inspection. In large industrial facilities, a UAV can transmit an online video stream to inspect difficult to access structures, such chimneys, deposits and towers. However, the communication range is limited, constraining the UAV operation range. This limitation can be overcome with relaying UAVs placed between the source UAV and the control station, creating a line of communication links. In this work we assume the use of a digital data packet network technology, namely WiFi, and tackle the problem of defining the exact placement for the relaying UAVs that creates an end-to-end channel with maximal delivery of data packets. We consider asymmetric communication links and we show an increase as large as $15$\% in end-to-end packet delivery ratio when compared to an equidistant placement. We also discuss the deployment of such a network and propose a fully distributed method that converges to the global optimal relay positions taking, on average, 1.4 the time taken by a centralized method.

The main purpose of this work is to contribute to understanding the mechanism of oxidation of the polymeric components of common disposable masks used during the COVID-19 pandemic to offer the chemical basis to predict their long-term behaviour under typical environmental conditions. Artificial ageing of representative mask layers under isothermal conditions (110℃) or accelerated photoageing showed that all the PP-made components underwent a fast oxidation process, following the typical hydrocarbon oxidation mechanism. In particular, yellowing and the melting temperature drop are early indicators of their diffusion-limited oxidation. Morphology changes also induced a loss of mechanical properties, observable as embrittlement of the fabric fibres. Results were validated through preliminary outdoor ageing of masks, which allows us to predict they will suffer fast and extensive oxidation only in the case of contemporary exposure to sunlight and relatively high environmental temperature, leading to their extensive breakdown in the form of microfiber fragments, i.e., microplastics.

Many neurodegenerative diseases are directly related to the formation of toxic protein aggregates, such as Parkinson’s and Alzheimer’s diseases, which are associated with the aggregation of alpha-synuclein (α-syn) and beta-amyloid (Aβ ), respectively. In this context, protein fibrils are the hallmark of these neurodegenerative diseases. In this sense, planning or designing compounds that are capable of preventing or reducing the formation of protein aggregation in the brain can be of fundamental importance for the curative treatment of these diseases. This work presents an in silico and experimental study to investigate the inhibitory potential of the ligands Octovespin (bioinspired by the wasp venom Polybia Occidentalis) and Fraternine-10 (bioinspired by the wasp venom Parachartergus fraternus wasp) against the aggregation of fibrils of the peptides Aβ(17-42) and α-syn, respectively. Using molecular docking and molecular dynamics simulations with 100 ns, the disaggregation capacity of these ligands was studied. The results obtained indicate that Octovespin and Fraternine-10 interact with the Aβ and α-syn protein fibrils throughout the simulation time. The RMSD values and the interactions with amino acids responsible for fibril aggregation demonstrate that both Octovespin and Fraternine-10 have a significant disaggregation potential, which corroborates the observations in vitro and in vivo. Furthermore, experimental results of Fraternine-10 demonstrate an anti-aggregation effect, indicating that it can promote the disaggregation of fibrils and prevent them from aggregating again to form oligomers. These discoveries qualify these molecules as potential candidates to become medicines against Parkinson’s and Alzheimer’s diseases.