Wildfires are important sources of landscape change in Mediterranean environments, creating large patches of natural habitats (i.e., scrublands) inside protected areas, whereas woodland patches remained at the border in the vicinity of human settlements. Landscape patterns resulting from these gradients influence habitat suitability for mesocarnivores regarding food and shelter. In winter and summer 2019, we sampled 16 independent line-transects of four camera traps each (for a total of 64 cameras), covering the main habitats of the study area (woodlands, scrublands, and crops). Cameras were baited to compensate for low detectability of target species, and mesocarnivore contacts were analyzed by means of GLMMs and occupancy models. We hypothesized that Mediterranean mesocarnivores were constrained by two opposing forces, pushing them living in semi-natural but highly fragmented and heterogeneous landscapes created by humans, or living in natural but less suitable and continuous habitats created by fire regimes. In the former case, mesocarnivores will find protection against predators and resting sites in forests, as well as improved food opportunities in crops and urban areas, despite the possible interference with humans and their pets. Potential cascading effects linked to ecological roles of Mediterranean mesocarnivores on the succession of Mediterranean landscapes would imply longer-term effects of human disturbance on landscape trends.

This study assessed the hydrological performance and runoff water quality of 12 green roof (GR) modular systems located at the Universidad de los Andes campus (Bogotá, Colombia). Based on 223 rainfall events spanning a 3-year period, average rainfall retention was 85% (SD = 25%). T-tests, Welch Test, multiple linear regressions and correlation analysis were performed in order to assess the potential effect of air temperature, substrate type, vegetation cover, relative humidity, antecedent dry weather period (ADWP), rainfall duration and rainfall maximum intensity. In some cases, GR design variables (i.e. growing media and type of vegetation) were found to be significant for describing rainfall retention efficiencies and, depending on the GR type, some hydrological variables were also correlated with the rainfall retention. Rainfall and GR runoff were monitored for Total Kjeldahl Nitrogen (TKN), Nitrates, Nitrites, Ammonia, Total Phosphorus (TP), Phosphates, pH, Total Dissolved Solids (TDS), Total Suspended Solids (TSS), Color, Turbidity, Biological Oxygen Demand (BOD), Chemical Oxygen Demand (COD), Total Coliforms, metals and Poliaromatic Hydrocarbons (PAHs). The results obtained confirmed that GR systems have the ability to neutralize pH, but are source of the rest of the aforementioned parameters, excluding PAHs (with concentrations below detection limits), Ammonia, TSS, Se and Li, where differences with reference values (rainfall and plastic panel runoff) were not statistically significant. Substrate type, event size and rainfall regime are relevant variables for explaining runoff water quality.

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.

We present the case of a 35-year-old male with first degree family history of gastric cancer (father diagnosed at the age of 45), that was presumed to have gastric cancer himself when evaluating the features of his upper endoscopy performed after hematemesis. Surprisingly, no cancer cells were found in the biopsies. Thanks to a different diagnostic suspicion subsequent to performing a full clinical history, a more favorable diagnosis was reached: gastric syphilis.

In the realm of educational technology, Data Analytics (DA) is reshaping teaching and learning. This paper investigates the impact of DA on education, specifically comparing Student Information Systems (SIS) and Learning Management Systems (LMS). Data-driven insights from SIS and LMS platforms enable educators to tailor instructional strategies to individual student needs effectively. While SIS manages student data for administrative tasks, LMS offers tools for content delivery and collaboration. Using the strengths of SIS and LMS, educators can optimise teaching and learning experiences, tracking student progress, and fostering collaboration. The comparison emphasises their distinct roles: SIS manages administrative tasks, while LMS focusses on content delivery and collaboration. Using both systems, educators improve the teaching and learning experience, leveraging DA for continuous improvement. In summary, this paper underscores the transformative role of DA in education, framed within the context of comparing the SIS and LMS functionalities. By examining the intersection of data-driven decision making and educational technology, educators are equipped with the tools and knowledge to harness the power of data for meaningful and impactful teaching and learning.

Background: Cancer therapy-related cardiac dysfunction (CTRCD) is a growing concern for public health, with a growing incidence due to improved survival rates for patients with hematological malignancies due to diagnostic and therapeutic advances. Identification of patients at risk CTRCD is vital to develop preventive strategies. Methods: A single-center retrospective cohort study was conducted between 1 January 2017 and 15 February 2023. Medical records of patients with lymphoma treated with first-line anthracyclines were reviewed. Demographic data, cardiovascular risk factors, biomarkers of myocardial damage and echocardiographic information were collected. Results: A total of 200 patients were included. The incidence of CTRCD was 17.4 % (35/200). Patients with CTRCD were older than those without CTRCD, with a mean age of 65.17 years vs 56.77 (p = 0.008). Dyslipidemia (DL) (31.4% vs 13.4% p = 0.017) and previous cardiovascular disease (40% vs 13.3%, p< 0.001) were more frequent in the group who developed an event. Mean baseline NT-proBNP levels in the subgroup with cardiovascular events were 388.73 kg /L ± 101.02, and 251.518 kg /L ± 26.22 in those who did not (p = 0.004). Differences in Troponin I levels were identified during and after treatment without exceeding the laboratory’s upper reference limit. Patients were followed for a median of 51.83 months (0.76-73.49). The presence of a CTCRD event had a negative impact on overall mortality from any cause (HR = 2.23 (95% CI 1.08-2.93), p = 0.031). Conclusions: Early identification of risk factors is crucial to manage patients at risk for CTRCD.

The rapid ageing of populations around the World is creating complex challenges for national governments. The establishment of sustainable and equitable long-term care systems for old and dependent people is one of the main issues of social policy in developed countries. The aim of this work is to define a cost model for residential and day care centres for dependent persons in Cantabria (Spain). The cost model will make it possible to establish the theoretical cost of attending to the needs of the different types of dependent persons in the different types of care centres, and the methodology used could be extrapolated to other regions. The daily cost per user for elderly residential care is €53.72. The cost per user in elderly day centres (5 days) is 32.56 euros. In residential centres for people with disabilities, the values range between €47.41 and €75.25 depending on the category of the centre. In three categories of centres the public price is not enough to cover the cost (physical disability, intellectual disability, mental illness – low care), and therefore the administration should reconsider their public prices for these kind of centres if they want to really contribute to the sustainability of these residential care centres. This research will have important implications for policy-makers in a context of fulfilment of SDGs and where better support for old and disabled people and their carers, as well as fair and efficient financing of social care services, are essential to address the current and future challenges of dependency.

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.

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&amp;D managers to direct R&amp;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&lt;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 &lt; 0.0001). TLC and DLCO were significantly reduced in UC patients compared to controls (p=0.011 and p&lt;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.

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.

The purpose of this paper is to explore the extent to which traditional economic policies can be oriented by sound practices. It is becoming widely accepted that sustainable economic growth (and not only economic growth) is the final target of economic policies; but most economic policies are applied just looking to the short-run without taking in account the long-run perspective. Our aim will be to show how a sustainable economic policy-making would be possible, making compatible the stabilization of the economy in the short-run with a sustainable economic growth in the long-run. We confront the design of economic policies with the 17 goals of the 2030 Agenda. We argue that all sustainable development goals can be attained by the design and implementation of sustainable economic policies. Finally, to illustrate this point we will conduct a simulation exercise to show under which combinations of demand policies technological shocks would promote a path of sustainable growth. Our results will provide a reference framework for a sustainable economic policy-making.

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.

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.

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.

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.

Sufficient evidence is currently available to demonstrate the reality of the warming of our planet's climate system. Global warming has different effects on climate at the regional and local levels. The detection of changes in extreme events using instrumental data provides further evidence of such warming and allows for the characterization of its local manifestations. The present study analyzes changes in temperature and precipitation extremes in the Mexican state of Zacatecas using climate change indices developed by the Expert Team on Climate Change Detection, Monitoring and Indices (ETCCDI). We studied a 40-year period (1976-2015) using annual and seasonal time scales. Maximum and minimum temperature data were used, as well as precipitation statistics from the Mexican climatology database (CLICOM) provided by the Mexican meteorological service. Weather stations with at least 80% of data availability for the selected study period were selected; these databases were subjected to quality control, homogenization, and data filling using Climatol, which runs in the R programming language. These homogenized series were used to obtain daily grides of the three variables at a resolution of 1.3 km. Results reveal important changes in temperature-related indices, such as the increase in maximum temperature and the decrease in minimum temperature. Irregular variability was observed in the case of precipitation, which could be associated with low-frequency oscillations such as the Pacific Decadal Oscillation and the El Niño–Southern Oscillation. The possible impact of these changes in temperature and the increased irregularity of precipitation could have a negative impact on the agricultural sector, especially given that the state of Zacatecas is the largest national bean producer. The most important problems in the short term will be related to the difficulty of adapting to these rapid changes and the new climate scenario, which will pose new challenges in the future.

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.

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.

This paper aims to establish a current relationship between pharmaceutical sciences and the development of perfumes and fragrances, which bring significant economic benefits and whose added value is among other professionals, the one made by professionals in Pharmacy. For this purpose, historical data are used as a starting point and galenic, chemical and botanical aspects are discussed in a transversal way. In this sense, it must be taken into account that in the case of Spanish pharmacy, it is closely linked to the knowledge and use of plants. Sources such as Web of Science (WOS) and databases such as Scopus, monographs and various web pages (where scientific-technical documents appear) have been used. The results and discussion are based on the selection of the 50 plant species most commonly used in high quality fragrances. Therefore, this publication should be considered as an approach to this subject based on an analysis of a representative sample of data. Some characteristics of perfumes (classification according to the concentration of essential oils and combination of plant extracts) are presented beforehand. They also briefly compile the traditional and modern ways in the treatment of these extracts. The main focus of this work is the botanical and chemical analysis of these described plants, pointing out their common name, correct botanical name, geographical place of origin, used part of the plant and main molecules. The 50 botanical species belong to 27 families of angiosperms and are represented in a large part of the phylogenetic tree of botanical systematics. The most significant families are aromatic: Rutaceae (16.7%), Lamiaceae (16.7%) and Apiaceae (6.5%). The most represented genus is Citrus (with seven species or hybrids). However, it should be noted that natural extracts of good quality natural fragrances may be supplemented with chemically synthesized molecules. Of the 50 botanical species selected, 84% of the extracts have their origin in Tropical Asia, the Middle East and the Mediterranean region. This figure generally coincides with the percentage of medicinal plants (or their extracts) admitted by the European Pharmacopoeia. All parts of a plant (depending on which one it is) can be a source of molecules for the elaboration of these products. The most commonly used parts to obtain extracts are flowers (34%) and leaves (30%), a biological circumstance that is explained in this work. On the opposite side are the resins (10%), rhizomes and roots (8%). In this work, 110 molecules have been found that are part of the essences of perfumes and fragrances, the most frequent are: linalool, limonene, 1,8-cineole, eugenol and derivatives, geraniol, vanillin and derivatives, β-cariophyllene, p-cmene and farnesene and derivatives (3.64%). However, in order to elaborate a quality perfume, many other molecules must be taken into account, according to the creative experience of the perfumer, which is subject to confidentiality and chemical analysis according to current legislation, which would avoid fraud, allergy and dermatitis problems.

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.

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.

Plastid genomes are in general highly conserved given their slow evolutionary rate, thus large changes in their structure are unusual. However, when specific rearrangements are present, they are often phylogenetically informative. Asteraceae is a highly diverse family whose evolution is long driven by polyploidy (up to 48x) and hybridisation, both processes usually complicating systematic inferences. In this study, we have generated one of the most comprehensive plastome-based phylogenies of family Asteraceae, providing information about the structure, genetic diversity, and repeat composition of these sequences. By comparing the whole plastome sequences obtained, we confirmed the double inversion located in the long single copy region, for most of the species analysed (with the exception of basal tribes), a well-known feature for Asteraceae plastomes. We also show that genome size, gene order and gene content are highly conserved along the family. However, species representative of the basal subfamily Barnadesioideae -as well as in the sister family Calyceraceae - are lacking the pseudogene rps19 located in one inverted repeat. The phylogenomic analysis conducted here, based on 63 protein-coding genes, 30 transfer RNA genes and 21 ribosomal RNA genes from 36 species of Asteraceae, are overall consistent with the general consensus for the family’s phylogeny, while resolving the position of tribe Senecioneae and revealing some incongruences at tribe level between reconstructions based on nuclear and plastid DNA data.

In contemporary construction, the prevalence of vibration serviceability issues in lightweight and slender structures has become increasingly common, owing to advancements in building materials and construction methods. While these structures often meet the criteria for ultimate limit states, they can still elicit complaints due to excessive vibrations induced by human activity. To address this challenge, the Integral Resonant Control (IRC) technique has emerged as a favored approach for actively damping vibrations in various systems. This study introduces a fresh perspective on implementing a multi-input multi-output (MIMO) IRC scheme for active vibration control (AVC) specifically tailored for pedestrian structures utilizing inertial mass actuators. Building upon a common framework and design methodology outlined in previous research, this work presents a novel application of MIMO IRC for AVC. The designed controller is rigorously tested and implemented on a laboratory floor structure to validate its efficacy.

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.

After 40 years of the discovery of metallocene catalysts, there are still several aspects that remain unresolved, especially when the “conventional” alkylaluminum activators are not used. Herein, we systematically investigate the synthesis of PE via three different zirconocene catalysts, with different alkyl substituents, activated via different organoboron compounds. The polymerization behavior, as well as the properties of the materials, are evaluated. The results demonstrate that the highest catalytic activity is shown by Bis(cyclopentadienyl)dimethylzirconium activated by trityl tetra(pentafluorophenyl)borate. Also finding that toluene is the optimum solvent for these systems and at these reaction conditions. Moreover, to validate our experimental results, a comprehensive mathematical model is developed on the basis of thermodynamic and kinetic principles. The concentration of ethylene transferred to the solvent phase (toluene) in a liquid-vapor equilibrium (LVE) system is estimated based on the Duhem’s theorem. Arrhenius expressions for the kinetic rate constants of a proposed kinetic mechanism are estimated by a kinetic model, in which the rate of polymerization is fitted by a least-square optimization procedure and the molecular weight averages by the method of moments. The simulations of the coordination polymerization suggest the presence of two types of active sites, principally at low temperatures, and the reactivation of the deactivated sites via a boron-based activator. However, the effect of the temperature on the reactivation step is no clear; a deeper understanding via designed experiments is required.

Anthropogenic lead pollution is an environmental problem that threatens the quality of soils and waters and endangers living organisms in numerous surface and subsurface habitats. Lead coprecipitation on mineral surfaces through dissolution-recrystallization processes has long term effects on lead bioavailability. Gypsum and calcite are among the most abundant and reactive rock forming minerals present in numerous geological settings. In this work, we study the interaction of slightly acidic (pHi = 5.5) Pb-bearing aqueous solutions ([Pb]i = 1 mM and 10 mM) with crystals of gypsum and /or calcite under atmospheric conditions. This interaction results in a reduction of the concentration of lead in the liquid phase due to the precipitation of newly formed Pb-bearing solid phases. The extent of this Pb removal mainly depends on the nature of the primary mineral phase involved in the interaction. Thus, when gypsum is the only solid phase initially present in the system the Pb-bearing liquid-gypsum interaction results in Pb removals in the 98-99.8 % range, regardless of [Pb]i. In contrast, when the interaction takes place with calcite, Pb removal strongly depends on [Pb]i. It reaches 99% when [Pb]i = 1 mM while it is much more modest (⁓13%) when [Pb]i = 10 mM. Interestingly, Pb-removal is maximized for both [Pb]i (99.9 % for solutions with [Pb]i = 10 mM and 99.7% for solutions with [Pb]i = 1 mM) when Pb-polluted solutions simultaneously interact with gypsum and calcite crystals. Despite the large Pb removals found in most of the cases studied, the final Pb concentration ([Pb]f) in the liquid phase always is well above the maximum permitted in drinking water (0.1 ppm), with the minimum ([Pb]f = 0.7 ppm) being obtained for solutions with [Pb]i =1 mM after their interaction with mixtures of gypsum and calcite crystals. This result suggests that integrating the use of mixtures of gypsum-calcite crystals might help to develop more efficient strategies for in-situ decontaminating Pb-polluted waters through mineral coprecipitation processes.

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.

Spent batteries recycling is an important way to obtain low-cost graphite. Nevertheless, the obtaining of crystalline graphite with a rather low density of defects is required for many applications. In the present work, high-quality graphites have been obtained from different kinds of spent batteries. Black masses from spent alkaline batteries (batteries black masses, BBM), and lithium-ion batteries from smartphones (smartphone black masses, SBM) and electric and/or hybrid vehicles (lithium-ion black masses, LBM) were used as starting materials. A hydrometallurgical process was then used to obtain recycled graphites by acidic leaching. Different leaching conditions were used depending on the type of the initial black mass. The final solids were characterized by a wide set of complementary techniques.

The aim of Predictive Maintenance, within the field of Prognostics and Health Management (PHM), is to identify and anticipate potential issues in the equipment before these become critical. The main challenge to be addressed is to assess the amount of time a piece of equipment will function effectively before it fails, which is known as Remaining Useful Life (RUL). Deep Learning (DL) models, such as Deep Convolutional Neural Networks (DCNN) and Long Short-Term Memory (LSTM) networks, have been widely adopted to address the task, with great success. However, it is well known that this kind of black box models are opaque decision systems, and it may be hard to explain its outputs to stakeholders (experts in the industrial equipment). Due to the large number of parameters that determine the behavior of these complex models, understanding the reasoning behind the predictions is challenging. This work presents a critical and comparative revision on a number of XAI methods applied on time series regression model for PM. The aim is to explore XAI methods within time series regression, which have been less studied than those for time series classification. The model used during the experimentation is a DCNN trained to predict the RUL of an aircraft engine. The methods are reviewed and compared using a set of metrics that quantifies a number of desirable properties that any XAI method should fulfill. The results show that GRAD-CAM is the most robust method, and that the best layer is not the bottom one, as is commonly seen within the context of Image Processing.

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.

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&amp;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.

Confinement can induce substantial changes in the physical properties of macromolecules in suspension. Soft confinement is a particular class of restriction where the boundaries that constraint the particles in a region of the space are not well-defined. This scenario leads to a broader structural and dynamical behavior than the observed in systems enclosed between rigid walls. In this contribution, we study the ordering and diffusive properties of a two-dimensional colloidal model system subjected to a one-dimensional parabolic trap. Increasing the trap strength makes it possible to go through weak to strong confinement, allowing a dimensional transition from two- to one-dimension. The non-monotonic response of the static and dynamical properties to the gradual dimensionality change affects the system phase behavior. We find that the particle dynamics is connected with the structural transitions induced by the parabolic trap. In particular, at low and intermediate confinement regimes, complex structural and dynamical scenarios arise, where the softness of the external potential induces melting and freezing, resulting in faster and slower particle diffusion, respectively. Besides, at strong confinements, colloids move basically along one direction, and the whole system behaves structurally and dynamically similar to a one-dimensional colloidal system.

In this work we aim to experimentally study the nucleation and growth of CaCO3 phases precipitated from supersaturated aqueous solutions in the presence of varying concentrations of sulphate oxyanion. The experiments were conducted under pH conditions close to neutral (7.6) and considering a wide range of initial (SO42-)/(CO32-) ratios (0 to ~ 68) in the aqueous solution. We paid special attention to the evolution of the precipitates during ageing within a time framework of 14 days. The mineralogy, morphology and composition of the precipitates were studied by X-ray diffraction, Fourier transform infrared spectroscopy, scanning electron microscopy and EDX microanalysis. The concentration of sulphate ions in the reacted aqueous solution was study by ICPs. The experimental results show that the mineral composition of the precipitate recovered in each run varied with the (SO42-)/(CO32-) ratio in the parental solution, which influences the mineral evolution of the precipitates during ageing. We observe that high concentrations of sulphate in the aqueous solution stabilize the vaterite precipitates and inhibit calcite formation. Furthermore, aragonite never precipitates directly form the solution and it is only formed via a dissolution-precipitation process in solutions with high (SO42-)/(CO32-) ratio after long reaction times. Finally, gypsum only precipitates after long ageing in those aqueous solutions with the highest concentration of sulphate. The reaction pathways during ageing, the morphology of the calcite crystals and the composition of vaterite and calcite are discussed considering both, kinetic and thermodynamic factors. These results show a considerably more complex behavior of the system than that observed in experiments conducted under higher pHs and supersaturation levels and lower (SO42-)/(CO32-) ratios in the aqueous phase.

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.

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.

This review describes the positive effects of growth hormone on the cardiovascular system. We analyze why the vascular endothelium is a real internal secretion gland, whose inflammation is the first step for developing atherosclerosis, as well as the mechanisms by which GH acts on the vascular endothelium improving its dysfunction. We also report how GH acts on coronary arterial disease and heart failure, and on peripheral arterial disease inducing the generation of new collateral vessels able to bypass a major artery occlusion. We include some preliminary data from a trial in which GH or placebo is given to elder people suffering from critical limb ischemia, showing the effects of the hormone on plasma markers of inflammation, and stating that the administration of GH in short periods of time is safe and effective even in diabetic patients. We also analyze how Klotho may have strong relationships with GH, inducing, after being released from the damaged vascular endothelium, the pituitary secretion of GH to repair the damaged tissue. Lastly, we show how GH induces wound healing by increasing the blood flow to the ischemic tissue. In summary, we postulate that short-time GH administration is useful for treating cardiovascular diseases.

Within the polyurethanes market, only 0.1% are from renewable sources. With the continuing concern about climate change and greenhouse gases in the atmosphere, the substitution of monomers and processes derived from petrochemical sources is crucial for the development of biomaterials. Therefore, polyhydroxyurethanes have propose due to their synthesis route with the incorporation of monomers from renewable sources such as vegetable oils and the substitution of isocyanates known for their high toxicity, carcinogenicity and petrochemical origin, and the use of carbon dioxide. There are few reports on the use of soybean oil and the possible application of these materials in wound healing applications. Based on this, polyhydroxyurethanes were obtained from carbonated soybean oil and two diamines, one aliphatic: 1,4-butadiamine (putrescine), and one cycloaliphatic: 1,3-cyclohexanobis(methylamine), and they were physiochemically, mechanically, and thermally characterized. Four polyhydroxyurethanes were obtained, with stability to hydrolytic and oxidative media, thermal stability above 200 °C, tensile strength between 0.9-1.1 MPa, elongation at break between 81 and 222%. And water absorption up 102% and contact angle between 63,70 and 101,39. Achieving new formulations of biobased NIPHUs that represent a more sustainable process which allow to achieve the physicochemical, mechanical, and thermal properties required for the preparation of wound dressings.

The 2030 Agenda sets out seventeen Sustainable Development Goals (SDGs). The educational goal is to promote the education of citizens on sustainable development, among other things. Educating today's digital citizens on sustainability means training them for justice and social activism, commitment and political engagement. However, research into the subject shows a lack of consistency in the education of university students. This paper presents a study of students of Education, on education on sustainability through the practice of active and critical digital citizenship. A quasi-experimental method was used to learn about the behaviours of digital citizens, and intervention was carried out by means of an SDG-focused workshop and observation of the final level of commitment. The results show a positive level of commitment and digital activism around content related to sustainable development, which can be addressed from the university syllabus in a cross-curricular way.

A via ferrata (from the German “klettersteig”, hereinafter VF) is a sports route located on forest and mountains vertical rock walls equipped with steps, chains, artificial dams, bridges and other fixed elements and which have a steel cable (safety cable) all the way along allowing users to secure their progress and avoid possible falls [1]. This article aims to analyse the state of the art of the VF sector in Spain, especially in terms of the regulations of obligatory compliance, in addition to defining the basic characteristics of the installations to ensure that these are safe for users, providing a previously non-existent summary of the most important recommendations regardless of the country where they are installed.

The FTF (Fusarium Transcription Factor) gene family is composed of two members (FTF1 and FTF2) with high sequence homology. Both genes encode Zn(II)2Cys6 binuclear zinc finger transcription factors involved in the modulation of virulence in the F. oxysporum species complex (FOSC). While FTF1 is a multicopy gene exclusive of highly virulent strains of FOSC and is located in the accessory genome, FTF2 is a single copy gene, located in the core genome, and well conserved in all filamentous ascomycete fungi, except yeast. The involvement of FTF1 in the colonization of the vascular system and regulation of the expression of SIX effectors has been stablished. To address the role of FTF2 we generated and characterized null FTF2 mutants in a F. oxysporum f. sp. phaseoli weakly virulent strain and analyzed them together with the equivalent mutants formerly obtained in a highly virulent strain. The results obtained highlight a role for FTF2 as a negative regulator of the production of macroconidia and demonstrate that it is required for full virulence and positive regulation of SIX effectors. In addition, gene expression analyses provide compelling evidence that FTF2 is involved in the regulation of hydrophobins likely required for plant colonization.

In Mexico there is a deficit in the production of pine resin, because it depends on natural forests. Therefore, it is necessary to select provenances and phenotypes of potential species such as P. oocarpa. The objective was to determine the difference between provenances and the variation of resin components and quality, as well as the effect of geographic and climatic factors. Resin from five provenances was collected from southern Mexico. The percentage of rosin, turpentine and water was obtained, as well as the acidity and saponification index. P. oocarpa resin had 80.94 % rosin, 7.7 % turpentine and 11.49 % water. The saponification and acidity index was 125.47 and 117.49 mg KOH.g_1, respectively. All variables showed differences (p≤ 0.0001) between provenances. The provenance contributed between 6.44 and 11.71 % to the total variance, the error contributed between 88.29 and 93.56 %. Geographic and climatic variables only had an effect on the percentage of turpentine; the correlation was negative with altitude and longitude, but positive with temperature and precipitation. The results allow defining seed collection sites for resin plantations and orienting the selection for a P. oocarpa improvement program.

This study aimed to assess the enhancement of physical fitness and quality of life through an 8 weeks strength program training in male adolescents soccer players. A lower body muscle groups intervention was performed, with 17 players in the experimental group (EG) and 15 in the control group (CG). The EG carried out soccer training complemented by specific strength work. Pre and post- intervention assessments included body composition, jump height, speed with change of direction, maximum speed in 20 m, movement velocity in back-squat, perceived fatigue effort, academic performance and quality of life. A general linear repeated measures model analysis was used considering for each variable, the interaction between groups (CG, EG) and time (basal, final), to analyze the differences between and within groups. The results showed reduction of fat in the upper limbs and trunk EG, improvements in jump height, maximum speed of 20 m, changes of direction and quality of life increased (p<0.05) in the EG too. It was concluded that a strength program could improve some components of physical performance in male adolescents soccer players.

How do sensor research and technologies grow over time? This paper applies the network analysis with a new computational approach to map the structure and evolution of sensor research and technologies over a 30-year time frame (1990-2020).The goal of this study is to analyze the evolution of sensor research for forecasting emerging scientific and technological trajectories. Results show that the scientific interaction within ecosystem (represented with networks) of sensor generates a co-evolution of scientific fields supporting the accelerated growth of different technological tra-jectories, such as: wireless sensors, fiber optic and optical sensors, gas sensors and biosensors. These results suggest main theoretical implications that explain the evolution of sensor research with critical aspects of innovation management to support R&D investments towards new technological trajectories having a high potential of growth.

The linkage between the salt wedge, tidal patterns, and the Magdalena River discharge is established by assessing the ensuing parameters: stratification (ϵ), buoyancy frequency (β), potential energy anomaly (φ), Richardson number (RL), and bottom turbulent energy production (P). The salinity, temperature, density, and water velocity data utilized were derived from MOHID 3D, a previously tailored and validated model for the Magdalena River Estuary. To grasp the dynamics of the river, a flow regime analysis was conducted during both wet and dry climatic seasons of the Colombian Caribbean. The utilization of this model aimed to delineate the estuary's spatial reach, considering flow rates spanning from 2000 to 6500 m³/s across two tidal cycles. This approach facilitates the prediction of the position, stability, and stratification degree of the salt front. Among the conclusions drawn, it is highlighted that: 1. The river flow serves as the principal conditioning agent for the system, inducing a strong estuary response to weather stations; 2. The extent of wedge intrusion and the river discharge exhibit a non-linear, inversely correlation; 3. Tidal waves cause differences of up to 1000 m in the horizontal extent of the wedge; 4. Widespread channel erosion occurs during the rainy season when the salt intrusion does not exceed 2 km; 5. Flocculation processes intensify during the transition between dry and wet seasons; 6. The stability of the salt layering and the consolidation of the FSI-TMZ are contingent upon the geometric attributes of the channel.

This study analyzed the levels of mental workload and the presence of burnout on a sample of fashion retailing workers from Spain and its relationship with the actual Covid-19 pandemic by exploring Covid-19 pandemic predictors of burnout and mental workload. We established a prospective cross-sectional design. Participants (n = 360) answered an online survey including questions about sociodemographic data, perception of Covid-19, CarMen-Q questionnaire (workload), and MBI (burnout syndrome). We obtained data throughout October-November 2020. The results showed that participants exhibit deep concern about the Covid-19 pandemic and its influence at the work level. Although the mental workload was near the middle point of the scale, participants showed moderate to high burnout levels, revealing that the sample is at risk of experiencing higher burnout levels over time as the pandemic and associated economic crisis continue. The multidimensional regression analysis results indicated that environmental changes, work overload, somatic symptoms, insomnia, negative job expectations, and uncertainty constituted significant mental workload predictors. Insomnia, somatic symptoms, and negative job expectations constituted significant predictors for burnout. In conclusion, the uncertainty at work derived from the Covid-19 pandemic is harming the psychological wellbeing of fashion retailing workers in Spain.

Type 2 Diabetes Mellitus and Alzheimer's disease are two diseases with a high incidence today that share similar pathophysiological mechanisms suggesting a potential causal relationship between them. In fact, Alzheimer-associated Mellitus Diabetes is also known as Type 3 Diabetes Mellitus and constitutes a diabetes intricately linked to Alzheimer's disease. Central to this association is insulin resistance, a key factor leading to decreased insulin sensitivity, hyperglycemia, and impaired glucose uptake. Because of this, the brain is altered resulting in energy deficits and neuronal damage associated with neurodegenerative disorder characteristic of Alzheimer's disease. Both diseases exhibit common biochemical and physiological characteristics such as inflammation, mitochondrial dysfunction, oxidative stress, and the formation of advanced glycation end products. Understanding the complex pathophysiology of Type 3 Mellitus Diabetes and identifying common features shared with Diabetes and Alzheimer's disease are essential steps towards potential therapeutic interventions targeting the insulin resistance pathway. The authors of this review on the relationships between type 2 diabetes and Alzheimer's disease have developed two works. In the first (Relationships between Type 2 Diabetes Mellitus and Alzheimer's Disease. I. Common pathogenic mechanisms), authors explore the shared (physiological, genetics and molecular) pathological changes occurring in Type 2 Mellitus Diabetes and Alzheimer's disease as well as pathways such as AMPK, PPARγ, cAMP, and PI3K/Akt as potential targets for managing Type 3 Diabetes Mellitus. By exploring these intricate mechanisms, the goal is to uncover their interdependencies and facilitate the discovery of innovative pharmacological and nutritional (epigenetics) strategies. In the second paper (Relationships between Type 2 Diabetes Mellitus and Alzheimer's Disease. II Potential therapies) we describe possible nutritional intervention, particularly dietary patterns and phytochemicals that can enhance the effects of pharmaceutical drugs designed against pathological mechanisms involved in the complex dual disease Type 2 Diabetes Mellitus and Alzheimer's disease (or in Type 3 Diabetes Mellitus as other authors consider).

This article is a scoping review analyzing advances in experimental studies on bacterial self-healing of concrete. From Scopus, ScienceDirect, Web of Science and Google Scholar search engine databases, 54 studies were selected for analysis, and an increasing trend of publications since 2015 was found, with India as the country with the largest research presence. Different ma-terials are used as replacement or admixture in concrete, such as fibers, particles and recycled material from construction waste. It was found that the most commonly used bacteria are Bacillus subtilis and Bacillus sphaericus, which can improve the strength of concrete by generating calcite and sealing cracks. In addition, it was found that the presence of materials such as fibers, ashes and construction recyclates can protect bacteria in an alkaline environment. The designs usually in-clude more than two experimental groups and a control. In summary, this study highlights the importance of bacterial self-healing in concrete and provides information on advances in this field of research.

Vaccination, particularly against pneumoccus and influenza, is a low-cost primary prevention, useful to avoid hard complications, particularly among frail older people. In this study, we aimed to assess the effect of a strategy for influenza and pneumococcal vaccination for outpatients, never practiced before, evaluating what could stimulate or demotivate vaccination among older people. This study was conducted during the 2023-2024 influenza season at the outpatient clinics of the Geriatrics section, University Hospital of Palermo (Italy). A total of 101 vaccinations were carried out. Half of the patients could be considered as pre-frail and about 20% frail, according to a comprehensive geriatric evaluation. Among participants, 46.3% received only vaccination against Pneumococcus and 26.8% only anti-influenza or the combination of anti-pneumococcus and anti-influenza. Compared with the previous seasons, a 19.5% increase of influenza and 90.2 % of pneumococcal vaccine uptake was observed. Side effects of vaccination were the main reason of the previous rejections, namely 74.8% for influenza and 29.5% for anti-pneumococcal vaccination. In conclusion, our study indicates how a new vaccination strategy in different settings is possible. Proposing influenza and pneumococcal vaccination for outpatients could be an effective instrument to improve immunization coverage that is still low among older people.

Graphs are largely used in computer science to model relations, or associations, among entities the compose complex systems. More recently, they found a broad field of application in bioinformatics and medical informatics supporting modelling, analysis of many systems. The applications span from representing interactions among molecules within cells, to model the functions of the brains. In order to support research, algorithms from graph theory that are able to extract knowledge from network should be coupled to efficient visualisation techniques. Although the importance of such topic, we retain that many challenges should be faced in the futures, such as automated pathway and network layout to better match biologists’ needs, the developing of a standard able to give more and better choices to represent nodes, edges finally, the developing of automated mechanism able to improve the network navigation methods that help users manage large and complex networks with the goal to improve the usability.

Removing one key barrier to the industrial uptake of green chemistry and nanocatalysis in the fine and specialty chemical industry requires to fill an ongoing “talent shortage” via expanded chemistry education. In this study we show how the use of hybrid sol-gel catalysts to synthesize fine chemicals and active pharmaceutical ingredients in flow chemistry reactors illustrates new ideas to reshape chemistry education based on recent research outcomes, visualization and digital tools. Several lessons learned from the industrial and academic utilization of these materials in continuous-flow conversions conclude the study.

Variability is the predisposition of phenomena to assume different values over time. Variability is higher when the differences of cases from each other are larger or diverge from a specific value, such as arithmetic mean. This study focuses on the variability of research topics within and between research fields to explain, whenever possible, how the variability shapes the structure and dynamics of technological trajectories. Analysis of variability here applies the entropy and variance decomposition on main research fields in quantum technologies. Empirical evidence shows that variability in research topics is inversely proportional to the age of research fields. Inductive implications are that higher variability in research topics of recent scientific fields is due to uncertain dynamics that generates a heterogeneity of different technological trajectories some of them can growth and develop towards fruitful directions others can be dismissed. Hence the variability seems to be one of the drivers that shapes technological evolution and can provide policy and managerial implications to improve the scientific and technological forecasting that may support appropriate decisions of R&D investments towards promising research fields and technologies.

The number of applications for nanobodies is steadily expanding, positioning these molecules as fast-growing biologic products in the biotechnology market. Several of their applications require protein engineering, which in turn would greatly benefit from having a reliable structural model of the nanobody of interest. However, as with antibodies, structural modeling of nanobodies is still a challenge. With the rise of artificial intelligence (AI), several methods have been developed in recent years that attempt to solve the problem of protein modeling. In this study, we have compared the performance in nanobody modeling of several state-of-the-art AI-based programs, either designed for general protein modeling, such as AlphaFold2, OmegaFold, ESMFold and Yang-Server, or specifically designed for antibody modeling, such as IgFold, and Nanonet. While all these programs performed rather well in constructing the nanobody framework and CDRs 1 and 2, modeling of CDR3 sill represents a big challenge. Interestingly, tailoring an AI method for antibody modeling does not necessarily translate into better results for nanobodies.

Flare stacks are a key element in the safety of petrochemical and refinery industries; the correct operating conditions thereof must be ensured through a schedule for the periodic reviewing of all parts thereof. Advances in Non-Destructive Testing (NDT) in recent years and the application thereof to this field allow reliable, objective information to be obtained. This article describes and groups together the main applicable NDT techniques, analysing their advantages and disadvantages, updated with the new possibilities offered by unmanned aircraft or drones.

Merkel cell carcinoma (MCC) is a rare, highly aggressive skin cancer characterized by two etiologies: the first one, observed in most cases, is attributed to Merkel cell polyomavirus (MCPyV), a DNA tumor virus, while the second one is due to ultraviolet (UV) radiation exposure. Currently, there are limited diagnostic, prognostic, and therapeutic biomarkers available for MCC. MicroRNAs (miRNAs) are small RNA molecules that do not code for proteins but regulate various cellular processes, including cell cycle progression, proliferation, differentiation, and apoptosis. The dysregulation of miRNAs has been associated with a wide range of cancers since they can act as either tumor suppressors or oncogenes. This paper aims to collect, summarize and re-organize the recent discoveries concerning miRNAs, whose dysregulation in the pathogenesis and progression of MCC is slowly emerging. Furthermore, the potential clinical applications of miRNAs as diagnostic biomarkers, possible differentiation between MCPyV-related and unrelated MCC, predictors of response to therapy and prognostics are also discussed. From this review, it emerges that miRNAs may have, in the near future, the potential to become clinically significant in improving the diagnostic accuracy, prognostic evaluation, and therapeutic options of MCCs. Finally, the new perspectives on the poorly explored field of artificial intelligence in MCC are provided.

The aim of the present study was to investigate the incidence of breast (females), prostate, testicular and thyroid cancer in the Italian National Priority Contaminated Sites (NPCSs), served by cancer registries, where the presence of endocrine disruptors (EDs), reported to be linked to these tumors, was documented. Evidence of carcinogenicity of EDs present in NPCs was assessed based on evaluation by international scientific institutions/committees. Standardized Incidence Ratios (SIRs) were computed for each NPCS and cancer site with reference to the time window 1996-2005. Excess incidence of one or more cancer site at study was found in twelve out of fourteen NPCSs. Significantly increased SIRs were found for breast cancer in eight NPCSs, for prostate cancer in six, for thyroid cancer (both gender) in four and for testicular cancer in two. Non significantly increased SIRs were found in five NPCSs for testicular cancer and in two for thyroid cancer (males). Even if increased incidence of one or more cancer sites at study were found in several NPCSs, the ecological study design and the multifactorial etiology of the considered tumors do not allow reaching conclusions in terms of causal links with environmental contamination. In light of the observation of some excesses in SIRs, continuing epidemiological surveillance is warranted.

Modern imaging strategies are paramount to studying living systems such as cells, bacteria, and fungi and their response to pathogens, toxicants, and nanomaterials as modulated by exposure and environmental factors. The need to understand the processes and mechanisms of damage, healing and cell survivability of living systems continues to motivate the development of alternative imaging strategies. Of particular interest is the use of label-free techniques that minimize interference of biological processes by foreign marking substances and reduce intense light exposure and potential photo-toxicity effects. This review focus on the potential synergic capabilities of atomic force microscopy (AFM) as a well-developed and robust imaging strategy with demonstrated applications to unravel intimate details in biomedical applications, with the label-free, fast, and enduring Holotomographic Microscopy (HT) strategy. We first review the operating principles that form the basis for the complementary details provided by these techniques regarding the surface and internal information provided by HT and AFM is essential and complimentary for the development of several biomedical areas studying the interaction mechanisms of nanomaterials with living organisms. First, AFM can provide superb resolution on surface morphology and biomechanical characterization. Second, the quantitative phase capabilities of HT enable superb modeling and quantification of the volume, surface area, protein content, and mass density of the main components of cells and microorganisms, including morphology of cells in microbiological systems. These capabilities result from directly quantifying refractive index changes without requiring fluorescent markers or chemicals. As such, HT is ideally suited for long-term monitoring of living organisms in conditions close to their natural settings. We present a case-based review of the principal uses of both techniques and their essential contributions to nanomedicine and nanotoxicology, emphasizing cancer and infectious disease control. The synergic impact of the sequential use of these complementary strategies provides a clear drive for adopting these techniques as interdependent fundamental tools.

Over the years, network analysis became a promising strategy to analyze complex system, i.e. systems composed by a large number of interacting elements. In particular, multilayer networks have emerged as a powerful framework for modelling and analysing complex systems with multiple types of interactions. Network analysis can be applied to pharmacogenomics to gain insights into the interactions between genes, drugs, and diseases. By integrating network analysis techniques with pharmacogenomic data, the goal consists to uncover complex relationships and identify key genes to use in pathway enrichment analysis to figure out biological pathways involved in drug response and adverse reactions. In this study, we model omics, diseases and drugs data together through the multilayer network representation. Then, we mined the multilayer network with a community detection algorithm by obtaining top communities. After that, we used the identified list of genes from the communities to perform pathway enrichment analysis (PEA) to figure out the biological function affected form the selected genes. The results show that the genes forming the top community have the multiple roles through different pathways.

Background: The duration of the vaccine's protective efficacy against SARS-CoV-2 is unknown. Evaluation of the clinical performance of available tests is required. Objectives: To evaluate the clinical performance of three immunoassays for the detection of IgG antibodies generated by mRNA vaccines against SARS-CoV-2. Methods: Two automated immunoassays (Euroimmun Anti-SARS-CoV-2 ELISA IgG and Abbott SARS-CoV-2 CLIA IgG) and one lateral flow immunoassay (LFIA Test Livzon IgG) were tested. 300 samples distributed in 3 groups were analyzed: 100 subjects over 18 years old and under 45 years old, 100 subjects between 45-65 years old and another 100 over 65 years old. collected before vaccination, at 21 days, 1, 2, 3 and 6 months post-vaccination. Sensitivity, specificity, positive predictive value, negative predictive value, positive likelihood ratio, negative likelihood ratio, and agreement (I. Kappa) were calculated for each serological test. Results: Maximum sensitivity for IgG was 98.7%, 98.1%, and 97.8% for the ELISA Euroimmun, CLIA Abbott, and Livzon LFIA assays and maximum specificity for IgG was 99.4%, 99.9%. % and 98.4% ELISA, CLIA and LFIA respectively at 3 months after vaccination with a decrease in antibody levels from the sixth month. The best agreement was observed between ELISA and CLIA 100%; (k = 1.00). The agreement between ELIA, CLIA and LIFIA was 99% (k = 0964) at the second and third month after vaccination. Seroconversion was faster and longer lasting in the younger age groups. Conclusion: Our study showed an equivalent and homogeneous clinical performance for IgG of three immunoassays after vaccination and that the LIFIA assay is the most cost-effective, reliable and accurate for routine use in population studies of seroconversion and seroprevalence.

A probe of a patient, seeking help in an emergency ward of a French hospital in late December 2019 because of Influenza like symptoms, was retrospectively tested positive to COVID-19. Despite the early appearance of the virus in Europe, the prevalence and virulence appeared to be low for several weeks, before the spread and severity of symptoms increased exponentially, yet with marked spatial and temporal differences. Here, we compare the possible linkages between peaks of fine particulate matter (PM2.5) and the sudden, explosive increase of hospitalizations and mortality rates in the Swiss Canton of Ticino, and the Greater Paris and London regions. We also discuss the influence of Saharan dust intrusions on the COVID-19 outbreak observed in early 2020 on the Canary Islands. We find that high PM2.5 concentrations – possibly favored by air temperature inversions or Saharan dust intrusions – are not only modulating but even more so boosting severe outbreaks of COVID-19. We conclude that the overburdening of the health services and hospitals as well as the high over-mortality observed in various regions of Europe in spring 2020 can be linked to peaks of PM2.5 and likely particular weather situations that have favored the spread and enhanced the virulence of the virus. In the future, we recommend to monitor not only the prevalence of the virus, but also to consider the occurrence of weather situations that can lead to sudden, very explosive COVID-19 outbreaks.

Convolutional Neural Networks (CNNs) present drawbacks for modeling geometric transformations, such as scaling and rotation, caused by the convolution operation’s locality. Deformable convolution (DCON), a mechanism that substitutes standard convolution, increasing the receptive field to capture relevant features, is a promising approach to solve this drawback and improve the robustness of CNNs. However, the optimal way to replace the standard convolution with its deformable counterpart in a CNN model is unclear. In this study, we clarify this aseveration by conducting several experiments using deformable convolutions applied in the layers that conform a small four-layer CNN model. We also use deformable convolutions on the four-layers of several ResNet CNNs with depths 18, 34, 50, and 101. The models were tested in binary balanced classes with 2D data for image classification: Cats &amp; Dogs, EyesPACS, Spyders &amp; Chickens, and Shapes. After this testing, we evaluated DCON in 3D data for action recognition: UCF101 and Human2 (a dataset we compiled to control movement, clothing and background). The contribution of this research lies in a guideline to use DCON. It can be summarized as follows: if DCON is used on the first layers of the proposal of model (with simple features), the computational resources expressed as the quantity of Flops will tend to increase and produce bigger misclassification than the standard CNN. However, if the DCON is used at the end layers, the quantity of Flops used in the training and testing will decrease, and the classification accuracy will improve by up to 20% about the base model. Moreover, it gains robustness when using deformable convolutions because it can adapt to the region of interest. Also, the best kernel size of the DCON is three. It showed better results than size five. In the last case, the quantity of Flops increase quadratically, but their performance does not increase significantly. With these results, we propose a guideline to use the DCON and contribute to understanding the impact of DCON on the robustness of CNNs.

The cancer stem cell hypothesis suggests that neoplastic cells with stem characteristics hierarchically regulate tumor generation and its high cellular heterogeneity. These cells have been detected in all cancer types, and specific signaling pathways give the regulation of self-renewal and differentiation. In prostate cancer, androgen receptor signaling has been extensively studied, and in non-stem cells, it promotes cell proliferation and tumor progression, but in the cancer stem cell population, it negatively regulates processes such as self-renewal. However, in other types of cancer, such as breast and glioblastoma, the androgen receptor seems to favor the maintenance of cancer stem cells, suggesting that androgen signaling has different effects depending on the tumor context. This review discusses the role of androgen receptor in maintaining cancer stem cells by regulating proliferation, self-renewal, and differentiation, as well as the possible signaling pathways involved in these processes.

Since the 1960s Rare earths (REs) applications gradually have expanded to everyday life. REs have great strategic importance in industrial and technological development, so it is expected an increase in their demand. Among the REs the European Commission considered Cerium and Lanthanum as critical raw materials. This research article studies the adsorption of Ce and La onto two carbon nanomaterials, multiwalled carbon nanotubes (MWCNT) and carboxylic functionalized multiwalled carbon nanotubes (MWCNT_ox). The latter has slightly more affinity for REs than MWCNT. The recovery percentage for Ce were 89 and 98% and in the case of for La were 99 and 92% using 0.8 g of MWCNT and 0.2 g of MWCNT_ox respectively. The adsorption process fits a pseudo second-order kinetic model and the Langmuir isotherm best represented the metal uptake.

Poikilodermatous plaque-like hemangioma (PPH) is a recently described clinical and pathological entity, with only 18 cases reported in the literature. Although uncommon, this benign condition presents consistent clinical and histological findings. We present a new case of PPH in an 81-year-old male and review the existing literature. The persistence over time and the need to distinguish PPH from more significant lesions underscore the importance of its clinical and pathological recognition.

The cerebellum is an encephalic region classically known for its central role in the control of movement, although recent research has revealed its involvement in other cognitive and affective tasks. Several different pathologies are known to affect this structure, causing a wide range of behavioral and gait impairments. Intriguingly, although the neurodegenerative factors affect all Purkinje cells of the cerebellum uniformly, certain neurodegeneration patterns can be distinguished, in which some Purkinje cells persist longer than other cell types. Precisely, there is a cerebellar region, lobe X, which is more resistant to different types of neurodegeneration regardless of the injury. This work will review the main models of cerebellar degeneration, with special emphasis on this region, and aims to reveal a common origin for its resistance to neuronal death.

In the past twenty years, the IT industry has moved away from using physical servers for workload management to workloads consolidated via virtualization and, in the next iteration, further consolidated into containers. In the next step, container workloads based on Docker and Podman as underlying container technologies were orchestrated/automated via Kubernetes or OpenShift. On the other hand, high-performance computing (HPC) environments have been lagging in that process, as there’s still much work to figure out how to apply containerization platforms for HPC in real-life scenarios. Kubernetes and OpenShift have many advantages – generally speaking, container technologies use quite a bit less overhead from the computing perspective while providing many benefits in flexibility, modularity, and maintenance. Therefore, they are ideal for tasks requiring a lot of computing power. There are also some tradeoffs regarding the complexity of these two platforms - they’re just not that user-friendly when used by people without years of experience managing them. In this paper, we propose a different architecture based on seamless hardware integration and user-friendly, dynamic workload placement based on real-time performance analysis and prediction coupled with Machine Learning-based scheduling.

The use of vitamin D (VitD) supplements has become widespread in the last decade due not only to the dissociation between the blood levels recommended as "optimal" and those shown by the healthy population, but also to its presumed beneficial effects on multiple disorders. This work evaluated the levels of 25-hydroxyvitamin D [25(OH)D] in a healthy population of European origin living in a region with high solar irradiation. In serum samples from a population-based study conducted in the Canary Islands, levels of 25(OH)D were analyzed. In 876 individuals who had no history of kidney or malabsorption disorders and who had not been treated with calcium and/or VitD supplementation, the median 25(OH)D level was 26.3 (5th;95th percentile, 14.3;45.8)ng/mL. Notably, 65.4% of the population had 25(OH)D blood levels below 30ng/mL, 23.4% below 20ng/mL and 6.4% below 15ng/mL. Based on the lack of evidence supporting causality between 25(OH)D levels below what is recommended as optimal (≥20ng/mL, or even ≥30ng/mL) and major skeletal and non-skeletal diseases, and in light of the distribution of the concentration of this vitamin in healthy adults living under optimal conditions of solar irradiation, it seems reasonable to consider 25(OH)D levels below 20ng/mL and close to 15ng/mL as adequate for the general population.

Cutaneous wound healing is a complex multi-stage process involving direct and indirect cell communication events with the aim of efficiently restoring the barrier function of the skin. One key aspect in cutaneous wound healing is associated with cell movement and migration into the physically, chemically and biologically injured area resulting in wound closure. Understanding the conditions under which cell migration is impaired and elucidating the cellular and molecular mechanisms that improve healing dynamics is therefore crucial in devising novel therapeutic strategies to elevate patient suffering, reduce scaring and eliminate chronic wounds. Following the global trend towards automation, miniaturization and integration of cell-based assays into microphysiological systems, conventional wound healing assays such as the scratch assay or cell exclusion assay have recently been translated and improved using microfluidics and lab-on-a-chip technologies. These miniaturized cell analysis systems allow precise spatial and temporal control over a range of dynamic microenvironmental factors including shear stress, biochemical and oxygen gradients to create more reliable in vitro models that resemble the in vivo microenvironment of a wound more closely on a molecular, cellular, and tissue level. The current review provides (a) an overview on the main molecular and cellular processes that take place during wound healing, (b) a brief introduction into conventional in vitro wound healing assays, and (c) a perspective on future cutaneous and vascular wound healing research using microfluidic technology.

Predatory research field in science is when an emerging scientific topic destroys current topics and characterizes a main scientific change. Predatory research field can be a basic driver of scientific and technological change that generates a 'creative destruction' in science and society in contexts of knowledge-based competition and rapid changes. The prediction of proposed theory of predatory research fields is that it destroys with a fast growth other research fields. The theoretical approach is tested here in research fields of large language models (LLM) by analyzing the transformers (a deep learning architecture based on the multi-head attention mechanism) proposed in 2017 and from November 2022 started main applications in generative artificial intelligence with innovations of BERT, ChatGPT, Microsoft Copilot (launched on February 7, 2023) and other natural language processing tools driven by AI technology for engaging conversations, gain insights, automate tasks, etc., etc. Statistical evidence suggests that growth rate of transformer technologies is 80.58%, a high level compared to all other research fields in machine learning (having a growth rate of 13.83%). Moreover, predatory research field of transformers has a destructive power such that all other domains in LLM from 2021 to 2023 have a general reduction of scientific growth. The impact of transformers is much more drastic of previous radical technologies such as CNN having a temporal growth rate of 0.16%, lower than 0.38% by transformers, ceteris paribus. These analysis reveals that transformers have characteristics to generate a radical scientific and technological change in a not-too-distant future. Overall, then, the study suggests that predatory research field on emerging topics and technologies can generate path-breaking innovations and the examination here can clarify the essential elements of the science dynamics for a better theory of scientific and technological change, providing also main implications for knowledge policy to support promising research fields and technologies to guide economic and social change.

Biological systems often need to operate in complex environments where conditions can rapidly change. This is possible due to their inherent ability to sense changes and adapt their behavior in response. Here, we detail recent advances in the creation of synthetic genetic parts and circuits whose behaviors can be dynamically tuned through a variety of intra- and extra-cellular signals. We show how this capability lays the foundation for implementing control engineering schemes in living cells and allows for the creation of biological systems that are able to self-adapt, ensuring their functionality is maintained in the face of varying environmental and physiological conditions. We end by discussing some of the broader implications of this technology for the safe deployment of synthetic biology.

The fundamental question in the field of sensor research is new directions of scientific fields, which play a vital role in the progress of science and technology. This study confronts this question here by developing a bibliometric analysis, which endeavors to explain the evolution of sensor research and new technologies that are critical to science and society. The database of Scopus concerning scientific documents and patents is used for statistical and computational analyses in these topics. Results suggest that emerging technological trajectories in sensors are wireless sensor networks, wearable sensors and biosensors. Main characteristics of these growing research fields and technologies in sensors are described for fruitful implications of research and innovation policy directed to science advances and technological change in society.

Production and transport of reactive species through plasma-liquid interactions plays a significant role in multiple applications in biomedicine, environment, and agriculture. We experimentally investigated the transport mechanisms of hydrogen peroxide H2O2 and ozone O3, as the typical plasma species, into water. We measured the solvation of gaseous H2O2 and O3 in airflow into water bulk vs. electrosprayed microdroplets while changing the gas and water flow rates, applied voltage that determines the gas-liquid interface area, and treatment time. The solvation rate of H2O2 and O3 increased with the treatment time and the gas-liquid interface area. The total surface area of the electrosprayed microdroplets was larger than that of the bulk, but their lifetime was much shorter. We estimated that only microdroplets with diameters below ~ 40 µm could achieve the saturation by O3 during their lifetime, while the saturation by H2O2 was impossible due to its depletion from air. Besides the short-lived flying microdroplets, the longer-lived bottom microdroplets substantially contributed to H2O2 and O3 solvation in water electrospray. This study contributes to a better understanding of the gaseous H2O2 and O3 transport into water as a function of different parameters and will lead to design optimization of the plasma-liquid interaction systems.

Dendroclimatology has gained relevance during the XXI century. We analyze the state of-the-art of dendroclimatology in Latin America during the past 28 years (1990 to 2019), identifying the current state and recent advances in the application of dendroclimatology in this region. We carried out a systematic review in ScienceDirect, Web of Science, and Scopus databases using Boolean operators to logically connect the keywords “dendrochronology,” “dendroclimatology,” “trend,” “climatic variability,” and “climatic variability trend”, for each country. Dendroclimatological research conducted in the region focused on climatic reconstruction and the evaluation of new tree species with dendrochronological potential, which increase in 2010, then there was a gap between 1995 and 1996, later increase to present. Dendroclimatological studies in Latin America have been mainly developed in temperate climate zones (82.4 %) followed by tropical or subtropical areas (17.6 %). Dendroclimatological research in Latin America has provided advances in the study of climate variability by defining response functions of tree rings to climate. The generated information allows for a better understanding of the spatial and temporal dynamics of climatic variability and about its effects on ecosystems and society. We also call for increased dendroclimatological research based on subtropical and tropical forests limited studied until today.

Carbonate rocks occupy about 6490 km2 in Albania (23% of the country) and the total exploitable karst water resources are estimated in 2.84*109 m3/year (about 65% of the total exploitable groundwater resources in the country, and about 70% of those used for water supply). In addition, karst massifs are very rich in thermal waters, related to the ascending fluids which are essential for the development of hypogenic karstification in the outer Albanides. This type of karst facilitates the circulation regime of deep fluids, which are revealed at the surface through both numerous phenomena of hypogene karst and hot springs. The relatively small Kruja Tectonic Zone is characterized by the presence of SE-NW oriented carbonate structures, rich in thermal sources, and contains more than the 80% of Albania thermal springs. One of its most interesting carbonate structures, for the presence of both cold and thermal waters, is the small karst structure of Makaresh, with a surface of 22 km2. The purpose of this article is to describe the characteristics and factors that affect the quantitative and qualitative formation of cold and thermal groundwater in this massif. Based on the physico-chemical characteristics, groundwaters of the study area are classified in cold and thermal waters. The former are mainly of HCO3-Ca or HCO3-Ca-Mg type (Electrical Conductivity 580-650 μS/cm, Temperature 13.9-16.6° C). Thermal waters are mainly of the Cl-Na-Ca type (EC 7200-7800 μS/cm, T 18.5-22.5° C); further, they are characterized by high hydrogen sulphide concentration, up to about 350 mg/l. The presence of two groundwater types in the Makaresh massif is connected to the presence of two groundwater circulation systems. The main factors of the groundwater physic-chemical quality are the solution of rocks and minerals therein contained, the presence of hypogenic speleogenesis, and the mixing of the groundwater of the two systems. The hydrogeological studies proved that karst rocks contain considerable fresh water resources; the capacity of water wells used for the drinking water supply reaches up to about 50 l/s. Thermal waters are not currently exploited due to their temperature, but they are potentially suitable for thermal uses, by drilling boreholes at depth of about 1000 m.

Abstract: Coal bed methane (CBM) reservoirs are complex systems whose properties differ from those of conventional reservoirs. Coal seams are dual-porosity systems that comprise the porosities of the matrix and cleat system. Gas in the coal seams can be stored as free gas in the cleat system and as adsorbed gas in the porous medium. The flow mechanisms of the natural gas through the formation include desorption, diffusion, and Darcy’s flow regimes. The permeability of CBM reservoirs is more sensitive to pressure variations than conventional gas reservoirs. To study the flow behavior of CBM reservoirs it is mandatory to use a model that considers their unique characteristics. The objective of this study was to propose a physical and mathematical model of production performance for horizontal wells in CBM reservoirs whose permeability is dependent on pressure. A solution for the model was obtained by applying Pedrosa´s transformation, perturbation theory, Laplace transformation, the point source method, and Sthefest´s algorithm. The solution to this problem was validated with previous work thoroughly. The type curves of the model were built and the pressure transient behavior of the model was analyzed and discussed. The effects of several parameters on pressure behavior were also discussed.

The initial development of seahorse juveniles is characterized by low digestion capabilities. Stable isotope analysis is an effective tool in studies of trophic food webs and animal feeding patterns. The present study provides new insights for the understanding of growth and food assimilation in early developing seahorses following a laboratory diet switch. The study was performed in early life stages of the seahorse Hippocampus reidi by assessing the influence of diet shift on changes and turnovers in carbon (δ13C) and nitrogen (δ15N) stable isotope in juveniles. Newborn seahorses were fed for 60 days following two feeding schedules (A6 and A11) based initially on copepods Acartia tonsa and subsequently on Artemia nauplii (since days 6 and 11, respectively). After prey shift, we determined δ13C and δ15N turnover rates as functions of change in either body mass (fitting model G) and days of development (fitting model D), contributions of metabolism and growth to those turnover rates, and diet-tissue discrimination factors. Survival, final dry weight and final standard length for diet A11 were higher compared to diet A6. The shift from copepods to Artemia lead to fast initial enrichments in δ13C and δ15N. Afterwards, the enrichment was gradually reduced until reaching the isotopic equilibrium with diet. In most cases, both fitting models performed similarly. The isotopic analysis revealed that 100% of tissue turnover was attributed to growth in diet A11, whereas 19-25% was endorsed to metabolism in diet A6. Diet-tissue discrimination factors were estimated for the first time in seahorse juveniles, resulting in higher estimates for diet A11 (2.9 ± 0.7‰ for δ13C; 2.5 ± 0.2‰ for δ15N) than in diet A6 (1.8 ± 0.1‰ for δ13C; 1.9 ± 0.1‰ for δ15N). This study highlights the relevance of feeding on copepods and their effect on isotopic patterns and discrimination factors in seahorse juveniles after a dietary shift. Regarding the application of the results achieved to feeding schedules in the rearing of H. reidi, a long period of feeding on copepods during the first days of development is highly recommended.

Coronavirus Disease 2019 (Covid-19) was first described in December 2019 in Wuhan, Hubei Province, China; and produced by a novel coronavirus designed as the acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Covid-19 has become a pandemic reaching over 1.3 million confirmed cases and 73,000 deaths. Several efforts have been done to identify pharmacological agents that can be used to treat patients and protect healthcare professionals. The sequencing of the virus genome not only has offered the possibility to develop a vaccine, but also to identified and characterize the virus proteins. Among these proteins, main protease (M^pro) has been identified as a potential therapeutic target, since it is essential for the processing other viral proteins. Crystal structures of SARS-CoV-2 M^pro and inhibitors has been described during the last months. To describe additional compounds that can inhibit SARS-CoV-2 M^pro, in this study we performed a molecular docking-based virtual screening against a library of experimental and approved drugs. Top 10 hits included Pictilisib, Nimorazole, Ergoloid mesylates, Lumacaftor, Cefuroxime, Cepharanhine, and Nilotinib. These compounds were predicted to have higher binding affinity for SARS-CoV-2 M^pro than previously reported inhibitors for this protein, suggesting a higher potential to inhibit virus replication. Since the identified drugs have both pre-clinical and clinical information, we consider that these results may contribute to the identification of treatment alternative for Covid-19. Nevertheless, in vitro and in vivo confirmation should be performed before these compounds could be translated to the clinic.

Urban wind energy has emerged as an attractive source of distributed generation in cities to achieve sustainable development goals. The advance in technologies for the use of urban wind energy has turned this source into an attractive alternative for the decarbonization of cities and the energy transition. The objectives of this work are (1) to identify the potential of wind energy through numerical weather prediction (NWP) data tools and (2) to identify the roles and responsibilities of the stakeholders involved in the decision-making process. A methodology was developed in two phases and applied to a case study in the Dominican Republic. The first phase consisted of estimating the wind energy potential for the 32 provinces at a height of 10 m using open-access geographic reference systems tools provided by NASA. In the second phase, 28 stakeholders were identified through snowball sampling. The Responsible, Accountable, Consult, and Informed (RACI) matrix tool was applied to identify the roles of the 28 institutions addressed at the country level as relevant in the decision-making process for the energy sector. The annual average wind speed and energy potential for each province were determined. It was found 24 provinces have poor potential, below &lt;4.5 m/s. In the northwest and east is where there is the greatest potential, between 4.83 - 6.63 m/s. The population density was established and was observed that the provinces with greater potential are less densely populated. Through 59 interviews 28 institutions were identified and evaluated due to their relevance in decision-making for the implementation of energy projects. The MEM has strongly categorized as “A”, electricity distribution companies as “R”, energy associations and universities as “C”, and educational and justice institutions as “I”.

The persistent threat of cancer remains a significant hurdle for global health, prompting the exploration of innovative approaches in the quest for successful therapeutic interventions. Cyclin-dependent kinase 9 (CDK9), a central player in transcription regulation and cell cycle progression, has emerged as a promising target to combat cancer. Its pivotal role in oncogenic pathways and the pressing need for novel cancer treatments has propelled CDK9 into the spotlight of drug discovery efforts. This article presents a comprehensive study that connects a multidisciplinary approach, combining computational methodologies, experimental validation, and the transformative PROTAC (Proteolysis-Targeting Chimera) technology. By uniting these diverse techniques, we aim to identify, characterize, and optimize a new class of degraders targeting CDK9. We explore these compounds for kinase inhibitory properties and potential to induce targeted protein degradation, offering a novel and potentially more sustainable approach to cancer therapy. This cohesive strategy expresses the interface between computational predictions and experimental insights, with the ultimate goal of advancing the development of effective anticancer therapeutics targeting CDK9.

The gate resistance is a parasitic element in transistors for RF and millimeter-wave circuits that can negatively impact power gain and noise figure. To develop accurate device models, a reliable measurement methodology is crucial. This article reviews the standard measurement methodology used in the literature and proposes also an additional method, which is evaluated using suitable test structures in a 16nm FinFET process. The advantages and disadvantages of the two approaches are discussed along with their respective application scenarios

Following an updated outlook of global energy production and utilization, we show through selected examples from both developing and developed countries how distributed generation from renewable energy sources, and from solar energy in particular, is the key solution to ending energy poverty across the world. Guidelines aimed at policy makers suggest a systems view of energy that will be instrumental in guiding the transition from fossil fuels to combustion-free renewable energy for all energy end uses.

The manufacture of SiC-based composites is quite widespread, and currently different methods are employed for to produce them. The most efficient method, taking into account the cost/performance ratio, is reactive melt infiltration. It consists in infiltrating liquid silicon into a porous preform that must contain carbon, so that SiC is produced during infiltration. This chemical reaction is, in fact, the driving force of the process. In the present work, the synthesis of two SiC-based composite materials with very different applications and microstructures has been studied and optimized. In both cases, materials have been obtained with suitable properties for the selected applications. One of the materials studied is SiCp/Si for protection systems such as armor jackets, and the other one is Cf/SiC for use in braking systems. For the optimization, the dwell time and the atmosphere (Ar or primary vacuum) were used as variables. It has been found that in both preforms the optimum conditions are 1 hour dwell time and a vacuum atmosphere at 1450 °C. The effect of these parameters on microstructure and infiltration kinetics are discussed.