Objectives: To assess the short-term impact of a single global stretching session on plantar pressures and lumbar range of motion (RoM) over one week in sedentary university students. Design: A randomised controlled trial with two parallel groups. Participants: Sixty-four university students were randomly assigned to a stretching group or control group. The stretching group received a single session of global stretching and the control group remained seated for the same length of time as the stretching session. Main outcome measures: Lumbar RoM and plantar pressures were assessed before, immediately after, 48 hours after, and 7 days after intervention. Results: Group-by-time interaction was significant for lumbar lateral flexion (p = 0.044), right maximal pressure (p = 0.003), left maximal pressure (p = 0.008), right mean pressure (p = 0.025), left mean pressure (p = 0.002), and maximal pressure minus mean pressure in right foot (p = 0.007). The model with plantar pressures showed a significant difference for group-by-time interaction (p = 0.010).Conclusion: Global stretching seems to counteract the ill-effects of prolonged sitting up to seven days with respect to plantar pressure in standing without improving lumbar ROM

Fifty bull calves of the Continental × British crossbred (147.0 ± 1.67 kg body weight, BW) were used in a completely randomized design to investigate the effect varying levels and duration of calcium propionate (CaPr) supplementation on the growth performance, body fat reserves, serum metabolites, and hemogram of high-risk newly received stocker calves. These calves were individually housed and fed a received-diet for 56 d. The calves received the following treatments: 1) No CaPr (CTL), 2) 20 g CaPr/calf/d, 3) 40 g CaPr/calf/d, 4) 60 g CaPr/calf/d, and 5) 80 g CaPr/calf/d, during 14, 28, 42 and 56 d the after arrival. The supplementation with 20 g CaPr from 28 to 56 d after arrival increases average daily gain (ADG) and BW (p < 0.05), and DMI is not affected (p > 0.05). This is reflected at 28 d with increases (p < 0.05) in ADG:DMI ratio and longissimus muscle area (LMA), and at 56 d in back fat thickness (BFT) y fat thickness at the rump (FTR). Also, with 20 g, blood urea nitrogen decreased (p < 0.05); and increases were observed in the activity of gamma glutamyltransferase, monocytes (quadratic trend, p < 0.07) and granulocytes% (quadratic effect, p < 0.03). However, as the level of CaPr increased during the first 14 d after arrival, daily water intake, creatinine, total cholesterol, mean corpuscular hemoglobin concentration (linear effect, p < 0.05), globulin, calcium and mean corpuscular volume (linear trend, p = 0.08) increased, while alkaline phosphatase (linear trend, p = 0.07) and lymphocytes (linear effect, p = 0.05) decreased. Finally, the different levels of CaPr supplementation did not produce any significant effects or differences (p > 0.05), in the remaining serum metabolites and hemogram (p > 0.05). Ultimately, the inclusion of 20 g CaPr/calf/d in the diet for 28 d in newly received stocker calves increases ADG, ADG:DMI ratio and LMA. If extended to 42 or 56 d, the increases in ADG persist, but there is also a rise in body fat reserves (BFT and FTR) at the expense of a reduction in ADG:DMI ratio. Furthermore, the different supplementation levels did not impact the reference range for most serum metabolites or the health of stocker calves.

Forty-five male Dorper crossbred lambs (40.17 ± 0.35 kg BW) were used in order to investigate the effects of the duration of calcium propionate (CaPr) supplementation in lambs finished with zilpaterol hydrochloride (ZH) on the productive performance, carcass characteristics, and meat quality. Lambs were individually housed and fed a finishing-diet for 42 d before being slaughtered. Lambs received the following treatments: 1) No additives (CTL), 2) ZH supplementation for 28 d (with 3 d ZH withdrawal before slaughter) at a dosage of at 7.2 mg/kg diet (ZH), for treatments 3, 4, and 5, lambs received ZH and 10g CaPr/lamb/d throughout the entire phase (42 d), or during the last 28 or 14 d before slaughter. Compared to CTL, ZH lambs exhibited a similar average daily gain (ADG) but had lower dry matter intake (DMI), leading to increased feed efficiency. Supplementing with ZH alone did not affect carcass traits, visceral mass, whole cuts, or meat quality. Lambs that received both CaPr and ZH exhibited quadratic increases (p < 0.05) in final BW (FBW), ADG, and dressing percentage (D%). These increases were optimal at an estimated inclusion durations of 26 d for FBW, 30 for ADG, and 39 d for D%. The ADG:DMI ratio and the longissimus muscle area (LMA) both exhibited quadratic increases (p < 0.05). The optimal duration of CaPr supplementation for ADG:DMI ratio was found to be 28 d, while for LMA, it was 14 d. As the period of CaPr supplementation increased, there was a linear increase (p <0.05) in hot carcass weight, leg circumference, and whole cuts of breast IMPS209 and shoulder IMPS207. Cook loss percent increased quadratically (p < 0.05), being higher when CaPr was included for an estimated duration of 26 d. As the duration of CaPr supplementation increased, the purge loss percentage (PLR) also increased linearly (p < 0.05). In conclusion, including CaPr in the diet for a duration of 28 d in lambs improved the response to ZH supplementation on the productive performance, carcass weight and some whole cuts. However, it can also have a negative effect on PRL%.

The use of different sources to energize a load is convenient in many applications, particularly those where two or more renewable energy sources are employed as: energy harvesting, hybrid vehicles, and off-grid systems. In these cases, a multi-input converter able to admit sources with different characteristics and, if necessary, select the output power of each source. Several topologies of multi-input converters have been proposed to this aim, however, most of them are based on multi-stage designs, which decreases efficiency and increases control complexity, particularly when more than two sources are used. In this work, a three-input step-up converter easy to control in open loop condition is analyzed. A designed procedure is described, and experimental results are presented for a 1 kW power converter. The implemented converter results in a higher voltage gain, less storage element keeping high efficiency compared to similar topologies. Using the procedure here proposed, this converter that was initially proposed for photovoltaic applications is enabled to be used in medium and high-power applications, for example when renewable energy sources are used.

Gestational diabetes mellitus (GDM) triggers alterations in the maternal gut microbiome. Alongside metabolic shifts, microbial products may impact clinical factors and influence pregnancy outcomes. Here, we performed two separate analyses to integrate the maternal microbiome-metabolomic differences from a subset of the “Choosing Healthy Options in Carbohydrate Energy” (CHOICE) study. Women diagnosed with GDM were randomized to a diet higher in complex carbohydrates (CHOICE, n=18, 60% complex carbohydrate/25% fat/15% protein) or a conventional GDM diet (CONV, n=16, 40% carbohydrate/45% fat/15% protein). All meals were provided, diets were eucaloric, and fiber content was similar. CHOICE diet was associated with increases in TMAO, lysophosphotidylcholines, indoxyl sulfate, and several triglyceride (TG) species, while CONV diet was associated with higher plasma hippuric acid, aspartic acid, betaine, glutamic acid, indole propionic acid, and indoleacetic acid, suggesting that differences in lipid metabolism and tryptophan utilization pathways are linked to specific maternal diets. We also identified two latent metabolic groups not associated with either diet treatment: one metabolome associated with higher fasting glucose, and the other associated with higher fasting TGs after 7 weeks on either diet. Our study underscores the importance of utilizing dietary approaches to optimize maternal-fetal health outcomes in GDM treatment.

Drawing on contextualization literature, this paper seeks to evaluate the impact of contextual theology from a Latin American perspective. Bevans' (2002) Praxis Model of contextual theology sets the conceptual framework used to evaluate the evangelical response to the sociopolitical crisis in Nicaragua. The case study provides an example of how Bevans’ Praxis Model can be applied by looking at the manner with which the evangelical and the catholic church have responded to the sociopolitical upheaval in Nicaragua. The literature on contextualization highlights how theologizing is inextricably tied to culture, that contextual theology is necessary to effectively communicate the truth of the Gospel in varying cultural contexts, and that the issues of syncretism and the plurality of theologies can be effectively addressed.

The complex interplay between dietary factors, inflammation, and macrophage polarization is pivotal in the pathogenesis and progression of chronic liver diseases (CLDs). Omega-3 fatty acids (FAs) have been attracted attention due to their potential to modulate inflammation and exert protective effects in various pathological conditions. This review explores the emerging role of omega-3 FAs and their specialized pro-resolving mediators (SPMs) in the context of macrophage polarization, with a focus on chronic liver diseases. Omega-3, eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA) have promising effects in mitigating inflammation and enhancing the resolution of inflammatory responses. They influence the M1/M2 macrophage phenotype balance, promoting a shift towards the M2 anti-inflammatory phenotype. SPMs, such as resolvins (Rvs), protectins (PDs), and maresins (MaRs), have emerged as potent regulators of inflammation and macrophage polarization. They show anti-inflammatory and pro-resolving properties. These mediators modulate the expression of cytokines, facilitate the phagocytosis of apoptotic cells, and promote tissue repair. MaR1, in particular, has demonstrated significant hepatoprotective effects by promoting M2 macrophage polarization, reducing oxidative stress, and inhibiting key inflammatory pathways such as NF-κB. In the context of CLD, such as nonalcoholic fatty liver disease (NAFLD) and cirrhosis, omega-3 and their SPMs have shown promise in attenuating liver injury, promoting tissue regeneration, and modulating macrophage phenotypes. However, the mechanisms underlying their effects and their interactions with other cell types within the liver microenvironment require further investigation. Understanding the intricate relationship among SPM and macrophage polarization holds unlimited potential for the development of novel therapeutic strategies for chronic liver diseases.

This compendium presents new mathematical techniques for modeling Point Absorbers. A combined frequency-time domain framework is developed. It is used to simulate the energy generated by the wave farms. With Matlab and Fortran as a base, this leads to obtain physical variables of primary importance, namely position, velocity and power to energy net balance relationships of absorption. Integration of different degrees of freedom with heave as main executable leads in turn to a single buoy motion focus. Acquisition of the needed hydrodynamic coefficients is provided through application of potential field solvers with Boundary Element Methodology background. Initially, this Wave-to-motion model is validated by comparison with previous experimental results for a floating cone cylinder shape (Buldra-FO3). A single, generic, vertical floating cylinder is contemplated then, that responds to the action of the passing regular waves excitation. Later, two equally sized vertical floating cylinders aligned with the incident wave direction are modeled for a variable distance between the bodies. For both unidirectional regular and irregular waves as an input in deep water, we approximate the convolutive radiation force function term through the Prony method. By changing the spatial disposition of the axisymmetric buoys, using for instance triangular or rectangular shaped arrays of three and four bodies respectively, the study delves into motion characteristics for regular waves. The results highlight efficient layouts for maximizing the energy production whilst providing important insights into their performance, revealing displacement amplification- and capture width-ratios, while deriving in possible interpretations of scenarios related to the known park effect. These terms are encompassed by the novelty of a new conceptual Post-Processing methodology in the field, which leads to obtain an optimal distance for the separated bodies with effective energy absorption in a regular wave regime. The main objective is to generate a tendency within the hydrodynamic field of study, which is the Wave to motion perspective. More generally, this computational excursion envisions and depicts potential fields of study, which will surely enhance new connections and link this renewable energy form. Therefore, this research delves first into the historical and technical background on Ocean Wave Energy. Next, it is in the section regarding Materials and Methods, where boundaries and related equations are introduced step by step, together with latter mentioned case scenarios, and their corresponding configuration parameters. A separate section frames then the scope of results, while finally, there is an ensuing discussion and conclusions for evaluation assessment.

This article presents an innovative approach to the design of a safe adaptive backstepping control system. Tailored specifically for underactuated marine robots, the system utilizes simple sensors for enhanced practicality and efficiency. Given their operation in diverse oceanic environments fraught with various sources of uncertainties, ensuring the system's safe and robust behavior holds paramount importance in the control literature. To address this concern, this paper introduces a control strategy designed to ensure robustness at both the kinematic and dynamic levels. By emphasizing the compensation for the system uncertainties, the design integrates a straightforward fuzzy system structure. To further ensure the system's safety, a funnel surface is defined, followed by the design of a suitable nonlinear sliding surface as a function of the funnel and tracking error. Specifically leveraging the Lyapunov function, the study formally establishes the Semi-globally Practically Finite-time Stability of the closed-loop system, validated through simulations conducted on underactuated marine robots.

In the whole world, including Mexico, the rising prevalence of diabetes poses significant challenges to healthcare systems, with a notable impact on hospital admissions even being an ambulatory care sensitive condition, that means, hospital admissions are avoidable. Traditional healthcare methodologies have been instrumental in managing diabetes and preventing complications, yet they often face limitations such as merging, cleansing, and outlier analysis of health data to identify and address diseases effectively. This paper aims to address this gap by conducting a comprehensive comparison of the methodologies used in healthcare and data science for this purpose. This work uses hospital diabetes discharge records from 2010 to 2023, a total of 36,665,793 records, which belong to medical units of the Ministry of Health of Mexico. In this work, we seek to provide the arguments why as a data scientist it is mandatory to learn the field of knowledge of the problem and its implications if this is not done, and therefore to disclose insights that can help in policy decisions and reduce the burden of avoidable hospitalizations. The approach is mainly based on the standardization or adjust rates by sex and age groups. This study provides the foundations for a new way of data scientist must deal with health data.

Breast cancer (BC) is a heterogeneous disease representing a substantial economic burden. In order to develop policies that successfully decrease this burden, the factors affecting costs need to be fully understood. Evidence suggests that early detection in Stage I has a lower cost than late detection. We aim to provide conservative estimates of BC's stage-wise medical costs from German healthcare and the payer's perspective. To this end, we conducted a literature review of articles evaluating stage-wise costs of BC in Germany through PubMed, Web of Science, and Econ Lit databases supplemented by Google Scholar. We developed a decision tree model to estimate BC related medical costs in Germany using available treatment and cost information. The review generated seven studies; none estimated the stage-wise costs of BC. The studies were classified into two groups: (1) case scenarios (five studies) and two studies based on administrative data. The first sickness funds data study (Gruber, Stock, et al. 2012) used 1999 information to approach BC attributable cost; their results suggest a range between €3,929 and €11,787 depending on age. The second study (Kreis, Plöthner, et al. 2020) used 2011-2014 data and suggested an initial phase incremental cost of €21,499, an intermediate phase cost of €2,620, and a terminal phase cost of €34,513 per incident case. Our decision tree model based BC stage-wise cost estimates were €21,523 for Stage I, €25,679 for Stage II, €30,156 for Stage III, €42,086 for Stage IV. Alternatively, the modeled cost estimates are €20,284 for the initial phase of care, €851 for the intermediate phase of care, and €34,963 for the terminal phase of care. Our estimates for phases of care are consistent with recent German estimates provided by Kreis and Plöthner et al. Furthermore, the data collected by sickness funds are collected primarily for reimbursement purposes, where the German ICD-10 classification system defines a cancer diagnosis. As a result, claims data lack the clinical information necessary to understand stage-wise BC costs. Our model-based estimates fill the gap and inform future economic evaluations of BC interventions.

High efficacy LED lamps combined with adaptive lighting control and greenhouse integrated photovoltaics (PV) could enable the concept of year-round cultivation and become a feasible option even in the harsh climate of the Nordic countries. Meteorological satellite data of this region was analyzed in a parametric study to evaluate the potential of these technologies. The generated maps showed monthly average temperatures fluctuating from -20°C to 20°C throughout the year. The natural photoperiod and light intensity also changed drastically, resulting in monthly average daily light integral (DLI) levels ranging from 45-50 mol·m-2·d-1 in summer and contrasting with 0-5 mol·m-2·d-1 during winter. To compensate, growth room cultivation independent from outdoor conditions could be used in winter. Depending on the efficacy of the lamps, the electricity required for sole-source lighting at 300 µmol·m-2·s-1 for 16 hours would be between 1.4 and 2.4 kWh·m-2·d-1. Greenhouses with supplementary lighting could help start the cultivation earlier in spring and extend it further into autumn. The energy required for lighting highly depends on several factors such as the natural light transmittance, the light threshold settings and the lighting control protocol, resulting in electric demands between 0.6 and 2.4 kWh·m-2·d-1. Integrating PV on the roof or wall structures of the greenhouse could offset some of this electricity, with specific energy yields ranging from 400 to 1120 kWh·kWp-2·yr-1 depending on the region and system design.

As companies increasingly undergo digital transformation, the role of talent management pro-cesses becomes pivotal in enhancing overall organizational performance. The research addresses the significance of talent management in corporate digital transformation, examining whether variations in the digitalization of these processes can be attributed to company size. A qualitative approach was employed, utilizing a questionnaire, collecting responses from 202 organizations across diverse sectors. Findings reveal disparities in digitalization throughout the talent man-agement process, with pronounced presence in the attracting, selecting, and rewarding phases, but diminishing in deployment and development, further declining in planning. A positive cor-relation between company size and adoption of specific digital platforms was observed. Larger enterprises exhibit greater utilization of digital platforms in talent deployment and development. Moreover, corporate communication tools are consistently utilized in the rewarding phase, irre-spective of company size. These findings offer practical insights for organizations to optimize their digitalization strategies based on their scale, thereby contributing to more effective and tailored digitalization endeavors. The uniqueness of this research lies in its exploration of the in-fluence of company size on the digitalization of talent management processes and its potential to explain variations across different stages of these processes.

Conventional academic debate on sustainability and transformation has begun to be disputed by researchers, policymakers and other stakeholders from the private sector. The complexity of linking sustainability with transformation necessitates the development of new ways of understanding and explaining actors, processes, issues, structures, and outcomes related to transformation to sustainability (T2S). A persistent problem in understanding and managing the T2S is the implied notion of a monolithic transformation to achieve sustainability. This notion underestimates the diversity of actors as well as the historical contexts of transformations. At the same time, achieving T2S is highly dependent on technical solutions as well as policies that can stir needed behavioural change, whereas these technical solutions and policies are not always socially acceptable or politically implementable. Therefore, achieving T2S also calls for evaluating normative foundations of policies and actions needed to advance T2S. This article argues that T2S is composed of different phases, each of which having a different set of actors, resources and audience. This article explains how collective decision can be achieved through multiple levels and types of negotiations that occur in an orchestrated manner. To understand this, this article introduces a theoretical model as an analytical framework to structure how T2S unfolds. This model uses insights from negotiation studies to focus on the actors’ perspectives on T2S. It proposes the division of the transformation process into phases – entry point, learning, sequencing, disrupting and fortifying. Using the Germany’s energy transition (Energiewende), each of these phases is analysed to determine the “quality” of cooperation that can help fulfil the tasks required to master the so-called “cognitive games” of T2S (ripeness game, power game, bargaining game, policy game, scaling game). Moreover, insights are presented to explain how the designated milestone can be achieved that indicates the advancing to the next phase and eventually entrench the transformation process. The lessons and findings resulting from the analysis of the phases of T2S suggest that there is also the need to revisit underlying assumptions on negotiations, sustainability and transformation.

Sensing Technology (ST) plays a key role in Structural Health Monitoring (SHM) systems. ST focuses on developing sensors, sensory systems or smart materials that monitor a wide variety of materials properties aiming to create smart structures and smart materials, using Embedded Sensors (ESs), and allowing continuous and permanent measurements of the structural integrity. The integration of ESs is limited to the processing technology to embed the sensor due to its high-temperature sensitivity and the possibility of damage during its insertion into the structure. In addition, the technological process selection is dependent on the base material composition, either metallic or composite parts. The selection of smart sensors or the technology underlying them is fundamental to the monitoring mode. This paper presents a critical review of the fundaments and applications of sensing technologies for SHM employing ESs, focusing on the actual developments and innovation of these, as well as analysing the challenges that these technologies present, to build a path that allows a connected world through distributed measurement systems.

Wildland fires are responsible for large socio-economic impacts. Fires affect the environment, damage structures, threaten lives, cause health issues, and involve large suppression costs. These impacts can be mitigated via accurate fire spread forecast to inform the incident management team. We show that a fire forecast system based on a numerical weather prediction (NWP) model coupled with a wildland fire behavior model can provide this forecast. This is illustrated with the Chimney Tops II wildland fire responsible for large socio-economic impacts. The system is run at high horizontal resolution (111 m) over the region affected by the fire to provide a fine representation of the terrain and fuel heterogeneities and explicitly resolve atmospheric turbulence. Our findings suggest that one can use the high spatial resolution winds, fire spread and smoke forecast to minimize the adverse impacts of wildland fires.

In a recent article, the author derived a new generalized Langevin equation and its associated Fokker-Planck equation of a Brownian particle in a parabolic potential where the thermal bath, consisting of $N$ harmonic oscillators, interacts bilinearly with the external field. The time needed for the system to reach a steady state is longer than that for the classical version where such an interaction is off. We find that there is a marked effect of the field-bath interaction on the average heat and entropy production of the bath represented through strong oscillations in such properties. The new theory applied to the system should improve the physical description of previous works done with the classical approach.

Concentrator photovoltaic (CPV) technology offers an alternative to conventional photovoltaic systems, focusing on the concentration of solar radiation through the optics of the system onto smaller and more efficient solar cells. However, the surface on which the solar beam is incident must remain oriented towards the position of the sun, which requires the use of large and heavy external elements known as solar trackers. In addition to their size, these elements must be as accurate as possible to avoid misalignment. To avoid the need of these solar trackers, the concept of tracking-integrated concentrating systems has been developed. This technology has been researched to make CPV systems accessible in places where conventional systems are not viable, such as building roofs or agrivoltaic fields. This review presents a detailed classification of the existing designs in the literature and providing an overview of this type of system. By eliminating the need for external solar trackers, tracking-integrated CPV systems offer a promising solution to increase the adoption of this technology. Therefore, it is expected that these systems will be a viable and effective option for solar power generation.

TP53 is a tumor suppressor gene that encodes a sequence-specific DNA-binding transcription factor activated by stressful stimuli and upregulates target genes involved in growth suppression, cell death, DNA repair, metabolism, among others. P53 is the most frequently mutated gene in tumors with mutations not only leading to loss-of-function (LOF), but also gain-of-function (GOF) which promotes tumor progression, and metastasis. The tumor-specific status of mutant p53 protein has suggested it is a promising target for cancer therapy. We summarize the current progress of targeting wild-type and mutant p53 for cancer therapy through biotherapeutic and biopharmaceutical methods for 1) boosting p53 activity in cancer, 2) p53-dependent and p53-independent strategies for targeting p53 pathway functional restoration in p53-mutated cancer, 3) targeting p53 in immunotherapy, and 4) combination therapies targeting p53, p53 checkpoints, or mutant p53 for cancer therapy.

This study aims to examine the non-volatile Particle Number (PN) emissions of a retrofitted Heavy-Duty Spark-Ignition (HD-SI) engine powered by liquefied petroleum gas (LPG) under both steady-state and transient conditions. The engine was tested under seven steady-state operating points to investigate the PN behavior and Particle Size Distribution (PSD) upstream and down-stream of the Three-Way Catalyst (TWC). This analysis intends to assess the impact of including particles with diameters ranging from 10 nm to 23 nm in the total particle count, a consideration for future regulations. The study employed the World Harmonized Transient Cycle (WHTC) for transient conditions to encompass the same engine working region used in the steady-state analysis. A Dekati FPS-4000 diluted the exhaust sample to measure the PSD and PN for particle diameters between 5.6 nm and 560 nm using the TSI-Engine Exhaust Particle Sizer (EEPS) 3090. Findings indicate that PN levels tend to increase downstream of the TWC under steady-state conditions in operating points with low exhaust gas temperatures and flows (equal to or less than 500 °C and 120 kg/h). Furthermore, the inclusion of particles with diameters between 10 nm and 23 nm leads to an increase in PN emissions by 17.70% to 40.84% under steady conditions and by an average of 40.06% under transient conditions, compared to measurements that only consider particles larger than 23 nm. Notably, in transient conditions, most PN emissions occur during the final 600 seconds of the cycle, linked to the most intense phase of the WHTC.

Microbial electrochemical technologies (MET) rely on the presence of the metabolic activity of electroactive bacteria for the use of solid-state electrodes for oxidizing different kind of compound, that could lead to the synthesis of chemicals, bioremediation of polluted matrices, the treatment of contaminants of interest, as well as the recovery of energy. Keeping in mind those possibilities, since the beginning of the present century, there has been a growing interest in the use of electrochemical technologies for wastewater treatment, and if possible with simultaneous power generation. In the last years, there has been a growing interest to explore the possibility of merging MET with constructed wetlands, to offer a new option of intensified wetland system that could keep a high performance with a lower footprint. Based on that interest, this paper explains the general principles of MET, and the different known extracellular electron transfer mechanisms ruling the interaction between electroactive bacteria and potential solid-state electron acceptors. Also, the adoption of those principles for the development of MET set-ups for simultaneous wastewater treatment and power generation, and the challenges that the technology face. Ultimately, the most recent developments in set-ups that merges MET with constructed wetlands are presented and discussed.

Marker-assisted selection (MAS) and genomic selection (GS) have been used to select individuals with desirable traits. MAS used a few markers associated with a specific trait to select individuals with desirable traits, which are determined after a Genome-wide association studies (GWAS). On the contrary, GS uses a large number of markers distributed across the genome to predict the genomic breeding values for a further selection of the individuals. In general, MAS has shown a high prediction accuracy but is not suitable for traits that are controlled for multiple genes, and has another constraint, it is required the phenotypic data; on the contrary, GS has not shown the highest prediction accuracy as MAS but it takes into account the effect of multiple genes controlling a target trait and it can be used without phenotypic data. Including GWAS-selected markers in GS can enhance the reduced prediction accuracy that GS shows in comparison with MAS. Thus, the objective of this study was to compare the prediction accuracy of MAS, and some models of genomic prediction (gBLUP, gBLUP including GWAs-selected markers, and some Bayesian models such as Bayes A, Bayes B, Bayes LASSO and Bayesian Ridge Regression) with GWAS-selected markers incorporated in gBLUP in order to confirm if the incorporation of GWAS in GS increases the prediction accuracy of GS. As a model for this study, it was used data from Sorghum which has shown population structure, to evaluate if the incorporation of GWAs-selected markers into GS improves prediciton accuracy. It was used a sample of 6000 SNPs out of the 265.487 reported in the study conducted by Morris et al (2013), and also it was considered some parameters that affect the efficiency of the selection such as the size of the training population, the heritability, and the number of QTNs. The GWAS-selected SNPs were identified after using the model BLINK. The results showed that the incorporation of GWAS-selected markers enhanced the performance of the genomic selection with similar prediction accuracy as MAS, the number of QTNs and size of the training population affected the accuracy, with higher accuracy with a bigger size of the training population and with a lower number of QTNs, but it seems that the heritability does not have any impact in the model where GWAS-selected SNPs were included in gBLUP.

The market for autonomous vehicles (AV) is expected to experience significant growth over the coming decades and to revolutionize the future of transportation and mobility. The AV is a vehicle that is capable of perceiving its environment and perform driving tasks safely and efficiently with little or no human intervention and is anticipated to eventually replace conventional vehicles. Self-driving vehicles employ various sensors to sense and perceive their surroundings and, also rely on advances in 5G communication technology to achieve this objective. Sensors are fundamental to the perception of surroundings and the development of sensor technologies associated with AVs has advanced at a significant pace in recent years. Despite remarkable advancements, sensors can still fail to operate as required, due to for example, hardware defects, noise and environment conditions. Hence, it is not desirable to rely on a single sensor for any autonomous driving task. The practical approaches shown in recent research is to incorporate multiple, complementary sensors to overcome the shortcomings of individual sensors operating independently. This article reviews the technical performance and capabilities of sensors applicable to autonomous vehicles, mainly focusing on vision cameras, LiDAR and Radar sensors. The review also considers the compatibility of sensors with various software systems enabling the multi-sensor fusion approach for obstacle detection. This review article concludes by highlighting some of the challenges and possible future research directions.

With the goal of representing common denominators of aging in different organisms López-Otín et al. in 2013 described nine hallmarks of aging. Since then, this representation has become a major reference point for the biogerontology field. The template for the hallmarks of aging account originated from landmark papers by Hanahan and Weinberg (2000, 2011) defining first six and later ten hallmarks of cancer. Here we assess the strengths and weaknesses of the hallmarks of aging account. As a checklist of diverse major foci of current aging research, it has provided a useful shared overview for biogerontology during a time of transition in the field. It also seems useful in applied biogerontology, to identify interventions (e.g. drugs) that impact multiple symptomatic features of aging. However, while the hallmarks of cancer provide a paradigmatic account of the causes of cancer with profound explanatory power, the hallmarks of aging do not. A worry is that as a non-paradigm the hallmarks of aging have obscured the urgent need to define a genuine paradigm, one that can provide a useful basis for understanding the mechanistic causes of the diverse aging pathologies. We argue that biogerontology must look and move beyond the hallmarks to understand the process of aging.

Taking into account Bar-On’s postulations about social-emotional intelligence, the aim of the current work is to find out the differences in the five dimensions of this intelligence between children that practice organized sport and those children that do not practice it at elementary school level, to show that an increasing in the number of hours per day performing this activity causes differences in some of these dimensions. Hence, a sample of 940 children from elementary schools, ranging in age from 6 to 12 years old, attending different schools from the Autonomous Community of Extremadura (Spain), was used. Results showed that children who practiced organized sport had better coping abilities for stress, adaptability, and mood states, and that they are more emotionally intelligent than those who did not. Moreover, children who practiced for fewer hours daily (up to 2 hours) had better stress coping than those who practiced more. To conclude, it is important to promote the sport federative practice in elementary education, in order to ensure that children learn to better regulate and manage their emotions, without increasing it to an excessive number of hours per day, which may generate greater stress that might be difficult to control.

The Industrial Internet of Things (IIoT) is bringing evolution with remote monitoring, intelligent analytics, and control of industrial processes. A reference architecture provides the general layout information for the flexible integration of IIoT systems; however, as the industrial world is currently in its initial stage of adopting the full-stack development solutions with IIoT, some challenges need to be addressed. To cope with the rising challenges and provide the blueprint guidelines to develop and implement IIoT in real-time, researchers around the globe have proposed IIoT architectures based on different architectural layers and emerging technologies. In this paper, we first review and compare some widely accepted IIoT reference architectures and present a state-of-the-art review of conceptual and experimental IIoT architectures in literature. We highlight scalability, interoperability, security, privacy, reliability, and low latency as the main IIoT architectural requirements and compare how the current architectures address these challenges. We also highlight the role of emerging technologies in current IIoT architectures to address these requirements and present the literature gap for future research work to address the challenges.

This work discusses the relationship between foreign direct investment (FDI) and pollution in Spain using an autoregressive distributed lag regression model (ARDL) from 1961 to 2018. The authors apply the theoretical context of pollution haven/halo and conclude that FDI in Spain does not contribute to the transfer of green technologies for cleaner production, despite being included within the European environmental regulatory framework. The authors also verify the adequacy of the environmental Kuznets curve (EKC) and the Load Capacity Curve hypothesis (LCC) in the Spanish environmental context and find that income per capita has a positive effect on environmental sustainability and quality. In this sense, the further development of an efficient renewable energy infrastructure could efficiently drive to a better standards all pollution indexes in Spain, including nuclear energy production, contributing the emissions neutrality aimed by the EU by 2050.

Proteins and DNA exhibit key physical chemical properties that make them advantageous for building nanostructures with outstanding features. Both DNA and protein nanotechnology have growth notably and proved to be fertile disciplines. The combination of both types of nanotechnologies is helpful to overcome the individual weaknesses and limitations of each one, paving the way for the continuing diversification of the structural nanotechnologies. Recent studies have implemented a synergistic combination of both biomolecules to assemble unique and sophisticate protein-DNA nanostructures. These hybrid nanostructures are highly programmable and display remarkable features that create new opportunities to build in the nanoscale. This review focuses on the strategies deployed to create hybrid protein-DNA nanostructures. Here, we will discuss strategies such as polymerization, spatial directing and organizing, coating, rigidizing or folding DNA into particular shapes or moving parts. The enrichment of structural DNA nanotechnology by incorporating protein nanotechnology has been clearly demonstrated and still shows a large potential to create useful and advanced materials with cell-like properties or dynamic systems. It can be expected that structural protein-DNA nanotechnology will open new avenues in the fabrication of nano-assemblies with unique functional applications and enrich the toolbox of bionanotechnology.

This thesis completion works it out to deepen into diverse modeling techniques for Point Absorbers. A combined frequency-time domain model is conceived, designed and developed in Matlab with Fortran as a base, leading to obtain physical variables of primary importance, namely position, velocity and power to energy net balance relationships of absorption. Integration of different degrees of freedom with heave as main executable leads in turn to a single buoy motion focus. Acquisition of the needed hydrodynamic coefficients is provided through application of NEMOH \& BEMIO solvers due to the Boundary Element Methodology. Initially, this Wave-to-motion model is validated by comparison with previous experimental results for a floating cone cylinder shape (Buldra-FO3). A single, generic, vertical floating cylinder is contemplated then, that responds to the action of the passing regular waves excitation. Later, two equally sized vertical floating cylinders aligned with the incident wave direction are modeled for a variable distance between the bodies. For both unidirectional regular and irregular waves as an input in deep water, we approximate the convolutive radiation force function term through the Prony method. By changing the spatial disposition of the axisymmetric buoys, using for instance triangular or rectangular shaped arrays of three and four bodies respectively, the study delves into motion characteristics for regular waves. The results highlight efficient layouts for maximizing the energy production whilst providing important insights into their performance, revealing displacement amplification- and capture width-ratios, while deriving in possible interpretations of scenarios related to the the known park effect. These terms are encompassed by the novelty of a new conceptual Post-Processing methodology in the field, which leads to obtain an optimal distance for the separated bodies with effective energy absorption in a regular wave regime. In conclusion, this computational excursion envisions and proposes potential fields of study, which will surely enhance new connections and link this renewable energy form.

Background: White matter hyperintensities (WMH), of presumed vascular origin, are visible and quantifiable neuroradiological markers of brain parenchymal change. These changes may range from damage secondary to inflammation and other neurological conditions, through to healthy ageing. Fully automatic WMH quantification methods are promising, but still, traditional semi-automatic methods seem to be preferred in clinical research. We systematically reviewed the literature for fully automatic methods developed in the last five years, to assess what are considered state-of-the-art techniques, as well as trends in the analysis of WMH of presumed vascular origin. Method: We registered the systematic review protocol with the International Prospective Register of Systematic Reviews (PROSPERO), registration number - CRD42019132200. We conducted the search for fully automatic methods developed from 2015 to July 2020 on Medline, Science direct, IEE Explore, and Web of Science. We assessed risk of bias and applicability of the studies using QUADAS 2. Results: The search yielded 2327 papers after removing 104 duplicates. After screening titles, abstracts and full text, 37 were selected for detailed analysis. Of these, 16 proposed a supervised segmentation method, 10 proposed an unsupervised segmentation method, and 11 proposed a deep learning segmentation method. Average DSC values ranged from 0.538 to 0.91, being the highest value obtained from an unsupervised segmentation method. Only four studies validated their method in longitudinal samples, and eight performed an additional validation using clinical parameters. Only 8/37 studies made available their method in public repositories. Conclusions: We found no evidence that favours deep learning methods over the more established k-NN, linear regression and unsupervised methods in this task. Data and code availability, bias in study design and ground truth generation influence the wider validation and applicability of these methods in clinical research.

The signature of chaotic systems can be characterized either by the sensitivity of the initial conditions or by the change of its parameters. This feature can be used for manufacturing high sensitivity sensors. Sensors based on chaotic circuits have already been used for measuring water salinity, inductive effects, and both noise and weak signals. This article investigates an impedance sensor based on the Van der Pol and Duffing damped oscillators. The calibration process is a key point and therefore the folding behavior of signal periods was also explored. A sensitivity of 0.15 kΩ/Period was estimated over a range from 89.5 to 91.6 kΩ. This range can be adjusted according to the application by varying the gain of the operational amplifier used in this implementation. The development of this type of sensor might be used in medical and biological engineering for skin impedance measurements, for example. This type of chaotic sensor has the advantage of sensing small disturbances and then detect small impedance changes within biological materials which, in turn, may not be possible with other detectors.

Explaining the emergence of behavior and understanding on the basis of neuronal mechanisms is still elusive. One renowned proposal is the Free Energy Principle (FEP), which uses an information-theoretic framework derived from thermodynamic considerations to describe how behavior and understanding would emerge. FEP starts from a whole organism approach, based on mental states and phenomena, mapping them into the neuronal substrate. An alternative approach, the Energy Homeostasis Principle (EHP), initiates a similar explanatory effort, but starting from single neuron phenomena and building up to the whole organism’s behavior and understanding. In this work, we develop the EHP as an alternative but complementary vision to FEP and try to explain how behavior and understanding would emerge from the local requirements of the neurons. Based on EHP and a strict naturalist approach that sees living beings as physical and deterministic systems, we explain scenarios where learning would emerge without the need for volition or goals. Given these starting points, we state several considerations of how we see the nervous system, particularly the role of function, purpose, and the conception of goal-oriented behaviors. We problematize these conceptions, giving an alternative teleology-free framework in which behavior and, ultimately, understanding would still emerge. We reinterpret neural processing explaining basic learning situations up to simple anticipatory behavior. Finally, we end the work with an evolutionary perspective of how this non-goal-oriented behavior appears. We acknowledge that in the current form of our proposal, we are still far from explaining the emergence of understanding. Still, we set the ground for an alternative neuron-based framework to ultimately explain understanding.

High-throughput screening technologies continues to produce large amounts of multiomics data from different populations and cell types for various diseases, such as cancer. However, analysis of such data encounters difficulties due to cancer heterogeneity, further exacerbated by human biological complexity and genomic variability. There is a need to redefine the drug discovery development pipeline, bringing an Artificial Intelligence (AI)-powered informational view that integrates relevant biological information and explores new ways to develop effective anticancer approaches. Here, we show SynPred, an interdisciplinary approach that leverages specifically designed ensembles of AI-algorithms, links omics and biophysical traits to predict synergistic anticancer drug synergy. SynPred exhibits state-of-the-art performance metrics: accuracy – 0.85, precision – 0.77, recall – 0.75, AUROC – 0.82, and F1-score - 0.76 in an independent test set. Moreover, data interpretability was achieved by deploying the most current and robust feature importance approaches. A simple web-based application available online at http://www.moreiralab.com/resources/synpred/ was constructed to predict synergistic anticancer drug combinations requiring only the upload of the two drug SMILES to be tested, allowing easy access by non-expert researchers.

A novel hybrid material based on Polyvinyl alcohol-Chitosan (PVA-Cs) was made, reinforced with conductive polymer fillers such as polypyrrole (PPy), Poly(3,4-ethylenedioxythiophene)-poly(styrenesulfonate) (PEDOT:PSS), carbon black (CB) and multi-wall carbon nanotubes (MW CNT). Our proposal is to use these fillers, which have not been studied in this context before, for obtaining composite materials, and to characterize them for the development of applications in microelectronics. FTIR analysis made evident the different func-tional groups present in the matrix and the fillers used. The use of quaternary mixtures (4 fillers) increased the contact angle, which increased the degree of hydrophobicity of the biocomposite. The Nyquist diagram of the analyzed samples showed a decrease in resistance and energy diffu-sion; the latter due to the transfer of electrons caused by the conductive polymers CB and the MWCNT. In the mechanical tension tests, Young's modulus values of 18.386 MPa were obtained, in contrast with the material matrix of PVA-Cs, which showed values of 11.628 MPa. Further-more, morphological analysis by SEM showed that the materials obtained were homogeneous, with no phase formation. The materials obtained showed higher electrical conductivity in the presence of the OH and NH2 groups, which could have possible applications in biopolymer elec-trodes.

Recent advancements in deep learning have spurred the development of numerous novel semantic segmentation models for land cover mapping, showcasing exceptional performance in delineating precise boundaries and producing highly accurate land cover maps. However, to date, no systematic literature review has comprehensively examined semantic segmentation models in the context of land cover mapping. This paper addresses this gap by synthesizing recent advancements in semantic segmentation models for land cover mapping from 2017 to 2023, drawing insights on trends, data sources, model structures, and performance metrics based on a review of 106 extracted articles. Our analysis identifies top journals in the field, including MDPI Remote Sensing, IEEE Journal of Selected Topics in Earth Science, and IEEE Transactions on Geoscience and Remote Sensing, IEEE Geoscience and Remote Sensing Letters, ISPRS Journal Of Photogrammetry And Remote Sensing as the leading journals. We find that research predominantly focuses on land cover, urban areas, precision agriculture, environment, coastal areas, and forests. Geographically, 35.29% of the study areas are located in China, followed by USA (11.76%), France (5.88 %), Spain (4%) and others. Sentinel-2, Sentinel-1, and Landsat satellites emerge as the most commonly used data sources. Benchmark datasets such as ISPRS Vaihingen & Potsdam, LandCover.ai, DeepGlobe, and GID datasets are frequently employed. Model architectures predominantly utilize encoder-decoder, and hybrid convolutional neural network-based structures because of their impressive performances, with limited adoption of transformer-based architectures due to its computational complexity issue, and slow convergence speed. Lastly, this paper highlights existing key research gaps in the field to guide future research directions.

Arboviruses are infections caused by arboviruses that may be either symptomatic or asymptomatic, according to individuals' resistance and immune response, which dietary patterns can influence. Thus, this study aimed to investigate the possible association between the occurrence of clinical manifestations of arboviruses and the dietary pattern of the population studied. The study was conducted in a rural population in the metropolitan area of Belém, Pará State, Brazil. The sampling consisted of 95 individuals during a febrile outbreak. Two investigations were conducted: clinical-epidemiological-dietary and laboratory investigation based on blood samples taken for arbovirus analysis. Out of the 95 individuals studied, more than half (57.89%) showed clinical manifestations. Following the laboratory serology (HI and IgM ELISA) analyses, viral isolation in C6/36 cells, and viral genome detection (RT-qPCR), the final diagnosis of the cases was 47.37% Oropouche Fever, 2.11% Oropouche Fever and Chikungunya Fever, and 1.05% Mayaro Fever. Regarding dietary pattern, as for the comparison analyses, statistical significance was observed between dietary pattern and classification regarding the presence of symptoms (p<0.05); after the correspondence analysis, symptomatic cases were more associated with a bad dietary pattern, while asymptomatic cases were more associated with a good dietary pattern.

The current management of colorectal cancer liver metastasis (CRCLM) patients involves a multidisciplinary approach with surgical resection remaining the primary curative option. The advances in liver surgery have improved outcomes, enabling more patients to undergo surgery successfully. In addition, the development of imaging software has improved the preoperative planning and patient selection for surgery and other interventions. Systemic therapies, such as targeted therapies and immunotherapies have enhanced the chances of complete resection. Targeted agents in combination with chemotherapy, have shown efficacy in downstaging tumors and increasing resectability.

Fogo volcano erupted in 2014-15 producing an extensive lava flow field in the summit caldera that destroyed two villages, Portela and Bangaeira. The eruption started with powerful explosive activity, lava fountains, and a substantial ash column accompanying the opening of an eruptive fissure. Lava flows spreading from the base of the eruptive fissure produced three arterial lava flows. By a week after the start of the eruption, a master lava tube had already developed within the eruptive fissure and along the arterial flow. In this paper, we analyze the emplacement processes on the basis of observations carried out directly on the lava flow field, remote sensing measurements carried out with a thermal camera, SO₂ fluxes, and satellite images, in order to unravel the key factors leading to the development of lava tubes. These were responsible for the rapid expansion of lava for the ~7.9 km length of the flow field, as well as the destruction of the Portela and Bangaeira villages. The key factors leading to the development of tubes were the low topography and the steady magma supply rate along the arterial lava flow. Comparing time-averaged effusion rates (TADR) obtained from satellite and Supply Rate (SR) derived from SO₂ flux data, we estimate the amount and timing of the lava flow field endogenous growth, with the aim of developing a tool that could be used for hazard assessment and risk mitigation at this and other volcanoes.

Inflammatory bowel diseases (IBD) represent a growing public health concern due to increasing incidence worldwide. The current notion on the pathogenesis of IBD is that genetically susceptible individuals develop intolerance to dysregulated gut microflora (dysbiosis) and chronic inflammation develops as a result of environmental triggers. Among the environmental factors associated to IBD, diet plays an important role in modulating the gut microbiome, influencing epigenetic changes and, therefore, could be applied as a therapeutic tool to improve the disease course. Nevertheless, the current dietary recommendations for disease prevention and management are scarce and of weak evidence. This review summarizes the current knowledge on the complex interactions among diet, microbiome and epigenetics in IBD. Whereas over-abundance of calories and some macronutrients increases gut inflammation, several micronutrients have the potential to modulate it. Immunonutrition has emerged as a new concept putting forward the importance of vitamins such as vitamins A, C, E, D, folic acid and beta-carotene and trace elements such as zinc, selenium, manganese and iron. However, when assessed in clinical trials, specific micronutrients exerted a limited benefit. Beyond nutrients, anti-inflammatory dietary patterns as a complex intervention approach have become popular over the recent years. Hence, exclusive enteral nutrition in pediatric Crohn’s disease is the only nutritional intervention currently recommended as a first-line therapy. Other nutritional interventions or specific diets including the Specific Carbohydrate Diet, the low fermentable oligosaccharides, disaccharides, monosaccharides, and polyol diet and most recently the Mediterranean diet have shown strong anti-inflammatory properties and provide a promise for improving disease symptoms. Definitely, more work is required to evaluate the role of individual food compounds and complex nutritional interventions with potential to decrease inflammation as means for prevention and management of IBD.

Mining for resources extraction may lead to several geological and associated environmental changes due to ground movements, collision with mining cavities and deformation of aquifers. Geological changes may continue in a reclaimed mine area, and the deformed aquifers may entail a breakdown of substrates and an increase in ground water tables, which may cause surface area inundation. Consequently, a reclaimed mine area may experience surface area collapse, i.e. subsidence, and degradation of vegetation health. Thus, monitoring short-term landscape dynamics in a reclaimed mine area may provide important information on the long-term geological and environmental impacts of mining activities. We studied landscape dynamics in Kirchheller Heide, Germany, which experienced extensive soil movement due to longwall mining without stowing, using Landsat imageries between 2013 and 2016. A Random Forest image classification technique was applied to analyse land-use and land-cover dynamics and the growth of wetland areas was assessed using a Spectral Mixture Analysis (SMA). We also analyzed the changes in vegetation health using a Normalized Difference Vegetation Index (NDVI). We observed a 19.9% growth of wetland area within the four years with 87.2% of growth in the coverage of two major waterbodies in the reclaimed mine area. NDVI values indicate that 66.5% of the vegetation of the study area was degraded due to changes in ground water tables and surface flooding. Our results inform environmental management and mining reclamation authorities about the subsidence spots and priority mitigation areas from land surface and vegetation degradation in Kirchheller Heide.

Shot peening is an attractive technique for fatigue enhanced performance of metallic components, because it promotes crack initiation retardation and later crack growth. Engineering design based on fatigue crack propagation predictions applying the principles of fracture mechanics is commonly used in aluminum structures for aerospace engineering. The main purpose of present work was to analyze the effect of shot peening on the fatigue crack propagation of the 7475 aluminum alloy, under both constant amplitude loading and periodical overload blocks. The tests were performed on 4 and 8 mm thickness specimen's with stress ratios of 0.05 and 0.4. The analysis of the shot-peened surface showed a small increase of the micro-hardness values, due to the plastic deformations imposed by shot peening. The beneficial effect of surface peening on fatigue crack growth rates is quite limited to an increasing near the threshold. The specimens’ thickness has only marginal influence on the crack propagation, in opposite to the stress ratio. Periodic overload blocks of 300 cycles promotes a reduction of the fatigue crack growth rate for both intervals of 7,500 and 15,000 cycles.

Electric vehicles (EVs) play a significant role in reducing carbon emissions. In the US, EVs are mostly owned by multi-vehicle households, and their usage is primarily studied in the context of vehicle miles traveled. This study takes a unique approach by analyzing EV usage through the lens of vehicle choice (between EVs and internal combustion engine vehicles) within multi-vehicle households. A two-step machine-learning framework (clustering and decision trees) is proposed. The framework determines the preferred trip category for EV use and captures the effects of household attributes, driver attributes, built-environment factors, and gas prices on EV use in multi-vehicle households. Results indicate that discretionary trips (accumulated local effect = 0.037) are mostly preferred for EV use. EV preference is more pronounced among households with fewer workers (<2) and lower income levels. These findings are valuable for policymakers and auto manufacturers in targeting specific market segments and promoting EV adoption.

Taxes on the consumption of certain products have played a key role in public revenue analysis in European countries. This work aims to assess the differences in tax planning on new non-combustion products across some European territories. Through theoretical analysis, the paper has three distinct aspects. Firstly, we show the taxpayer profile in different countries. Secondly, the study analyzes the risks for the health system and the individual. Thirdly, the design of the land tax is based on previous experience and planning in Europe. This paper concludes with a case study for different countries: 1) Spain “vapers” and “smokers”, where the analysis is based on micro-data from the European Health Interview Survey 2020. 2) Sweden with the analysis of snus, shows it as a practice to reach economic savings while decreasing economic costs thanks to the nudging of consumers towards better products. The results show taxation and, specially, land taxation, should consider differences in planning in the case of new products, such as the non-combustion products, given the user per capita income and the potential lower health risks involved.

The forehead and temporal region are a frequent area of skin cancer development. After tumor removal, reconstruction must be performed maintaining the frontal-temporal line of the scalp and the symmetry of the eyebrows, trying to hide the scars in these marks or in natural folds and wrinkles. Second wound healing and skin grafts generally do not produce an acceptable cosmetic result. When direct closure is not possible, the technique of choice is skin flaps. In the midfrontal line, continuation of the glabella, there is a remnant of skin to be used as a donor area for local flaps; similarly, it occurs in the preauricular cheek, which can move towards the temple. In addition to the classic advancement and rotation flaps, the frontalis myocutaneous transposition flap is an excellent technique for closing defects which are wider than higher on the forehead. Its design is very versatile and can be done between the two pupil lines at different heights depending on the location of the defect. On the other hand, the preauricular skin advancement flap with an infralobular Burow's triangle is also an excellent option for reconstructing tumors in the temporal area.

Legacy mining industry has left a large number of tailings ponds exposed to water and wind erosion that causes serious environmental and health problems. Prior to rehabilitation actions a deep sampling of the materials infilling the pond used to be necessary. Thus, the primary objective of this study is to demonstrate the usefulness of the Electrical Resistivity Tomography (ERT) method as a non-invasive tool to determine the physicochemical composition of mine tailings ponds, enabling more efficient and low-cost surveys. To achieve this objective, three ERT profiles and three boreholes in each profile were carried out, from each borehole three waste samples from differents depths were collected and a geochemical characterization of the samples was carried. In order to estimate the composition of the infilling wastes in tailing ponds from electrical resistivity measures, several regression models were calculated for different physicochemical properties and metal concentrations. As a result, a high resistivity area was depicted in profiles G2 and G3 while a non-resistive area (profile G1) was also found. Relationships among low resistivity values and high salinity, clay content and high metal concentrations and mobility were established. Specifically, calibrated models were obtained for electrical conductivity, particles sizes of 0.02-50 µm and 50-2000 µm, total Zn and Cd concentration, and bioavailable Ni, Cd and Fe. Therefore, the ERT technique could be considered as a useful tool for mine tailings ponds characterization, and it can be used to estmate some physicochemical properties and metal concentrations of this mine waste.

Chromatin is dynamically remodeled to adapt to all DNA-related processes, including DNA damage responses (DDR). This adaptation requires DNA and histone epigenetic modifications, which are mediated by several types of enzymes; among them are lysine methyltransferases (KMTs). Methods: KMT inhibitors, chaetocin and tazemetostat (TZM), were used to study their role in the DDR induced by ionizing radiation or doxorubicin in two human sarcoma cells lines. The effect of these KMT inhibitors was tested by the analysis of chromatin epigenetic modifications, H4K16ac and H4K20me2. DDR was monitored by the formation of γH2AX, MDC1, NBS1 and 53BP1 foci, and the induction of apoptosis. Results: Chaetocin and tazemetostat treatments caused a significant increase of H4K16 acetylation, associated with chromatin relaxation; and increased DNA damage, detected by the labeling of free DNA-ends. These inhibitors significantly reduced H4K20 dimethylation levels in response to DNA damage and impaired the recruitment of 53BP1, but not of MDC1 and NBS1, at DNA damaged sites. This modification of epigenetic marks prevents DNA repair by the NHEJ pathway and leads to cell death. Conclusion: KMT inhibitors can function as sensitizers to DNA damage-based therapies and be used in novel synthetic lethality strategies for sarcoma treatment.

AML is a highly aggressive and heterogeneous form of hematological cancer. Proteomics-based stratification of patients into more refined subgroups may contribute to a more precise characterization of the patient-derived AML cells. Here, we reanalyzed liquid chromatography-tandem mass spectrometry (LC-MS/MS) generated proteomic and phosphoproteomic data from 26 chemoresistant/relapse (RELAPSE) and 15 relapse-free (REL_FREE) AML patients. We considered not only the RELAPSE and REL_FREE characteristics but also integrated the French-American-British (FAB) classification, along with considering the presence of nucleophosmin 1 (NPM1) mutation and cytogenetically normal AML. We found a significant number of differentially enriched proteins (911) and phosphoproteins (257) between the various FAB subtypes in RELAPSE patients. Patients with the myeloblastic M1/M2 subtype showed higher levels of RNA processing-related routes and lower levels of signaling related to terms like translation and degranulation, when compared to the M4/M5 subtype. Moreover, we found that high abundance of proteins associated to mitochondrial translation and oxidative phosphorylation, particularly observed in the RELAPSE M4/M5 NPM1 mutated subgroup, distinguishes relapsing from non-relapsing AML patient cells with the FAB subtype M4/M5. Thus, the discovery of subtype-specific biomarkers through proteomic profiling may complement the existing classification system for AML and potentially aid in selecting personalized treatment strategies for individual patients.

The SARS-CoV-2 infection is a cause of hypoxemic acute respiratory failure, leading to frequent intensive care unit (ICU) admission. Due to invasive organ support and immunosuppressive therapies, these patients are prone to nosocomial infections. Our aim was to assess the value of daily measurements of C-reactive protein (CRP) and Procalcitonin (PCT) in the early identification of ICU-acquired infections in COVID-19 patients Methods: We undertook a prospective observational cohort study (12 months). All adult me-chanically-ventilated patients admitted for ≥ 72 hours to the ICU with COVID-19 pneumonia were divided into an infected group (n=35) and a non-infected group (n=83). Day 0 was considered as the day of the diagnosis of infection (infected group) and day 10 of ICU stay (non-infected group). The kinetics of CRP and PCT were assessed from day -10 to day 10 and evaluated using a general linear model, univariate, repeated-measures analysis. Results: 118 patients (mean age 63 years, 74% males) were eligible for the analysis. The groups did not differ in patients' age, gender, CRP, and PCT serum levels at ICU admission. However, the infected group encompassed patients with a higher severity (SOFA score at ICU admission, p=0.009) and a higher 28-day mortality (p<0.001). Before D0, CRP kinetics showed a significant increase in infected patients, whereas in noninfected it remained almost unchanged (p<0.001), while PCT kinetics did not appear to retain diagnostic value to predict superinfection in COVID-19 patients (p=0.593). Conclusion: COVID-19 patients who develop ICU-acquired infections exhibited different biomarker kinetics before the diagnosis of those infections. Daily CRP monitoring and the recognition of the CRP kinetics could be useful in the prediction of ICU-acquired infections.

Seed bank survival underpins plant population persistence but studies on seed bank trait-environment interactions are few. Changes in environmental conditions relevant to seed banks occur in desert ecosystems owing to solar energy development. We developed a conceptual model of seed bank survival to complement methodologies using in-situ seed bank packets. Using this framework, we quantified the seed bank survival of two closely related annual desert plant species, one rare (Eriophyllum mohavense) and one common (Eriophyllum wallacei) and the seed bank-environment interactions of these two species in the Mojave Desert within a system that emulates microhabitat variation associated with solar energy development. We tracked 4,860 seeds buried across 540 seed packets and found, averaged across both species, that seed bank survival was 21% and 6% for the first and second growing seasons, respectively. After two growing seasons, the rare annual had a significantly greater seed bank survival (10%) than the common annual (2%). Seed bank survival, across both species, was significantly greater in Shade (10%) microhabitats compared to Runoff (5%) microhabitats and Control microhabitats (3%). Our study confers insight into this early life-stage across rare and common congeners and their environmental interactions using a novel conceptual framework for seed bank survival.

The present review paper aims at collecting and discussing the research work, numerical and experimental, carried out in the field of Fluid-Structure Interaction (FSI) in one-dimensional (1D) pressurized transient flow in the time-domain approach. Background theory and basic definitions are provided for the proper understanding of the assessed literature. A novel frame of reference is proposed for the classification of FSI models based on pipe degrees-of-freedom. Numerical research is organized according to this classification, while an extensive review on experimental research is presented by institution. Engineering applications of FSI models are described and historical accidents and post-accident analyses documented.

This work presents the results of three connection types in double-shear with dowel fasteners, using the simplified equations from the Eurocode 5. All design parameters were established and compared using three different wood strength and density properties, which constitute the members connections. Eighty-one connections were obtained, allowing to conclude about the number of fasteners needed to the applied tensile load. An increase in the number of dowels was obtained with the increased applied tensile load, lower dowel diameter, lower wood density, and lower strength material in all connection types in the study. The design characteristic load-carrying capacity per shear plane and fastener also decrease with the previously considered parameters.

Sustainability addresses environmental and social issues affecting this and future generations. When family businesses perceive that the community is disrupted, recognize an environmental problem and respond by implementing new environmental policies or regulations, the family business’s socio-emotional values press to transition to a more sustainable production system, such as the ‘Circular Economy.’ Drawing on the Dubin (1978) methodology—a paradigm for building models through deduction—we design a sustainable model, which shows family businesses’ responses to changes in the environment. It explains the reasons why family firms transition to the Circular Economy, based on the theory of Socio-Emotional Wealth (SEW). We check the model through the case study of the food retail leader in the Spanish market—Mercadona—which applies policies about energy, resources and waste to become a Circular Economy business model. Because of the strong family character of Mercadona, this case can be useful for the decision-making of other family businesses.

Recently, coastal swamps have been acknowledged for their capability to alleviate shorelines and defend coastal communities. Mangroves play a prominent role in obstructing water currents in riverbanks, shorelines, and coastal areas. Mangrove roots have the significant contribution to the resiliency of the vegetation structure. Yet, mangrove model has lately been called into question by lab experimental evidence. In this paper, the flow characteristics past root models are reviewed. coastal swamps are among the most fruitful and carbon‐rich ecosystems on the planet. Long‐term carbon putting away in coastal wetlands happens mostly below ground as soil organic matter. Mangrove servs as a carbon sink, impacts wetland ecosystem configuration, purpose, and firmness. To expect and ease the properties of climate change, there is a necessity to advance considerate of environmental controls on wetland. The impact of four soil formation factors are reviewed. Across the shorelines, soil organic matter was highest in mangrove forests and it was lower areas.

With an increasing demand for quality of care and lower costs, hospitals are looking for industry-based methods to improve efficiency in their processes. This study aims to reduce waste in a public hospital in Mexico by improving the medical supply process for the operating room. To this end, a lean healthcare (LH) implementation following the DMAIC approach (Define-Measure-Analyze-Improve-Control) is carried out. We analyze the value stream of the supply process, including main surgical procedures and their related medical supplies, and identify different causes of inefficiency, which are evaluated and controlled through different tools, including a value stream map, Kanban, and the 5S program. As a result, five types of waste were reduced. Over-processing requests were reduced by 15.3%, defective identification numbers were reduced by 46.5%, redundant processing was improved by 94.8%, near 2.8% of the unnecessary inventory was reduced, and transportation waste was reduced by up to 16.7%. Finally, the lead-time for the main supplies was reduced by 33 days. This work demonstrates that LH and DMAIC are effective in reducing waste and are highly conducive to improving sustainability in healthcare processes. Moreover, it provides practical insights for practitioners regarding the implementation of LH in public hospitals in developing countries.

The use of botanical extracts of the plant Jatropha curcas (Euphorbiaceae) represents a valuable alternative to control insect pests and avoid the detrimental effects on the environment and health that arise due to synthetic chemical insecticides. Thus, we conducted a systematic review to summarize the published evidence on the bioactivity of J. curcas against insect pests. Electronic databases were searched to identify studies that assessed J. curcas extracts against insect pests in various types of crops. We included 39 articles that reported the insecticidal and insectistatic activity of several botanical extracts from J. curcas against insects of eight different taxonomic orders. The evidence demonstrates that aqueous and methanolic extracts from seeds and leaves, seed oil, and petroleum ether seed extracts were effective against insect pests of stored grains, aphids of cabbage, sorghum, fruit flies, and desert locusts. The extracts caused high mortality, controlled the populations, reduced oviposition, diminished hatchability, and increased the antifeedant effect. However, the type of solvent used to obtain the botanical extract and the method of application (contact or food) are fundamental to increase its bioactivity. Therefore, botanical extracts from seeds and leaves of J. curcas should be considered as an alternative against insect pests and may be incorporated into integrative and sustainable management for insect control.

In this work a new method is proposed to tackle down the multiple objective optimization problem of the calculation of cation distribution in spinels structure, through the difference of intensity ratios between experimental and calculated intensities of cation sensitive Bragg planes, by introducing a new factor, Rabs, in Bertaut method. This factor is introduced as the sum of absolute R factors, and it is minimized by varying cation distribution. To test this method aluminate manganese spinel where synthesized though modified Pechini method and characterized though XRD. The results show to be in agreement with literature for the aluminum inversion in tetrahedral sites, which is near to the reported value of 10%. Also, it was noticed that the manganese atoms are present in octahedral sites with a mixed valence state of +2 and +3. Which might be an indicator that oxygen vacancies are present in the structure, so the vacancies value of oxygen is proposed considering the total charge of cations and thus proposing the value of 3.678 mol per formula unit of the spinel, thus having the next stoichiometry considering normalized Al and Mn, MnAl2O3.678. Finally, the last cation distribution proposed was [Mn0.867^(+2) Al0.129^(+3) ][Mn0.034^(+2) Mn0.098^(+3) Al1.871^(+3) ] O3.678 with a Rabs factor value of 0.6466, which considers the cation distribution and oxygen vacancies.

Objective: The primary objective of this trial was to assess the transfer of drospirenone to breast milk after daily administration of an oral test preparation containing 4 mg of drospirenone at the steady state. The secondary objective of the trial was to assess the safety of the preparation based on safety clinical and laboratory measurements (at the beginning and at the end of the trial) and reporting of adverse events and/or adverse drug reactions. Patients and Methods: This was an open label, non-comparative single center study. Drospirenone 4mg per day was the first postpartum contraceptive for the study participants who were no longer breastfeeding yet were still lactating. It was administered for 7 (seven) days to achieve steady-state concentration. All participants were volunteers who planned to use oral contraceptives as their family planning method in the future. Results: A total number of 12 volunteers completed the trial according to the protocol and the samples of all the 12 study completers were analyzed. The average concentration-time curve of drospirenone in plasma 24 h after the administration of the last dose (AUC(0-24h)) was 635.33 ng*h/mL and 120 h after the single repeat dose administration (AUC(0-120h) was 1180.57 ng*h/mL, respectively. The average Cmax was 48.64 ng/mL. The average concentration-time curve of drospirenone in milk 24 h after the administration of the last dose (AUC(0-24h)) was 134.35 ng*h/mL and 120 h after the single repeat dose administration (AUC(0-120h) was 227.17 ng*h/mL respectively. The average Cmax was 10.34 ng/mL. Conclusion: On average 18.13% of plasma drospirenone made it to breast milk and the highest concentration of drospirenone in breast milk was 17.55% of that in plasma. The total quantity of drospirenone passing to breast milk is on average 4478 ng during a 24 h period representing 0.11% of the maternal daily dose. Thus, at the recommended doses, no effects on breastfed newborns/infants are anticipated with drospirenone 4 mg.

Larus michahellis increased its population throughout the 20th century in its worldwide distribution area. The increase in the Salinas de San Pedro del Pinatar has produced changes in the habitats due to the contribution of guano, predation on birds, incidents with workers, and the production of salt. The objective is to analyze the impacts of L. michahellis on the landscape, habitats, waterfowl, salt production, and workers, as well as to evaluate the effectiveness of control activities. Censuses of wintering L. michahellis have been carried out between 1990-2021, of nesting aquatic birds between 1994-2021, and nests and eggs of L. michahellis have been eliminated between 2000-2021. The result has been a decrease in pairs of L. michahellis, recovery of waterfowl populations, colonization of others, absence of incidents with workers, and reduction of damage to salt production. However, to reach a definitive solution, measures should be adopted to prevent L. michahellis from accessing the main sources of human food: urban solid waste dumps, aquaculture farms, and fish discards.

Multicompartment compliance aids (MCAs) are devices with each discrete section denoting a single dosing occasion. The purpose of an MCA is to maximize patient adherence and thereby optimize the treatment benefits. These devices are widely employed throughout western Europe and UK and use appears to be rapidly increasing (2) although the RPS as moved away from these devices as a means to improve adherence. We analysed MCAs from various pharmacies over a wide geographic area in England and North Wales. We concluded that most MCA users are elderly patients. Also, most of the patients suffer of combined cardiovascular disease. However, a significant proportion of patients falls in the mental/ neurological disease category. Additionally, most of the externals added to MCAs are inhalers and painkillers. Moreover, SDIs are more frequent in female patients and these SDI are mainly related with mental health medication, cardiovascular disease medication and neurological medication. In conclusion, a directive for dispensing of MCAs in pharmacies by pharmacists through an enhanced service should be elaborated having in consideration PIMs, SDIs, drug stability and use of externals and MCA design and brand.

Sound absorbing materials are used in building to dissipate sound energy into heat by viscous and thermal processes. Sound absorbers increase the transmission loss of walls, decrease the reverberation time of rooms and attenuate the noise generated by internal sound sources. Porous absorbers (fibrous, cellular or granular) are the most used materials in noise control applications, since their high performance-to-cost ratio in the frequency band of interest. However, when cleaning and health reasons are of concern, microperforated panel (MPP) absorbers can be preferred. MPPs, consisting of many minute (sub-millimetric) holes in a panel, are tunable absorbers in a prescribed frequency band, which main shortcomings are high manufacturing cost and limited absorption frequency band. Production cost of MPP can nowadays be drastically cut down by means of modern techniques. Absorption frequency band can be considerably enlarged by designing multiple-layer MPPs (ML-MPPs). The aim of this article is to review the high potential of ML-MPPs as a modern, clean and healthy alternative of porous materials for sound absorption.

Maternal obesity is increasingly prevalent and is associated with elevated morbidity and mortality rates in both mothers and children. As the interface between the mother and fetus, the placenta has mediates the impact of the maternal environment on fetal development. Most of the literature data on the effects of maternal obesity on placental functions do not exclude potential confounding factors like metabolic diseases (e.g. gestational diabetes). Moreover, it is now clear that the placental response to maternal environment depends on the fetal sex. In this context, we reviewed how maternal obesity (in the absence of gestational diabetes) affects the human placenta in terms of (i) endocrine function, (ii) morphological characteristics, (iii) nutrient exchanges and metabolism, (iv) inflammatory/immune status, (v) oxidative stress, and (vi) transcriptome, with a focus on fetal sex specificities. A better understanding of sex-specific placental responses to maternal obesity is crucial for improving pregnancy outcomes and the health of mothers and children.

Background: Effectiveness of Anastrozole and levonorgestrel-releasing intrauterine device (LNG-IUD, Mirena®) in the treatment of endometriosis. Methods: Randomized clinical trial. Elegibility criteria: Endometriomas >3×4 cm, CA-125>35 U/mL and symptoms suggestive of endometriosis. Thirty-one women were randomized to anastrozole+Mirena®+Conservative Surgery(CS) (n=8), anastrozole+Mirena®+transvaginal ultrasound-guided puncture-aspiration(TUGPA) (n=7), Mirena®+CS (n=9), or Mirena®+TUGPA (n=7). Interventions: Anastrozole 1 mg/day and/or only Mirena® for 6 months. CS or TUGPA one month after starting medical treatment. Results: A significant improvement in symptoms during the treatment (difference of 43%, 95% CI 29.9-56.2) occurred, which was maintained at 1 and 2 years. It was more significant in patients treated with anastrozole. For CA-125, the most significant decrease was observed without anastrozole. After CS for endometriosis, a reduction of findings of endometriomas and long-term recurrences occurred, with or without anastrozole, although anastrozole seems to delay recurrences. At 4,2±1,7 years, 88% of the patients who underwent CS were asymptomatic, compared to only 21% if TUGPA was performed, with or without anastrozole (p=0.019). Conclusion: Dosing anastrozole for 6 months, starting one month before CS of endometriosis, reduces more significantly the painful symptoms and delays recurrences, but has no other significant advantages over the single insertion of LNG-IUD (Mirena®) during the same time.

The Atlantic Goliath Grouper Epinephelus itajara (Lichtenstein, 1822) is thought to occur on both sides of the Atlantic, from the Carolinas (USA) to Brazil in the western Atlantic, and from North Senegal to North Angola off West Africa in the eastern Atlantic. While there are fairly good data on their distribution in the western Atlantic, genetic verification of species status, confirmed occurrences, population status, fishing reports, and trade data are almost non-existent off West Africa. Part of the problem is that tropical West African countries lack a network of marine reserves that might protect this species. Add to this destruction of mangrove forests and other coastal habitats on which the species depends when in the post-larval and juvenile stages coupled heavy pollution and intense overfishing and it becomes clear that their survival is deeply threatened. The focus of this paper is to describe all of the known historical data and examine all current data to better evaluate their present status.

This paper presents the mathematical modeling for designing a 10[kW] DC-AC inverter system from 48 [V] DC to 120 V ACrms, considering its non-linear operation, allowing to obtain a detailed simulation to assess the proposed fuzzy PI control (with anti-windup action) and its optimal operation. The performance assessment of the converter was carried out with the discrete treatment of the voltage and current signals using spectral analysis, filtering considerations, and evaluation of limit cycle technique to determine the system's stability. The main results showed that THD at the filter output (transformer and capacitor) was around 0.0322% and 0.0632% at nominal load in open loop and closed loop, respectively. The inverter system presented more sensitivity in the current signal with a ripple at 120 [Hz] of 2.02% and at 5000 [Hz] of 10.62% (at nominal load). However, when the system operates in a closed loop, the current ripple at 120 [Hz] is 2.38% and at 5000 [Hz] is 10.62%.

Pomegranate extract (PG-E) has been reported to exert a protective effect in skin due to its antioxidant activity. Ingredients rich in phenolic compounds are unstable in extract solutions and, therefore, the use of a suitable nanosystem to encapsulate this type of extract could be necessary in different biotechnological applications. Thus, we investigated the capacity of Brassica oleracea L. (cauliflower) inflorescence vesicles (CI-vesicles) to encapsulate PG-E and determined the stability and the antioxidant capacity of the system over time. In addition, the protective effect against UV radiation and heavy metals in HaCaT cells was also tested. The CI-vesicles had an entrapment efficiency around 50% and accelerated stability tests did not show significant changes in the parameters tested. The results for the HaCaT cells show the non-cytotoxicity of the CI-vesicles containing PG-E and their protection against heavy metals (lead acetate and mercuric chloride) and UV-B radiation through a reduction of oxidative stress. The reduction of the percentage of deleted mtDNA (mtDNA4977, “common deletion”) in UV-treated HaCaT cells due to the presence of CI-vesicles containing PG-E indicates the mechanism of protection. Therefore, the effects of CI-vesicles loaded with PG-E against oxidative stress support their utilization as natural cosmeceuticals to protect skin health against external damage from environmental pollution and UV radiation.

Due to the growing demand for Medicinal and Aromatic Plants (PAMs), environmental risks associated with overexploitation and inadequate waste management are increasing. Since MAPs residues have a notable potential to be valorised, the implementation of Circular Economy solutions can play a central role in transforming waste management problems into economic opportunities and in responding to the growing demand for MAPs. Circular economy is viewed as a solution for fostering a sustainable system planet and positively contributes to the economy and society. A systematic review was conducted aiming to identify potential applications for the valorisation of MAP, under a sustainable waste management and circular economy approach. A total number of 47 studies were analysed and it was verified that MAPs residues can be valorised for energy purposes, crop management and applications in chemical, food, pharmaceutical, cosmetic industries, among others. Despite the wide range of possible applications, to promote a progressive implementation of circular economy strategies by the industry, further investigation is needed regarding the development of more efficient techniques and technology to develop value-added products and the assessment of sustainable performance in empirical investigations, considering both economic and environmental indicators.

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

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

Variations in geochemical signatures of fossil brachiopod shells may be due to diagenesis and/or biological processes (i.e. ‘vital effects’). Characterize them is crucial to identify reliable areas into the shell suitable to paleoclimatological studies. This investigation contributes to an in-depth understanding of geochemical variations of Gigantoproductus sp. shells (SW Spain, Serpukhovian age), which could affect to the Late Paleozoic Ice Age interpretation. Microstructural, crystallographic, cathodoluminescence and geochemical (minor and trace elements, δ18O, δ13C, and strontium isotopes) characterisation have been performed on the tertiary layer of the ventral valve, to assess the preservation state. Poorly-preserved areas exhibit microstructural and geochemical changes such as recrystallisation, fracturing and higher Mn and Fe enrichment. Moreover, these areas have higher dispersion of ⁸⁶Sr, ⁸⁷Sr, δ18O and δ13C than well-preserved areas. Three structural regions have been identified in well-preserved areas of ventral valve by differences in valve curvature and thickness, such as the umbonal, thick and thin regions. These regions have different proportions of Mg, S, Na, δ18O, and δ13C, whom are interpreted as ‘vital effects’ and probably are related with growth rate differences during shell growth. Gigantoproductus tertiary layer seems the best suitable to paleoclimatological studies because it retains the original microstructure and geochemistry.

Quality control is a critical component in industrial manufacturing, directly influencing efficiency, product reliability, and ultimately, customer satisfaction. In the dynamic environment of industrial manufacturing, traditional methods of inspection may not adequately meet the evolving complexity, necessitating innovative approaches to bolster precision and productivity. In this study, we explore the application of mixed reality (MR) technology for real-time quality control in the assembly process. Our methodology involved the integration of smart glasses with a server-based image recognition system, designed to conduct real-time component analysis. The innovative aspect of our study lies in the harmonization of MR and computer vision algorithms, providing immediate visual feedback to inspectors and thereby improving the speed and accuracy of defect detection. YOLOv8 have been adopted in this study for detection object model. The project implementation occurred in a controlled environment to enable a comprehensive evaluation of the system functionality, the identification of possible problems and improvements in the system performance. The results indicated the viability of mixed reality as a powerful tool for enhancing traditional inspection processes. The fusion of MR and computer vision offers possibilities for future advancements in industrial quality control, paving the way for more efficient and reliable manufacturing ecosystems.

Abiotic stress in plants is an increasingly common problem in agriculture, and thus, studies on plant treatments with specific certain compounds that may help to mitigate these effects have increased in recent years Melatonin (MET) application and its role in mitigating the negative effects of abiotic stress in plants have become important in the last few years. MET, a derivative of tryptophan, is an important plant-related response molecule involved in the growth, development, and reproduction of plants, and the induction of different stress factors. In addition, MET plays a protective role against different abiotic stresses such as salinity, high/low temperature, high light, waterlogging, nutrient deficiency and stress combination by regulating both the enzymatic and non-enzymatic antioxidant defense systems. Also, MET interacts with many signaling molecules, among these, reactive oxygen species (ROS) and nitric oxide (NO), and participates in a wide variety of physiological reactions. It is well known that NO produces S-nitrosylation and NO2-Tyr of important antioxidant-related proteins, being this an important mechanism for maintaining the antioxidant capacity of the AsA/GSH cycle under nitro-oxidative conditions, being extensively reviewed here under different abiotic stress conditions. Lastly, in this review, we show the coordination between NO and MET as a long-range signaling molecule, regulating many responses in plants, including plant growth and abiotic stress tolerance. Despite all the knowledge acquired over the years, there is still more to know about how MET and NO act on tolerance to abiotic stresses.

Asthma is the most prevalent cause of chronic respiratory diseases. Herein, we evaluate asthma burden in Mexico based on results from the Global Burden of Disease (GBD 2019) study 2019. Using data from the GBD 2019, we estimated asthma prevalence, incidence, mortality, and disability-adjusted lived years (DALYs) counts and crude and age-standardized rates per 100,000 people with a 95% uncertainty interval (UI) by sex and age at the national and subnational levels in Mexico from 1990 to 2019. At the national level, asthma affected 3.35 million (95% UI, 2.59-4.37) people, with 606.0 thousand (433.0-811.1) new incident cases and 1,655 (3-1,931) deaths during 2019. Asthma caused a slightly higher burden in females and affected mainly age groups between 1 and 14 years of age. The burden of asthma gradually decreased from 1990 to 2010. However, during the last decade (2010-2019), prevalence increased by 8.2%, as did incidence by 11.3%, whereas mortality and DALYs decreased by 23.3 and 1.6%, respectively. Finally, the burden of asthma displayed a heterogeneous pattern of disease at the subnational level. In conclusion, asthma causes a significant health loss in Mexico that differentially affects the population distributed among the states of the country, thus causing health disparities that should be addressed to provide sustainable asthma diagnosis and control to reduce its burden, especially at early stages of life.

The positional cloning of single nucleotide polymorphisms (SNPs) of the neutrophil cytosolic factor 1 (Ncf1) gene, advocating that a low oxidative burst drives autoimmune disease, demands an understanding of the underlying molecular causes. A cellular target could be T cells, which have been shown to be regulated by reactive oxygen species (ROS). However, the pathways by which ROS mediate T cell signaling remain unclear. The adaptor molecule linker for activation of T cells (LAT) is essential for coupling T cell receptor-mediated antigen recognition to downstream responses, and it contains several cysteine residues that have previously been suggested to be involved in redox regulation. To address the possibility that ROS regulate T cell-dependent inflammation through LAT, we established a mouse strain with cysteine-to-serine mutations at positions 120 and 172 (LATSS). We found that redox regulation of LAT through C120 and C172 mediate its localization and phosphorylation. LATSS mice had reduced numbers of double-positive thymocytes and naïve peripheral T cells. Importantly, redox insensitivity of LAT enhanced T cell-dependent autoimmune inflammation in collagen-induced arthritis (CIA), a mouse model of rheumatoid arthritis (RA). This effect was reversed on an NCF1-mutated (NCF1m1j), ROS-deficient, background. Overall, our data shows that LAT is redox-regulated, acts to repress T cell activation, and is targeted by ROS induced by NCF1 in antigen-presenting cells (APCs).

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

This review paper investigates the influence of gestures on foreign language (FL) vocabulary learning through a series of experiments conducted in our laboratory. The manipulation of the gesture-word relationship was a consistent factor across the studies. Firstly, we examined the impact of gestures on noun and verb learning. The results revealed that participants exhibited better learning outcomes when FL words were accompanied by congruent gestures compared to a no gesture condition. This suggests that gestures have a positive effect on FL learning when there is a meaningful connection between the words and the accompanying gestures. However, in general, the recall of words in conditions where gestures were incongruent or lacked meaning was lower than in the no gesture condition. This indicates that under certain circumstances, gestures may have a detrimental impact on FL learning. We analyzed these findings in terms of their implications for facilitating or interfering with FL acquisition. Secondly, we addressed the question of whether individuals need to physically perform the gestures themselves to observe the effects of gestures on vocabulary learning. To explore this, participants were divided into two experimental groups. In one group, participants learned the words by actively performing the gestures ("do" learning group), while the other group simply observed the gestures performed by others ("see" learning group). The processing of congruent gestures facilitated the recall of FL words in both the "see" and "do" learning groups. However, the interference effect associated with processing incongruent gestures was more pronounced in the "see" learning group than in the "do" learning group. Thus, the performance of gestures appears to mitigate the negative impact that gestures may have on the acquisition of FL vocabulary. In conclusion, our findings suggest that iconic gestures can serve as an effective tool for learning vocabulary in a FL, particularly when the gestures align with the meaning of the words. Furthermore, the active performance of gestures helps counteract the negative effects associated with inconsistencies between gestures and word meanings. Consequently, if a choice must be made, a FL learning strategy in which learners acquire words while making gestures congruent with their meaning would be highly desirable.

The emergence of the COVID-19 pandemics prompted a fast development of novel diagnostic methods of the etiologic virus SARS-CoV-2. Methods based on CRISPR-Cas systems have been particularly promising because they can achieve a similar sensitivity and specificity to the golden standard RT-qPCR, especially when coupled to an isothermal pre-amplification step. Furthermore, they have also solved inherent limitations of RT-qPCR that impede its decentralized use and deployment in the field, such as the need for expensive equipment, high cost per reaction, and delivery of results in hours, among others. In this review, we evaluate publicly available methods to detect SARS-CoV-2 that are based on CRISPR-Cas and isothermal amplification. We critically analyze the steps required to obtain a successful result from clinical samples and pinpoint key experimental conditions and parameters that could be optimized or modified to improve clinical and analytical outputs. The COVID outbreak has propelled intensive research in a short time, which is paving the way to develop effective and very promising CRISPR-Cas systems for the precise detection of SARS-CoV-2. This review could also serve as an introductory guide to new labs delving into this technology.

Pepino mosaic virus (PepMV) causes significant economic losses in tomato crops worldwide. Since its first detection infecting tomato in 1999, aggressive PepMV variants have emerged. This study aimed to characterize two aggressive PepMV isolates, PepMV-H30 and PepMV-KLP2. Both isolates were identified in South-Eastern Spain infecting tomato plants, which showed severe symptoms, including bright yellow mosaics. Full-length infectious clones were generated, and phylogenetic relationships were inferred using their nucleotide sequences and another 35 full-length sequences from isolates representing the five PepMV known strains. Our analysis revealed that PepMV-H30 and PepMV-KLP2 belong to the EU and CH2 strains, respectively. Amino acid sequence comparisons between these and mild isolates identified 8 and 15 amino acid substitutions for PepMV-H30 and PepMV-KLP2, respectively, potentially involved in severe symptom induction. None of the substitutions identified in PepMV-H30 had previously been described as symptom determinant. The E236K substitution, originally present in the PepMV-H30 CP, was introduced into a mild PepMV-EU isolate, resulting in a virus that causes symptoms similar to those induced by the parental PepMV-H30. In silico analyses revealed that this residue is located at the C-terminus of the CP and is solvent-accessible, suggesting its potential involvement in CP-host proteins interactions. We also examined the subcellular localization of PepGFPm2E236K in comparison to that of PepGFPm2, focusing on chloroplast affection, but no differences were observed in the GFP subcellular distribution between the two viruses. Due to the easily visible symptoms that PepMV-H30 and PepMV-KLP2 induce, these isolates represent valuable tools in programs destined to breeding resistance to PepMV in tomato.

This review paper presents a comprehensive synthesis of current knowledge on the contamination of water systems by polycyclic aromatic hydrocarbons (PAHs). PAHs, organic contaminants characterized by two or more fused aromatic rings, are notably problematic due to their persistence, bioaccumulation, and significant health risks. The review commences with an examination of various sources of PAHs in aquatic environments, encompassing both anthropogenic activities, such as industrial discharges, urban runoff, and oil spills, and natural phenomena including volcanic eruptions and wildfires. Subsequently, the discussion shifts to the distribution patterns of PAHs within different aquatic ecosystems, with an analysis of factors that influence their transport. Considerable focus is placed on the entry mechanisms of PAHs into water systems and their interactions with diverse environmental matrices. Additionally, the ecotoxicological effects of PAHs on aquatic life are scrutinized, with particular emphasis on molecular, individual, and ecosystemic impacts. This includes an exploration of PAH bioaccumulation in aquatic organisms and their potential mutagenic and carcinogenic consequences. The review further addresses the challenges associated with detecting and quantifying PAHs in aquatic settings, reflecting on the advancements in analytical methodologies and the complexities introduced by their varied physicochemical properties. The paper concludes with a summary of existing regulatory frameworks and guidelines governing PAH contamination in water systems, underscoring the imperative for global collaboration in the monitoring and management of PAH pollution.

The continuous casting tundish is non-isothermal due to heat losses and temperature variation from the inlet stream generating relevant convection forces. This condition is commonly avoided through qualitative fluid dynamic analysis only. This work searches to establish the conditions for which non-isothermal simulations are mandatory or for which isothermal simulations are enough to accurately describe the fluid dynamics inside the tundish by quantifying the buoyant and inertial forces. The mathematical model, simulated by CFD software, considers the Navier-Stokes equations, the realizable k- model for solving the turbulence, and the Lagrangian discrete face to track the inclusion trajectories. The results show that temperature does not significantly impact the volume fraction percentages or the mean residence time results, nevertheless, bigger velocity magnitudes under non-isothermal conditions than in isothermal conditions and noticeable changes in the fluid dynamics between isothermal and non-isothermal cases in all the zones where buoyancy force dominates over inertial forces were observed. Because of the results, it is concluded that isothermal simulations can accurately describe the flow behavior in tundishes when the flow control devices control the fluid dynamic, but the simulation without control devices or with a weak fluid dynamic dependence on the control devices requires non-isothermal simulations.

Socioeconomically disadvantaged people are disproportionally more likely to develop obesity and obesity-related diseases. However, it remains unclear to what extent diet quality contributes to socioeconomic inequalities in obesity. We aimed to assess the role of diet quality in the association between socioeconomic status (SES) and obesity. Data originated from the national nutrition survey, a cross-sectional sample of the adult Swiss population (N=1860). We used education and income as proxies for SES; calculated the Alternate Healthy Eating Index (AHEI) as measure of diet quality; and used body mass index (BMI), waist circumference (WC), waist-to-hip ratio (WHR), and waist-to-height ratio (WHtR) as obesity markers. We applied counterfactual mediation modelling to generate odds ratios, 95% confidence intervals, and the proportion mediated by diet quality. Individuals with less than a tertiary education were two to three times more likely to be obese, regardless of the marker (OR; 95% CI: 3.36 (2.01, 5.66) using BMI; 2.44 (1.58, 3.75) using WC; 2.48 (1.63, 3.78) using WHR; and 2.04 (1.43, 2.96) using WHtR). The proportion of the association between educational level and obesity that was mediated by diet quality was 22.1% using BMI, 26.6% using WC, 31.4% using WHtR, and 35.8% using WHR. Similar findings were observed for income. Our findings suggest that diet quality substantially contributes to socioeconomic inequalities in obesity while it does not fully explain them. Focusing efforts on improving the diet quality of disadvantaged groups could help reduce social inequalities in obesity.

Rapid and extensive urbanization has adversely impacted humans and ecological entities in the recent decades through a decrease in surface permeability and the emergence of urban heat islands (UHI). While detailed and continuous assessments of surface permeability and UHI are crucial for urban planning and management of landuse zones, they have mostly involved time consuming and expensive field studies, and single sensor derived large scale aerial and satellite imageries. We demonstrated the advantage of fusing imageries from multiple sensors for landuse and landcover (LULC) change assessments as well as for assessing surface permeability and UHI emergence in Tirunelveli, Tamilnadu, India. Cartosat-2 and Landsat-7 ETM+ imageries from 2007 and 2017 were fused and classified using a Rotation Forest (RF), while surface permeability and temperature were quantified using Soil-Adjusted Vegetation Index (SAVI) and Land Surface Temperature (LST) index, respectively. Fused images exhibited higher classification accuracies than non-fused images, i.e. overall kappa coefficient values 0.83 and 0.75, respectively. We observed an overall increase of 20 km2 (45%) in the coverage of urban (dry, real estate plots and built-up) areas, while a decrease of 27 km2 (37%) for vegetated (cropland and forest) areas in Tirunelveli between 2007 and 2017. The SAVI values indicated an extensive decrease in surface permeability for Tirunelveli overall (0.4) and also for almost all LULC zones. The LST values exhibited an associated overall increase (1.30C) of surface temperature in Tirunelveli with the highest increase (2.40C) for urban built-up areas between 2007 and 2017. The SAVI-LST combined metric depicted the Southeastern built-up areas in Tirunelveli as a potential UHI hotspot, while a caution for the Western riparian zone for UHI emergence in 2017. Our results provide important metrics for surface permeability and UHI monitoring, and inform urban and zonal planning authorities about the advantages of satellite image fusion.

The use of selective pro resolving mediators including the monohydroxylates are promising substances for the management of different acute and chronic diseases.In the field of obstetrics many clinical entities like uterine contractions or the occurrence of pre-eclampsia are still serious complications during pregnancy.The use of enriched marine oil nutritional’s may contribute to an attenuation of these diseases as the containing selective pro resolving mediators exhibit pro resolutive actions that can positively modulate inflammatory diseases and those leading to serious obstetrical complications.

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

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

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

A tunable quantum cascade laser (QCL) spectrometer was used to develop methods for detecting and quantifying high explosives (HE) in soil based on multivariate analysis (MVA) and artificial intelligence (AI). For quantification, mixes of 2,4-dinitrotoluene (2,4-DNT) with concentrations from 0% to 20% w/w were investigated using three types of soils: bentonite, synthetic soil, and natural soil. A Partial least squares regression model was generated for predicting 2,4-DNT concentrations. To increase its selectivity, the model was trained and evaluated using additional analytes as interferences, including other HEs such as PETN, RDX, and TNT and non-explosives such as benzoic acid and ibuprofen. For detection, mixes of different explosives in soils were used to implement two AI strategies. In the first strategy, the spectra of the samples were compared with those of soils recorded in a database to identify the most similar soils based on QCL spectroscopy. Next, a Classical Least Squares preprocessing (Pre-CLS) was applied to soils spectra selected from the database. The parameter obtained based on the sum of the weights of Pre-CLS was then used to generate a simple binary discrimination model for distinguishing between contaminated and uncontaminated soils, achieving an accuracy of 0.877. In the second AI strategy, the same parameter was added to a principal component matrix obtained from spectral data of samples and used to generate multi-classification models based on different machine learning algorithms. A Random Forest model worked best with 0.997 accuracy and allowing to distinguish between soils contaminated with DNT, TNT, or RDX and uncontaminated soils.

Inflammation is considered an important target for stroke therapy because it induces secondary brain damage after the initial ischemic insult. Peripheral monocytes migrate to the brain parenchyma after a central insult. They then differentiate to macrophages in a positive feedback fashion contributing to damage instead of ischemic resolution and inflammation control. A cyclic diterpenoid, (1S,2E,4R,6R,7E,11E)-cembra-2,7,11-triene-4,6-diol (4R), decreases neurodegeneration after ischemia with central anti-inflammatory activity. This study aims to determine whether the central anti-inflammatory effect of 4R is effective against peripheral inflammation triggered by brain ischemia. To investigate the anti-inflammatory effect of 4R, we treated macrophages with lipopolysaccharide (LPS) as an inflammatory model, followed by treatment with 4R. Microarray transcriptome analysis of over 30,000 genes identified the differential expression of 393 genes. Genes related to inflammation, cell adhesion, and transcription were validated with qPCR, and reduced expression was determined. Quantification of NF-kB phosphorylation served as a marker for the modulation of inflammation through gene transcription. Our results show that 4R was associated with a reduction in NFKB1 and ITGB5 gene expression, increased phosphorylation of NF-kB, and a decrease in macrophage adhesion in a blood-brain barrier model. These results indicate that 4R can partially modulate the peripheral immune response, making 4R a potential drug against post-ischemic inflammation.

Globally mangrove forests are substantially declining and a globally synthesized database of the drivers of deforestation and drivers’ interaction is scarce. Here we synthesized the key social-ecological drivers of global mangrove deforestation by reviewing about two hundred published scientific studies over the last four decades (from 1980 to 2021). Our focus was on both natural and anthropogenic drivers with gradual and abrupt impacts and their geographic ranges of effects and how these drivers interact. We also summarized the patterns of global mangrove coverage decline between 1990 and 2020 and identified the threatened mangrove species and their geographic ranges. Our consolidated studies reported a 8,600 km2 decline in the global mangrove coverage between 1990 and 2020 with the highest decline occurring in South and Southeast Asia (3870 km2). We could identify 11 threatened mangrove species, two of which are critically endangered (Sonneratia griffithii and Bruguiera hainseii). Our reviewed studies pointed to aquaculture and agriculture as the predominant driver of global mangrove deforestation though the spatial distribution of their impacts varied. Gradual climate variations, i.e. seal-level rise, long-term precipitation and temperature changes and driven coastline erosion, constitute the second major group of drivers. Our findings underline a strong interaction across natural and anthropogenic drivers with the strongest interaction between the driver groups aquaculture and agriculture and industrialization and pollution. Our results suggest prioritizing globally coordinated empirical studies linking drivers and mangrove changes and a global development of policies for mangrove conservation.

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

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

The present study aims to measure the technical efficiency and establish core factors effecting rice production in Cambodia. Four-years dataset generated from the central government document “Profile on Economics and Social” of entire 25 provinces between 2012-2015 and the stochastic production frontier model (SFA) was applied. The results indicated that the level of output (quantity) of Cambodian rice production varied according to the different level of capital investment in agricultural machineries, total rice actual harvested area, and technically fertilizers application within provinces. Furthermore, evidence revealed the overall mean efficiency of rice production is 78.4% implies that there is still room to further improve technical efficiency by given the same level of inputs and technology. More importantly, the findings revealed that irrigation, production technique and amount of agricultural supporting staffs are being as the most important influencing factors of rice production’s technical efficiency in Cambodia. In conclusion, present study strongly recommends the development of irrigation systems and good water management practices to be considered and bring into more effective actions by the central government as well as related agencies for improving rice production in Cambodia in addition to capital investment and improving technical skills of supporting staffs and rural farmers.

Leaf area estimation is a critical component in the study of plant growth and productivity within agricultural systems. This research introduces the LeafArea package, a specialized tool designed to calculate the leaf area of six distinct Andean fruit species: S. quitoense, S. betaceum, P. peruviana, R. fruticosus, P. ligularis and P. edulis. Leveraging response variables such as species type, leaf length and width, the package employs advanced machine learning algorithms to estimate leaf area accurately. The primary focus of the study is to identify the most effective model for describing the relationship between leaf width, length, and area for each plant species. Currently, the LeafArea package utilizes four different machine learning algorithms, namely generalized linear model (GLM), generalized linear mixed model (GLMM), Random Forest and XGBoost. Among these, XGBoost stands out as a top-performing algorithm, exhibiting exceptional predictive accuracy. The evaluation metrics employed in the program provide valuable insights for researchers, aiding in informed decision-making. Specifically, XGBoost demonstrates significantly lower prediction errors and approaches a near-perfect R2 value, emphasizing its potential to enhance predictive accuracy. These results underscore the efficacy of machine learning techniques, as a compelling choice for researchers seeking precise and robust predictions in leaf area estimation. The LeafArea package thus represents a valuable tool for advancing our understanding of plant growth dynamics, resource allocation, and overall productivity within agricultural ecosystems.

Arsenic is highly toxic, affecting millions of people in many regions of the world. That is why developing economic and efficient technologies is imperative to eliminate it. Sorption techniques are attractive as efficient and inexpensive sorbents can be used. Chitosan is an abundant, naturally occurring, biodegradable, low-cost biopolymer that can be combined with metal oxide to enhance its removability. This work aimed to synthesize a new chitosan-magnetite-based sorbent for arsenic removal. The synthesized sorbent does not present pores, and by FT-IR, functional groups of the chitosan and the presence of As(V) in the sorbent treated with arsenic were identified. The synthesized magnetite was characterized by XRD spectroscopy. Application of the Composite Central Design model showed that 0.22 g of the sorbent at pH 6.0 could remove 27.6% of As(V). Kinetic data, fitted with the pseudo-first and second-order models, indicated an ion exchange sorption and activation energy of 28.1-31.4 kJ mol-1. The isotherms were fitted with the Langmuir model, indicating a favourable monolayer adsorption with high affinity. The sorption energy, calculated by Dubinin-Radushkevich, 9.60-8.80 kJ mol-1, confirms a sorption mechanism mediated by ion exchange. The thermodynamic parameters of the process were ΔG°(-21.7/-19.7 kJ mol-1), ΔH°(16.7 kJ mol-1) and ΔS°(123.3 J mol-1 K-1).

Diffuse optical tomography (DOT) technology enables a differentiation between oxyhemoglobin (HbO) and deoxyhemoglobin (HbR) in the sensory and motor cerebral gyri, resulting in greater sensitivity for cerebral activation compared to functional magnetic resonance imaging (fMRI). Here, we introduce a novel approach where functional regions of interest (ROIs) are created based on the specific signal behavior observed in DOT measurements, in contrast to the conventional use of structural-ROIs obtained from anatomical information. The generation of cerebral activation maps involves using the general linear model (GLM) to compare the outcomes obtained from both the functional and structural ROI approaches. DOT-derived maps are then compared with maps derived from fMRI datasets considered the gold standard for assessing functional brain activity. The results obtained demonstrate the effectiveness of employing functional ROIs to improve the spatial location of functional activations in the sensory and motor cerebral gyri by leveraging the neural synchronization data provided by DOT. Furthermore, this methodology simplifies data processing in animal models, where anatomical differences compared to the human head can pose challenges. By incorporating functional ROIs prior to GLM application, this study offers enhancements to DOT analysis techniques and broadens its applicability in both human and animal models.

Cotton is the most ubiquitous and profitable fiber with diverse industrial and domestic applications. Grown in over 100 countries, it has a global market value of about $40 billion and employs over 350 million people from fields to textile mills, contributing about 7% of total labor-force recruitment in developing economies. Cotton has an indeterminate growth habit and an extensive tap root system affected by soil physicochemical and environmental conditions. There is a consensus among experts that conventional cotton cultivation still has a long way to attain sustainability, which is essential if cotton will maintain its competitive edge over other natural and synthetic fibers like hemp, polyesters, and rayon. Despite several efforts already committed to growing cotton sustainably, sustainability has eluded cotton cultivation globally because of the intense farm inputs (freshwater, pesticides, and heavy-duty equipment) needs, especially in developing economies. Some of the technological advancements towards achieving the goal of sustainable cotton cultivation include the development of new varieties, improved irrigation and mulching and precision agriculture techniques, application of remote sensing and Unmanned Aerial Systems (UAS) combined with image processing, and the introduction of autonomous and multi-purpose robotic platforms for growing and harvesting cotton. This review attempts to evaluate the successes already achieved by stakeholders in moving cotton towards sustainable production and identify areas where efforts are still needed to reach sustainable production and improved profitability goals for cotton with projections for future research directions.

The energy sector plays an important role in Mexico’s development trajectory. Mexico makes an interesting case study, because it shows how difficult it is to reduce fossil energy dependence despite geographic and climatic conditions that favour renewable energy deployment and use. Resolving path dependencies and the related carbon lock-in are key to Mexico’s sustainable energy transition. This case study aims to identify and discuss how carbon lock-in affects Mexico’s sustainable energy transition. Mexico’s carbon lock-in involves oil and oil-run power plants that are costly to build but relatively inexpensive to operate. This case study identifies potential entry points for transitioning towards sustainable energy in Mexico – resources that can promote the use of clean energy despite carbon lock-in. For example, focusing on electrification – particularly of the carbon-intensive sectors – can help Mexico transit towards sustainable energy despite institutional constraints. Complementing this case study is a teaching guide with recommendations for using Mexico’s energy transition in courses on sustainability. It introduces a “learning activation framework” to identify emerging opportunities that can advance sustainable energy transitions in different cases of carbon lock-in. Finally, the framework also gives students a chance to help dismantle or cope with carbon lock-ins.

Basketball playing entails the repetitive performance of short intense actions using lower limb explosive power. As such, it is important to measure this capability in basketball players, especially among young players, and to optimize training programs and game plans. After presenting an in-depth understanding of the specific physiological requirements when playing basketball, as well as the type of movements required, The aim of this review is to better understand the importance of the physiological energy systems in basketball, to examine the contribution of each energy system and, accordingly, to heighten awareness of the importance and dominance of the alactic anaerobic physiological system in basketball, for actions requiring high level explosive power. This review of the literature depicts the horizontal and vertical physical movements and physiological requirements entailed in playing basketball, and presents eight standardized anaerobic alactic measurement tools relevant to the game. As some of these tests suit a number of ball games, the findings of this review article are important for making order of the elements unique to basketball as well as additional parameters to consider when testing basketball players. By reliably and validly testing the anaerobic alactic capabilities of basketball players, test results can be used for training purposes and for improving game outcomes. Despite the fact that much of the information in this review is familiar to coaches, highlighting the specific needs of basketball may help them to choose the most suitable tools, and may also shed light on new directions for developing basketball-specific assessment tests.

Novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants of concern (VOC) are constantly threatening global public health. With no end date, the pandemic still persists with the emergence of novel variants that threaten the effectiveness of diagnostic tests and vaccines. Mutations in the Spike surface protein of the virus are regularly observed in the new variants, potentializing the emergence of novel viruses with different tropism from the current ones, which may change the severity and symptoms of the disease. Growing evidence has shown that mutations are being selected in favor of variants that are more capable of evading the action of neutralizing antibodies. In this context, the most important factor guiding the evolution of SARS-CoV-2 is its interaction with the host’s immune system. Thus, as current vaccines cannot block the transmission of the virus, measures complementary to vaccination, such as the use of masks, hand hygiene, and keeping environments ventilated remain essential to delay the emergence of new variants. Importantly, in addition to the involvement of the immune system in the evolution of the virus, we highlight several chemical parameters that influence the molecular interactions between viruses and host cells during invasion and are also critical tools making novel variants more transmissible. In this review, we dissect the impacts of the Spike mutations on biological parameters such as (1) increase of Spike binding affinity to hACE2; (2) bound time for the receptor to be cleaved by the proteases; (3) how mutations associate with increase of RBD up-conformation state in the Spike ectodomain; (4) expansion of uncleaved Spike protein in the virion particles; (5) increment of Spike concentration per virion particles; and (6) evasion of the immune system. These factors play key roles in the fast spreading of SARS-CoV-2 variants of concern, including the Omicron.

Divergences have become a very useful tool for measuring similarity (or dissimilarity) between probability distributions. Depending on the field of application a more appropriate measure may be necessary. In this paper we introduce a family of divergences we call gamma-divergences. They are based on the convexity property of the functions that generate them. We demonstrate that these divergences verify all the usually required properties, and we extend them to weighted probability distribution. We investigate their properties in the context of kernel theory. Finally, we apply our findings to the analysis of simulated and real time series.

Indonesia is an interesting case study for students of sustainable development and sustainable energy due to its ability to connect the multiple “worlds” it has become part of. Indonesia is an important bridge to Muslim countries, the voice of the Global South in the G20 and a main pillar of the 134-country-strong G77. Indonesia’s development trajectory is also key to the achievement of the Paris Climate Agreement as well as of the 2030 Agenda. Students can learn from how Indo-nesia address contradictions that would have been unsurmountable for other countries. Indone-sia’s energy transition offers helpful lessons, because of its aspiration to become a developed country by 2045. This goal is only possible when a country is able to effectively address barriers and caveats to sustainable energy. It is interesting how Indonesia focuses on silver linings and come up with pragmatic solutions to energy-related issues. This is followed by the “teaching guide,” which provides recommendations how the lessons from Indonesia can be embedded into a learning experience. The “learning activation approach” is introduced, which encourages stu-dents to systematically reflect on the complexity of selected contexts and understand this com-plexity by looking at the technical issues and processes that allow decision-making.