This research investigates the application of Fused Filament Fabrication (FFF) in producing WC-10Co hardmetals, focusing binder formulations and understanding its influence on extrusion force and the influence of printing variables on green density of the samples. By examining the interplay between different binder compositions and backbone contents, the study aims to enhance the mechanical properties of the sintered parts while reducing defects inherent in the printing process. Evidence suggested that formulated feedstocks influenced the hardness of the sintered hardmetal, not due to microstructural changes but to macrostructural responses like macro defects introduced during printing, debinding and sintering of the samples. The results demonstrate the critical role of PP-MA content in improving part density and sintered hardness, suggesting the need for specific thermal debinding protocols tailored to each feedstock. The study provides insights into the formulation of feedstocks for hardmetal FFF, proposing a path toward refining manufacturing processes for better quality and performance of 3D printed hardmetal components.

Conventional chemotherapy for colorectal cancer (CRC) gives only a small increase in patient survival, since it is often diagnosed in late stages, when tumor has disseminated to other organs. Besides, it is common to observe that malignant cells acquire tumor escape mechanisms which leads to therapy resistance. Considering these facts, the discovery of new molecules with therapeutic potential has become an invaluable tool in chemoprevention. In this context, we previously evaluated two hybrids (SAC-CAFA-MET and SAC-CAFA-PENT) which exhibited selective cytotoxicity against SW480, with better results than the conventional chemotherapeutic agent (5-fluorouracil; 5-FU). Here, we investigated a little deeper in the possible mechanism of these molecules to identify potential therapeutic alternatives for the treatment of CRC. Both compounds induced cell damage and reduced ROS formation. Further evaluations showed that SAC-CAFA-MET induces cell death independent from caspases and p53, but probably mediated by the negative regulation of the proapoptotic Bcl-2. In addition, the lack of activation of caspase 8 and the positive regulation of caspase 3 induced by SAC-CAFA-PENT suggest this compound acts through an apoptotic mechanism, probably initiated by intrinsic pathway. Besides, the down regulation of IL-6 by SAC-CAFA-PENT suggests it also induces a significant anti-inflammatory process. In addition, docking studies would suggest caspase-3 modulation as the primary mechanism by which hybrids elicits apoptosis in human colorectal adenocarcinoma SW480. Meanwhile, DFT calculations suggest that hybrids would produce effects in modulation of ROS in SW480 cells via hydrogen atom transfer pathway (HAT). Finally, both, SAC-CAFA-MET and SAC-CAFA-PENT displayed a favorable pharmacokinetic profile. The current work highlights the potential of the lead compounds SAC-CAFA-MET and SAC-CAFA-PENT as potential agents for colorectal cancer chemoprevention.

In this study, ignition delay and burning rate are experimentally investigated in relation to the effect of pristine carbon nanotubes (CNTs), sodium dodecylbenzene sulfonate (SDBS), and diesel blends. Single droplet combustion tests were conducted in a combustion system for 21 days using CNTs at concentrations of 50 ppm and 100 ppm, that were dispersed in Colombian commercial diesel and stabilized by SDBS. Additionally, recordings of the combustion were collected, and the Shadowgraph optical method was utilized for monitoring the evolution of droplet size during combustion. The measurements were done over a four-week period. The results demonstrated that the temporal stability has a direct impact on the single droplet combustion tests because a concentration of CNTs of 100 ppm showed higher stability than those achieved by 50 ppm. Consequently, improvements were found with a concentration of 100 ppm, for instance, thermal conductivity increased by about 20%, ignition delay time by 16.2%, and burning rate by 30.5%.

In most organizations there is an information system where data is recorded regarding events, activities, times, and variables associated with the execution of all organizational processes; this information is generally not used to its maximum potential, limited only to the registration of processes. With process mining, a field of engineering research, responsible for the design of processes through mining algorithms, it is possible to characterize bottlenecks, reprocessing, and opportunities for improvement in organizational processes. In this article, the construction of the collection and billing process is carried out in a case study of the Colombian Pharmaceutical sector supported by process mining and business intelligence. The objective of this research is oriented to the construction of the real process of a case study of the pharmaceutical sector in Colombia supported by the alpha mining algorithm, within the framework of process mining and business intelligence to facilitate decision-making at an organizational level. The result of this research is the proposal of a methodology to implement process mining in organizations in the pharmaceutical sector in Colombia supported by the Design Science Research (DSR) methodology and the construction of the real process in the billing and collection case study in the pharmaceutical sector supported by process mining, business intelligence is also used to complement the points of improvement of the accounting process in the case study. In conclusion, the artifact built in DSR shows a rigorous methodology from obtaining data, and types of documents that make up the knowledge base to proceeding to the application of the alpha mining algorithm that built the real billing and collection process of the case study, in which points of reprocessing and activities susceptible to improvements in the case study are evident. As a contribution, this article develops an alternative approach that contributes to the knowledge gap related to the actual construction of billing and collection processes in organizations, which generates an impact an alternative paradigm in the construction of organizational processes, by proposing a methodology that Builds a billing and collection process through process mining complemented by business intelligence.

The cattle sector is strategic sector for both the economic development and food security of Africa. However, the low availability and quality of forage puts the most vulnerable population in the field at risk. Hybrid forages have proven to be a real alternative for enhancing both the food security and sustainability of the sector. They are the product of genetic improvements and combine the superior traits of different materials. In 1987, the International Center for Tropical Agriculture (CIAT) began this line of research and together with the private sector various ma-terials have been released until today. Despite their beforementioned potential, forage hybrid adoption levels are still low in Africa, which is related to various factors among which the availability of seeds and planting material stands out. This document analyzes the potential markets for new forage hybrids adapted to the environmental conditions of eastern Africa and partially western Africa. Likewise, an estimation of the commercial value of these markets is provided. The results show a potential market of 414,388 ha for new interspecific hybrids of Urochloa and 528,409 ha for potential hybrids of Megathyrsus maximus, with approximate values of 73.5 and 101.1 million dollars, respectively. Ethiopia, Tanzania, and Kenya have a 70% market share for Urochloa, while South Sudan, Ethiopia, and Tanzania have a 67% share for Megathyrsus maximus. The results will help different actors in decision-making, i.e., regarding private sector investments in forage seed commercialization or public sector incentives supporting adoption processes, and thus contribute to increasing food security and sustainability in the region.

The study describes the acute and delayed time course of recovery following the CrossFit® Benchmark Workout Karen. Eight trained men (28.4±6.4 years; 1RM back squat 139.1±26.0 kg) undertook the Karen protocol. The protocol consists of 150 Wall Balls, aiming to hit a target 3 meters high. Countermovement jump height (CMJ), creatine kinase (CK), and perceived recovery status scale (PRS) (general, lower and upper limbs) were assessed pre, post-0h, 24h, 48h and 72h after the session. The CK concentration 24h after was higher than pre-exercise (338.4 U/L vs. 143.3 U/L; effect size: 0.74; p≤0.05). At 48h and 72h following exercise, CK concentration had returned to baseline levels. The PRS general and of the lower limbs were lower in the 24-hours post-exercise compared to pre-exercise (PRS general: 4.7 ±1.5 and 7.9 ±1.7 mmol/L; and PRS of the lower limbs: 4.0 ±2.5 and 7.9 ±0.8, respectively). The PRS general, lower, and upper limbs were reduced at 48-post exercise compared to 72-hours post-exercise scores. Our findings provide insights into the fatigue profile and recovery in acute CrossFit® and can be useful to coaches effectively design the daily session.

The effect of embryo reinsertion immediately after embryo flushing was studied to determine its effect on luteal function, pregnancy outcome, endometrial bacterial contamination, and embryo morphology. In Experiment 1, eight mares were used during 32 cycles (8 cycles in each group): for the first two groups, inseminated mares were flushed 8 days after ovulation and prostaglandin F2α was not administered: in group EF-ET (embryo flushing and embryo transfer) the embryo was reinserted in the same donor mare, while in the EF group, no further procedure was performed. In the third group (ET), non-inseminated mares (recipients) received a Day 8 embryo 5 to 8 days after ovulation. Progesterone concentration was measured before EF/ET and 72 h after in the 3 groups. Pregnancy diagnosis was performed within 6 days of transfer. In Experiment 2, twelve mares were used during 17 cycles in two groups: EF-ET (n=11) and ET (n=6), as in Experiment 1, except that every mare was flushed 24 h after embryo transfer to retrieve the embryo. Fewer pregnancies resulted after transfer in EF-ET cycles (0(8, 0%) than in the ET group (6/8, 75%). Progesterone concentration decreased significantly (p=0.05) 72 h after EF-ET, but not in EF or ET cycles (p>0.1). Three mares from the EF-ET showed full luteolysis and signs of endometritis. In Experiment 2, more (5/6; p=0.08) grade I embryos were recovered in the ET compared to the EF-ET group (3/7); 4 embryos were graded III-IV (were broken or had signs of degeneration) in the EF-ET group, but none in the ET group. In both groups, capsule fragments were obtained as indicative of the presence of a recently destroyed embryo in the EF-ET (n=3) and ET (n=1) groups. Positive bacterial cultures were obtained in 2/11 and 1/6 embryo flushes from the EF-ET and ET groups, respectively.

Zoonoses are diseases transmitted from (vertebrate) animals to humans. Control and prevention of these diseases require an appropriate way to measure health for prudent and well-balanced decisions in public health. We propose a framework that aims to explore, understand and open up a conversation about the non-monetary value of animals through environmental and normative ethics. As an example of its application, participants can choose what they are willing to give in exchange for curing an animal in hypothetical scenarios selecting a human health condition to suffer, the amount of money, and lifetime as a tradeoff. We believe that considering animals beyond their monetary value in public health decisions will contribute to a more rigorous assessment of the burden of zoonotic diseases, among other health decisions. This method might help us complement the existing metrics in health, adding more comprehensive values for animal and human health for the “One Health” approach.

Course-based Undergraduate Research Experiences (CUREs) in high-enrollment, introductory classes are a 37 potentially transformative approach to retaining more students in STEM majors. We developed and piloted a CURE 38 in the introductory biology courses at the University of Washington. This CURE focuses on analyzing experimental 39 evolution of antibiotic resistance in Escherichia coli and generates data on two topics relevant to clinical practice: 40 compensatory mutations and cross-drug effects. By studying mutations in central cellular machinery that confer drug 41 resistance, students not only gain insight into fundamental cellular phenomena, but also recognize the molecular 42 basis of a medically important form of evolutionary change, connecting genetics, microbiology, and evolution.

The PILAR model provides a dynamical systems perspective on collaboration. Two studies are performed using peer assessment data, both testing empirical support for the five Pillars (prospects, involved, liked, agency, respect) that constitute member’s perceptions of collaboration viability. The first study analyses peer-assessment data collected online from 458 first-year engineering students (404 males; 54 females). A nine-item instrument was inherited from past year’s usage in the course, expanded with four additional items to elaborate upon the agency and liked Pillars. Exploratory factor analysis was conducted on student responses to test whether they thematically aligned to constructs consistent with the five Pillars. As anticipated, twelve of the thirteen items grouped into five components, each aligned with a Pillar, providing empirical evidence that the five Pillars represent perceptions of collaboration. The second study replicated the first study using a retrospective analysis of 87 items included in the Comprehensive Assessment of Team Member Effectiveness (CATME) peer-assessment tool. The associated factor analyses resulted in five components and conceptual alignment of these components with Pillars was evident for three of five CATME components. We recommend a peer-assessment instrument based upon PILAR as potentially more parsimonious and reliable than an extensive list of behaviours, such as employed by CATME. We also recommend including items that target inter-rater bias, which is aligned with the liked Pillar, that instruments such as CATME exclude.

Background: When we talk about zoonoses, it is undeniable that we have a human and animal population that has been isolated in studies over time. Besides human and animal health, zoonoses also impact the economy and society. Therefore, the integration of the analysis in this area is essential to optimize resources in public health decisions. We have new challenges in public health that we need to overcome in a more comprehensive method such as One Health. For better measures in public health, the dual burden of zoonoses seems a logical way to determine the integral impact of such diseases in society and thus take better measures to prevent and reduce the impact of these diseases. Methods: We follow the guidelines for “Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA). We search human and animal zoonoses on Embase, Ovid Medline, Scopus, Web of Science, and Google Scholar, from an unrestricted period until November 2021. For the search, we consider the Disability Adjusted Life Years (DALYs) for the human zoonotic burden and the animal zoonotic burden in monetary terms. A librarian collaborates to optimize the search string for the databases, and two reviewers screen eligible articles (first by title, then by abstracts, and finally, by full-text assessment.) For the analysis, we aim to convert the burden of zoonoses of all selected studies into the zoonotic Disability Adjusted Life Years (zDALYs) – including the human and animal components. Discussion: The study results will provide information on published studies that have accounted for the dual burden of zoonoses (both human and animal health aspects.) In addition, the synthesis of the available literature will address the knowledge gap in this area in order to know to what extent it is possible to convert the burden of human zoonoses to the animal burden of zoonoses and integrate them into a more comprehensive approach (dual burden of zoonoses.)

The fact that real dissipative (entropy producing) processes may be detected by non–comoving observers (tilted), in systems that appear to be isentropic for comoving observers, in general relativity, is explained in terms of the information theory, in analogy with the explanation of the Maxwell's demon paradox.

The Puuc Biocultural State Reserve (PBSR is an unique model for tropical dry forest conservation in Mexico. Preserving forest biodiversity and carbon within the PBSR depends on the mainte-nance of low impact productive activities coordinated by multiple communal and private land-owners. In this study, we used state-of-the-art remote sensing data to investigate past spatial patterns in forest clearing dynamics and its relation to forest carbon density and forest plant species richness and diversity in the context of the forest conservation goals of the PBSR. We used a Landsat-based continuous change detection product for the 2000-2021 period and compared it to carbon density and tree species richness models generated from ALOS-2 PALSAR 2 imagery and national scale forest inventory data. The estimated error-adjusted area of detected annual forest clearings from the year 2000 until the year 2021 was 230,511 ha in total (+19,979 ha). The analysis of annual forest clearing frequency and area suggests that although forest clearing was significantly more intensive outside of the PBSR than within the PBSR during the entire 2000-2021 period, there is no evidence suggesting that the frequency and magnitude of forest clearing has changed over the years after the creation of the PBSR in 2011. An emergent hotspot analysis shows, however, that high spatiotemporal clustering of forest clearing events (hotspots) during the 2012-2021 pe-riod was less common than prior to 2011 and these more recent hotspots have been confined to areas outside the PBSR. After comparing forest clearing events to carbon density and tree species richness models, results show that land owners outside the PBSR often clear forests with lower carbon density and species diversity than land owners inside the PBSR. This suggests that, compared to land owners outside the PBSR, land owners within the PBSR might be practicing longer fallow periods allowing forests to attain higher carbon density and tree species richness and hence better soil nutrient recovery after land abandonment. In conclusion, our results show that the PBSR effectively acted as a stabilizing forest management scheme during the 2012-2021 period minimizing the impact of productive activities by lowering the frequency of forest clearing events and preserving late secondary forests within the PBSR. We recommend the continuation of efforts for providing alternative optimal field data collection strategies and modeling techniques to spatially predict key tropical forest attributes. The combination of these models with contin-uous change detection datasets will allow to reveal underlying ecological processes and generate information better adapted to forest governance scales.

We show broadband sum-frequency generation (SFG) in the Green-Yellow-Orange-Red spectral range using bismuth triborate, BiB3O6 crystal (BIBO) as nonlinear material. We perform a noncollinear phase-matching configuration within BIBO crystal using the remaining light behind the second harmonic generation stage and the infrared idler of an optical parametric amplifier (OPA). The obtained mixing radiation of ultrafast light sources to generate femtosecond pulses across 520.5 to 742.5 nm region is observed. SFG spectrum from single-pass cross-correlation intensity over such visible range is showed. The SFG wavelengths as a function of tunable wavelength idler OPA agrees with the expectations of parametric conversion condition and open the door to practical multi-beam or multi-color sum-frequency generators.

The broad bean plant contains L-DOPA, a compound that is essential for patients with Parkin-son’s disease. However, little has been reported on other broad bean compounds that have bene-ficial effects on health. The objective was to evaluate plants of four Mexican broad bean varieties to determine the content and yield of total phenolic compounds (TPC), total flavonoids (TF), and L-DOPA, as well as to analyze the flavonoid profile and antioxidant (AA) and anti-inflammatory (AANTI) activity in vitro. Broad bean seeds were sown in the field and plants were harvested 20 days after emergence. The analyses were performed with visible UV spectrophotometry and HPLC. The variety José María produced the highest yield of TPC (9.30 g m-2), TF (8.08 g m-2) and L-DOPA (5.64 g m-2) per unit of area. The highest yields per plant were obtained with the Rojita variety: TPC (0.25 g plant-1), TF (0.21 g plant-1) and L-DOPA (0.17 g plant-1). This variety also had the highest antioxidant (CI50= 87.68 µg mL-¹) and anti-inflammatory (CI50= 74.40 mg mL-1) activi-ty, which was attributed to the L-DOPA compounds and to rutin and isoorientins, respectively. The flavonoid profile revealed the presence of rutin and isoorientins, which had not been previ-ously detected in the broad bean plant.

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.

As the most commonly used hydrogel material in contact lenses, the amount of water in a lens affects its optical properties and comfort for the wearer. Therefore, an important challenge is to determine the safety and efficacy of contact lenses by accurately and non-destructively measuring the water content in real time. In this study, we demonstrate the accurate detection of water content in hydrogel contact lenses using a high-precision ATR format in a portable terahertz time-domain spectroscopy system. The technique can resolve small variations in the dielectric constant in solution, which is difficult to achieve with traditional transmission and reflection measurement modes. Information is obtained from the interaction between the sample and the swift waves propagating along the prism surface. The swift waves can excite longitudinal modes that are not directly accessible by conventional techniques. It is worth noting that the reference wave can be measured by removing the sample without disturbing the optical path. We also enhance the plasma effect at the interface with the hydrogel by using PVDF dielectric films of different polarities. We observed that the water content and refractive index changes in the ATR mode show different response patterns for nonpoled PVDF and poled PVDF membranes. This suggests that reflection and relative phase can be accurately evaluated in the THz-ATR technique, resulting in an accurate method for determining complex dielectric constants in the reflection geometry. This will allow accurate measurement of both surface and in vivo water content in hydrogels in the future and is a potential technical route for application in bioaqueous tissue measurements.

COVID-19, caused by SARS-CoV-2, was first identified in China in 2019. The exact origin of the disease remains uncertain, with theories suggesting it may have emerged from animals or accidentally leaked from a research laboratory. If the hypothesis that COVID-19 originated from a research laboratory is accurate, it is crucial to investigate potential pathways for pathogens to escape from biocontainment research animal facilities (BRAFs). We examine key biosafety issues associated with BRAFs, including inadequate decontamination procedures for water and experimental samples, handling high biosafety level pathogens in lower level laboratories, risks of animal bites and sharps injuries, contamination of bedding and enrichment materials, and improper management and transportation of biohazard samples. Additionally, we discuss the role of veterinarians in African research animal facilities and the challenges they encounter in maintaining biocontainment standards. We emphasize the importance of routine monitoring of effluent water to detect possible disease outbreaks. We recommend a thorough investigation of the COVID-19 pandemic to identify potential sources of pathogen release from BRAFs, which could serve as hotspots for future disease outbreaks. Findings from such investigations will inform the development of policies aimed at safeguarding human populations from future pandemics and preventing BRAFs from becoming sources of infectious disease outbreaks.

The diagnosis and treatment of autoimmune diseases are major challenges. Their signs, symptoms, and their clinical severity change throughout the course of the disease. The available treatments for these conditions do not result in complete remission, and their long-term use generates several side effects. The main challenges in this field are the development of more sensitive diagnostic tools, and effective treatments. Studies in patients and animal models reported alterations in monocyte phenotype, activation, and function. These cells play an essential role in the pathogenesis of chronic inflammatory states and have become a target for extracorporeal monitoring and specific intervention. Nanoparticles (NPs) are ultrafine particles that can be used as contrast agents in diagnostic imaging techniques to detect specific cells in inflammatory infiltrates in tissues that are not easily accessible by biopsy. In addition, NPs can be designed to deliver drugs to a cell population or tissue. This review describes several experimental pieces of evidence demonstrating that monocytes and macrophages can specifically uptake various types of NPs, thus becoming detectable in vivo by magnetic resonance imaging and susceptible to be modulated by therapeutic agents. Hence, nanoparticles targeting mononuclear phagocytes represent promising tools for diagnosing and treatment.

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

We summarize the results on electron transport in hybrid superconducting S/B/S' mesa-structure consisted of the oxide epitaxial S/B heterostructures, where S is the cuprate YBa2Cu3O 7-x superconductor, B – an interlayer with the spin dependent characteristics, and S’ is the Nb top superconductor. Josephson effect was observed manifested in appearance of oscillating Shapiro steps amplitudes with microwave signal power due to synchronization of junction self-generation of electromagnetic radiation and the external microwave probe signal. Triplet component of superconducting correlations emerged when the interlayer comprised two magnetic materials SrRuO3 and La0.7Sr0.3MnO3 with non-collinear magnetizations as well in the case of antiferromagnetic insulator Sr2IrO4 characterized by strong spin-orbit interaction. Thickness of the interlayer in the both cases considerably exceeded the coherence length of the magnetic spin active interlayer hinting on appearance of long-range proximity effect and spin-triplet superconducting current. Magnetic field dependences measured at dc, and the existence of the second harmonic in superconducting current–phase relation revealed by measurements at microwave frequencies will be discussed.

School-aged children may benefit from education interventions focused on healthy eating and physical activity to improve their quality of life. This article aims to review scientific evidence on food and nutrition education (FNE) in Spanish-speaking countries for the prevention of overweight and obesity in school-aged children (6-12 y). Articles were searched between April and August 2021. The searches were conducted using MEDLINE, Google Scholar, and SciELO. The primary search for articles focused on the experience of FNE interventions in Spanish-speaking countries. Overall, 518 articles were found and 33 studies were eligible for data extraction. Forty-two percent of the studies had a focus on FNE and 64% were focused on describing the eating habits of schoolchildren. Nutritional assessments (anthropometric) were found frequently with 91% and 30% of the studies focused on physical activity. All interventions focused on preventing or reducing overweight and obesity in school-age children. Educational, cognitive, dietary, and physical activity practices were described, whit being educational the most frequent intervention. Interventions reported positive effects of FNE interventions to improve knowledge and practices of healthy lifestyles in school-age children.

This project focuses on using machine learning classification algorithms to determine whether two people are 6 feet apart or not. Two Raspberry Pis were used simulate smart phones. RSSI values of the Bluetooth beacons transmitted between the Raspberry Pis were collected and recorded to train the classifier. The Gaussian Support Vector Machine Classifer yielded the highest testing accuracy of 79.670 and the Decision Tree Classifier yielded the highest AUC of 0.80.

Microbial Fuel Cells (MFCs) representing a promising technology for the extract of energy and resources through wastewater and it also offer an economic solution to the problem of environment effluent and energy crisis in near future. The advance device is rather appealing, due its potential benefits, its practical application is, however hindered by several drawbacks, such an internally competing microbial reaction, and low power generation. This report is an endeavor to address various design connected to the MFCs application to wastewater treatment, in particular cost effective bioelectricity from waste water are reviewed and discussed with a multidisciplinary approach. The conclusions drawn herein can be of practical interest to all new researchers dealing with effluent wastewater treatment using MFCs.

The agro-biodiversity present in agro-ecosystems is fundamental in guaranteeing sustainability and resilience. However, there are very few proposals for evaluating it and, even less, ones that include indicators to analyze the influence of the structural and spatial configuration of a landscape in order to favor agro-biodiversity connectivity to productive systems, management and conservation practices, and the producer (farmer)’s perceptions, awareness and ability to favor it on his farm. The Main Agro-ecological Structure MAS is redefined as an environmental agro-biodiversity index. New indicators are established for a total of 10 criteria and 29 indicators of systems that describe the agro-biodiversity of agro-ecosystems. Methodologies for its evaluation are also described, and the possibility of adapting certain indicators according to the ecological and cultural contexts where the farms are located is discussed.

Hearing loss stands as the most prevalent sensory deficit among humans, posing a significant global health challenge. Projections indicate that by 2050, approximately 10% of the world's population will grapple with disabling hearing impairment. While approximately half of these cases have a genetic etiology, traditional interventions such as hearing aids and cochlear implants do not completely restore normal hearing. The absence of biological treatment has prompted significant efforts in recent years, with a strong focus on gene therapy to address hereditary hearing loss. Although several studies have exhibited promising recovery of common forms of genetic deafness in mouse models, existing challenges must be overcome to make gene therapy applicable in the near future. Herein, we summarize the primary gene therapy strategies employed over past years, provide an overview of the recent achievements in the preclinical studies for genetic hearing loss, and outline the current key obstacles to cochlear gene therapy.

Background: The Davidson Airway Function & Nasal Evaluation (DAFNE) Scoring System was developed as an intuitive and research-based scoring system that could be validated through beta testing and easily introduced to healthcare providers of several subspecialties who treat nasal obstruction and breathing disorders (MDs, PAs, PTs, APRNs, DDSs, and DCs). This scoring system was shown to increase the knowledge of airway function, nasal measurement parameters, and identification of proper treatment options for sleep and breathing disorders. The basis for the DAFNE score was developed from a systematic review of nasal measurement data. Methods: Electronic searches of PubMed, MEDLINE, EMBASE Cochrane Library, and Scopus of publications between 1988-2022 were used to identify studies validating nasal function measurement parameters to create the algorithm for the DAFNE Score™. The systematic review was accomplished using the 2020 ‘Preferred Reporting Items for Systematic Reviews’ (PRISMA) guidelines. Results: Twenty studies met the inclusion criteria for systematic review. Primary outcomes measurements demonstrated reliability, repeatability and validity of the DAFNE measurement technologies, data and output. Conclusions: The data analysis and systematic review uncovered a need and framework to develop and validate a web-based software algorithm for global access to improve the understanding of data interpretation of nasal measurements from three nasal measurement technologies. DAFNE Scoring should be used as an adjunct tool in routine clinical practice and research to further understand the technology data output and how to collaborate with other healthcare providers to improve patient outcomes.

Ovarian cancer is the most lethal gynecological malignancy. Poor overall survival, particularly for patients with high grade serous (HGS) ovarian cancer, are often attributed to late stage at diagnosis and relapse following chemotherapy. HGS ovarian cancer is a heterogenous disease in that few genes are consistently mutated between patients. Additionally, HGS ovarian cancer is characterized by high genomic instability. For these reasons personalized approaches may be necessary for effective treatment and cure. Understanding the molecular mechanisms that contribute to tumor metastasis and chemoresistance are essential to improve survival rates. One favored model for tumor metastasis and chemoresistance is the cancer stem cell (CSC) model. CSCs are cells with enhanced self-renewal properties that are enriched following chemotherapy. Elimination of this cell population is thought to be a mechanism to increase therapeutic response. Therefore, accurate identification of stem cell populations that are most clinically relevant is necessary. While many CSC identifiers (ALDH, OCT4, CD133, and side population) have been established, it is still not clear which population(s) will be most beneficial to targeted in patients. Therefore, there is a critical need to characterize CSCs with reliable markers and find their weaknesses that will make the CSCs amenable to therapy. Many signaling pathways are implicated for their roles in CSC initiation and maintenance. Therapeutically targeting pathways needed for CSC initiation or maintenance may be an effective way of treating HGS ovarian cancer patients. In conclusion, the prognosis for HGS ovarian cancer may be improved by combining CSC phenotyping with targeted therapies for pathways involved in CSC maintenance.

The large quantity of information retrieved from communities, public data repositories, web pages, or data mining can be sparsed and poorly classified. This work shows how to employ unsupervised classification algorithms such as K-means proper to classify user reviews into their closest category, forming a balanced data set. Moreover, we found that the text vectorization technique significantly impacts the clustering formation, comparing TF-IDF and Word2Vec. The value for mapping a cluster with movie genre was 81.34% ± 20.48 of the cases when the TF-IDF was applied, whereas Word2Vec only yielded a 53.51% ± 24.1. In addition, we highlight the impact of the removal of stop-words. Thus, we detected that pre-compiled lists are not the best method to remove stop-words before clustering because there is much ambiguity, centroids are poorly separated, and only 57% of clusters could match a movie genre. Thus, our proposed approach achieved a 94% of accuracy. After analyzing the classifiers’ results, we appreciated a similar effect when divided by the stop-words method removal. Statistically significant changes were observed, especially in precision metric and Jaccard scores in both classifiers, using custom-generated stop lists rather than pre-compiled ones. Reclassifying sparse data is strongly recommended as using custom-generated stop lists.

Fall armyworm (FAW), Spodoptera frugiperda, has been causing significant crop losses and has now become the most economically important pest of corn globally. With the challenges arising from the extensive use of synthetic chemicals such as reports that FAW gained resistance to various insecticides, researchers are developing environmentally sound control measures to address these issues. An example is the application of the RNA interference in managing FAW populations. RNA interference is a biological process where dsRNA molecules silence specific gene of interest. Here, dsRNA fragments were generated to target Cytochrome P450 monooxygenases CYP321A7 and CYP321A8 in FAW. Mortality and phenotypic effects of RNAi-mediated knockdown of essential genes of target CYP450s through RNAi in FAW were analyzed. Results showed that RNA in vitro transcription yielded ~14 μg/μL of dsCYP321A7 and dsCYP321A8. The mortality rate of dsCYP321A7- and dsCYP321A8-fed larvae following exposure to insecticide with dual active ingredient of Chlorantraniliprole and Thiamethoxam increased by 90% and 80%, respectively as compared to dsGFP-fed larvae with 40% at 2 days post insecticide exposure. This study provided evidence for the potential of RNAi for FAW management strategies particularly for insecticide-resistant populations, including the potential for biopesticide development.

Abstract: Background: The diagnosis of nasal airway disorders relies on questionnaires, subjective data, and objective data. Interpretation of objective data obtained from measurement technology is not well understood by providers and researchers who use the equipment to test nasal airway function, justifying the need to cre-ate a new clinical tool. The Davidson Airway Function & Nasal Evaluation (DAFNE) Scoring System is a web-based scoring system that allows healthcare providers (MDs, PAs, PTs, APRNs, DMDs, DDSs, SLPs, and DCs) and researchers who treat nasal obstruction and breathing disorders to make more accurate diagnostic decisions, select the appropriate treatment for individualized patient care, monitor treatment progression and outcomes, and show how to approach a collaborative care model with other healthcare professionals. The current technologies, such as 4-phase rhinomanometry, use a simple approach that relies on a measurement tracing intersecting a color-coded y-axis on a four-quadrant graph with diagnostic numeric data output de-scribing nasal airflow and resistance. This is a good source of biofeedback demonstrating abnormal nasal breathing patterns but lacks interpretation guidelines to describe the severity of disease. The more sophisti-cated proprietary DAFNE approach uses multiple parameters which include airflow restriction, speed, vol-ume, and patient characteristics to identify patients’ disease progression much more accurately. Additionally, it explains how to segregate patients into appropriate treatment options which minimizes risks and compli-cations associated with sleep and breathing disorders while improving patient outcomes. Methods: Electronic searches of PubMed, MEDLINE, EMBASE Cochrane Library, and Scopus of publications between 1988-2022 were necessary to identify studies which determined the ranges of nasal function measurement parameters among three airway measurement technologies used in writing the DAFNE Score algorithm. The performance of DAFNE was evaluated compared to the research data and patient demographics used in previous studies. Results: By using primary outcome measurements from the literature, we were able to create a reliable, re-peatable, and validated tool to facilitate patient identification, treatment stratification, and collaboration for sleep and nasal breathing dysfunction. Subsequently, we found DAFNE could be used to identify the appro-priateness of a sleep study. Conclusions: DAFNE Scoring System has demonstrated the ability to detect high risk patients in the pediatric and adult populations susceptible of sleep apnea and breathing dysfunction needing a sleep study and treatment to improve nasal airway function and sleep. DAFNE Scoring System should be used as an adjunct tool in routine clinical practice and research to further understand the technol-ogy data output, identify patients at risk, stratify treatment options, progress, and stabilization after treatment, and how to collaborate with other healthcare providers to improve patient outcomes.

Spike-and-wave discharge (SWD) pattern detection in electroencephalography (EEG) signals is a key signal processing problem. It is particularly important for overcoming time-consuming, difficult, and error-prone manual analysis of long-term EEG recordings. This paper presents a new SWD method with a low computational complexity that can be easily trained with data from standard medical protocols. Precisely, EEG signals are divided into time segments for which the Morlet 1-D decomposition is applied. The generalized Gaussian distribution (GGD) statistical model is fitted to the resulting wavelet coefficients. A k-nearest neighbors (k-NN) self-supervised classifier is trained using the GGD parameters to detect the spike-and-wave pattern. Experiments were conducted using 106 spike-and-wave signals and 106 non-spike-and-wave signals for training and another 96 annotated EEG segments from six human subjects for testing. The proposed SWD classification methodology achieved 95 % sensitivity (True positive rate), 87% specificity (True Negative Rate), and 92% accuracy. These results set the path to new research to study causes underlying the so-called absence epilepsy in long-term EEG recordings.

The cornea is an avascular tissue which has attracted much attention by the uniqueness of its anatomical characteristics, it has, in proportion, an enormous size, in relation to the number of vessels, because on average few cells in the organism are away more than 30 microns of a blood vessel. However, the cornea, with a diameter of between 11 and 12 mm, is a unique example. It has been tried to explain the notable absence of blood vessels in the cornea, arguing that corneal tissues are able to take oxygen directly from the air. In this article we are explaining that based on the physicochemical characteristics of molecular oxygen and the cell membrane, cytoplasm, water, and cellular metabolism, it is not possible that epithelial corneal cells directly take oxygen from the air, instead, corneal cells have molecules that can dissociate the water molecules thereby these cells, like any other eukaryotic cells, take the oxygen from the intracell water, like plants.

A multiscale mathematical model is proposed seeking to study the propagation dynamics of the Human Immunodeficiency Virus (HIV) in a group of young people between 15 and 24 years of age, through sexual contact without protection, considering the use of antiretroviral therapy (ART) and therapeutic failure. The model consists in a scale-free complex network that follows a power law, coupled with the immunological dynamics of each individual, that is, it considers the infection by the virus in the immune system of each HIV carrier, through a system of non-linear differential equations that govern the infection’s behavior in the immune system. Propagation of the virus in the network is modelled by taking into account information from the immunological status of each person. The study found that for a population to have high HIV prevalence, it is not necessary at the beginning of the simulation time for the virus to propagate rapidly. In addition, the study proves that with a higher number of sexual partners, there will be greater prevalence of HIV in the population and that the use of ART helps to control the propagation of the infection in the population. As an interesting result, it was also found that there is a higher number of HIV carriers who abandon ART than those who have access to it.

The Omicron variant of SARS-CoV-2 is the latest pandemic lineage causing COVID-19. Despite having a vaccination rate ≥ 85% Ecuador recorded a high incidence of Omicron from December 2021 to March 2022. Since Omicron emerged it is evolving into multiple sublineages with distinct prevalence in different regions. In this work, we use all Omicron sequences from Ecuador available at GISAID until March 2022 and the software Nextclade and Pangolin to identify which lineages circulate in this country. We detected 12 different sublineages (BA.1, BA.1.1, BA.1.1.1, BA.1.1.14, BA.1.1.2, BA.1.14, BA.1.15, BA.1.16, BA.1.17, BA.1.6, BA.2, BA.2.3), which has been reported in Africa, America, Europe, and Asia suggesting multiple introduction events. Sublineages BA.1.1 and BA.1 were the most prevalent. Genomic surveillance must continue to evaluate the dynamic of current sublineages, early introduction of new ones and vaccine efficacy against evolving SARS-CoV-2.

High pathogenicity avian influenza (HPAI) H5N1 clade 2.3.4.4b continues to have a substantial impact on wildlife, globally. A recent study has described the putative detection of HPAI in clinically healthy penguins, and those which were fitted with satellite tags reportedly engaged in apparently normal foraging behaviour in the months following sample collection. Herein we investigate the diagnostic approach utilised, and reveal that while the authors likely did detect subtype H5 influenza A virus, the most parsimonious conclusion is that they detected low pathogenicity H5 rather than HPAI H5N1. In response, we have provided an overview key considerations when selecting a diagnostic and outline published diagnostic assays that should be considered for future studies.

Several sun models suggest the radioactive balance where the concentration of greenhouse gases and the albedo effect are related to the Earth's surface temperature. There is a considerable increment of greenhouse gases due to anthropogenic activities. Climate change correlates with this alteration in the atmosphere and an increase in surface temperature. Efficient forecasting of climate change and its impacts of 1.5°C global warming above pre-industrial levels could be helpful to respond to the threat of c.c. and develop sustainably. Many studies have predicted the temperature change in the coming years. The global community has to create a model that can realize good predictions to ensure the best way to deal with the warming. Thus, we propose a finite-time thermodynamic (FTT) approach in the present work. The FTT can solve problems such as the faint young sun paradox. In addition, we use different machine learning models to evaluate our method and compare the experimental prediction and results.

An especially important species in southern Brazil, yerba mate (Ilex paraguariensis) is traditionally consumed as tea, chimarrão and tererê. Yerba mate consumption has been stimulated by scientific discoveries that have identified high concentrations of bioactive compounds and their health benefits. There are no studies or scientific evidence to certify or guarantee stability of these compounds’ concentrations during different years in the same plants. We were interested in quantifying caffeine, theobromine, total phenolic compounds and proteins concentrations in leaves of yerba mate genotypes and their stability in the same plants over four consecutive years. Mature leaves from yerba mate genotypes selected on a provenance and progenies trial were collected in August of 2015, 2016, 2017 and 2018. Methylxanthines (caffeine and theobromine), total phenolic compounds and total protein contents were quantified. Our results indicate large variations between genotypes regarding caffeine (0.035 to 2.385 g 100 g^-1), theobromine (0.0004 to 1.772 g 100 g^-1), total phenolic compounds (7.028 to 9.424 g 100 g^-1) and proteins (10.39 to 16.58 g 100 g^-1) contents, and also high stability of those compounds over the four evaluated years. A great variation of the studied bioactive compounds in different Ilex paraguariensis genotypes was found and its stability over four consecutive years was showed.

Background: The electroretinogram is a clinical test used to assess the function of the photoreceptors and retinal circuits of various cells in the eye, with the recorded waveform being the result of the summated response of neural generators across the retina. Methods: The present investigation involved an analysis of the electroretinogram waveform in both the time and time-frequency domain through the utilization of the discrete wavelet transform and continuous wavelet transform techniques. The primary aim of this study was to monitor and evaluate the effects of treatment in a New Zealand rabbit model of endophthalmitis via electroretinogram waveform analysis and to compare these with normal human electroretinograms Results: The wavelet scalograms were analyzed using various mother wavelets, including the Daubechies, Ricker, Wavelet Biorthogonal 3.1 (bior3.1), Morlet, Haar, and Gaussian wavelets. Distinctive variances were identified in the wavelet scalograms between rabbit and human electroretinograms. The wavelet scalograms in the rabbit model of endophthalmitis showed recovery with treatment in parallel with the time -domain features. Conclusions: The study compared Adult, Child, and Rabbit electroretinogram responses using DWT and CWT, finding that Adult signals had higher power than Child signals, and Rabbit signals showed differences in a-wave and b-wave depending on the type of response tested, while Haar Wavelet was found to be superior in visualizing frequency components in electrophysiological signals in following the treatment of endophthalmitis and may give additional outcome measures for the management of retinal disease.

1960s Europe saw a large number of residential neighborhoods built to house those migrating from the countryside. Today, more than 50 years later, these neighborhoods suffer high levels of functional, social, and technical obsolescence. In response to this, University of Seville developed the Aura Strategy as an intervention methodology to find global solutions to issues in outdated neighborhoods. To provide visibility to this aspect of the Aura strategy, the retrofit proposal presented in this article provides a solution to improve the roofing of buildings in a case study neighborhood (Polígono de San Pablo, Seville) and an analysis of the results in terms of energy and financial savings for local residents. The results show that for a population of roughly 18,000 (in 2018), net savings, including energy and retrofitting costs, ranging from nearly 6.5 to over 8.6 million can be made over the 20-year life cycle span. Likewise, the results obtained on the reduction of thermal loads indicate a 72% decrease in energy consumption, equivalent to a saving of close to 4,500 tons of greenhouse gas emissions for the district and the entire life cycle time period, with the consequent benefits on the impact on air quality and and the fight against climate change. climate change.

The study was carried out in zone 7 of Ecuador, in ecosystems of the Southern Montane Evergreen Forest of the Eastern Cordillera of the Andes that goes from 2200 to 3000 masl. In the Evergreen Seasonal Lower Montane Forest of Catamayo-Alamor, which ranges from 1600-2000 meters above sea level and finally in the Semideciduous Foot Montane Forest of Catamayo-Alamor, which ranges from 400-1600 meters above sea level. The objective was to know the occurrence, structure and abundance of J. neotropica. The investigation consisted of collecting secondary information on the occurrence of the species, to later verify it in situ. Six sites with areas ≥ 0.5 hectares were identified, four in the province of Loja and two in the province of Zamora Chinchipe. Regarding the structure, it was determined that there are significant statistical differences as well as in the dasometric variables between one site and another, presenting better growths El Tundo with average values in DAP(cm)= 45.16; G(m2) = 1.41; HT(m)= 19.22; HC(m)= 13; VC(m3) = 3.55; VT(m3) = 5.22. Regarding the Morisita index, the species presents adistribution pattern >1. Regarding abundance, it was determined that Algeria presented a maximum of 297 (ind/ha), and La Victoria 46 (ind/ha) with a minimum.

We study the effect of oblique illumination on the functioning of a plasmonic nanoantenna for chiral light. The antenna is designed to receive a structured beam of light and produce a nanosized near-field distribution that possesses non-zero orbital angular momentum. The design consists of metal (gold) micro-rods laid on a dielectric surface and is compatible with well-developed nanofabrication techniques. Experimental arrangements often require such an antenna to operate in a tilted geometry, where input light is incident on the antenna at an oblique angle. We analyze the limitations that the angled illumination imposes and discuss approaches to mitigate these limitations. Through our numerical simulations, we find that tilt angles larger than 30 degrees require modifications to the antenna design. Our analysis guides current and future experimental configurations to pushing the limits of resolution and sensitivity.

This study investigated the presence and characteristics of Juglans neotropica in three ecosystems in Southern Ecuador: Montane Evergreen Forest, Evergreen Seasonal Lower Montane Forest, and Semideciduous Foot Montane Forest. The main focus was on the species' multipurpose nature as both a fruit and timber source. Six study sites, totaling at least 0.5 hectares each, were established, with four in Loja province and two in Zamora Chinchipe province.The results showed significant differences in dendrometric variables across the sites, with the most favorable growth recorded in The Tundo, where trees exhibited an average diameter at breast height (DBH) of 45.16 cm, basal area (G) of 1.41 m2, total height (TH) of 19.22 m, canopy height (CH) of 13 m, cubic volume (CV) of 3.55 m3, and total volume (TV) of 5.22 m3. The species displayed a clumped distribution pattern, as indicated by a Morisita index greater than 1. Regarding abundance, the highest density of 297 trees per hectare was found in Argelia, while Victoria had the lowest density of 46 trees per hectare. This research highlights the importance of Juglans neotropica as a multipurpose species, providing both valuable fruits and wood resources in the studied ecosystems of Southern Ecuador.

This study comprehensively evaluates the DNA/RNA Defend Pro (DRDP) sample collection buffer designed to inactivate and stabilize patient samples. The primary objectives encompassed assessing DRDP's efficacy in ensuring sample stability, facilitating extraction-free polymerase chain reaction (PCR), and ensuring compatibility with rapid antigen testing.Ninety-five diagnostic nasopharyngeal swab samples tested for influenza A/B, RSV A/B, and/or SARS-CoV-2 were diluted 1/10 with DRDP and anonymized. Stability testing involved incubating 31 positive samples at 4 °C, 20 °C, and 37 °C for 7 days, with regular extraction-free nucleic acid amplification testing (NAAT).Results demonstrated that DRDP guaranteed viral RNA stability at all temperatures for influenza, SARS-CoV-2 and RSV showing stability up to 7 days at 4 °C. DRDP-diluted samples exhibited robust compatibility with direct PCR, as 72 out of 88 samples positive for cobas Liat also tested positive for direct PCR. Non-concordant results could be explained by the 200-fold lower input in the extraction-free NAAT.Compared to NAAT, rapid antigen testing demonstrated lower sensitivity, as expected, while maintaining perfect specificity. Clear cutoffs between positive and negative rapid antigen testing results were observed in both cobas Liat and direct PCR analyses, validating DRDP's compatibility with these techniques. In conclusion, DRDP is an effective stabilizing medium compatible with direct PCR and rapid antigen testing and shows great potential for optimizing diagnostic processes, particularly in resource-limited or time-sensitive scenarios.

Alfalfa (Medicago sativa L.) is the most cultivated forage legume around the world. Under a variety of growing conditions, forage yield in alfalfa is stymied by biotic and abiotic stresses including heat, salt, drought, and disease. Given the sessile nature of plants, they use strategies such as differential gene expression to respond to environmental cues. Transcription factors control the expression of genes that contribute to or enable tolerance and survival during periods of stress. Basic-leucine zipper (bZIP) transcription factors have been demonstrated to play a critical role in regulating plant growth and development as well as mediate the responses to abiotic stress in several species, including Arabidopsis thaliana, Oryza sativa, Lotus japonicus, and Medicago truncatula. However, there is little information about bZIP transcription factors in cultivated alfalfa. In the present study, 237 bZIP genes were identified in alfalfa from publicly available sequencing data. Multiple sequence alignments showed the presence of intact bZIP motifs in the identified sequences. Based on previous phylogenetic analyses in Arabidopsis thaliana, alfalfa bZIPs were similarly divided and fell into 10 groups. The physicochemical properties, motif analysis, and phylogenetic study of the alfalfa bZIPs revealed high specificity within groups. The differential expression of alfalfa bZIPs in a suite of tissues indicates that particular bZIP genes are specifically expressed at different developmental stages in alfalfa. Similarly, expression analysis in response to ABA, cold, drought, and salt stresses, indicates that a subset of bZIP genes are also differentially expressed and likely play a role in abiotic stress signaling and/or tolerance. These expression patterns were further verified by qRT-PCR. However, further functional characterization of bZIP transcription factors in alfalfa will help illuminate the role they play in stress tolerance mechanisms in legumes and facilitate the molecular breeding of stress tolerance in alfalfa.

In this research, the photocatalytic degradation of cypermethrin using Fe-TiO2 nanoparticles supported in a biomaterial was evaluated. The nanoparticles of TiO2 were synthesized by the green chemistry method assisted by ultrasound and doped by chemical impregnation using molar ratios Fe:Ti of 0, 0.05, 0.075 and 0.1, to make efficient use of direct sunlight (λ>310 nm). All nanoparticles were immobilized on the surface of spathe of coconut palm (Cocos nucifera). The degradation was carried out at room temperature and natural pH in a flat plate solar reactor, on which the composite material was subjected. The concentration of cypermethrin was determined after 12000 J/m2 of accumulated radiation from GC-MS and the resulting material was characterized by Scanning electron microscopy (SEM), Transmission electron microscopy (TEM) image and selected area electron diffraction (SAED), Fourier transform infrared spectroscopy (FTIR), UV-Vis spectrophotometry of diffuse reflectance and BET surface area BET surface area. The best results were achieved with the use of Degussa TiO2 P-25, Fe:Ti=0 and Fe:Ti=0.05 in suspension, with percentages of degradation of cypermethrin of 99.84, 99.62, and 100%, respectively. However, the materials supported on the biomaterial of coconut, they allowed to reach degradation percentages higher than 80% with the advantage that it minimizes operating costs, since they are not necessary filtering or centrifuging processes to separate the catalyst.

Children with central nervous system (CNS) malignancies often suffer from high symptom burden and risk of death. Pediatric palliative care is a medical specialty, provided by an interdisciplinary team, which focuses on enhancing quality of life and minimizing suffering for children with life-threatening or life-limiting disease, and their families. Primary palliative care skills which include basic symptom management, facilitation of goals-of-care discussions, and transition to hospice can and should be developed by all providers of neuro-oncology care. This chapter will review the fundamentals of providing primary palliative care

Resilience has emerged as a buzzword among researchers and practitioners. However, despite its popularity, there has been little progress in moving it from an elaborate metaphor describing an idyllic state of the system to a tool for planning and managing adaptation. While case study research is rich with examples of systems that have proven to be resilient or are striving to develop resilience, there is no defined approach that operationalises concepts described in the literature into the planning process. This paper helps close this gap by illustrating how facilitated modelling can be used for resilience planning in socio-ecological systems. The paper summarizes our experience using facilitated system dynamics to inform a model-based discussion of food security resilience to climate change in Guatemala. We identify at least three positive outcomes from the intervention, which a) helped to build consensus about the meaning of resilience, b) improved stakeholders understanding of adaptation and c) outlined potential policies to enhance resilience.

The extrusion of food for human and animal consumption is a unit operation that includes mixing, shearing and force to the materials related to the rheological properties of the materials in the extruder. The present work aims to study the rheological behavior of an extruded fish diet incorporating hydrolyzed protein flour processed by extrusion. The measurement was carried out online with a slit die rheometer, defining the rheological models and parameters that fit the process. During the extrusion process, the raw materials used were hydrolyzed protein meal, fish meal and cassava starch. For the results, the evaluated treatments were adjusted to the Power Law, where an increase in the shear rate decreases the viscosity of the material, corresponding to a pseudoplastic behavior. The incorporation of hydrolyzed protein flour presented a significant effect on the value of n and Klp, increasing the viscosity with the increase in the percentage of inclusion of HPH. The models obtained for the prediction of the viscosity are adjusted to the changes in shear rate, temperature and humidity of the system.

The process of testing software is examining the artifacts and behavior of the software under test by validating and verifying it. Testing can provide valuable information about the software. Given an input to the system, there is a challenge of distinguishing correct from potentially incorrect behavior, which is the test oracle problem. Although the combinatorial testing approach can effectively reduce the number of test cases, the manual inspection of the outputs is still required. In this paper, we propose an approach to automatically classify the return pages with conducting combinatorial testing based on page similarities and hierarchical clustering, by which potential output anomalies can be identified. In the experiment, we apply our approach to a real-world e-commerce website, an anomaly can be found with the visualization of the clustering hierarchy, which suggests the potential of the applicability of the approach.

Human endogenous retroviruses (HERVs) are ancient retroviral DNA sequences established into germline. They contain regulatory elements and encoded proteins few of which may provide benefits to hosts when co-opted as cellular genes. Their tight regulation is mainly achieved by epigenetic mechanisms which can be altered by environmental factors, e.g. viral infections, leading to HERV activation. Aberrant expression of HERVs associates with neurological disease, such as multiple sclerosis (MS) or amyotrophic lateral sclerosis (ALS), inflammatory processes and neurodegeneration. This review summarizes recent advances on the epigenetic mechanisms controlling HERV expression and the pathogenic effects triggered by HERV derepression. The article ends describing new promising therapies targeting HERV elements, one of which, temelimab, has completed phase II trials with encouraging results in treating MS. The information gathered here may turn helpful in the design of new strategies to unveil epigenetic failures behind HERV-triggered disease, opening new possibilities for druggable targets and/or for extending the use of temelimab to treat other associated diseases.

Chronic Traumatic Encephalopathy (CTE) is a neurodegenerative disease consistently associated with repetitive traumatic brain injuries (TBIs), which makes multiple professions, such as contact sports athletes, especially susceptible to its onset. There are currently no approved biomarkers to diagnose CTE, thus it can only be confirmed through a post-mortem brain autopsy. Several imaging and cerebrospinal fluid biomarkers have shown promise in the diagnosis. However, blood-based biomarkers can be more easily obtained and quantified, increasing their clinical feasibility and potential for prophylactic use. This article aimed to comprehensively review the studies into potential blood-based biomarkers of CTE, discussing common themes and limitations as well as suggesting future research directions. While the interest in blood-based biomarkers of CTE has recently increased, the research is still in its early stages. The main issue for many proposed biomarkers is their lack of selectivity for CTE. However, several molecules, such as tau phosphorylated on different epitopes, were able to discern CTE from different neurodegenerative diseases. Further, results from studies of exosomal biomarkers suggest that exosomes are a promising source of biomarkers reflective of the internal environment of the brain. Nonetheless, more longitudinal studies combining imaging, neurobehavioral and biochemical approaches are warranted to establish robust biomarkers of CTE.

A two scalar field model that incorporates non Riemannian Measures of integration or usually called Two Measures Theory (TMT) is introduced, in order to unify the early and present universe. In the Einstein frame, a K-essence is generated and as a consequence for the early universe, we can have an Inflation for the very early universe and then, after inflation, an early dark energy period and a late dark energy period for the present universe dark, both dark energy epochs have a consistent generation of dark energy (DE), dark matter (DM) and stiff matter. This is obtained when the scale invariance is introduced and then is spontaneously broken from the integration of the degrees of freedom associated with the modified measures. The resulting effective potentials and K-essence in the Einstein frame produce the three flat regions corresponding to the different epochs mentioned before. For the first flat region, we can associate an inflationary universe. Also assuming this first plateau, we study the inflation in the framework of the slow-roll approximation. In this scenario under the slow roll approximation, we obtain a linear combination that is a constant. The corresponding cosmological perturbations in our model are determined and we also obtain the different constraints on the parameter-space from the Planck data. The slow roll approximation can be arranged so that the transition from inflation to the next flat region can be achieved without problems. In the following two flat regions, in addition to the inflation phase, representing the Early Dark Energy and Late Dark Energy Periods, with DE and also the DM, do not need to be introduced separately, they are instead a result of a K-essence induced by the multi measures, multi field theory. Therefore the scalars generate both the DE and the DM . Also a stiff matter component is automatically generated from the K-essence theory from two scalar fields. From the perturbative analysis associated to the perturbation solution of background, we find a correlation between the two scalars. Besides, we obtain that our model during the dark epoch has a behaviour of tracking freezing mode

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

Cell-based therapy in regenerative medicine is a powerful tool that can be used both to restore various cell lost in a wide range of human disorders, and in renewal processes. Stem cells show promise for universal use in clinical medicine, potentially enabling the regeneration of numerous organs and tissues in the human body. This is possible due to their self-renewal capacity, and their ability to differentiate into various cell types. To date, pluripotent stem cells seem to be the most promising regeneration tool. Recently, a novel stem cell niche, called multilineage-differentiating stress-enduring (Muse) cells, is emerging. These cells are of particular interest because they are pluripotent and are found in adult human mesenchymal tissues. One of their most significant features is that they can produce cells representative of all the three germ layers. Furthermore, they can be easily harvested from fat, and isolated from the mesenchymal stem cells. This makes them very promising, allowing autologous treatments and avoiding the problems of rejection, typical of transplants. Muse cells have recently been employed, with encouraging results, in numerous preclinical studies, performed to test their efficacy in the treatment of various pathologies, exploiting their regenerative potential in different tissues. This systematic review aimed to 1) highlight the specific potential of Muse cells, and provide a better understanding of this niche, and 2) originate the first organized review of already tested applications of Muse cells in regenerative medicine. The obtained results could be useful to extend the possible therapeutic applications of Muse cells.

Adolescence is a stage of change and transition, which together with the COVID-19 situation, has been a huge source of vulnerability and facilitated the development of emotional disorders. This study aims to analyse internalising (anxiety and depression) and externalising (anger and aggression) symptoms in adolescence according to gender, as well as personal resources (self-esteem, social competence and integration, and awareness of problems) put in place as a mechanism of protection and coping after the situation of the pandemic. The study population encompassed 445 adolescents, of whom 230 were boys and 215 were girls, between the ages of 12 and 17. A self-reported Likert-type test was used. Findings indicate that girls show greater levels of internalising (anxiety and depression) and externalising problems (anger), finding no differences for the variable aggression between the two groups. Personal resources are closely linked to emotional symptomatology, providing a source of protection in both genders. The findings indicate a maladaptive pattern for adolescents that requires early intervention within the field of education.

The current work shows the optimization in the preparation of nanosized titanium carbide (TiC) in-situ through mechanical alloying (MA). Metallic titanium (Ti) powders, along with two carbon sources, carbon nanotubes (CNTs), and stearic acid (SA), were used to reduce the particle size using a high-energy Spex800 mill. The combined use of 2 wt % of these carbon sources and n-heptane as a liquid process control agent (PCA) proved crucial in generating nanoscale powder composites through a simple and scalable synthesis process within a 4-hour timeframe. The use of 20 wt % of both carbon sources was compared to determine the ability of CNTs to form carbides and the decomposition of PCAs during mechanical milling. The result reveals structures like nanoblocks and nanolumps with and important size reduction. The structure and morphology of the composites and starting materials were evaluated through x-ray diffraction (XRD), Raman spectroscopy, scanning electron microscopy (SEM), and transmission electron microscopy (TEM).

Background: This study investigated the incidence, characteristics and functional outcomes associated with unplanned Acute Care Unit Readmissions (ACUR) during inpatient traumatic brain injury (TBI) rehabilitation in an Asian cohort. Methods: Retrospective review of electronic medical records from single rehabilitation unit was conducted from 1 Jan 2012 to 31 Dec 2014. Inclusion criteria were first TBI, aged >18 years, admitted < 6 months of TBI. ACUR were characterized into either of neurological, medical or neurosurgical subtypes. The main outcome measure was discharge Functional Independence Measure (FIM). Secondary outcomes included rehabilitation length of stay (RLOS). Results: Of 121 eligible TBI records, the incidence of ACUR was 14% (n=17), comprising neurologic (76.5%) and medical (23.5%) subtypes, occurring at median of 13 days (IQR 6, 28.5) after rehabilitation admission. Patients without ACUR had significantly higher admission mean (SD) FIM score compared to those with ACUR (FIM ACUR-negative 63.4 (21.1) vs FIM ACUR-positive 50.53(25.4), P =0.026). Significantly lower discharge FIM was noted in those with ACUR compared to those without. (FIM ACUR-positive 65.8(31.4) vs FIM ACUR-negative 85.4 (21.1), P = 0.023) Furthermore, a significant near-doubling of RLOS was noted in ACUR patients compared to non-ACUR counterparts [ACUR-positive median 55 days (IQR 34.50, 87.50) vs ACUR-negative median 28 days (IQR 16.25, 40.00), P = 0.002]. Conclusion: This study highlights the significant negative functional impact and lengthening of rehabilitation duration of ACUR on inpatient rehabilitation outcome for TBI.

Introduction: IFITM3, an innate immune protein linked to COVID-19 severity, has recently been identified as a novel γ-secretase modulator. Independent research has shown that IFITM3 may facilitate SARS-CoV-2 neurotropism in an ACE2-independent manner. In a previous study, we had detected perturbations in IFITM3 networks in both the CNS and peripheral immune cells donated by AD patients. The purpose of this study is to explore the transcriptomic evidence of the SARS-CoV-2 / IFITM3 / AD interplay, validating previous findings from our group. Methods: Exploratory analyses involved meta-analysis of bulk and single cell RNA data for IFITM3 and FYN differential expression. For confirmatory analyses, we performed gene set enrichment analysis (GSEA) on an AD gene signature from AD Consensus transcriptomics; using the Enrichr platform, we scrutinized COVID-19 datasets for significant, overlapping enriched biological networks. Results: Bulk RNA data analysis revealed that IFITM3 and FYN were differentially expressed in two CNS regions in AD: the temporal cortex (AD vs. Controls, adj.p-value=1.3e^-6) and the parahippocampal cortex (AD vs. controls, adj.p-value=0.012). Correspondingly, single cell RNA analysis of IFITM3 and FYN revealed that it was differentially expressed in neuronal cells donated from AD patients (astrocytes, microglia and oligodendrocyte precursor cells), when compared to controls. Discussion: IFITM3 and by extent FYN were found as interactors within biological networks overlapping between AD and SARS-CoV-2 infection. SARS-CoV-2-mediated FYN/IFITM3 induction would mechanistically result in increased Tau fibrilization and Aβ oligomerization. FYN recruitment by viral processes results in abrogation of both fusion of IFITM3 vesicles with lysosomes; immunoevasion, by FYN-mediated impairment of autophagy would then serve to promote impaired detoxification from Aβ, while propagating Tau pathology in an IFITM3-independent manner.

Risk attitudes are relevant factors affecting the production and investment decisions at farm level. They are key factors that are related to farmers’ attitudes towards environment and climate change. Several methodological approaches are available to measure the level of stated risk of an economic agent. The Multiple Price List (MPL) method is one of the methods that is gaining relevance. In this study we apply the MPL and relate the risk outcomes with farmers’ characteristics and their perception towards environment and climate change. Data was collected using a face to face survey carried out for a group of 370 agricultural producers of the irrigation district located in northwest of Mexico. Results showed an average risk of about 0.32, locating the agricultural producers of the region in a group with risk aversion, according to the MPL scale. The heterogeneity analysis showed that the socioeconomic factors and the perceptions towards climate change are related to the farmers´ stated risk level. Farmers who are young women with propensity to use public support to invest were shown to be greater risk lovers. Farmers in the region have perceived climate change to a greater extent like floods, hail, diseases and pests, and changing vegetation.

Conceptual distance refers to the degree of proximity between two concepts within a conceptualization. It is closely linked with semantic similarity and relationship, but its computation relies entirely on the context of the given concepts. The DIS-C algorithm, which requires using search algorithms such as Breadth First Search, represents an advance in computing the semantic similarity/relation regardless of the type of knowledge structure and semantic relationships. The shortest path algorithm facilitates the determination of the semantic closeness between two indirectly connected concepts in an ontology by propagating local distances. This process is implemented for each concept pair to establish the most effective and efficient paths to connect these concepts. The algorithm identifies the shortest path between the concepts, allowing for the inference of the most relevant relationships between them. This approach contributes to developing a comprehensive understanding of the ontology and enhances the accuracy and precision of the semantic representation of the concepts. However, one of the critical issues is associated with the computational complexity due to the nature of the algorithm, which is errorn3. This paper studies alternatives to accelerate the DIS-C based on approximation and optimized algorithms, focusing on Dijkstra, pruned Dijkstra, and Sketched-based algorithms to compute conceptual distance. Based on the experiments, we discovered that the bottleneck can be avoided using the proposed 2-hop coverages, bringing DIS-C almost linearity.

Google Trends data can be informative for infectious disease incidences, including Lyme disease. However, the use of Google Trends for predictive purposes is underutilized. In this study, we tested the ability of Google Trends search data to predict monthly state-level Lyme disease case counts in the United States. We requested Lyme disease data for the years 2010-2021. We downloaded Google Trends search data on terms for Lyme disease, symptoms of Lyme disease, and diseases with similar symptoms as Lyme disease. We built mixed negative binomial models based on a training dataset (2010-2016) and tested the models on a test dataset (2017-2021). A model was built for each search term and monthly lags of search terms were included as predictors. The highest performing models had high predictive ability, indicated by low Root Mean Squared Errors (RMSEs) and close association between observed and predicted case counts. The highest performing model was for the search term “Summer Flu”, which indicates low specificity of some of the terms. We outline challenges of using Google Trends data, including data availability and a mismatch between geographic units. We discuss opportunities for Google Trends data, including prediction of additional zoonotic diseases and incorporating environmental and companion animal data.

Systems Engineering is an ubiquitous discipline of Engineering overlapping industrial, chemical, mechanical, manufacturing, control, software, electrical, and civil engineering. It provides tools for dealing with the complexity and dynamics related to the optimisation of physical, natural, and virtual systems management. This paper presents a review of how multi-agent systems and complex networks theory are brought together to address Systems Engineering and management problems. The review also encompasses current and future research directions both for theoretical fundamentals and applications in Industry. This is made by considering trends such as mesoscale, multiscale, and multilayer networks; along with the state-of-art analysis on network dynamics and intelligent networks. Critical and smart infrastructure, manufacturing processes, and supply chain networks are instances of research topics for which this literature review is highly relevant.

Viscoelastic testing (VET) by both TEG and ROTEM has demonstrated hypercoagulability early in Covid Associated Coagulopathy (CAC). Additional VET studies demonstrated fibrinolytic shutdown late in a majority of severely ill Covid-19 patients with associated elevation of D-dimer. Elevated d-dimer confirms that coagulation, followed by fibrinolysis, has occurred. These findings imply that, during CAC, three enzymes—thrombin, Factor XIIIa and plasmin—must have acted in sequence. However, limitations in standard VET analyses preclude exploration of the earliest phases of clot induction, as well as clot formation and clot dissolution in flowing blood. Herein we describe a novel method illuminating aspects of this unexplored area. In addition, we created an ex vivo blood flow model in which the interactions of thrombin, Factor XIII and plasmin with fibrinogen can be studied, allowing determination of Soluble Fibrin (SF), the highly unstable form of fibrin that precedes the appearance of a visible clot. This model allows determination of the SF level at which fibrin microclots begin to form and the length of time the resulting microclots persist under normal fibrinolytic attack. In addition, the flow model allows exploration of the late fibrinolytic shutdown that VET has previously demonstrated in CAC through standard methodology.

Due to their contribution to human health, the production of healthy snacks has garnered the attention of both the scientific community and the food industry. This study was conducted to determine the suitability of frying and baking processing methods for producing green banana chips using two varieties: Barraganete and Dominico. The aim was to identify a treatment geared towards producing healthy snacks. Initially, the physicochemical properties of the raw materials were analyzed, revealing significant differences in starch, fat, fiber, and protein content. Subsequently, the bananas were processed into baked and fried chips. Multivariate statistical techniques such as ANCOVA, MANOVA, and post-hoc tests were applied to examine the influence of initial characteristics and detect variations attributable to the cooking method. The main findings showed that the initial protein level had a significant covariate effect on the final content in the chips. The Dominico variety generally proved more suitable for making baked chips, retaining higher percentages of protein, starch, fiber, and lower fat content than Barraganete. Baked chips showed significantly lower sodium and fat values than fried ones when differentiated by processing method. The "Dominico + Baked" treatment emerged as the superior alternative, with favourable levels of protein, starch, and low sodium and fat, positioning it as the most suitable for producing a healthy snack.

(1) Background: Elite sport can increase vulnerability to developing mental health pathologies. The purpose of the study is to determine the frequency at which these behavioural disorders appear in elite footballers and evaluate their relationship with other addictions. (2) Methods: A cross-sectional study was conducted between November 2020 and January 2022 on 306 participants. The variables of gambling and gaming were studied. The different groups were compared using Chi-squared tests. Probabilities exceeding 95% (p-values < 0.05) and residuals results greater than 2 or less than −2 were considered significant. (3) Results: There were significant differences between the two groups in terms of alcohol (p < 0.001), tobacco (p < 0.001), and cannabis (p < 0.018) consumption. We also found differences between those who had a history of a nervous disease (p < 0.015). 6.6% of the of football players had a probable diagnosis of gambling disorder compared to 1% in the general population (p < 0.007). Among the pathological and non-pathological cases of gambling in the football population, significant differences were found between those with a salary of €900–1,500/month (p < 0.033) or a history of a nervous pathology (p < 0.001). (4) Conclusions: This study showed that professional football players were vulnerable to mental health pathologies related to gaming.

The aim of this research was to evaluate the essential oil of Cymbopogon schoenanthus (L.) Spreng. (C. schoenanthus) from Burkina Faso in cytotoxic activity against LNCaP cells, derived from prostate cancer, and HeLa cells, derived from cervical cancer. Antioxidant activities were evaluated in vitro. Essential oil (EO) was extracted by hydrodistillation and analyzed by GC / FID and GC / MS. Thirty-seven compounds were identified, the major compounds being piperitone (49.9%), alpha terpinene isomer (24.02%), elemol (5.79%) and limonene (4.31%). EO exhibited a poor antioxidant activity, as shown by the inhibition of DPPH radicals (IC50 =1730 ± 80 µg/mL) and ABTS+. (IC50 = 2890 ± 26.9 µg/mL). Conversely, EO decreased the proliferation of LNCaP and HeLa cells with respective IC50s of 135.53 ± 5.27 µg/mL and 146.17 ± 11 µg/mL. EO also prevented LNCaP cell migration and led to the arrest of their cell cycle in the G2/M phase. Altogether, this work points out for the first time that EO of C. schoenanthus from Burkina Faso could be an effective natural anticancer agent.

Head and neck squamous cell carcinoma (HNSCC) is a type of cancer that arises from the epithelium lining of the oral cavity, hypopharynx, oropharynx, and larynx. Despite advancement of the current treatment to HNSCC, such as surgery, chemotherapy, and radiotherapy, the overall survival rate of HNSCC remains poor due to late diagnosis and acquired resistance to treatment. Natural products have been extensively explored as a safer and more acceptable alternative to current treatments, with numerous studies displaying their potential against HNSCC. This review highlights preclinical studies in the past 5 years involving natural products against HNSCC and explores the signalling pathways altered by these products. This review also addresses challenges and future directions of the use of natural products as chemotherapeutic and chemoprevention agents against HNSCC.

The effects of different priming techniques were evaluated to improve the dormancy and germination of wild seeds of “Piquín” chili pepper. Three experiments were designed for pre-sowing treatment of seeds: a) chemical seeds digestion; b) halopriming (with K⁺ or NH₄⁺ of NO₃^-, SO₄^2- or Cl^-) at different priming times (24, 48 or 72 h) and osmotic potential (-5, -10 or -15 atm) and c) previously selected halopriming (KNO₃ and NH₄NO₃) + Gibberellic acid (GA₃, at 100 or 200 ppm) were tested. Digestion treatments did show a negative effect on seed germination. Recommended values of osmotic potential (Ψ_s), to improve Piquín chili seed germination, must be between -10 and -15 atm (-1.0 and -1.5 MPa) and the priming time must be between 48 and 72 hours. Priming techniques can considerably reduce Capsaicinoids content on seeds, improve dormancy, seed germination performance, and increase the rate and uniformity of seedling establishment. KNO₃ and secondly GA₃ treatments may improve rapid and uniform germination and seedling emergence. The results provide basic information to develop guidelines for commercial establishment of Piquín pepper crops.

The common dry bean (Phaseolus vulgaris L.) is a nutrient dense food produced globally as a major pulse crop for direct human consumption, and is an important source of protein and micronutrients for hundreds of millions of people across Latin America, the Caribbean and Sub-Saharan Africa. Beans require large amounts of heat energy and time to cook, deterring consumers worldwide from purchasing beans. In regions where consumers rely on expensive fuelwood for food preparation, the yellow bean is often marketed as fast cooking. A Yellow Bean Panel (YBP) was assembled to explore the cooking time and health benefits of the five major seed types within the yellow bean market class (Amarillo, Canary, Manteca, Mayocoba, Njano) over two field seasons. This study shows how the Manteca yellow bean possess a fast cooking phenotype, which could serve a genetic resource for introducing fast cooking properties into a new generation of dry beans with cooking times < 20 minutes when pre-soaked and < 80 minutes unsoaked. Nutritional evaluation revealed fast cooking yellow beans have high iron retention (>80%) after boiling. An in vitro digestion/Caco-2 cell culture bioassay revealed a strong negative association between cooking time and iron bioavailability in the YBP (r values > -0.73). When either pre-soaked or left unsoaked the highest iron bioavailability scores were measured in the fast cooking Manteca genotypes providing evidence that this yellow market class is worthy of germplasm enhancement through the added benefit of improved iron quality after cooking.

Glaucoma poses a serious public health concern as it is the second leading cause of blindness after cataracts, while also being the leading cause of irreversible blindness worldwide. Glaucoma is more prevalent among Black, Latino, and Asian populations and it is essential to examine both racial and ethnic disparities that exist in treatment and prevention. As the number of people with glaucoma continues to grow, it is important to review aspects of this condition in order to better care for those affected. This article will review significant forms of glaucoma and what differentiates them in a diagnosis, treatment options, and recommendations on prevention and improving awareness

Oxidative stress has been implicated in cellular senescence and aging, as well as in the onset and progression of many diverse genetic and acquired diseases and conditions. The search for biomarkers of oxidative stress has become relevant to many biomedical fields using many different methods and approaches. Fluorescence methodology is advantageous because of its simplicity and high sensitivity. Fluorescent probes are frequently used to investigate the role of reactive oxygen species in oxidative stress in experimental or clinical settings, often involving the use of flow cytometry and related single-cell based technologies. To assess the specific role of reactive oxygen species in oxidative stress studies by cytometric methodologies, it is essential to detect and characterize these species accurately. However, the detection and quantitation of individual intracellular ROS is still a challenge, but different and complementary strategies may focus on other endpoints of oxidative stress. In this review we present and discuss briefly the limitations and perspectives of such approaches. Based on our results, we also provide recommendations for proper design of cytometric studies of oxidative stress in order to prevent or minimize experimental errors..

Agriculture is the main driver of depletion resources worldwide, and its duty is to ensure food security within a rapidly increasing demographic and urbanization, so it is important to transition to sustainable production systems. Vertical crops (VCs) can reduce the pressure on conventional agriculture because they save water and nutrients and increase crop yield. Therefore, this study aimed to validate a proposed predictive model (PM) to simulate water and nutrient uptake in vertical crops under greenhouse conditions. Based on the Penman-Monteith equation, PM estimates transpiration, while nutrient uptake was estimated using the Carmassi-Sonneveld submodel. PM was experimentally evaluated for vertically grown lettuce under Mediterranean greenhouse conditions, during spring 2023. The irrigation technique was a closed-loop fertigation circuit. The experimental consisted of testing two densities (50 and 80 plants·m-2), where each unit of the experiment unit was divided into three heights (low, medium, and upper). It performed ANOVA with a value of p &lt; 0.05 and R2 to assess PM performance. The results suggest a high degree of PM, since R2 ranged from 0.7 to 0.9 for the uptake of water and nutrients. Both densities had a yield between 17-20 times higher than conventional lettuce production and significant savings in water, between 85-88%. In this sense, PM has great potential to intelligently manage VC fertigation, saving water and nutrients, which represents an advance towards reaching SDG 6 and SDG 12, within the 2030 Agenda.

‘Arrayana’ mandarin fruits have a short postharvest life and are sensitive to chilling injury (CI) during cold storage. Brassinosteroids (BR) have been used as a sustainable technology to alleviate CI in fruits and improve postharvest quality. This study evaluated the effect of applying the 24-epibrasinolide analogue (EBR), at doses of 5 mg L-1; DI-31 analogue, at 5 and 10 mg L-1; and control, on the main physical and biochemical characteristics of 'Arrayana' mandarin stored at 4°C for 40 days and, subsequently, 7 days at room temperature (shelf life). The application of EBR and DI-31 analogues reduced the appearance of CI in the exocarp of 'Arrayana' mandarin fruits by reducing electrolyte leakage, maintaining membrane integrity, and increasing antioxidant activity and phenol content at the end of cold storage and shelf life. This was especially pronounced with 5 mg L-1 of EBR. Similarly, the BR maintained the postharvest quality of mandarins by reducing weight loss, respiratory intensity and chlorophyll degradation; increasing β-carotene; and maintaining titratable acidity, and soluble solids. Our research reports for the first time CI tolerance in Arrayana mandarin using natural (EBR) and spirostanic (DI-31), analogues and illustrates the tolerance functionality of the DI-31 analog on CI in fruit postharvest.

Hormones act as master ripening regulators. In non-climacteric fruit ABA plays a key role in ripening. Recently we confirmed in Fragaria chiloensis fruit that in response to ABA treatment the fruit induces ripening associated changes such as softening and color development. In consequence with these phenotypic changes, transcriptional variations associated with cell wall disassembly and anthocyanins biosynthesis were reported. As ABA stimulates ripening of F. chiloensis fruit, the molecular network involved in ABA metabolism was analyzed. Therefore, the expression level of genes involved in ABA biosynthesis and ABA perception were quantified during development of the fruit. Four NCED/CCDs and 6 PYR/PYLs family members were identified in F. chiloensis. Bioinformatics analyses confirmed the existence of key domains related to functional properties. Through RT-qPCR analyses the level of transcripts were quantified. FcNCED1 codifies a protein that displays crucial functional domains and the level of transcripts increased as the fruit develops and ripens, in parallel with the increment in ABA. In addition, FcPYL4 codifies for a functional ABA receptor and its expression follows an incremental pattern during ripening. The study concludes that FcNCED1 is involved in ABA biosynthesis, meanwhile FcPYL4 participates in ABA perception during ripening of F. chiloensis fruit.

This research uses the computing of conceptual distance to measure information content in Wikipedia categories. The proposed metric, generality, relates information content to conceptual distance by determining the ratio of information a concept provides to others compared to the information it receives. The DIS-C algorithm calculates generality values for each concept, considering each relationship's conceptual distance and distance weight. The findings of this study were compared to current methods in the field and found to be comparable to results obtained using the WordNet corpus. This method offers a new approach to measuring information content applied to any relationship or topology in conceptualization.

The results of the bibliographic analysis show that the most explored nanomaterials in dentistry are graphene and carbon nanotubes, and their derivatives. A detailed analysis and a comparative study on their applications show that, although they are quite similar, graphene based materials seem to be more promising for most of the applications of interest in dentistry. The bibliographic study also demonstrated the potential of zeolite based materials, although the low number of studies on their applications shows that they have not been totally explored, as well as other porous nanomaterials that found important applications in medicine, such as metal organic frameworks, have not been explored. Subsequently, it is expected that the research effort will concentrate in graphene and zeolite based materials in the incoming years. Thus, present review paper presents a detailed bibliographic study, with more than 200 references, in order to describe briefly the main achievements that have been described in dentistry using nanomaterials, compare and analyze them in a critical way, with the aim of predicting the future challenges.

In this paper, the active front-end (AFE) converter topology for the total harmonic distortion (THD) reduction in a wind energy system (WES) is used. A higher THD results in serious pulsations in the wind turbine (WT) output power and in several power losses at the WES. The AFE converter topology improves capability, efficiency and reliability in the energy conversion devices; by modifying a conventional back-to-back converter, from using a single voltage source converter (VSC) to use pVSC connected in parallel the AFE converter is generated. The THD reduction is done by applying a different phase shift angle at the carrier of digital sinusoidal pulse width modulation (DSPWM) switching signals of each VSC. To verify the functionality of the proposed methodology, the WES simulation in Matlab-Simulink® is analyzed, and the experimental laboratory tests using the concept of rapid control prototyping and the real-time simulator Opal-RT® Technologies is achieved. The obtained results show a type-4 WT with total output power of 6MVA, generating a THD reduction up to 5.5 times at the WES.

Increased connectivity between coastal lagoons and the sea is expected to entail a greater proportion of marine species in the former. Chetumal Bay, estuary of the Hondo river into the Caribbean, had a limited access to the sea until the opening of the Zaragoza Canal. We sought changes in the fish community from 1999-2001 (just after an expansion of the canal) to 2015-2018. The same fishing gear was used, in the same localities, during all seasons. Total fish abundance and mean local richness decreased, although total abundance increased in the polyhaline zone. Diversity was greater in the oligohaline zone in 1999-2001, but in the mesohaline zone in 2015-2018. Three guilds were absent in 2015-2018: medium-sized herbivores, large piscivores, and medium-sized planktivores. Abundance of small benthivores decreased by decade; medium-sized piscivores and small planktivores became more abundant in 2015-2018 in the polyhaline zone. These changes may be due to the opening of the channel, but illegal fishing outside the bay may explain the decrease in juveniles of large piscivores, and erosion in the innermost part may be destroying important habitats. Our findings can be a reference for similar situations, as coastal development and climate change interact and affect tropical estuaries.

Background: Sudden changes in clinical practice and the altered ability to care for patients due to the COVID-19 pandemic have been associated with moral distress and mental health concerns in healthcare workers internationally. This study aimed to investigate the severity, prevalence, and predictors of moral distress experienced by Australian healthcare workers during the COVID-19 pandemic. Methods: A nationwide, voluntary, anonymous, single time-point, online survey of self-identified frontline healthcare workers was conducted between 27th August and 23rd October 2020. Participants were recruited through health organisations, professional associations or colleges, universities, government contacts, and national media. Results: 7846 complete responses were received from nurses (39.4%), doctors (31.1%), allied health staff (16.7%) or other roles (6.7%). Many participants reported moral distress related to resource scarcity (58.3%), wearing PPE (31.7%) limiting their ability to care for patients, exclusion of family going against their values (60.2%), and fear of letting co-workers down if they were infected (55.0%). Many personal and workplace predictors of moral distress were identified, with those working in certain frontline areas, metropolitan locations, and with prior mental health diagnoses at particular risk of distress. Moral distress was associated with an increased risk of adverse mental health outcomes. Feeling appreciated by the community mitigated this risk in healthcare workers. Conclusions: Safeguarding healthcare workforces during crises is important for both patient safety and workforce longevity. Targeted interventions are required to prevent or minimise moral distress and associated mental health concerns in healthcare workers during COVID-19 and other crises.

Spent nuclear fuel and high-level radioactive waste can be disposed in deep horizontal drillholes in sedimentary, metamorphic, or igneous rocks. Horizontal drillhole disposal has safety, operational, and economic benefits: The repository is deep in the brine-saturated zone far below aquifers in a reducing environment of formations that can be shown to have been isolated from the surface for millions of years; its depth provides safety against inadvertent intrusion, earth¬quakes, and near-surface perturbations; it can be placed close to the reactors and interim storage facilities, minimizing transportation; disposal costs per ton of waste can be kept substantially lower than for mined repositories by its smaller size, reduced infrastructure needs, and staged imple¬mentation; and, if desired, the waste could be retrieved using “fishing” technology. In the proposed disposal concept, corrosion-resistant canisters containing unmodified fuel assemblies from commercial reactors would be placed end-to-end in up to 50 cm diameter horizontal drill¬holes, a configuration that reduces mechanical stresses and keeps the temperatures below the boiling point of the brine. Other high-level wastes, such as capsules containing 137Cs and 90Sr, can be disposed in small-diameter drillholes. We provide an overview of this novel disposal concept and its technology, discuss some of its safety aspects, and compare it to mined repositories and the deep vertical borehole disposal concept.

Groundwater models serve as support tools to among others: assess water resources, evaluate management strategies, design remediation systems and optimize monitoring networks. Thus, the assimilation of information from observations into models is crucial to improve forecasts and reduce uncertainty of their results. As more information is collected routinely due to the use of automatic sensors, data loggers and real time transmission systems; groundwater modelers are becoming increasingly aware of the importance of using sophisticated tools to perform model calibration in combination with sensitivity and uncertainty analysis. Despite their usefulness, available approaches to perform this kind of analyses still present some challenges such as non-unique solution for the parameter estimation problem, high computational burden and a need of a deep understanding of the theoretical basis for the correct interpretation and use of their results, in particular the ones related to uncertainty analysis. We present a brief derivation of the main equations that serve as basis for this kind of analysis. We demonstrate how to use them to estimate parameters, assess the sensitivity and quantify the uncertainty of the model results using an example inspired by a real world setting. We analyze some of the main pitfalls that can occur when performing such kind of analyses and comment on practical approaches to overcome them. We also demonstrate that including groundwater flow estimations, although helpful in constraining the solution of the inverse problem as shown previously, may be difficult to apply in practice and, in some cases, may not provide enough information to significantly constrain the set of potential solutions.

In 2011 over 1.7 million people were hospitalized because of a fragility fracture, and direct costs associated with osteoporosis treatment exceeded 70 billion dollars in the United States. Failure to reach and maintain optimal peak bone mass during adulthood is a critical factor in determining fragility fracture risk later in life. Physical activity is a widely accessible, low cost, and highly modifiable contributor to bone health. Here, we will review the evidence linking exercise and physical activity to bone health in women. Bone structure and quality will be discussed, especially in the context of clinical diagnosis of osteoporosis. We will review the mechanisms governing bone metabolism in the context of physical activity and exercise. Questions such as, when during life is exercise most effective, and what specific types of exercises improve bone health, will be addressed. Finally, we will discuss some emerging areas of research on this topic, and will summarize areas of need and opportunity.

: This study aims at examining how B Corporations advance Sustainable Development Goals (SDGs) in their practices by analyzing the socioenvironmental problems they address and the solutions they provide to those problems. All Argentinian B corporations, certified by early 2023 (135 companies), were investigated using a mixed approach, combining social network analysis with textual data analysis. The results showed that the environmental practices are primarily linked to waste, water, energy and chemical management, as well as product innovation. In turn, the social practices address the training, education, and well-being of employees and other stakeholders, diversity, equity and inclusion management, and the creation of an inclusive and fair environment, integrating local communities. Thus, in the flow of their sustainability practices, Argentinian B Corporations contribute to SDGs 8, 12, 13, 9, 6, 7, 5, 10, 11, 4, and 17, in line with the SDGs declared by these companies. Our findings contribute to the theoretical knowledge of the B Corp movement and have practical implications by providing inputs to improve the management of B Corporations and to guide public policies encouraging these companies to advance sustainable development dimensions lacking attention.

The role of agricultural transport costs in core-periphery structures has habitually been ignored in New Economic Geography (NEG) models. This is due to the convention of treating the agricultural good as the numéraire, thus implying that agricultural transportation costs are assumed to be zero in these models. For more than three decades, this has been the standard setting in spatial equilibrium analysis. The paper examines the effects of agricultural transport costs on the spatial organisation of regional structures in Peru. In doing so, the Krugman’s formulation of iceberg transport costs is modified to introduce the agricultural transport costs into the dynamic of the NEG models. We use exploratory spatial flow data analysis methods and non-spatial and spatial origin-destination flow models to explore how the regional spatial structure change when real transportation data for agricultural goods is included into the iceberg transport costs formulation. We show that agricultural transport costs generate flows that are systematically associated with flows to or from nearby regions generating thus the emergence of spatial spillovers across Peruvian regions. The results of the paper support the contention that NEG models have overshadowed the role of agricultural transport costs in determining the spatial configuration of economic activities.

The practice of spatial econometrics revolves around a weighting matrix, which is often supplied by the user on previous knowledge. This is the so called $\mathbf{W}$ issue. Probably, the aprioristic approach is not the best solution although, nowadays, there few alternatives for the user. Our contribution focuses on the problem of selecting a $\mathbf{W}$ matrix from among a finite set of matrices, all of them considerer appropriate for the case. We develop a new and simple method based on the Entropy corresponding to the distribution of probability estimated for the data. Other alternatives, which are common in current applied work, are also reviewed. The paper includes a large Monte Carlo to calibrate the effectiveness of our approach compared to the others. A well-known case study is also included.

Protein malnutrition is present in developing countries but also in developed ones, due by the actual eating habits with insufficient protein intake, in addition to this it is estimated by the Food and Agricultural Organization of the United Nations an increase of world population of 9.1 billion people in less those 30 years, posing the challenge of nourish the mankind. There are different strategies to afford this challenge, one of the most promising ones is to approach novel protein sources like plants, microorganisms, and insects from dry lands.

Citizens face online privacy threats from social media, organisations and governments. Privacy-enhancing tools (PETs) can help people to preserve their privacy, but the uptake of these is limited. We developed a conceptual framework for privacy self-protection, using a classification framework of four distinct privacy threats and our own novel staged model of PET adoption requisites. Through an expert survey (N = 12) and a lay user survey (N = 500), we identified suitable PETs for non-expert users and identified potential barriers to PET adoption. Based on the studies and our theoretical framework, we then developed and implemented a PET decision support tool called PEDRO, and conducted expert evaluations (N = 10).

The present study aims to evaluate the capability of the TRMM-3B42-(V7) precipitation product to estimate appropriate precipitation rates in the Upper Indus basin (UIB) and the analysis of the dependency of the estimates’ accuracies on the time scale. To that avail statistical analyses and comparison of the TMPA- products with gauge measurements in the UIB are carried out. The dependency of the TMPA estimates’ quality on the time scale is analysed by comparisons of daily, monthly, seasonal and annual sums for the UIB. The results show considerable biases in the TMPA- (TRMM) precipitation estimates for the UIB, as well as high false alarms and miss ratios. The correlation of the TMPA- estimates with ground-based gauge data increases considerably and almost in a linear fashion with increasing temporal aggregation, i.e. time scale. The BIAS is mostly positive for the summer season, while for the winter season it is predominantly negative, thereby showing a slight over-estimation of the precipitation in summer and under-estimation in winter. The results of the study suggest that, in spite of these discrepancies between TMPA- estimates and gauge data, the use of the former in hydrological watershed modelling, endeavoured presently by the authors, may be a valuable alternative in data- scarce regions, like the UIB, but still must be taken with a grain of salt.

Functional somatic disorders (FSD) characterized by persistent and disabling physical symptoms are common in adolescents. Diagnostic uncertainty and insufficient illness explanations are proposed perpetuating factors that may constitute barriers for treatment engagement. This study evaluates the impact of manualized assessment and psychoeducation on diagnostic certainty and various clinical outcomes in adolescents with multi-system FSD. Ninety-one adolescents (15-19 years) included in a randomized trial testing group-based therapy (AHEAD) received systematic assessment (4 hrs.) and a subsequent psychiatric consultation (1.5 hrs.). Clinical outcomes included self-reported physical health, symptom severity, illness perception, illness related behavior, and psychological flexibility assessed before and approximately two months after assessment, prior to specialized treatment. Data were analyzed using t-tests. Immediately following assessment 71 (80.7%) adolescents out of 88 reported a higher diagnostic certainty and 74 (84.1%) reported that attending assessment gave them positive expectations for future treatment. A clinically relevant improvement of physical health was not observed at two months but considerable reductions were seen on symptom severity, illness worry, negative illness perceptions, limiting illness behavior and psychological inflexibility. The results underpin the importance of systematic assessment and psychoeducation which may be effective in their own right in specialized treatment of adolescents with severe FSD.

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

Despite increased protection globally, climate change and other anthropogenic factors have caused a significant decline in seagrass cover. Identifying the specific causes of this decline is paramount if they are to be addressed. Therefore, we identified the causes of long-term change in seagrass/submerged aquatic vegetation (SAV) percentage cover and extent in the Bluefields Bay Special Fish Conservation Area (BBSFCA), a marine protected area on Jamaica’s southern coast. We used two random forest regression (RFr) models that included 2013 hydroacoustic survey SAV percentage cover data (dependent variable), and auxiliary data, reflectance data from level 2 processed 2013 Landsat 7 and 8 images and image band texture statistics maps (mean and variance) as predictors to generate 24 SAV percentage cover maps for the period 1984 – 2021 (37 years) using data from Landsat 4-5, 7 and 8 images., from which benthic features maps (SAV present, absent and coral reef) were created. Rainfall and map data were used to determine if SAV extent/area (km2) and average percentage cover and annual rainfall changed significantly over time and to evaluate the influence of rainfall. Rainfall impact on the overall spatial patterns of SAV loss, gain, and percentage cover change was assessed using a pixel-based regression. Finally, the most important spatial pattern predictors (two rainfall proxies (distance and direction from river mouth), benthic topography, depth, and hurricane exposure (a measure of hurricane disturbance)) of SAV loss, gain, and percentage cover change during 23 successive 1-to-4-year periods were identified using spatial Bayesian INLA generalized linear mixed models. SAV area/extent was largely stable with &gt; 70% mean percentage cover for multiple years. However, Hurricane Ivan (in 2004) caused a significant decline in SAV area/extent (by 1.62 km2, or a 13%) during 2002 – 2006 and a second hurricane (Dean) in 2007 delayed recovery until 2015. Additionally, rainfall declined significantly by &gt;1000 mm since 1901, and mean monthly rainfall positively influenced SAV percentage cover change. The pixel-based regression highlighted areas where mean monthly rainfall had a positive overall effect on SAV cover percentage change (across the entire bay) and gain (closer to the mouth of a river). The most frequently selected important spatial pattern predictors were the two rainfall proxies (areas closer to the river mouth were more likely to experience SAV loss and gain) and depth, with shallow areas generally having a higher probability of SAV loss and gain. Three hurricanes had significant but different impacts depending on their distance from the southern coastline. Hurricane Gilbert, which made landfall in 1988, resulted in higher SAV percentage cover loss in 1987 - 1988. Benthic locations with a northwestern/northern facing aspect (the predominant direction of Ivan’s leading edge wind bands) experienced higher SAV losses during 2002 – 2006. Although some locations impacted by Ivan and not by Dean recovered during 2006 – 2008, exposure to Ivan explained percentage cover loss during 2006 – 2008 and average exposure to (the cumulative impact of) Ivan and Dean (both with tracks close to the southern coastline) explained SAV loss during 2013 – 2015. Therefore, despite historic lows in annual rainfall, overall, higher rainfall was beneficial, multiple hurricanes impacted the site, and despite two hurricanes in three years SAV recovered within a decade. Hurricanes and a further reduction in rainfall may pose a serious threat to SAV persistence in the future.

Coronavirus Disease 2019 (COVID-19) has become a global health threat and has placed an extraordinary demand for healthcare workers around the world. In this study, we aim to examine the prevalence of burnout, its associating factors, and experience among Malaysian healthcare workers through an embedded mixed-method study design. We found that more than half of Malaysian health care workers in this sample experienced burnout. Direct involvement in COVID-19 screening or treatment, having a medical condition, and less psychological support in the workplace emerged to be the significant factors for personal-, work- and patient-related burnout. Participants described workload, uncertainties from the pandemic, challenged work-family balance and stretched workplace relationships as the sources of burnout. Exhaustion appeared to be the major symptom and many participants utilized problem-focused coping to deal with the adversities experienced during the pandemic. Participants reported physical, occupational, psychological, and social-related negative impacts emanating from burnout. As the pandemic trajectory is yet unknown, the findings provide early insight and guidance for possible interventions.

Like other organisms, fungi produce extracellular vesicles (EVs) that are involved in various biological processes, including intercellular communication and the transport of molecules between cells. These EVs can be applied in fungal pathogenesis, virulence, and interactions with other organisms, including host cells, in the case of fungal infections. While some types of mycoses are relatively common and easily treatable, certain neglected mycoses pose significant public health challenges, such as sporotrichosis, chromoblastomycosis, and paracoccidioidomycosis. These infectious diseases can cause significant morbidity and disability, leading to a reduced quality of life for the patients. So, research about the virulence factor is essential to understand how fungi escape the immune system. In this context, this manuscript reviews the study of fungi EVs, their cargo, their obtaining, and their role during the infectious process, which is extremely important for understanding this neglected mycosis.

Pure monocular 3D reconstruction is an ill-posed problem that has attracted the research community's interest due to the affordability and availability of RGB sensors. SLAM, VO, and SFM are disciplines formulated to solve the 3D reconstruction problem and estimate the camera’s ego-motion, so many methods have been proposed. However, most of these methods were not evaluated in large datasets, under various motion patterns, had not been tested under the same metrics, and most of them had not been evaluated following a taxonomy, making their comparison and selection difficult. In this research, we performed a comparison of ten publicly available SLAM and VO methods following a taxonomy, including one method for each category of the primary taxonomy, three machine learning-based methods, and two updates of the best methods, to identify the advantages and limitations of each category of the taxonomy and test if the addition of machine learning or the updates made on those methods improved them significantly. Thus, we evaluated each algorithm under the TUM-Mono benchmark and performed an inferential statistical analysis to identify significative differences through its metrics. Results determined that sparse-direct methods significantly outperformed the rest of the taxonomy, and fusing them with machine learning techniques significantly improves the performance of geometric-based methods from different perspectives.

Among the knowledge areas in which process mining has had an impact, the audit domain is particularly striking. Traditionally, audits seek evidence in a data sample that allows to make inferences about a population. Mistakes are usually committed when generalizing the results and anomalies, therefore, appear in unprocessed sets. However, there are some efforts to address these limitations using process mining-based approaches for fraud detection. To the best of our knowledge, no fraud audit method exists that combines process mining techniques and visual analytics to identify relevant patterns. This paper presents a fraud audit approach based on the combination of process mining techniques and visual analytics. The main advantages are: (i) a method is included that guides the use of the visual capabilities of process mining to detect fraud data patterns during an audit; (ii) the approach can be generalized to any business domain; (iii) well-known process mining techniques are used (Dotted Chart, Trace Alignment, Fuzzy Miner…). The techniques were selected by a group of experts and were extended to enable filtering for contextual analysis, to handle levels of process abstraction, and to facilitate implementation in the area of fraud audits. Based on the proposed approach, we developed a software solution that is currently being used in the financial sector as well as in the telecommunications and hospitality sector. Finally, for demonstration purposes, we present a real hotel management use case in which we detected suspected fraud behaviors, thus validating the effectiveness of the approach.

In this systematic review of the literature on using Machine Learning (ML) for credit risk prediction, we raise the need for financial institutions to use AI and ML to assess credit risk, analyzing large volumes of information. We posed research questions about algorithms, metrics, results, data sets, variables, and related limitations in predicting credit risk. We searched renowned databases to answer them and identified 52 relevant studies with the credit industry microfinance. Challenges and approaches in credit risk prediction using ML models we identified, difficulties with the implemented models such as the black box model, the need for explanatory artificial intelligence, the importance of selecting relevant features, addressing multicollinearity, and the problem of the imbalance in the input data. By answering the questions, we identified that the Boosted Category is the most researched family of ML models; the most commonly used metrics for evaluation are Area Under Curve (AUC), Accuracy (ACC), Recall, precision measure F1 (F1), and Precision; Research mainly uses public data sets to compare models, and private ones to generate new knowledge when applied to the real world. The most significant limitation identified is the representativeness of reality, and the variables primarily used in the microcredit industry are related data to the demographic, the operation, and payment behavior. This study aims to guide the developers of credit risk management tools and software towards the existing offer of ML methods, metrics, and techniques used to forecast it, thereby minimizing possible losses due to default and guiding risk appetite.

Our bodies produce a host of electrophilic species that can label specific endogenous proteins in cells. The signaling roles of these molecules are underactive debate. However, in our opinion it is becoming increasingly likely that electrophiles can rewire cellular signaling processes at endogenous levels. Attention is turning more to understanding how nuanced electrophile signaling in cells is. In this perspective, we describe recent work from our laboratory that has started to inform on different levels of context-specific regulation of proteins by electrophiles. We discuss the relevance of these data to the field, and to the broader application of electrophile signaling to precision medicine development, beyond the traditional views of their pleiotropic cytotoxic roles.

Remediation of IT issues encoded into domain-specific or user-defined alerts occurring in cloud environments and customer ecosystems in a vast majority of cases suffers from accurate recommendations which could be timely supplied for recovery of performance degradations. That, of course, is hard to realize through furnishing those abnormality definitions with an appropriate expert knowledge which varies from one environment to another. At the same time, in a large proportion of support cases, the reported problems under Global Support Services (GSS) or Site Reliability Engineering (SRE) treatment ultimately go down to the product teams making them waste costly development hours on investigating self-monitoring metrics of our solutions. Therefore, the mean-time-to-resolution (MTTR) rates of problems/alerts are significantly impacted from lack of a systematic approach towards adopting AI Ops. That would imply building, maintaining, and continuously improving/annotating a data store of insights that ML models are trained and generalized across the whole customer base and corporate cloud services. Our ongoing study is in line with such a vision and validates an approach that learns the alert resolution patterns in such a global setting and explains them using interpretable AI methodologies. The knowledge store of causative rules is then applied in predicting potential sources of the application degradation reflected in an active alert instance. In this communication, we share our experiences with a prototype solution and up to date analysis demonstrating how root conditions are discovered with a high accuracy for a specific type of problem. It is validated against the historical data of resolutions performed by heavy manual development efforts. We also offer a Dempster-Shafer theory-based rule verification framework for experts as a what-if analysis tool to test their hypotheses about underlying environment.

In the knowledge era, intellectual capital has been considered a key factor in creating value within organisations. This study examines the relationships and interactions between the components of intellectual capital and the profitability of Panamanian banking, and financial institutions listed on the Latin American Stock Exchange (LATINEX) from 2014 to 2020. Utilising the Valued-Added Intellectual Coefficient (VAIC)™ model, which evaluates the intellectual capital of organisations based on information from financial statements, the study constructs a regression model to examine the relationship between the Return on Equity (ROE) and the components of the VAIC™. The findings confirm the study’s hypothesis, demonstrating that the Structural Capital Efficiency (SCE) and company size (SIZE) variables explain 57% of the variance in ROE for the analysed institutions. The results suggest that the Intellectual Capital (IC) of financial sector institutions listed on LATINEX is significantly influenced by the SCE coefficient, which shows a negative relationship, suggesting that investment in structural capital does not enhance profitability. On the other hand, larger institutions exhibited higher profitability during the study period.