Bovine lactoferrin (bLf) is a milk-derived protein that exhibits multiple biological activities and has been explored towards different therapeutic applications. Since this molecule is susceptible to degradation and some of its properties depend on its tertiary structure, the encapsulation of bLf in stimuli-responsive therapeutic formulations provides an added value to potentiate its biological activities when administered. Plasmonic magnetoliposomes emerge as promising nanosystems for dual hyperthermia (magneto-photothermia) and local therapy, since the combination of magnetic and gold nanoparticles (NPs) in a single nanosystem (multifunctional liposomes) enables the targeting and controlled release of encapsulated drugs. In this work, plasmonic magnetoliposomes (PMLs) containing manganese ferrite nanoparticles (28 nm size) and gold nanoparticles (~ 5 nm size) functionalized with 11-mercaptoundecanoic acid or octadecanethiol, were synthesized and loaded with bLf. The structural, magnetic and optical properties of the nanoparticles were measured by TEM, SQUID and UV/vis/NIR absorption spectroscopy. Specific Absorption Rate was determined to assess the capabilities for magnetic and photothermal hyperthermia. Finally, Saccharomyces cerevisiae was used as an eukaryotic cellular model to assess the biological activity and the mechanism of entry of bLf-loaded PMLs, through counting of colony forming units and fluorescence microscopy, respectively. The results demonstrate that PMLs are mainly internalized through an energy- and temperature-dependent endocytic process, though the contribution of a diffusion component cannot be discarded. Most notably, only bLf-loaded PMLs exhibit cytotoxicity with an efficiency similar to free bLf, attesting their promising potential for bLf delivery in the context of therapeutic interventions.

Emerging infectious diseases are a major threat to biodiversity and an important public health issue. West Nile virus (WNV) is an emerging vector-borne zoonotic arbovirus that is currently broadening its distribution in Europe. The evidence of WNV circulating in resident and migratory species has implications for both animal and public health, and should therefore be studied in depth. An integrated surveillance program, namely in birds, is essential for reducing the risk of infection in human populations within the One Health principles. In the present study, wild birds admitted to wildlife rehabilitation centres in Portugal were sampled. Two-hundred and eight blood samples were assayed serologically to antibodies to WNV, by using a commercial ELISA kit. An overall seroprevalence of 19.6% (95% confidence interval [CI]: 13.7-26.7%) was observed. Antibodies to WNV were detected in 13 (35.1%) different species of wild birds. Accipitriformes (26.7%; 95% CI: 18.5-36.2%) and Strigiformes (26.7%; 95% CI: 14.6-42.0%) were the orders with the highest seroprevalence recorded. There were no statistically significant differences (p = 0.725) between the geographical regions (NUTS II) studied, but statistically significant difference (p = 0.017) was found between gender (male: 34.4%; female: 4.8%). A higher seroprevalence was found in adults (32.1%) compared to juvenile birds (9.3%) (p = 0.014), and age was considered a risk factor to WNV infection in wild birds (odds ratio 1.4; 95% CI: 0.5–4.0). More epidemiological studies are needed in Portugal, since the actual spread of the WNV throughout the country is unknown.

Predictive studies are essential to establish fundamental data for monitoring and controlling Xylella fastidiosa infections in our country. Limited knowledge exists about how Xylella fastidiosa interacts with the plant host's immune system, leaving numerous unanswered questions regarding Xylella fastidiosa biology and its interactions with national plant hosts. Key inquiries include understanding of how the plant immune system interfaces with Xylella fastidiosa in the xylem and identifying the specific or shared mechanisms underlying the susceptibility of different hosts. Factors such as the presence of insect vectors, abundance of host plants, and climate suitability play pivotal roles in Xylella fastidiosa dispersal. We recommend that countries identified with relatively high risk, like Portugal, undertake thorough individual risk analyses. The implementation of preventive measures and, if necessary, the enhancement of surveillance systems for early detection of Xylella fastidiosa in plants and insect vectors are crucial steps. Additionally, raising awareness is of equal importance to mitigate socioeconomic and ecological impacts on their ecosystems.

Paratuberculosis, or Johne's disease, caused by Mycobacterium avium subsp. paratuberculosis (MAP), is a chronic granulomatous enteritis affecting both domestic and wild ruminants. The agent was also found in wild mammals such as wild boar (Sus scrofa), however, the role of wild mammals in the epidemiology of MAP is unclear. During the research period, 941 free-ranging wild boar (S. scrofa) legally hunted in two locations in the Centre-eastern region of Portugal were examined. Ninety-seven wild boar exhibited one or more gross lesions and were tested for the presence of Mycobacterium avium subsp. paratuberculosis using acid-fast staining, mycobacterial culture, poly-merase chain reaction (PCR), and histopathological examination. Forty-five animals (46.4%, 95% CI: 36.5-56.3%) were identified as infected, as indicated by positive results in culture and/or PCR. The findings revealed that the most significant risk factor was being a juvenile compared to year-lings and adults (OR = 10.2, 95% CI: 2.2-48.0). Based on our results, 37.9% (n = 11) of the infected animals were considered suitable for human consumption. Our findings offer novel insights into mycobacterial infections in wild boar populations in Portugal and suggest that wild boar could be a source of human infection if zoonotic potential is considered.

Environmental, social, and governance (ESG) investment has become a common trend in capital markets, and many institutional investors have publicly declared their long-term ESG investment target (ESGIT). This study focuses on investors who conduct strategic asset allocation (SAA) using composite indices but establish their ESGIT outside the SAA process. A mismatch could arise between investors’ planned and actual portfolios because they must pursue their ESGIT by asset selection, which inevitably makes the constituents of their portfolios different from those of composite indices. To scrutinize the potential existence of a misalignment between their SAA and ESGIT, this study analyzes actual stock and bond indices over the past decade using traditional mean-variance optimization. The results reveal significant differences between the expected and realized performances, and the misalignment is more significant when the analysis period is divided into two sub-periods: stable and volatile. Specifically, the results indicate that the efficient frontier constructed using ESG indices significantly differs from that constructed using composite indices, and that the difference between these two efficient frontiers becomes more significant during volatile periods. Furthermore, the results show that investors cannot meet their targets if their ESGIT is established outside the SAA process.

MIMO (multiple-input multiple-output) radar provides much more flexibility than the traditional radar for its ability to realize far more observation channels than the actual number of T/R (transmit and receive) elements. Designing the array of MIMO imaging radar, the commonly used virtual array theory generally assumes that all elements are placed on the same line. However, due to the physical size of the antennas and coupling effect between T/R elements, a certain height difference between T/R arrays is essential, resulting in the defocusing of edge points of the scene. On the other hand, the virtual array theory implies far-field approximation, leading to inevitable high grating lobes in the imaging result of near-field edge points of the scene observed by common MIMO array. To tackle these problems, this paper derives the relationship between target’s PSF (point spread function) and pattern of T/R arrays, by which the design criterion of near-field imaging MIMO array is presented. Firstly, the proper height between T/R arrays is designed to focus the near-field edge points well. Secondly, the far-field array is modified to suppress the grating lobes in the near-field area. Finally, the validity of the proposed methods is verified by simulations and an experiment.

The Folla Redonda grape is indigenous to the region of Rias Bajas in Galicia, Spain. This grape is distinguished by its characteristic acid flavor and pulp of remarkable coloration. Despite the wine obtained from this grape is highly valued by consumers of this region for its surprising acidic notes and thickness, it is important to note that it is not a variety of Vitis vinifera and its production is not legally regulated. In the present study, an evaluation of the physicochemical properties of the Folla Redonda grape (pH, °Brix, °Bé, density, acidity, sugar content, etc.) as well as its content in bioactive compounds (total polyphenols and anthocyanins) was carried out. Additionally, the antioxidant potential of the extracts obtained from this grape was demonstrated. This study proved the interesting organoleptic characteristics of the grape, along with a high content of compounds of interest and an important antioxidant activity comparable to that of Vitis vinifera grapes. Therefore, the grape's natural consumption and its application in different industries such as nutraceutical or pharmacological would result in an important revaluation of the grape and significant health benefits. In case that the production of wine from this variety is legalized, consumers will not only be able to enjoy a wine with a characteristic dense reddish color and important acid tones, but also with interesting concentrations of bioactive compounds.

Whilst prior works have characterised the affordances of prototyping methods in terms of generating knowledge about a product or process, the types, or ‘dimensions’ of knowledge towards which they contribute are not fully understood. In this paper we adapt the concept of ‘design domains’ as a method to interpret, and better understand the contributions of different prototyping methods to design knowledge in new product development. We first synthesise a set of ten dimensions for design knowledge from a review of literature in design-related fields. A study was then conducted in which participants from engineering backgrounds completed a Likert-type questionnaire to quantify the perceived contributions to design knowledge of 90 common prototyping methods against each dimension. We statistically analyse results to identify patterns in the knowledge contributions of different methods. Results reveal that methods exhibit significantly different contribution profiles, suggesting different methods to be suited to different knowledge generation. Thus, this paper indicates potential for new methods, methodology and processes to leverage such characterisations for better selection and sequencing of methods in the prototyping process.

Knowing the number of cases of an epidemic is the first function of epidemiological surveillance. An important underreporting of cases was observed in many places during the first wave of COVID-19 pandemic. To estimate this underreporting in the COVID-19 outbreak of Borriana (Valencia Community, Spain), during “Falles” mass gathering events in March 2020, a cross-sectional study was performed in June 2020 querying public health register. Logistic regression models were used. From a total of 468 symptomatic COVID-19 cases diagnosed in the outbreak by anti-SARS-CoV-2 serology, 36 cases were reported (7.7%), thus an underreporting of 92.3% (95% Confidence Interval [CI] 89.5%-94.6%), 13 unreported cases for every reported case. Only positive SARS-CoV-2 polymerase chain reaction cases were predominantly reported due to a limited testing capacity and following a national protocol. Significant factors associated with underreporting were no medical assistance for COVID-19 disease, adjusted odds ratio [aOR] 10.83 (95% CI 2.49-47.11), no chronic illness, aOR=2.81 (95% CI 1.28-6.17), middle and lower social classes, aOR=3.12 (95% CI 1.42-6.85), younger age, aOR=0.97 (95% CI 0.94-0.99), shorter duration of illness, aOR=0.98 (95% CI 0.97-0.99). To improve surveillance, studies of representative population samples are necessary to estimate the magnitude of future epidemics, and novel approaches are recommended.

The Galápagos Islands are one of the most emblematic protected areas on the planet, and also one of the most studied. Their main economic activity is tourism, which has grown rapidly in recent years. The increase in tourists is associated with the increase in population and the introduction of invasive species, which puts conservation at risk. This makes adequate management even more necessary and relevant on an international scale, since the economy of Galápagos depends on the good state of conservation of its ecosystems and species. Numerous studies have shown that social factors, rather than physical-natural ones, determine the success or failure of a marine protected area (MPA), so they must be urgently incorporated into all phases of MPA management. In this study we have analyzed the management of the protected areas of Galápagos: the National Park and the Marine Reserve. The methodology used presents five prescribed scenarios in which priority is given to one or other factors, each of which has an impact on biophysical and socio-economic systems that are influenced by the MPA. These scenarios have been called: proactive, interactive, centralized, learning, and formal management. The results show that the archipelago's protected areas follow a proactive management model, with a continuous feedback loop. This feedback is a key element in any adaptive management process, which also allows practitioners to anticipate future problems. Both public participation and strategic planning are essential.

Our goal was to determine the cellular immune response (CIR) among a random sample of the Borriana COVID-19 cohort (Spain) to identify its associated factors and their relationship with infection, reinfection and sequelae. We conducted a nested case-control study using a randomly selected sample of 225 individuals age 18 and older, including 36 individual naïve to SARS-CoV-2 infection, and 189 infected patients. We employed flow cytometry-based immunoassays for intracellular cytokine staining, utilizing Wuhan and BA.2 antigens and chemoluminescence microparticle immunoassay for detection SARS-CoV-2 antibodies. Logistic regression models were used. A total of 215 (95.6%) participants exhibited T-cell response (TCR) to at least one antigen. Positive responses of CD4+ and CD8+ T cells were 89.8% and 85.3% respectively. No difference in CIR was found for naïve and infected patients. Patients who experienced sequelae exhibited higher CIR than those without. A positive correlation was observed between TCR and Anti-Spike IgG levels. Factors positive associated with TCR included A-blood group, number of SARS-CoV-2 vaccine doses received, and Anti-N IgM; factors inversely related were the time elapsed since the last vaccine dose or infection, and B-blood group. These findings contribute valuable insights into the nuance immune landscape shaped by SARS-CoV-2 infection and vaccination.

Coastal environments are complex systems that are influenced by a combination of natural processes and human activities. Scientific interest in the effects of coastal erosion/accretion and climatic change-related processes greatly increased in recent decades due to the growing human development along coastal areas. This paper investigates the state and evolution of beach-dune systems for the 1977-2001 and 2001-2019 periods of the Mediterranean coast of Andalusia (Spain) using two different proxies: the dune toe line, which was used to track foredunes evolution, and the high-water line, which was used to assess shoreline evolution. Results showed a general erosional behavior of the studied beach-dune systems and identified cases where the main trend was altered through human interventions. In the 1977-2001 period, 54% of foredunes showed erosion, 24% accretion and 22% stability while and 34% of shorelines showed erosion, 40% accretion and 34% stability. In the 2001-2019 period, 42% of foredunes showed erosion, 28% accretion and 30% stability, and 40% of shorelines showed erosion, 34% accretion and 26% stability. Combining the evolution classes of each proxy (dune toe/shoreline) allows the behavior of both shoreline proxies to be assed together and provides insights additional to those derive from the use of a single proxy. In this regard, Erosion/Erosion (EE) was the most frequent behavior, with 25% and 27% in the first and second periods respectively, and Accretion/Accretion (AA), with 17% in both periods. Erosion of foredunes combined with stability or accretion of the shoreline (ES and EA) were the most common pairings in the first period, while stability of dunes combined with accretion of the shoreline (SA) and Stability/Stability (SS) dominated in the second period. The results obtained provide additional insights on the nature and drivers of coastal change that aid local coastal managers and administrations in understanding erosion processes. The method can be applied at other areas around the world where a similar data base is available.

Aiming at the problems of inaccurate segmentation of long object and information loss of small object in real-time semantic segmentation algorithm, this paper proposes a lightweight multi-branch real-time semantic segmentation network based on BiseNetV2. The new auxiliary branch makes full use of spatial details and context information to cover the long object in the field of view. Meanwhile, in order to ensure the inference speed of the model, the asymmetric convolution is used in each stage of the auxiliary branch to design a structure with low computational complexity. In the multi-branch fusion stage, the alignment and fusion module is designed to provide guidance information for deep and shallow feature mapping, so as to make up for the problem of feature misalignment in the fusion of information at different scales, and thus reduce the loss of small target information. In order to further improve the model’s awareness of key information, a global context module is designed to capture the most important features in the input data. The proposed network uses NVIDIA GeForce RTX 3080 Laptop GPU experiment, on the road street view data set Cityscapes and CamVid average occurring simultaneously ratio reached 77.1% and 78.4% respectively, with running speed of 127 frames/s respectively and 112 frames/s. The experimental results show that the proposed algorithm can achieve real-time segmentation and improve the accuracy significantly, showing good semantic segmentation performance

Female sexual functioning and satisfaction are impaired by the presence of sexual difficulties. Current study aims to analyze the differences on sexual satisfaction in women according to types of sexual problems (absence of sexual problems, self-perceived and assessed by the FSFI cut-off). A total of 329 women answered to a specific question about presence of self-perceived sexual problems, the Sexual Satisfaction Scale for Women, and the Female Sexual Functioning Index. Main findings revealed that sexually health women had better levels of sexual satisfaction when compared to women who self-report sexual difficulties and women who scored clinical levels in FSFI. Also, women who scored clinical levels in FSFI scored lower on sexual satisfaction compared to women who self-report sexual difficulties. Female sexual satisfaction was negatively affected by sexual difficulties assessed according to the FSFI cut-off. Although with lower impact, self-perceived sexual problems also affect negatively sexual satisfaction in women.

Understanding the optimal strategy for a real estate investment and how performance changes based on characteristics is crucial for optimising the achievable return. This is prominent in tourist areas such as Paphos where there is no clear distinction as to whether short or long-term approaches are optimal. The study aimed to develop a model for predicting the optimal rental strategy whilst assessing which model performed best and which property attributes impacted its return the greatest. Short-term data was collected from AirDNA and long-term data was manually collected from real estate agents websites. Furthermore, Random Forest, K-Nearest Neighbour and Multiple Linear Regression models were created to predict the highest and best use for each property. Model accuracy varied between data sets with the best performing model for short-term properties being Random Forest (R-Squared: 0.843), and Distance-Based Multiple Linear Regression for long-term approach (R-Squared: 0.843). The study demonstrated that accurate models could be created to predict the optimal rental strategy with the number of bedrooms being the main driver for rental income, followed by luxury finishes and the presence of a pool. It found that locational characteristics didn’t impact the returns significantly assuming that the property was located within a tourist area.

The rapid increase in metabolic diseases occurred in the last three decades in both industrialized and developing countries has been related to the rise in sugar-added foods and sweetened beverages consumption. An emerging topic in the pathogenesis of metabolic diseases related to modern nutrition is the role of Advanced Glycation Endproducts (AGEs). AGEs can be ingested with high temperature processed foods, but also endogenously formed as consequence of a high dietary sugars intake. Animal models of high sugars consumption, in particular fructose, have reported AGEs accumulation in different tissues in association with peripheral insulin resistance and lipid metabolism alterations. The in vitro observation that fructose is one of the most rapid and effective glycating agent when compared to other sugars has prompted the investigation of the in vivo fructose-induced glycation. In particular, the widespread employment of fructose as sweetener has been ascribed by many experimental and observational studies for the enhancement of lipogenesis and intracellular lipid deposition. Indeed, diet-derived AGEs have been demonstrated to interfere with many cell functions such as lipid synthesis, inflammation, antioxidant defences, and mitochondrial metabolism. Moreover, emerging evidences also in humans suggest that this impact of dietary AGEs on different signalling pathways can contribute to the onset of organ damage in liver, skeletal and cardiac muscle, and brain, affecting not only metabolic control, but global health. Indeed, the here reviewed most recent reports on the effects of high sugars consumption and diet-derived AGEs on human health suggest the need to limit the dietary sources of AGEs, including added sugars, to prevent the development of metabolic diseases and related comorbidities.

Different types of disasters, whether natural or human character, lead to the significant loss of human lives. In the latter case, the quick action of identification of corpses and human remains is mandatory. There are a variety of protocols to identify victims, however, genetics is one of the tools that allow an exact identification of the victim. However, several factors may interfere with this identification, from the biological samples’ degradation not allowing the analysis of nuclear information, to failure to dispose of biological samples from family members. Access to certain family members could be a determinant of the proper choice of genetic markers that allow the identification of the victim, or his/her inclusion in a given genetic maternal or paternal lineage. With the new advances in the genetic field, it is expected to allow soon the identification of victims from disasters only with his/her biological postmortem samples, being possible to draw a robot portrait and its most likely physical characteristics. In all cases, genetics is the only modern tool with universal character and can be used in essentially all biological samples, giving and identification of more or less accurate statistical character, depending on whether nuclear or lineage markers are used.

Nowadays the relationship between planning land use and actual land use is not so clear in general. A lot of efforts have been put in the failures of regulation for the expansion of construction land. However, it still lacks an integrated approach to study the effectiveness of land use regulation in terms of different land use types. Furthermore, the existing evaluation of land use plan mainly focuses on a general level, a detailed research on the regulation effectiveness of each construction land use type is absent. Therefore, this research tries to evaluate regulation effectiveness of land use plan, which takes Cangwu country, Guangxi Province as an example. The finding by analysis is that the total area of construction land expansion was about 3494.73 ha, nearly 1.1 times of the plan quota. Moreover, the effectiveness differs greatly in various construction land use types. Town, industrial/mining sites can be well regulated through the quota of land use plan. While, the quota regulation system is not as effective for other type of construction land. Thus, we suggest to improve the regulation effectiveness of construction land through different plan instruments.

The genome sequencing of Botrytis cinerea has supplied a general overview of the map of genes involved in secondary metabolite synthesis. B. cinerea genomic data have revealed that this phytopathogenic fungus has seven sesquiterpene cyclase (Bcstc) genes that encode proteins involved in the farnesyl diphosphate cyclization. Three sesquiterpene cyclases (BcStc1, BcStc5 and BcStc7) have been characterized, related to the biosynthesis of botrydial, abscisic acid and (+)-4-epi-eremophilenol, respectively. However, the role of the other four sesquiterpene cyclases (BcStc2, BcStc3, BcStc4 and BcStc6) remains unknown. BcStc3 is a well-conserved protein with homologues in many fungal species, and here, we have undertaken its functional characterization in the life cycle of the fungus. A null mutant ΔBcstc3 and an overexpressed–Bcstc3 transformant (OvBcstc3) were generated, and both strains show deregulation of those other sesquiterpene cyclase-encoding genes (Bcstc1, Bcstc5, Bcstc7). These results suggest a co-regulation of the expression of the sesquiterpene cyclase gene family in B. cinerea. Phenotypic characterization of both transformants revealed that BcStc3 is involved in oxidative stress tolerance, production of reactive oxygen species and virulence. The metabolomic analysis allowed the isolation of characteristic polyketides and eremophilenols from the secondary metabolism of B. cinerea, although no sesquiterpenes different from those already described were identified.

The digital transformation in Industry 4.0 has revolutionized quality control paradigms, integrating advanced technologies such as augmented reality, deep learning, and computer vision systems into a new era called "Quality 4.0". This study systematically reviews how these technologies are shaping new practices in continuous quality supervision and improvement, adapting to increasingly automated and connected production environments. Through a comprehensive analysis of the literature, practical applications in various industrial sectors, from manufacturing and agriculture to the production of sweets and snacks, are highlighted. Additionally, the conceptual and detailed design of a quality control system using artificial intelligence tools is presented, focusing on the inspection of dimensions, color, weight, and labeling of MDF boxes. The proposed system demonstrates an effective integration of sensors, high-definition cameras, and deep learning algorithms, validated through tests with boxes of different sizes. The results suggest that the adoption of these technologies not only improves the accuracy and efficiency of inspections but is also essential to maintaining high-quality standards in a dynamic and competitive industrial environment.

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

Inadequately managed agricultural waste significantly impacts the environment, health, and economy. This form of pollution arises from the underutilization, poor awareness, and insufficient treatment of agricultural waste. Fruit and vegetable wastes are valuable sources of bioactive compounds. This study aims to revalorize discarded waste from red habanero chili peppers (Capsicum chinense) by extracting bioactive compounds through different extraction processes: maceration (ME), maceration assisted by ultrasound (US), Soxhlet extraction (SE), supercritical fluid extraction (SFE), and supercritical fluid extraction with a co-solvent (SFEC). Extraction processes have significant effects on extraction efficiency and phytochemical profile (capsaicinoids and carotenoids recovery). The results indicate that the highest efficiency process is obtained with SFEC, also a high phytochemicals recovery (14.9 mg of total capsaicinoids and total carotenoids 292.09 µg per gram of sample). Concerning to phytochemical profile in the extract, the maceration process gets the highest concentration of compound followed by US and SFEC. These data reveal that the use of SFE and SFEC extraction is recommended for extraction of phytochemicals with biologically activity from red habanero chili pepper waste for diverse industries application.

The weakness of the dispersion-managed link combined with optical phase conjugation to compensate for optical signal distortion caused by chromatic dispersion and nonlinear Kerr effect of standard single mode fiber is its limited structural flexibility. We propose dispersion map that can simultaneously compensate for the distorted wavelength division multiplexed signal while increasing the configurational flexibility. Each residual dispersion per span (RDPS) in the former half of the proposed link is randomly determined, and in the latter half, the arrangement order of RDPS is the same as or inverted in the former half. We confirm that the dispersion maps in which the RDPS distribution pattern in the latter half is opposite to the arrangement order in the former half are more effective in compensation, and rather, the compensation effect is better than in the dispersion map of the conventional scheme. The notable result of this paper is that the increase of flexibility can be achieved through random arrangement of RDPS in the former half, and the compensation improvement can be achieved by through inverse arrangement in the latter half which make the distribution profile of each half link roughly symmetric with respect to the midway optical phase conjugator.

Knowing the reasons for mobility choices, how users evaluate the characteristics of public transport and how satisfied they are with the travel experience is essential to promote the use of LTP (Local Public Transport), especially in rural or suburban areas where the use of private car is often prevalent. The present study aimed to investigate the mobility experience and the reasons for use and non-use of the LPT in a suburban area by the people travelling to a large Hospital Centre in a Province of the North-east of Italy. An anonymous questionnaire was completed by people from different categories travelling to the hospital (students, employees, clients), user and non-users of the LPT. The results showed that insufficient hourly coverage and accessibility of the service are the primary reasons for opting not to use LPT and together with reliability and comfort, these factors contribute to user satisfaction with their travel experience. Perceived sustainability of LPT contributes to overall travel satisfaction. However perceived sustainability alone does not appear to influence the choice of LPT if the service lacks adequate accessibility and does not meet the needs of travelers in terms of hourly coverage

The confinement experienced due to the COVID-19 pandemic has prompted a rethink of the teaching-learning process to which teachers have responded without planning and instead using their resources. This study aims to analyze the relationships between work-family interactions, technostress, and perceived organizational support in teachers during the confinement period in Spain that began in March 2020. An online survey was administered to 640 pre-school, primary, and secondary school teachers. Positive reciprocal work-family interactions and their relationship with organizational support were found, with differences according to gender, with women showing a more negative perception of the impact on the family. There were no marked levels of technostress in the overall sample, although higher levels of perceived ineffectiveness and skepticism were found in teachers aged 46 years or older. Teachers in private and subsidized schools showed a higher level of perceived support than those in public schools. There is a need to continue this work to verify the values of these dimensions in other contexts and to apply institutional measures and public policies to improve these indicators in this group.

Although the influence of climate on the fire regime is unanimously recognized, most publications are studies on this influence are at the global scale. Therefore, this study aims to demonstrate the role of climate in the incidence of wildfires at the country and regional scale using statistical analysis and machine learning methods. Mainland Portugal was chosen as a case study due to its climate and because it is the European region most affected by wildfires. Results demonstrate the climate signature in the spatial and temporal distribution of the wildfire incidence. The conclusions of the study include (i) the existence of two pyro-regions, with different types of climate (Csb and Csa) composed of NUTS II regions: the northern region composed of the Norte and Centro regions and the southern region composed of Alentejo and Algarve; (ii) the intra-annual variability in the incidence of wildfires, characterized by two peaks, one in spring and the other in summer, are a consequence of the country's type of climate; and, (iii) how the annual cycle of wildfire incidence varies over the years depends on the weather conditions throughout each year. These results are of fundamental importance for wildfire managers, especially in the context of climate change.

Identified by the eponym “Edwards’ Syndrome,” trisomy 18 (T18) represents the second most common autosomal trisomy after T21. The pathophysiology underlying the extra chromosome 18 is a nondisjunction error, mainly linked with the advanced maternal age. More frequent in female fetuses, the syndrome portends high mortality, reaching a rate of 80% of miscarriages or stillbirths. The three-step evaluation includes first trimester screening for fetal aneuploidy using a combination of maternal age, fetal nuchal translucency thickness, fetal heart rate and maternal serum free ß-hCG and PAPP-A; followed by the research for fragments of fetal DNA in maternal blood; and, finally, invasive techniques leave to the established diagnosis. Starting with the first trimester scan, selected ultrasound findings should be investigated to define not only the impact of the genetic problem on the fetus, but also to address the prenatal counselling. Previous series underline that T18 is not uniformly lethal. An active dialogue on the choices in the management of infants with T18 has emerged, sustained by the transition from the comfort care to the intervention attitude. Survival rates for individuals with supposedly fatal conditions have increased. In this novel scenario, an ad hoc counselling is pivotal. To support it, a comparative analysis by pictorial assays between ultrasound and autopsy findings could be beneficial. We provide an illustrative tool from a clinical case managed in early second trimester, with the purpose to strive a balanced approach in the hard choice faced by couples of fetuses with T18.

Two decades after the antiretroviral therapy (ART) introduction, several challenges still prevail in maintaining people living with HIV (PLHIV), even with "Test and Treat" and/or "Rapid Start of ART" initiatives, as well as the scale-up of ART worldwide to promote access and adherence to treatment. This review examined articles on ART adherence in Africa between 2016 and 2023, published in English and indexed in PubMed. A total of 16 articles out of 2415 were eligible and included for analyses. Overall, ART adherence rates in SSA regions ranged from 43% to 84%. Rates in the centre of the SSA region ranged from 58% to 80%, in the north from 50% to 83%, in the south from 77% to 84%, in the west from 43% to 60% and in the east from 69% to 73%. Most African countries use the self-report to assess treatment adherence, although unreliable. The main factors with negative influence on ART adherence were comorbidities, lack of motivation, socioeconomic difficulties or side effects. Conclusion: Adherence to ART is a good indicator for controlling the spread of HIV. It is important to overcome the barriers that make it difficult to comply with ART and reinforce the factors that facilitate the accession of medication.

In the field of railroad safety, effective detection of surface cracks is critical, necessitating reliable, high-speed non-destructive testing (NDT) methods. This study introduces a hybrid Eddy Current Testing (ECT) probe, specifically engineered for railroad inspection, to address the common issue of ’lift-off noise’ due to varying distances between the probe and test material. Unlike traditional ECT methods, this probe integrates transmit and differential receiver coils, aiming to enhance detection sensitivity and minimize lift-off impact. The study optimizes ECT probes employing different driver coils, emphasizing three main objectives: a) quantitatively evaluating each probe using signal- to-noise ratio (SNR) and outlining a real-time data processing algorithm based on SNR methodology; b) exploring the frequency range proximal to the electrical resonance of the receiver coil; c) examining sensitivity variations across varying lift-off distances. The experimental outcomes indicate that the newly designed probe with figure 8-shape driver coil significantly improves sensitivity in detecting surface cracks on railroads. It achieves an impressive SNR exceeding 100 for defects with minimal dimensions of 1 mm in width and depth. Simulation results closely align with experimental findings, validating the investigation of optimal operational frequency and lift-off distance for selected probe performance, determined to be 0.3 MHz and 0.5 mm, respectively. The realization of this project would lead to notable advancements in enhancing railroad safety by improving crack detection efficiency.

The necessity for precise and current data concerning the dynamics of land cover change in Indonesia is crucial for efforts to reduce natural vegetation cover due to agricultural expansion. The functionality of monitoring systems that incorporate Terra-MODIS is currently compromised by the limited availability of data for the immediate future. This study seeks to assess the potential of VIIRS satellite imagery in developing an early warning system for monitoring vegetation cover change in Indonesia. The Normalized Differential Open Area Index (NDOAI) computed from the 8-day’ VIIRS data was employed to detect changes in vegetation cover based on pixel-by-pixel subtraction in the NDOAI data time series. Evaluating the pixel-level accuracy of change detection is complicated due to the fact that we evaluate a change map at a coarser resolution than the Landsat-based reference map. The results revealed that increasing the threshold percentage is associated with improved accuracy. In change detection, there is often a trade-off between accuracy and sensitivity. A threshold that is too low may result in false positives, while a threshold that is too high may lead to missed changes. This study demonstrates that when a threshold value of less than 20% is applied, Landsat can identify vegetation cover changes at an earlier stage. Conversely, when a threshold value greater than 20% is employed, VIIRS will detect the change 4.5 days earlier than Landsat. Additionally, VIIRS is capable of detecting changes 25.4 days and 54.8 days faster than Landsat, respectively, when using thresholds of 40% and 75%.

In the last decades we have experienced great social, cultural, and educational changes, spending more time performing tasks in near vision and less hours in outdoor activities, having more overexposure to digital screens, especially the youngest and increasingly from younger ages. It is common to see cases when performing tasks in near vision the posture or position of the head is not adequate, especially the youngest, being essential to have a correct posture of the head to avoid visual, muscular, or articular problems. We present a procedure to try to control the correct position of the head in real time when performing close-up activities. The aim is to detect the inclination of the head and to know if a bad position is adopted due to a visual problem or simply to inadequate visio-postural habits, warning us of the postural anomaly to correct it.

Accurate traffic simulation models play a crucial role in developing intelligent transport systems that offer timely traffic information to users and efficient traffic management. However, calibrating these models to represent real-world traffic conditions accurately poses a significant challenge due to the dynamic nature of traffic flow and the limitations of traditional calibration methods. This article introduces a machine learning-based approach to calibrate macroscopic traffic simulation models using real-time traffic video stream data. By leveraging computer vision technologies to extract key traffic parameters from video streams, the approach demonstrated a notable improvement in aligning the generated data from the calibrated simulation model with car sensor data, achieving an average improvement of over 50% compared to the uncalibrated macroscopic model. Moreover, there was a substantial reduction in data drift for the machine learning model integrated into the virtual transport space using vehicle-to-everything technology, resulting in a more than fourfold decrease in the average absolute error of the model.

Leptin, acting centrally or peripherally, has complex effects on cardiac remodeling and heart function. We previously reported that central leptin exerts an anti-hypertrophic effect in the heart via cardiac PPARβ/δ activation. Here, we assessed the impact of central leptin administra-tion and PPARβ/δ inhibition on cardiac function. Various cardiac properties, including QRS du-ration, R wave amplitude, heart rate (HR), ejection fraction (EF), end-diastolic left ventricular mass (EDLVM), end-diastolic volume (EDV), and cardiac output (CO) were analyzed. Central leptin infusion increased cardiac PPARβ/δ protein content and decreased HR, QRS duration and R wave amplitude. These changes induced by central leptin suggested a decrease in the ventricu-lar wall growth which was confirmed by MRI. In fact, the EDLVM was reduced by central leptin, while increased in rats co-treated with leptin and GSK0660, a selective antagonist of PPARβ/δ ac-tivity. In summary, central leptin plays a dual role in cardiac health, potentially leading to ven-tricular atrophy and improving heart function when PPARβ/δ signaling is intact. The protective effects of leptin are lost by PPARβ/δ inhibition, underscoring the importance of this pathway. These findings highlight the therapeutic potential of targeting leptin and PPARβ/δ pathways to combat cardiac alterations and heart failure, particularly, in the context of obesity

Onions are known not only for their culinary importance but also for their nutritional and health-promoting properties. Both properties are closely linked to its content of organosulfur compounds, which account for up to 5% of the dry weight of an onion. Given the importance of these compounds, suitable analytical methods are required for their study. Two techniques should be highlighted in this context: gas chromatography coupled to mass spectrometry (GC-MS), and liquid chromatography coupled to mass spectrometry (LC-MS). In this study, eight different onion varieties were analyzed using two distinct analytical techniques: direct thermal desorption–gas chromatography-mass spectrometry (DTD-GC-MS) and high-resolution mass spectrometry (HRMS) on an LC-ESI-QqTOF instrument. Each method identified 18 different organosulfur compounds, with LC-HRMS targeting non-volatile compounds, such as cysteine sulfoxides, and GC-MS targeting volatiles, such as disulfides and trisulfides. The results obtained were studied using Pearson correlations and principal component analysis. No precise correlation was found between the initial organosulfur compounds in onions and their hydrolysates. Consequently, although GC is one of the most employed techniques in the scientific literature, the use of LC-HRMS or a combination of both techniques may offer a more comprehensive and accurate description of the metabolomic profile of onions.

This review resumes published data on fungal diversity in and within monuments (e.g., religious and secular monuments, museums, and statues), covering a multidisciplinary investigation into the complex interactions between fungi and cultural heritage structures. Fungi represent remarkable adversaries to monuments, potentially compromising their structural integrity and aesthetic value. Based on a bibliographic search of manuscripts published, the knowledge of fungal communities colonizing monuments was comprehensively assessed. This work first describes the diverse fungal species implicated in the degradation of monument materials (e.g., stone, metal, and glass). It elucidates the factors governing fungal colonization and proliferation in and within these structures (e.g., environmental conditions, construction materials, and human interventions). Finally, the efficacy of preservation and restoration techniques to mitigate fungal threats and safeguard our cultural heritage is also discussed. This synthesis highlights the pivotal role of mycological research in heritage conservation, and a platform for future studies to address critical knowledge gaps is provided. Understanding fungal diversity in and within monuments is critical to preserving these invaluable cultural treasures, as it informs targeted conservation strategies and ensures their longevity in the face of fungal challenges.

The enormous growth in the penetration of electric vehicles (EVs), has laid the path to advancements in the charging infrastructure. Connectivity between charging stations is an essential prerequisite for future EV adoption to alleviate users’ “range anxiety”. The existing charging stations fail to adopt power provision allocation and scheduling management. To improve the existing charging infrastructure data based on real-time information and availability of reserves at charging stations could be uploaded to the users to help them locate the nearest charging station for an EV. This research article focuses on an a interactive user application developed through SQL and PHP platform to allocate the charging slots based on estimated battery parameters, which uses data communication with charging stations to receive the slot availability information. The proposed server-based real-time forecast charging infrastructure avoids waiting times and its scheduling management efficiently prevents the EV from halting on road due to battery drain out. The proposed model is implemented using a low-cost microcontroller and the system etiquette tested.

Utilizing bioinformatics tools, this study expands our understanding of secondary metabolism in Botrytis cinerea, identifying novel genes within polyketide synthase (PKS), non-ribosomal peptide synthetase (NRPS), sesquiterpene cyclase (STC), diterpene cyclase (DTC), and dimethylal-lyltryptophan synthase (DMATS) families. These findings enrich the genetic framework associ-ated with B. cinerea's pathogenicity and ecological adaptation, offering insights into uncharted metabolic pathways. Significantly, the discovery of previously unannotated genes provides new molecular targets for developing targeted antifungal strategies, promising to enhance crop pro-tection and advance our understanding of fungal biochemistry. This research not only broadens the scope of known secondary metabolites but also opens avenues for future exploration into B. cinerea's biosynthetic capabilities, potentially leading to novel antifungal compounds. Our work underscores the importance of integrating bioinformatics and genomics for fungal research, paving the way for sustainable agricultural practices by pinpointing precise molecular interven-tions against B. cinerea. This study sets a foundation for further investigations into the fungus's secondary metabolism, with implications for biotechnology and crop disease management.

A single paragraph of about 200 words maximum. For research articles, abstracts should give a pertinent overview of the work. We strongly encourage authors to use the following style of structured abstracts, but without headings: (1) Background: Place the question addressed in a broad context and highlight the purpose of the study; (2) Methods: briefly describe the main methods or treatments applied; (3) Results: summarize the article’s main findings; (4) Conclusions: indicate the main conclusions or interpretations. The abstract should be an objective representation of the article and it must not contain results that are not presented and substantiated in the main text and should not exaggerate the main conclusions.

: A comprehensive analysis was performed, considering blockchain technology (BT) proprieties in digital health, addressing medico-legal, privacy, and regulatory considerations. Adherence to personal data protection and healthcare regulatory guidelines were analyzed and compared for GDPR (Europe), HIPAA (United States), CCPA (California), PIPEDA (Canada), Privacy Act of 1988 (Australia), APPI (Japan), and LGPD (Brazil). Issues such as Health Systems, Strengthening and aligning policy orientations and initiatives, and emphasizing the role of data analysis in shaping health policies were explored. The study addressed conflicts between the legal frameworks and blockchain, comparing and suggesting solutions like revision of laws and integration of com-pliance mechanisms. Additionally, it sought to enhance IT-health literacy by integrating healthcare and legal domains. Ongoing collaboration between legal, health, and IT experts is essential for designing systems that effectively balance privacy rights and data protection while maximizing the benefits of disruptive technologies like blockchain.

This paper aims to provide the smart grid research community with an open and accessible general mathematical framework to develop and implement optimal flexibility mechanisms in large-scale network applications. The motivation of this paper is twofold. On the one hand, flexibility mechanisms are currently a hot topic of research, which is aimed to mitigate variation and uncertainty of electricity demand and supply in decentralised grids with a high aggregated share of renewables. On the other hand, a large part of such related research is performed by heuristic methods, which are generally inefficient (such methods do not guarantee optimality) and difficult to extrapolate for different use cases. Alternatively, this paper presents an MPC-based (Model Predictive Control) framework explicitly including a generic flexibility mechanism which is easy to particularise to specific strategies such as Demand Response, Flexible Production and Energy Efficiency Services. The proposed framework is benchmarked with other non-optimal control configurations to better show the advantages it provides. The work of this paper is completed by the implementation of a generic use case which aims to further clarify the use of the framework and thus, to ease its adoption by other researchers in their specific flexibility mechanisms applications.

This paper investigates the use of deep learning techniques to perform energy demand forecasting. Specifically, the authors have adapted a deep neural network originally thought for image classification and composed of a convolutional neural network (CNN) followed by a multilayered fully connected artificial neural network (ANN). The convolutional part of the network was fed with a grid of temperature forecasting data distributed in the area of interest in order to extract a featured temperature. The subsequent ANN is then fed with this calculated temperature along with other data related to the timing of the forecast. The proposed structure was first trained and then used in a real setting aimed to provide the French energy demand forecast using ARPEGE forecasting weather data. The results show that the performance of this approach is in the line of the performance provided by the reference RTE subscription-based service, which opens the possibility to obtain high accuracy forecasting using widely accessible deep learning techniques through open-source machine learning platforms.

This longitudinal study aimed to analyze the effects of a team rowing-based training program on physical fitness and anthropometric parameters in female breast cancer survivors (n=40; 56.78±6.38 years). Participants were divided into two groups: one rowed in fixed seat rowing (FSR) boats (n=20; 56.35±4.89 years) and the other in sliding seat rowing (SSR) boats (n=20; 57.20±7.7 years). Both groups engaged in two 75-minute sessions per week for 24 weeks. Significant improvements were observed in both groups in terms of weight (FSR: -1.93 kg, SSR: -1.75 kg), body mass index (FSR: -0.73 kg/m², SSR: -0.67 kg/m²), waist circumference (FSR: -2.83 cm, SSR: -3.66 cm), and hip circumference (FSR: -2.02 cm, SSR: -2.88 cm). Muscle strength improved in lower extremities (jump test: FSR: 2.99 cm, SSR: 3.11 cm) and upper extremities (dominant: FSR: 4.13 kgf, SSR: 4.34 kgf; non-dominant: FSR: 3.67 kgf, SSR: 3.32 kgf). Aerobic capacity also improved, with the SSR group showing a greater increase (FSR: 63.05 m, SSR: 93.65 m). Flexibility tests revealed better results in the SSR group for both dominant (SSR: 1.75 cm vs. FSR: -5.55 cm) and non-dominant limbs (SSR: 1.72 cm vs. FSR: -3.81 cm). These findings suggest that the type of rowing modality can influence physical fitness outcomes, with the SSR group showing superior improvements compared to the FSR group.

This study presents the design and comprehensive 3D multiphysics simulation of a novel microfluidic immunosensor for real-time, non-invasive monitoring of pro-inflammatory biomarkers in human sweat. The patch-like device, designed using COMSOL Multiphysics, integrates magnetofluidic manipulation with direct-field capacitive sensing. The sensor comprises two distinct units: an immunocomplex enhancement unit, employing a series of microcoils to optimize the binding efficiency, reaction kinetics, and homogeneity of biomarker-magnetic nanoparticle (MNP) interactions, thereby enhancing the sensor's specificity; and a layered capacitive sensing unit, designed to concentrate and detect biomarker-tagged MNPs, thus amplifying sensitivity. Simulations of the capacitive sensing unit revealed a substantial sensitivity increase of up to 42.48\% at an 85\% MNP concentration within the detection zone. These findings highlight the potential of the proposed immunosensor for efficient and precise real-time biomarker monitoring, which may facilitate early disease diagnosis and enable personalized healthcare interventions.

Real-time object detection remains a pivotal topic in the realm of computer vision. Balancing the accuracy and speed of object detectors poses a formidable challenge for both academic researchers and industry practitioners. While recent transformer-based models have showncase the prowess of the attention mechanism, delivering remarkable performance improvements over CNNs, their computational demands can hinder their effectiveness in real-time detection tasks. In this paper, we elect to use YOLOX as our robust starting point and introduce a series of effective enhancements, culminating in a new high-performance detector named YOLOAX. To further exploit the power of the attention mechanism, we devise multi-dimensional attention-based modules that activate CNNs, emphasizing the most pertinent regions and bolstering the capacity to learn the most informative image representations from feature maps. Moreover, we introduce a novel leading label assignment strategy called STA, along with a groundbreaking loss function named GEIOU Loss, to further refine our detector's performance. We provide extensive ablation studies on the COCO and PASCAL VOC 2012 detection datasets to validate our proposed methods. Remarkably, our YOLOAX is trained solely on the MS-COCO dataset from scratch, without leveraging any prior knowledge, which achieves an impressive 54.2% AP on the COCO 2017 test set while maintaining a real-time speed of 72.3 fps, surpassing YOLOX by a significant margin of 3.0% AP. Our source code and pre-trained models are openly accessible at https://github.com/KejianXu/yoloax.

Conventional cancer clinical trials can be time-consuming and expensive, often yielding results with limited applicability to real-world scenarios and presenting challenges for patient participation. Real-world data (RWD) studies offer a promising solution to address evidence gaps and provide essential information about the effects of cancer treatments in real-world settings. Defining RWD based on its original intent, which is the collection of data at the point of care for clinical purposes, can distinguish it from conventional clinical trial data. RWD can be generated using experimental designs that resemble those used in conventional clinical trials, but with several advantages, such as improved efficiency and a better balance between internal and external validity. RWD can support pharmacovigilance, insights into disease progression, and the development of external control groups. Prospective RWD collection enables evidence generation based on pragmatic clinical trials (PCTs) that support randomized study designs and expand clinical research to the point of care. To ensure the quality of real-world studies, it is crucial to implement auditable data abstraction methods and develop new incentives to capture clinically relevant data electronically at the point of care. The treatment landscape is constantly evolving, with the integration of front-line immune checkpoint inhibitors (ICIs), either alone or in combination with chemotherapy, affecting subsequent treatment lines. Real-world effectiveness and safety in underrepresented populations, such as the elderly, patients with poor performance status (PS), hepatitis, or human immunodeficiency virus-infected patients, are still largely unexplored. Similarly, the cost-effectiveness and sustainability of these innovative agents are important considerations in the real world.

Premortem clinical diagnoses and postmortem autopsy findings do not match throughout history. These clinicopathological discrepancies are expected to be raised during the coronavirus disease 2019 (COVID-19) pandemic due to increased pressure on healthcare. At the same time, autopsies and clinicopathological discrepancies accurately display the quality of the healthcare system. To assess that, we examined the relevant works of literature according to the PRISMA-based protocol. As discrepancy rate changes in the correlation to the length of stay in the hospital, we also checked whether studies with patients from the intensive care unit (ICU) differed in discrepancies significantly. We found overall risk differences pretty much alike in "pre-COVID" and "during the pandemic" groups of studies. Based on that, we concluded that healthcare quality did not drop significantly during the pandemic. Be it as it may, the pandemic exposed some shortcomings in mortem healthcare regarding consensus to the autopsy, organ retention, burial, and the postponed burial or the digitalization of post mortem healthcare. All of these issues should be addressed in the future.

The development of biofuels and biodiesel industry specifically, has resulted in the generation of large amounts of glycerol as a surplus. The conversion of glycerol, into chemicals with indus-trial interest, through anaerobic fermentation using E. coli as a biocatalyst is an attractive alter-native to improve economic performance in the biodiesel industry, for example through the bi-otransformation of residual glycerol into ethanol. For 2019, the size of the global ethanol market was valued at $ 89.1 billion US dollar. Biodiesel can be produced from several materials like rapeseed, palm, soya, corn, palm kernel, frying oil or olive-pomace oil (OPO). The last, can be extracted from alperujo, byproduct of olive oil process. However, olive-pomace oil converting into biodiesel is not enough established to achieve a global olive-oil/biodiesel derived process with minimized waste generation. Traditionally biodiesel production process produces an equivalent of 10% by mass of glycerol as a waste or by-product. This work explores the conver-sion of residual glycerol into chemicals like ethanol and hydrogen with a focus on projecting raw material potential availability from OPO, contributing to the promotion of the use of biofu-els and biodegradable compounds.

The systematic sampling is used as a method to get the quantitative results from the tissues and the radiological images. Systematic sampling on real line (R) is a very attractive method within which the biomedical imaging is consulted by the practitioners. For the systematic sampling on R, the measurement function (MF) is occurred by slicing the three-dimensional object equidistant systematically. The currently used covariogram model in variance approximation proposed by [28,29] is tested for the different measurement functions in a class to see the performance on the variance estimation of systematically sampled R. This study is an extension of [17], and an exact calculation method is proposed to calculate the constant λ(q,N) of confidence interval in the systematic sampling. The exact value of constant λ(q,N) is examined for the different measurement functions as well. As a result, it is observed from the simulation that the proposed MF should be used to check the performances of the variance approximation and the constant λ(q,N). Synthetic data can support the results of real data.

The purpose of this longitudinal study was to determine the effects of a rowing training program on physical fitness and body composition in female breast cancer survivors (56.78 ± 6.38 years). Over six months, the participants (n=40) performed two training sessions per week for an average of 75 minutes, combining resistance and muscle strength exercises with rowing. To evaluate the impact of the program, physical fitness tests and anthropometric measurements were carried out before and after the training protocol. The results show statistically significant improvements in measures such as weight (-1.84 kg), BMI (-0.7 kg/m2), hip (-3.24 cm) and waist circumference (-2.45 cm). In addition, variables associated with physical fitness also improved including leg strength (3.04 cm), dominant handgrip strength (4.24 kgf), non-dominant handgrip strength (3.49 kgf), aerobic endurance (78.35 m) and muscle flexibility (3.96 cm). We can therefore conclude that a rowing-based exercise program is an effective strategy to improve physical fitness in this type of population, yielding improvements in both anthropometric measurements and basic physical capacity variables, essential factors for better health and quality of life.

This paper proposes an innovative mechatronic piezo-actuated module to control vibrations in modern machine tools. Vibrations represent one of the main issues that compromise seriously the quality of the workpiece. The active vibration control (AVC) device is composed by a host part integrated with sensors and actuators synchronized by a regulator, able to make a self-assessment and adjust to the environmental alteration. This study presents the mechatronic model based on the kinematic and dynamic analysis of the AVC device. To ensure a real time performance, a H2-LQG controller has been developed and validated by simulations involving machine tool, PZT actuator and controller models. The Hardware-in-the-loop (HIL) architecture is adopted to control and attenuate the vibrations. A set of experimental tests has been performed to validate the AVC module on a commercial machine tool. The feasibility of the real time vibration damping is demonstrated and the simulation accuracy is evaluated.

This paper presents the results of aerodynamical performance research focused on maintaining the thermal comfort and increasing the energy efficiency of a typical social housing unit located in a high-density urban area. Bioclimatic design strategies are used to develop a sustainable and economic technology in existing housing clusters in Mexico City. A full-scale prototype, built on campus facilities, was used to study the flow conditions around the design. All scaled prototypes implement similar criterion. Furthermore, a scaled prototype is evaluated within a low speed wind tunnel installation. Additionally, numerical simulations were performed at transient state based on previous physical measurements and historical local climatic conditions to determine preferable modifications.

Angola is vulnerable to climate change, as most of its agriculture is rain-fed and repre-sents the backbone of the people of the southern region of the country, and many peo-ple’s livelihoods depend on it. All crops can suffer from the impacts of climate change, which can lead to challenges in agricultural production and food security in different regions of the world. The work consisted of a systematic review of the impacts of climate change on agriculture in Angola, particularly in the southern region. To achieve this objective the PRISMA2020 methodology was used, using the flowcharts for the selection of studies evaluated from the databases that are: Scopus and Web Sci-ence, resulting in 431 documents published between 1996 and 2023, and of these only 63 were included in the systematic review, with inclusion and exclusion criteria. Research on the short and long-term effects of climate change impacts in agriculture in Angola and in particular the southern region is scarce and insufficient. Temperatures are pre-dicted to rise and precipitation generally decreases over time (approximately -2% by 2100), with the southern region experiencing a stronger drop in precipitation. Agri-culture in Angola will be hit hard and some models show that agricultural productiv-ity will be up to 7% lower by 2050 owing to climate change.

Several evidences suggest that the positive association between meat intake and colorectal adenoma (CRA) and cancer (CRC) risk is mediated by mutagenic compounds generated during cooking at high temperature. A number of epidemiological studies have estimated the effect of meat-related mutagens intake on CRC/CRA risk with contradictory and sometime inconsistent results. A literature search was carried out (PubMed, Web of Science and Scopus) to identify articles reporting the relationship between the intake of meat-related mutagens (2-amino-1-methyl-6-phenylimidazo[4,5-b]pyridine: PhIP, 2-amino-3,8-dimethylimidazo[4,5-f] quinoxaline: MeIQx, 2-amino-3,4,8-trimethylimidazo[4,5-f] quinoxaline: DiMeIQx, benzo(a) pyrene: (B(a)P) and “meat derived mutagenic activity”: MDM) and CRC/CRA risk. A random-effect model was used to calculate the risk association. Thirty-nine studies were included in the systematic review and meta-analysis. Polled CRA risk (15229 cases) was significantly increased by intake of PhIP (OR=1.20; 95%CI:1.13,1.28; p<0.001), MeIQx (OR=1.14; 95%CI:1.05,1.23; p=0.001), DiMeIQx (OR=1.13; 95%CI:1.05,1.21; p=0.001), B(a)P (OR=1.10; 95%CI:1.02,1.19; p=0.017) and MDM (OR=1.17; 95%CI:1.07,1.28; p=0.001). A linear and curvilinear trend was observed in dose-response meta-analisis between CRA risk in association with PhIP and MDM, MeIQx, respectively. CRC risk (21344 cases) was increased by uptake of MeIQx (OR=1.14; 95%CI:1.04,1.25; p=0.004), DiMeIQx (OR=1.12; 95%CI:1.02,1.22; p=0.014) and MDM (OR=1.12; 95%CI:1.06,1.19; p<0.001). No publication bias could be detected whereas heterogeneity was in some cases rather high. Mutagenic compounds formed during cooking of meat at high temperature may be responsible of its carcinogenicity.

The main objective of this review is to determine the main risks that agricultural workers are exposed to during pesticide application, which may have a harmful effect on their health and on public health. This systematic review was based on the PRISMA guidelines. A search for articles was conducted in the Medline/PubMed, ScienceDirect, and Web of Science databases. Fifteen articles were selected considering their assessment of agricultural workers' knowledge, perceptions, attitudes, practices, and behaviours, identifying the main risks and risk factors for disease associated with the unsafe handling of pesticides. The main risk factors identified were age, education, pesticide safety training, farming experience, and contact with other farmers/intermediaries resulting in pesticide access. The most frequent risk behaviours were: application of pesticides without personal protective equipment (PPE), incorrect disposal of empty packaging and waste, and undervaluation of label information, as well as other unsafe practices. A multidisciplinary and more effective training must be delivered in order to enhance pesticide safe usage. This will empower workers to adopt more conscious and safer behaviours while using pesticides.

The implementation of systems condition monitoring is of utmost importance in ensuring effective maintenance, optimal efficiency, and adherence to established design criteria. This research presents a novel and economically efficient Digital Twin Model (DTM) designed for the purpose of Live Condition Monitoring (LCM) and Predictive Lifecycles. This study discusses the enhancement of DTs modelling by decreasing the number of dimensions from five to three: Physical, Digital, and Connection entities. The resulting model exhibits a notable improvement in accuracy and efficiency. The suggested Dynamic Time Model (DTM) enhances the empirical pre-set average load for both simulation and experimentation by 35.7%, which is equivalent to a 1.6-fold increase. The DTM demonstrates a significant enhancement in the empirical predefined average lifecycles of the system, as shown in the real-life case study. Specifically, the DTM achieves a 12-fold improvement compared to the simulated results and a nine-fold improvement compared to the experimental findings. The suggested Dynamic Time Management (DTM) demonstrates a significant enhancement in the average lifecycles of the system, with a 19.7% improvement (equivalent to 1.2 times greater) compared to the wireless DTM results obtained through the application of the real system load. The suggested Dynamic Time Warping (DTW) method's accuracy and efficiency are shown via a practical case study using the suspension system of a Peugeot 3008 vehicle.

Overweight/obesity is one of the most important health problem worldwide. Birth by cesarean section has been shown to influence long-term health outcome including obesity. The aim of this systematic review-meta-analysis is to examine whether cesarean section increases the risk of offspring’ s overweight/obesity. The study follows the PRISMA and MOOSE guidelines. A systematic literature search was con-ducted on Scopus, PubMed, and WoS until December 2020. For inclusion, studies must have re-ported either (I) both Birth by cesarean section and adult (≥ 18 years) offspring BMI, (II) cohort or case–control study design and (III) a risk estimate. Heterogeneity testing was performed using Cochran's Q and I2 statistics. Publication bias was assessed by Egger’s test and Begg’s test. Me-ta-analysis was performed through a random effect model. Eleven studies with a combined population of 180.408 subjects were included in the meta-analysis. The overall analysis (n = 18) yielded a combined risk estimate for overweight/obesity of 1.19 (95% CI 1.08-1.31) and the test of heterogeneity resulted Q=53,37 (I2 = 70,37 %, P≤0•0001). The risk of offspring obesity is 1.23 (95% CI 1.09-1.39) and the test of heterogeneity resulted Q=39.50 (I2= 72,15%, P≤0•0001). Children born by cesarean section have an increased risk of developing obesity in adulthood

Frosty pod rot, caused by Moniliophthora roreri, is the most damaging disease of cacao in Latin America. However, to better comprehend its epidemiology, we must understand its dissemination and proliferation. Still, we ignore how loads of M. roreri spores fluctuate across growing seasons since we lack a reliable technique to quantify M. roreri spores in the fields. Therefore, we developed a method that uses a spore trap to capture M. roreri spores and qPCR to quantify them. This study demonstrated that this technique could quantify 3.9 x104 M. roreri spores with a 95 % confidence level. However, it could not differentiate between M. roreri and its close relative, M. perniciosa. Despite this limitation, we could detect and quantify Moniliophthora spores from environmental samples taken from a cacao field. This technique can help the phytopathologist address studies more accurately in disseminating cacao pathogens.

Based on the need for real-time sag monitoring of Overhead Power Lines (OPL) for electricity transmission, this article presents the implementation of a hardware and software system for online monitoring of OPL cables and cable sag determination. The mathematical model based on differential equations and the methods of algorithmic calculation of OPL cable sag are presented. Considering that, based on the mathematical model presented, the calculation of OPL cable sag can be done in different ways depending on the sensors used, and the presented application uses a variety of sensors. Therefore, a direct calculation is made using one of the different methods. Subsequently, the verification relations are highlighted directly and, respectively, the calculation by the alternative method, which uses another group of sensors, to generate both a verification of the calculation and the functionality of the sensors, thus obtaining a defect observer of the sensors. The hardware architecture of the OPL cable online monitoring application is presented, together with the main characteristics of the sensors and communication equipment used. The configurations required to transmit data using the ModBUS and ZigBee protocols are also presented. The main software modules of the OPL cable condition monitoring application are described, which ensure the monitoring of the main parameters of the power line and the visualisation of the results both on the electricity provider's intranet using a web server and MySQL database, and on the Internet using an Internet of Things (IoT) server. This categorisation of the data visualisation mode is done in such a way as to ensure a high level of cyber security. Starting from the mathematical model of the OPL cable sag calculation, it goes through the stages of creating such a monitoring system, from the numerical simulations carried out using Matlab to the real-time implementation of this monitoring application. The main modules of the application software are: the software module for reading quantities from the sensor network through a ModBUS Input/Output (I/O) server, the software module for real-time calculation of the OPL cable sag, the software module for read/write operations based on MySQL type data, the software module for transferring data to the user's intranet through a web server, and the software module for viewing data by authorised users based on user and password through an IoT server. The development software environments used are Matlab and Laboratory Virtual Instrument Engineering Workbench (LabVIEW).

This paper investigates the feasibility of a backend design for real-time, multiple-channel processing digital phased array system, particularly for high-performance embedded computing platforms constructed of using general purpose digital signal processors. Frist, we obtained the lab-scale backend performance benchmark from simulating beamforming, pulse compression, and Doppler filtering based on MicroTCA chassis using Serial RapidIO protocol in backplane communication. Next, a field-scale demonstrator of a multifunctional phased array radar is emulated by using the similar configuration. Interestingly, the performance of a barebone design is compared to that of emerging tools that systematically take advantage of parallelism and multicore capabilities, including Open Computing Language.

Analyzing BRCA1/2 tumor pathogenic variants (TPVs) in epithelial tubal/ovarian cancers (EOC) has become an essential part of the diagnostic workflow in many centers to guide treatment options and genetic cascade testing. However, there is no standardization of testing procedures, including techniques, gene assays, or sequencers used, and data on the execution of tumor tests remains scarce. Therefore, we evaluated characteristics of BRCA1/2 tumor testing in advanced-stage EOC with real-world national data. Pathology reports of patients diagnosed with EOC in 2019 in the Netherlands were obtained from the Dutch Pathology Registry (PALGA), and data regarding histological subtype and BRCA1/2 tumor tests were extracted. A total of 999 patients with advanced-stage EOC were included. Tumor tests were performed for 502 patients (50.2%) and BRCA1/2 TPVs were detected in 14.7%. Of all tests, 48.6% used hybrid capture techniques and 26.5% used PCR-based techniques. More than half of the tests (55.0%) analyzed other genes in addition to BRCA1/2. Overall, this study highlights the heterogeneity in the execution of BRCA1/2 tumor tests. Despite a lack of evidence of quality differences, we emphasize that adequate reporting and internal and external quality monitors are essential for high-quality implementation and execution of reliable BRCA1/2 tumor testing, which is crucial for identifying all patients with BRCA1/2 TPVs.

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.

Background. False memories tend to increase in healthy and pathological aging, and their reduction could be useful in improving cognitive functioning. The objective was to use an active-placebo method to verify whether the application of tDCS in improving true recognition and reducing false memories in healthy older people. Method. Participants were 29 healthy older adults (65-78 years old) assigned to active or placebo group; active group received anodal stimulation at 2mA for 20 min over F7. An experimental task was used to estimate true and false recognition. The procedure took place in two sessions on two consecutive days. Results. A mixed ANOVA of true recognition showed a significant main effect of session (p = .004), indicating an increase from before treatment to after it. False recognition showed a significant main effect (p = .004), indicating a decrease from before treatment to after it and a significant session x group interaction (p < .0001). Conclusions. Overall, our results show that tDCS is an effective tool for increasing true recognition and reducing false recognition in healthy older people, and suggest that stimulation improves recall by increasing the number of items a participant can recall and reducing the number of memory errors.

The main purpose of the study was to study the effects of a specific rowing ergometer training program on the athletic performance of young adolescents (n=56; 11.73 ± 1.4 years old) com-pared to a workout based on general strength training. Eight-week training program was im-plemented, with four sessions per week and two-hours per session. Sample was divided in two groups: a control group (CG) that performed circuit training with exercises aimed at building general strength and an experimental group (EG) who focused on specifically training on a rowing ergometer (rowing machine). The data obtained in a rowing meter test over the compe-tition distance were analyzed to obtain the average power attained (W) at the beginning of the training, at the middle (4 weeks), at the end of the training (8 weeks) and one year after the ex-perimentation. The results show that, although both forms of training improve the average W obtained in both categories, the EG subjects (+29.94W) obtained better averages in all phases of the study compared to the CG (+5.88W). Furthermore, this increase was greater in male rowers (+ 34.06W) than in female rowers (+24.54W). These results reveal that a specific rower rowing ergometer training program has a significant effect than a general strength program and these effects can even be observed a year after the intervention.

Despite soccer popularity, comparatively little scientific information is available concerning the assessment of youth players’ physiological characteristics. The use of medical software integrating wearable sensors to provide accurate and objective data is necessary. In the present study, the objective assessment of physical performance of 128 adolescent soccer players at two timepoints (pre-season and end-season) has been performed. Participants completed a comprehensive test battery including stability, countermovement jumps (CMJ), plyometric jumps (PJ), agility, and quick feet tests. A single Inertial Measurement Unit (IMU) sensor provided quantitative data on various performance metrics. Principal Component Analysis (PCA) reduced the dataset to four principal components (PCs) explaining over 80% of the variance: power (PC1), balance (PC2), speed/agility (PC3), and stiffness (PC4). Paired samples t-test between the two timepoints showed no significant differences in the PCs between the two timepoints, indicating that the training program did not significantly alter the assessed physical attributes. However, subtle individual changes may still inform personalized training adjustments. The study highlights the importance of continuous monitoring and individualized training strategies to optimize athlete performance and reduce injury risk.

In this study, the distribution patterns of southern horse mackerel are examined using commercial fine-scale resolution data. Using landings by size category and VMS data from the Portuguese commercial bottom trawl fishery, which consistently targets horse mackerel, this study provides a comprehensive analysis of horse mackerel age distributions spanning a decade (2010-2020). Importantly, the study addresses potential biases in commercial effort data and establishes the usefulness of commercial bottom-trawl gear as a suitable method for sampling and evaluate southern horse mackerel stock dynamics. Ordered regression models were applied to allow for the modelling of the distribution of multiple age categories and investigate spatio-temporal migrations off the Portuguese coast. Southern horse mackerel shows a widespread age distribution range and stable abundance with indications of seasonal and spatial patterns in the distribution of specific age groups. The insights derived from this research contribute valuable knowledge for understanding the dynamics and distribution patterns of fish populations.

This paper introduces actual considerations on the progressive disuse of residential space in the Alpine territory, considering possible actions. Nowadays, the building complexes built around the 60s and 70s (symbol of the mass tourism) fell to be suffering and searching of a new identity: the generation of owners, who bought them, has aged and the propensities of the new generations for holiday in those places have changed, which, moreover, now offer fewer opportunities for leisure, particularly in winter. Due to the great attention (and seeming opportunities) of current incentive policies towards the energy improvement of the existing stock, authors investigate the private conveniences of transformations through the refurbishment of these buildings. Starting from the study of the territory and the dynamics of local population, the research analyses a possible set of energy works, based on the 110% Superbonus tax incentive, introduced by L.D. 34/2020. A large part of the insights is focused on technical and economic feasibility study of the possible actions, following a process based on the evolution of the legislation. The work carried out is based on a specific case study, located in a small municipality in Piedmont mountain area, consisting of three apartment blocks of mostly second homes. The adopted methodology lends itself as a guide for the feasibility study of the Superbonus and, used as a tool for policy evaluation, leads to interesting results from the point of view of both private and public convenience.

Purpose: We aimed to develop a nomogram able to predict treatment failure, skeletal events and overall survival (OS) in patients with castration-resistant prostate cancer with bone metastases (CRPC-BM) treated with Radium-223 dichloride (223Ra). Patients and Methods: Patients from Castilla-La Mancha Spanish region was prospectively included in ChoPET-Rad multicenter study, from January 2015 to December 2022. Patients underwent baseline, interim, and end-of-treatment bone scintigraphy (BS) and 18F-Fluorocholine PET/CT (FCH PET/CT) scans, obtaining multiple imaging radiomics as well as clinical and biochemical variables during follow-up and studying their association with the previously defined end-points. Survival analysis was performed using Kaplan-Meier method and Cox regression. Multivariate logistic and Cox regression models were calculated, and these models were depicted by means of nomograms. Results: Median progression-free survival (PFS) and OS for our population were 4 and 14 months (mo), respectively. The variables that showed the most robust independent significant association with therapeutic failure were baseline alkaline phosphatase (AP) levels (p=0.022) and the characteristics of BM on CT portion of PET/CT (p=0.017). In the case of OS, the significant variables were therapeutic failure (p=0.038), the number of lines received after 223Ra (p

Biopolymer gels have gained tremendous potential for therapeutic applications due to their biocompatibility, biodegradability, and ability to adsorb and bind biological fluids, making them attractive for drug delivery and therapy. The versatility of biopolymer gels in theranostic backgrounds, with a focus on integrating imaging features and facilitating real-time monitoring of drug delivery. Different methods of delivery are explored imaging agents into biopolymer gels, including encapsulation, surface functionalization, nanoparticle encapsulation and layer-by-layer assembly techniques. Integration of Agents and Real-Time Monitoring Drug Delivery We summarize the synthesis methods, general properties, and mechanisms of biopolymer gels functionality, demonstrating their broad applications as multimodal systems for imaging-based therapeutics. These techniques not only enable multiple imaging but also provide signal enhancement and imaging a targeted facilitates, increasing the diagnostic accuracy and therapeutic efficacy. In addition, current techniques for incorporating imaging agents into biopolymer gels are discussed, and their role in precise drug delivery and monitoring.

This paper presents the monitoring of an extremely eroding phenomenon (ravine) near Ciurila, Cluj County, Romania, using UAV (Unmanned Aerial Vehicle) and GNSS (Global Navigation Satellite System) technologies, taking into account the objectives of SDG 15 of the UN resolution, which refers to life on earth. In this sense, the results of a monitoring through sustainable and non-invasive technologies are presented, follo-wing three cycles of observations, carried out between June 2019 and April 2021.The paper aims to present the advantages and limitations of such a study , as well as the importance of monitoring erosion phenomena (in this case, ravines) for the ecosystem, but also for the nearby inhabitants. Software and technologies are used that allow the automatic calculation of the volume of the ravine and the displacements between the different measurement cycles, which allows obtaining objective conclusions and pro-posing further measures.

Collagen is the most abundant protein in the animal kingdom. Industrial collagen is mainly bovine and porcine origin. However, due to religious beliefs, allergic issues, and infectious diseases, alternative sources of collagen as marine are gaining increasing interest. In this work, the acid-soluble collagen (ASC) were extracted from salt-cured Atlantic cod (Gadus morhua) skin and characterized. The extraction yield was about 2.0%, equivalent to the extraction yield reported for other fish skins. The electrophoretic pattern showed the typical type I structure (α, β and γ chains). UV-VIS and FTIR absorbance spectra suggested a very pure ASC with an intact triple helical structure. The integrity and the adequate porosity required for different applications were then confirmed by electron micrograph. Our findings allow us to say that, for the first time, we extracted acid-soluble type I collagen from salt-cured Atlantic cod skin, with characteristics suitable for application in various fields, such as biomedical.

XGBoost is recognized as an algorithm with exceptional predictive capacity. Models for a binary response indicating the existence of accident claims vs. no claims can be used to identify the determinants of traffic accidents. We compare the relative performances of logistic regression and XGBoost approaches for predicting the existence of accident claims using telematics data. The dataset contains information from an insurance company about individuals’ driving patterns – including total annual distance driven and percentage of total distance driven in urban areas. Our findings show that logistic regression is a suitable model given its interpretability and good predictive capacity. XGBoost requires numerous model-tuning procedures to match the predictive performance of the logistic regression model and greater effort as regards interpretation.

Breast cancer is a complex and heterogeneous disease that displays diverse molecular subtypes and clinical outcomes. Although it is known that the location of tumors can affect their biological behavior, the underlying mechanisms are not fully understood. In our previous study, we found a differential methylation profile and membrane potential between left (L) and right (R)-sided breast tumors. In this current study, we aimed to identify the ion channels responsible for this phenomenon and determine any associated phenotypic features. To achieve this, experiments were conducted in mammary tumors in mice, human patient samples, and with data from public datasets. The results revealed that L-sided tumors have a more depolarized state than R-ones. We identified a 6-ion channel-gene signature (CACNA1C, CACNA2D2, CACNB2, KCNJ11, SCN3A, and SCN3B) associated with side: L-tumors exhibit lower expression levels than R-ones. Additionally, in silico analyses show that the signature correlates inversely with DNA methylation writers and with key biological processes involved in cancer progression, such as proliferation and stemness. The signature also correlates inversely with patients’ survival rates. In an in vivo mouse model, we confirmed that KI67 and CD44 markers were increased in L-sided tumors and similar tendency for KI67 was found in patient L-tumors. Overall, this study provides new insights into the potential impact of anatomical location on breast cancer biology and highlights the need for further investigation into possible differential treatment options.

The healthcare sector has undergone a profound transformation, owing to the influential role played by IoMT (Internet of Medical Things) technology. However, there are substantial concerns over these devices' security and privacy-preserving nature. Current literature on IoMT tends to focus on specific security features like data confidentiality or data integrity or data availability or access control and most solutions are simulated and not tested in a real-world live network. This paper proposes a smart secure by design solution that safeguards user’s data during health and wellbeing monitoring of patients locally (home, care-home, and hospital) and remotely. The proposed innovative solution is known as Secure by Design Real Time IoMT Architecture for e-Health Population Monitoring (RTPM) for smart hospitals and any healthcare monitoring management. In this system, keys can also be generated by the patient monitoring system independent to maintain high privacy standard and trust during the monitoring process and to enable the IoMT devices run independently even if the server is compromised and are made safe from external exploits to the client nodes. However, the session keys are controlled by the trusted IoMT server to lighten the IoMT devices overheads and the session keys are securely exchanged between the client system and the monitoring server. The proposed RTPM focuses on addressing the major security requirements for an IoMT system: confidentiality, integrity, availability, conducts authentication, protect from DoS attacks and prevent from non-repudiation attack of patient medical data and the devices in a real time, sensory data communication environment for live e-health monitoring. A secure communication is tested by capturing the live network traffic and the system’s performance analysis of RTPM using different security algorithms with different key sizes of RSA, AES, and SHA shows that resource constraint low powered system can also successfully integrate with high-end state-of-the-art secure parameters and features and have the potential to support real time secure interaction. A stress test is also conducted to ensure that the system can withstand huge key sizes and different data types including multi-media information.

Addressing real-time aircraft target detection in microsatellite-based visible light remote sensing video imaging requires considering the limitations of imaging payload resolution, complex ground backgrounds, and the relative positional changes between the platform and aircraft. These factors lead to multi-scale variations in aircraft targets, making high-precision real-time detection of small targets in complex backgrounds a significant challenge for the detection algorithms. Hence, this paper introduces a real-time aircraft target detection algorithm for remote sensing imaging using an improved lightweight attention mechanism that relies on the YOLOv7 framework (SE-CBAM-YOLOv7). The proposed algorithm replaces the standard convolution (Conv) with a lightweight convolutional SEConv to reduce the computational parameters and accelerate the detection process of small aircraft targets, thus enhancing real-time onboard processing capabilities. Besides, the SEConv-based SPPCSPC (Spatial Pyramid Pooling and Connected Spatial Pyramid Convolution) module extracts image features. It improves detection accuracy while the feature fusion section integrates the CBAM hybrid attention network, forming the CBAMCAT module. Furthermore, it optimizes small aircraft target features in channel and spatial dimensions, improving the model's feature fusion capabilities. Experiments on public remote sensing datasets reveal the proposed SE-CBAM-YOLOv7 improves detection accuracy by 3% and mAP value by 4.2% compared to YOLOv7, significantly enhancing the detection capability for small-sized aircraft targets in satellite remote sensing imaging.

The microbioma is presently one of the hottest areas of scientific and medical research and exerts a marked influence on the host during homeostasis and disease. Fermented foods arise in the human relationship to the microbial environment. Further to the traditionally recognized effects of fermented foods and beverages on the digestive health and well-being there is now strong evidence on their general health benefits, namely the significance on the gut microbiota and brain functionality. We highlight the possibilities in this field, how little is still known, and call for a convergence of interdisciplinary research fields of One Health microbe-nutrition with fermented foods and gut-brain research. A consequence of civilisation, changes in present-day society in diets with more sugar, fat and salt, habits and lifestyle, contributes to the likelihood of an inflammatory microbiome, particularly the global epidemics of obesity and mental health. Although two recent papers claim that probiotics perturb rather than aid in microbiota recovery back to baseline after antibiotic administration in humans, consuming fermented foods has shown to reduce inflammation so improve gut health and the proper function of the body’s immune system.

Brain-Computer Interface (BCI) processes and converts brain signals to provide 20 commands to output devices to carry out certain tasks. The main purpose of BCI is to replace or 21 restore missing or damaged functions of disabled people including neuromuscular disorders like 22 Amyotrophic Lateral Sclerosis (ALS), cerebral palsy, stroke, or spinal cord injury. Hence, BCI does 23 not use neuromuscular output pathways. Scientists have used several techniques like 24 Electroencephalography (EEG), intracortical, and Electrocorticographic (ECoG) to collect brain 25 signals which are used to control robotic arms, prosthetics, wheelchairs, and several other devices. 26 The non-invasive method of EEG is used for collecting and monitoring the signals of the brain. 27 Implementing EEG-based BCI technology in home automation systems may facilitate a wide range 28 of tasks for people with disabilities. It is important to assist and empower individuals with paralysis 29 to engage with existing home automation systems and gadgets in this particular situation. This 30 paper proposed a home security system to control a door and a light using EEG-based BCI. The 31 system prototype consists of the EMOTIV Insight™ headset, Raspberry PI 4, servo motor to 32 open/close the door, and LED. The system can be very helpful for disabled people including arm 33 amputees who cannot close/open doors or use remote control to turn on/turn off doors. The system 34 includes an application made in Flutter to receive notifications on the smartphone related to the 35 status of the door and the LEDs. The disabled person can control the door as well as the LED using 36 his/her brain signals detected by the EMOTIV Insight™ headset.

Objective: to retrospectively evaluate the incidence rate (IR) of echocardiographic signs suspected for pulmonary hypertension (PH) in Systemic sclerosis (SSc) patients after the introduction of a combination therapy with bosentan and sildenafil for treatment or prevention of digital ulcers. Methods: patients attending the Scleroderma Unit of the Universital Hospital of Careggi from July 2010 to July 2023 were enrolled. Patients older than 18 years old, with an history of digital ulcers, treated with bosentan and sildenafil in combination for at least 12 months were included. Patients with a diagnosis of PH preceding the introduction of the therapy were excluded. Demographical data, disease duration, laboratoristic and instrumental data (pulmonary function tests, echocardiographic estimation of pulmonary artery pressure (PAPs) and ultrasonographic value of renal resistive index) were collected. The IR of echocardiographic signs suspected for pulmonary hypertension and their 95% confidence interval were calculated in events/1000 patients-years.Results: forty-seven patients were enrolled; mean disease duration was 12,14 years (SD 5,87). Mean duration of the combination treatment was 78.33 (SD 41.37) months and total at-risk time was 3525 months. Two patients (4,2%) presented echocardiographic signs of PH (sPAP 50 mmHg and 40 mmHg); the IR was calculated to be 6.8/1000 patients-years (95% CI 6,02-7,7). In one of the 2 patients RHC excluded PAH, while the other patient refused to undergo to RHC and PAH could not be confirmed/excluded. A stability of PFTs and echocardiografic PAPs was observed during the observation time. Conclusions: the results of this retrospective study suggest that combination therapy with endothelin receptor antagonist and Phosphodiesterase-5 (PDE5) inhibitors could help in preventing PAH in SSc; prospective case-control studies on larger population are needed to improve knowledge in this field.

Alcohol effects on hepatic lipid metabolism through various mechanisms, leading synergistically to an accumulation of fatty acids (FA) and triglycerides. Obesity, as well as, the dietary fat [saturated fatty acids (FA) versus poly-unsaturated fatty acids (PUFA)] may modulate the hepatic fat. Alcohol inhibits adenosine monophosphate activated kinase (AMPK). AMPK activates peroxisome proliferators activated receptor a (PPARα) and leads to a decreased activation of sterol regulatory element binding protein 1c (SRABP1c). The inhibition of AMPK, and thus of PPARα results in an inhibition of FAs oxidation. This ß-oxidation is further reduced due to mitochondrial damage induced through cytochrome P4502E1 (CYP2E1) driven oxidative stress. Furthermore, the synthesis of FAs is stimulated through an activation of SHREP1. In addition, alcohol consumption leads to a reduced production of adiponectin in adipocytes due to oxidative stress and to an increased mobilization of FAs from adipose tissue and from the gut as chylomicrons. On the other side, the secretion of FAs via very low density lipoproteins (VLDL) from the liver is inhibited by alcohol. Alcohol also affects signal pathways such as early growth response 1 (Egr-1) associated with the expression of tumour necrosis factor  (TNF), and the mammalian target of rapamycin (mTOR) a key regulator of autophagy. Both have influence the pathogenesis of alcoholic fatty liver. Alcohol-induced gut dysbiosis is contributing to the severity of ALD by increasing metabolism of ethanol in the gut and promoting intestinal dysfunction. Moreover, pathogen associated molecular paterns (PAMPS) via specific Toll-like receptors (TLR) bacterial overgrowth is leading to the translocation of bacteria. Endotoxins, and toxic ethanol metabolites enter the enterohepatic circulation reaching the liver, inducing the activation of the nuclear factor kappa-B (NFB) pathway. Pro-inflammatory cytokines released in the process contribute to inflammation and fibrosis. In addition, cellular apoptosis is inhibited in the favor of necrosis.

Dysmenorrhea symptoms are frequent and often self-treated using non-prescription medicines. To further characterize women with dysmenorrhea using a combination of hyoscine butylbromide and paracetamol (PLUS) for self-management of their complaints, we performed a secondary analysis of a published pharmacy-based patient survey. 314 women (mean age 32.3 years) with dysmenorrhea reported a pain and cramps intensity of 7.45 ± 2.13 on a 0-10 Likert scale, which was reduced to 2.86 ± 1.81 upon treatment. Associated impairments of work/daily chores, leisure activities, and sleep were improved by 64.6%, 62.2% and 70.4%, respectively. The onset of symptom relief was within 60 min in 84.7%. Tolerability was rated as very good or good by 97.2%. These findings confirm the efficacy and tolerability data on PLUS from randomized controlled trials in a larger group of women conducting self-management of their dysmenorrhea.

The energy efficiency of existing buildings is a crucial factor in addressing Europe’s energy con-sumption challenges, accounting for nearly 40% of the total energy usage. The ongoing energy crisis, driven by the reliance on fossil fuels and increasing prices, has underscored the urgency of adopting sustainable and energy efficient practices especially to the existing building stock. Cyprus is par-ticularly vulnerable due to its heavy dependence on imported fuels for electricity generation and faces significant challenges in transforming its existing building stock into energy-efficient and sustainable structures. Extensive focus has been made by the government on the energy-efficient retrofit of non-residential public buildings. This study examines an existing cultural hall. The case study of the Cultural Hall represents the building stock before 2010 which is lacking thermal in-sulation, double glazing and any energy efficient element. It then offers an ideal case study to ex-plore sustainable solutions which can be easily adopted from the construction industry and from the building owners. The primary objective of this research is twofold: first, to develop a comprehensive retrofit plan to transform the cultural hall into a net-zero energy building; and second, to explore how this transformation can give value back to the local community. After running two simulation scenarios and providing two energy performance certificates, one with at the existing state and one with the intended retrofit measures, it is clear that the building can be a net zero energy consump-tion building. Some interesting results derived, present also how this building can provide value back to the community i.e. through solar carports for EV charging.

Lactoperoxidase system (LPS) effect on quality of raw and pasteurized milk under real conditions along the dairy value chain in Ethiopia was evaluated. A total of 250 milk samples were collected from farmers, collectors, and factories. Experimental samples were LPS-activated of morning and overnight milk. The samples were tested with several chemical and microbiological tests such as total bacterial count (TBC), total coliform count (TCC) and Escherichia coli count (EC). Results indicated that all LPS-activated milk samples had a higher quality than all the control samples. For instance, both the morning and overnight farm milk samples had a mean TBCs of 5.79 log and 6.55 log cfu/ml which is significantly (p

Because of the large number of parameters that interact in their function, determining dynamic regime parameters as well as the mode of function of amplifying stages is an extremely complex problem. This paper describes a LabVIEW application for studying the functioning of an ampli-fier in various connections. The user selects the generator's parameters, the type of connection and its parameters, as well as the electric charge characteristics. The application can determine both the stage characteristics and the Bode characteristics. The amplifier's stability zone, as well as its gain and phase, are determined based on these characteristics. An important advantage of this application is that the design of the amplifier stage can be made starting from some param-eters that the amplifier can establish, from which the values of components can be determined. In order to validate the simulation results using the LabVIEW application, a specialized program Multisim was used, as well as experimental measurements using the Electronics Explorer Board. Both Multisim and Electronics Explorer Board can determine Bode characteristics. In both simu-lations and experimental amplifiers, the same schemes with the same transistor was used. The application can be used for educational purposes as well as to design the amplifier's stage to achieve specific parameters.

The hazard and the carcinogenic risks due to the exposure to some potentially toxic elements by the Santiago Island (Cape Verde) population where calculated, considering soil ingestion, inhalation and dermal contact as exposure pathways. The topsoil of Santiago Island is enriched in Co, Cr, Cu, Ni, V, Zn, Mn and Cd to upper crust values. Hazard indices (HI) were calculated for these metals and As exposures, of Santiago Island population and the calculations were performed for children and adults. For children HI are higher than 1 for Co, Cr and Mn. So there is indication of potential non-carcinogenic risk for children, due to the high Co (HI=2.995), Cr (HI=1.329) and Mn (HI=1.126), values in soils. For the other elements and for adults there is no potential non-carcinogenic risk. Cancer risk was calculated for As, Cd, Cr and Ni exposures, for adults and children and the results are always lower than the carcinogenic target risk of 1x10-6, for As, Cd, and Ni. However, cancer risk are higher than the carcinogenic target risk for Cr, for adults. Regarding As, for children the fraction due to Riskingestion represents 51.6%, while Riskinhalation represents 48.0% and Riskdermalcontact represents only 0.4% of total risk. For adults Riskinhalation represents 81.3%, Riskingestion represents 16.6% and Riskdermal contact represents 2.1%. These results reflect the higher daily ingestion dose for children and the higher inhalation rate and higher dermal contact surface for adults. For the other elements and for adults the cancer risk due to Cr, Ni and Cd inhalation is always higher than for children, reflecting the higher inhalation rate for adults.

Taste and smell function decline with age, with robust impairment in the very old. Much less is known about taste and smell function in young and middle old. We investigated taste and smell sensitivity via thresholds in a sub-sample of the NutriAct Family Study (NFS), the NFS Examinations cohort (NFSE; N=251, age M=62.5 years). We examined different aspects relating to taste and smell function: the degree to which taste and smell sensitivity relate to another and to taste and smell preferences, the role of gender and age, as well as effects on Quality of Life (QOL). Taste thresholds were highly correlated but no correlation was observed between taste and smell thresholds and between thresholds and preference. Women were more sensitive for both taste and smell than men. We found no effect of age on sensitivity and no effect of sensitivity on QoL. All null-findings were corroborated with Bayesian statistics providing evidence for the null hypotheses. Together our results indicate the independence of taste and smell despite their overlap during sensorial experiences. We found no evidence for age-related sensory decline, which could be due to our sample´s characteristics of non-clinical volunteers with good dental health and 93% non-smokers.

Background: Study to assess glucose levels of people with type 1 diabetes (T1D) overnight based on insulin type and timing. Methods: Real-world, retrospective study in T1D using multiple daily insulin injections. Contin-uous glucose monitoring and insulin injections data were collected for ten hours after dinner us-ing the Insulclock® connected cap. Meal events were identified using ROC detection methodology. The timing of rapid insulin, second injections, and the type of insulin analogs used were evaluat-ed. Results: Nocturnal profiles (n=775, 49 subjects) were analyzed. Higher glucose AUC over 180mg/dL was observed in delayed injections (number; %; mg/dL x h): -45-15min (n=136; 17.5%, 175.9 ±271.0); -15-0min (n= 231; 29.8%, 164.0 ±237.1); 0+45min (n= 408; 52.6%, 203.6 ±260.9), (p 0.049). The use of ultrarapid (FiAsp®) (URI) vs rapid insulin analogs (RI) was associated with less hypoglycemia events (7.1 vs 13.6%; p 0.005) and TBR70 (1.7 +6.9 vs 4.6 +13.9%; p 0.003). Us-ers of glargine U300 vs degludec had higher TIR (70.7 vs 58.5 %) (Adjusted R-squared: 0.22, p < 0.001). The use of a correction injection (n= 144, 18.6%) was associated with higher hypoglycemia events (18.1 vs 9.5%; p 0.003), TBR70 (5.5 +14.2 vs 3.0 +11.1%; p 0.003), glucose AUC over 180 mg/dL (226.1 +257.8 vs 178.0 +255.3 mg/dL x h; p 0.001), and lower TIR (56.0 +27.4 vs 62.7 +29.6 mg/dL x h; p 0.004). Conclusions: Dinner rapid insulin timing, insulin types and correction injections affect nocturnal glucose profile in T1D.

The consequences of a fall on an elderly person can be reduced if the accident is attended by medical personnel within the first hour. Independent elderly people use to stay alone for long periods of time, being in more risk if they suffer a fall. The literature offers several approaches for detecting falls with embedded devices or smartphones using a triaxial accelerometer. Most of these approaches were not tested with the target population, or are not feasible to be implemented in real-life conditions. In this work, we propose a fall detection methodology based on a non-linear classification feature and a Kalman filter with a periodicity detector to reduce the false positive rate. This methodology requires a sampling rate of only 25 Hz; it does not require large computations or memory and it is robust among devices. We test our approach with the SisFall dataset achieving 99.4% of accuracy. Then, we validate it with a new round of simulated activities with young adults and an elderly person. Finally, we give the devices to three elderly persons for full-day validations. They continued with their normal life and the devices behaved as expected.

Severe malaria is a major public health concern in Angola, particularly among adults, with limited data on clinical outcomes and manifestations. The study therefore assessed the clinical manifestations and outcome of severe Plasmodium falciparum malaria in adult patients admitted to Hospital Central Dr. António Agostinho Neto of Lubango, Angola. The study retrospectively reviewed the individual records of patients over 14 years old, admitted for severe malaria during the first trimester of 2021 and 2022. World Health Organization (WHO) criteria were used to define severity. A total of 640 patients were recorded into the study, 167 in 2021 and 473 in 2022, distributed across the departments; Intensive Care Unit (ICU; n=81), Medicine (MED; n=458) and Infectiology (INF; n=101). The median age was 26 years and 59.4% were males. The most common manifestation of severe malaria was renal impairment (37.4%). The overall mortality rate was 7% and decreased considerably from 10.2% in 2021 to 5.9% in 2022. The increase in malaria cases during 2022 with increased in prevalence of life-threatening signs like renal impairment, jaundice and impaired conscience, underscores the urgent need for enhanced malaria control and surveillance strategies to mitigate morbidity and mortality, highlighting the potential for antimalarial drug resistance.

Viral variant analysis is a bedrock of the disease surveillance. When combined with temporospatial analysis variant analysis can further the knowledge of disease spread in a study area. This paper suggests a method to perform the analysis in an operational setting which will allow for real-time surveillance of viral variants and allow local public health professionals to rapidly respond to changes in the evolution of the disease. This method includes three main subprocesses: preprocessing, analysis, and rendering. This method can be performed across multiple software platforms. A use case is given in which it was found that this method helped a hospital system understand the spread of SARS-CoV-2 in Northeast, Ohio.

Real-world evidence (RWE) is increasingly involved in the early benefit assessment of medicinal drugs. It is expected that RWE will help to speed up approval processes comparable to RWE developments in vaccine research during the COVID-19 pandemic. Definitions of RWE are diverse marking the highly fluid status in this field. So far, RWE comprises information produced from data routinely collected on patient’s health status and/or delivery of health care from various sources other than traditional clinical trials. These sources can include electronic health records, claims, patient-generated data including in home-use settings, data from mobile devices as well as patient, product and disease registries. The aim of the present update was to review the current RWE developments and guidelines mainly in the U.S., the UK, Europe and Germany field during the last decade. RWE has already been included in various approval procedures of regulatory authorities reflecting its actual acceptance and growing importance in evaluating and accelerating new therapies. However, since the RWE research is still in a transition process and since a number of gaps in this field have been explored, more guidance and a consented definition are necessary to increase the implementation of real-world data.

The coronavirus disease (COVID-19) is a respiratory tract infection caused by the new virus SARS-CoV-2. In March 2020, the World Health Organization (WHO) declared a worldwide COVID-19 pandemic. Since then, there has been a rush to find preventative or curative treatment. This arrived with the appearance of the COVID-19 vaccine, months after the declaration of the pandemic. In the setting of global COVID-19 immunization, there have been reports of rare skin immune-mediated diseases (IMD) after COVID-19 vaccination, particularly systemic sclerosis. Systemic sclerosis (SSc) is the most reported new onset IMD following messenger RNA (mRNA) COVID-19 vaccination. The pathogenesis of SSc is not fully understood, and the diagnosis is based on clinical symptoms. We report a 54-year-old male, with no prior history of autoimmune disorder, with rapid and progressive skin thickening (Modified Rodnan skin score 30/51), weeks after his mRNA COVID-19 vaccination. Antinuclear antibodies (ANA) showed a strongly positive nuclear fine-speckled pattern, but no SSc autoantibodies were found. The patient was diagnosed with SSc based on the persistence of autoantibodies and the clinical criteria according to the 2013 American College of Rheumatology/European League Against Rheumatism classification. Due to the proximity of the two events, we hypothesized a cross-reaction between COVID-19 vaccination and, in genetically predisposed patients, an emergence of systemic sclerosis. Our case suggests a potential relationship between the mRNA COVID-19 vaccine and new-onset autoimmune diseases. Physicians should be aware of this possible association.

The incidence of gastrointestinal diseases (cancer in particular) has increased progressively with considerable morbidity, mortality, and a high economic impact on the healthcare system. Dietary intake of natural bioactive phytochemicals showed to have cancer-preventing and therapeutic effects. This includes the cruciferous vegetable derivative phenethyl isothiocyanate (PEITC), a bioactive compound from watercress. PEITC antioxidant, anti-inflammatory and anti-cancer properties are of particular importance. This review summarizes the current knowledge on the role of PEITC as a potential natural nutraceutical or an adjuvant against oxidative/inflammatory-related disorders in the gastrointestinal tract. We also discuss the safe and recommended dose of PEITC. Besides, we establish a framework to guide the research and development of sustainable methodologies for obtaining and stabilizing this natural nutraceutical for industrial use. This is a topic that still needs more scientific development, but with the potential to lead to a viable strategy in the prevention of cancer and other associated diseases of the gastrointestinal tract.

As part of a project ordered by the Ministry of Science, Technology and Innovation of Brazil, an assessment of Brazilian biological collections was conducted by the Brazilian Societies of Botany, Microbiology, Virology and Zoology to obtain data on the current state of these collections. The goal was to provide subsidies for future public policies, including financial support and prioritization policies. Herein, we present the results of the microbiological collections, which play a fundamental role in the ex situ conservation of biodiversity and support research, development and innovation. A survey was sent to public and private institutions in Brazil and answered by 168 microbiological collections from 79 different institutions. Among these, 73 comprise public research institutions and universities, demonstrating the State's importance in preserving and safeguarding Brazilian microbial diversity. The main taxonomic groups are bacteria (present in 70.24% of the collections) and fungi (52.98% of the collections) from different Brazilian ecosystems and biomes, including several type strains. Furthermore, the collections preserve microorganisms with biotechnological potential for application in environmental protection, public health, industry, and agribusiness. However, despite all these economic and biotechnological potentials, the data analysis showed serious limitations and fragilities, especially regarding physical infrastructure and human resources, and raises alerts about the risk that Brazilian collections are subjected to.

Buttonweed (Cotula coronopifolia) is native to South Africa but invasive in wetlands in Europe, North America, and Australasia, where it excludes native plants. Despite being dry-fruited, field studies suggest migratory waterbirds can disperse its seeds via gut passage (endozoochory), aiding its expansion. To explore the potential for endozoochory in different regions and habitats, we collected seeds from six populations in Spain, Sweden, and the UK. Germination was tested under different salinity levels (0, 5, 10, 15 g/L) and simulated gut passage treatments: scarification, acidification, or both. No germination occurred at 15 g/L. Higher salinity reduced and delayed germination, but full gut passage treatment increased germinability and accelerated germination. Scarification or acid treatment alone resulted in intermediate germination patterns. There were significant salinity x population and gut passage x population interactions on germinability. The acceleration effect of gut passage on germination was stronger at 5-10 g/L than at 0 g/L. This study highlights how migratory birds can facilitate the spread of alien plants introduced by humans. Non-classical endozoochory by waterbirds is an understudied mechanism for the long-distance dispersal of dry-fruited alien plants. Further research on C. coronopifolia, including population genetics, is necessary to understand dispersal mechanisms and facilitate management strategies.

Seeing atomic configuration of single organic nanoparticles at sub-Å spatial resolution by transmission electron microscopy has been so far prevented by the high sensitivity of soft matter to radiation damage. The difficulty is related to the need to irradiate the particle with a total dose of few electrons/Å2, not compatible with the electron beam density necessary to search the low-contrast nanoparticle, to control its drift, to finely adjust the electro-optical conditions and particle orientation, and to finally acquire an effective atomic resolution image. On the other hand, the capability to study individual pristine nanoparticles, such as proteins, active pharmaceutical ingredients, and polymers, with peculiar sensitivity to the variation of the local structure, defects, and strain, would provide advancements in many fields, including materials science, medicine, biology, and pharmacology. Here we report direct sub-ångström resolution imaging at room temperature of pristine unstained crystalline polymer-based nanoparticles. This result is obtained by combining low-dose in-line electron holography and phase-contrast imaging on state-of-the-art equipment, providing an effective tool for the quantitative sub-angstrom imaging of soft matter.

The kidney and the heart work together in balancing the body circulation and although their physiology is based on strict inter dependence, their performance fulfills different aims. While the heart can rapidly increase its own oxygen consumption to comply with the wide changes in metabolic demand linked to body function, the kidney physiology is primarily designed to maintain a stable metabolic rate and has limited capacity to cope with any steep increase in renal metabolism. In the kidneys the glomerular population filters a large amount of blood and the tubular system has been programmed to reabsorb 99% of filtrate by reabsorbing sodium together with other filtered substances including all glucose molecules. Glucose reabsorption involves the sodium-glucose cotransporters SGLT2 and SGLT1 on the apical membrane in the proximal tubular section; it also enhances bicarbonate formation so as to preserve the acid-base balance. The complex work of reabsorption in the kidney is the main factor in renal oxygen consumption; analysis of renal glucose transport in disease states is providing better understanding of the renal physiology changes that occur when clinical conditions alter the neurohormonal response leading to an increase in glomerular filtration pressure. In this circumstance glomerular hyperfiltration occurs, imposing a higher metabolic demand on kidney physiology and causing progressive renal impairment. Albumin urination is the warning signal of renal engagement over-exertion and most frequently heralds heart failure development, regardless of disease etiology. The review analyzes the mechanisms linked to renal oxygen consumption, focusing on sodium-glucose management.

Oscillations in global modes of variability (MoV) form global teleconnections that affect regional climate variability and modify the potential for severe and damaging weather conditions. Understanding the link between certain MoVs and regional climate can improve the ability to more accurately predict environmental conditions that impact human life and health. In this study, we explore the connection between different MoVs, including the Arctic Oscillation (AO), Eurasian teleconnection, Indian Ocean Dipole (IOD), North Atlantic Oscillation (NAO), and El Niño Southern Oscillation (Nino34), with winter and summer climate in the High Mountain Asia (HMA) region, including geopotential height at 250 hPa (z250), 2-m air temperature (T2M), total precipitation (PRECTOT), and fractional snow cover area (fSCA). Relationships are explored for the same monthly period between the MoVs and the climate variables, but also using a lagged correlation analysis to investigate whether any relationship exists at different time lags. We find that T2M has a negative correlation with the Eurasian teleconnection in the Inner Tibetan Plateau and Central China in both winter and summer and a positive correlation in Western China in summer. PRECTOT has a positive correlation with all MoV in most regions in winter, especially with the IOD, and a negative correlation in summer, especially with the Eurasian teleconnection. Snow cover in winter is positively correlated with most indices throughout many regions in HMA, likely due to wintertime precipitation also being positively correlated with most indices. Generally, the AO and NAO show similar correlation patterns with all climate variables, especially in the winter, possibly due to their oscillations being so similar. Furthermore, the AO and NAO are shown to be less significant in explaining the variation in HMA climate compared to other MoVs such as the Eurasian teleconnection. Overall, our results pinpoint different time-windows and specific regions within HMA that exhibit high correlation between climate and MoVs, which might offer additional predictability of the MoVs as well as of climate and weather patterns in HMA and throughout the globe.

We analyze real telematics information for a sample of drivers with usage-based insurance policies. We examine the statistical distribution of distance driven above the posted speed limit – which presents a strong positive asymmetry – using quantile regression models. We find that, at different percentile levels, the distance driven at speeds above the posted limit depends on total distance driven and, more generally, on such factors as the percentages of urban and nighttime driving and on the driver’s gender. However, the impact of these covariates differs according to the percentile level. We stress the importance of understanding telematics information, which should not be limited to simply characterizing average drivers, but can be useful for signaling dangerous driving by predicting quantiles associated with specific driver characteristics. We conclude that the risk of driving long distances above the speed limit is heterogeneous and, moreover, we show that prevention campaigns should target primarily male, non-urban drivers, especially if they present a high percentage of nighttime driving.

Computer vision is a powerful technology that has enabled solutions in various fields by analyzing visual attributes in images. One field that has taken advantage of computer vision is agricultural automation, which promotes high-quality crop production. The nutritional status of a crop is a crucial factor in determining its productivity. This status is mediated by approximately 14 chemical elements acquired by the plant, and their determination plays a pivotal role in farm management. To address the timely identification of nutritional disorders, this study focuses on the classification of three levels of phosphorus deficiencies through individual leaf analysis. The methodological steps include: (1) generating a database with laboratory-grown maize plants that were induced to total phosphorus deficiency, medium deficiency, and total nutrition, using different capture devices; (2) processing the images with state-of-the-art transfer learning architectures (i.e. VGG16, ResNet50, GoogLeNet, DenseNet201, and MobileNetV2); and (3) evaluating the classification performance of the models using the created database. The results show that the VGG16 model achieves superior performance, with 98% classification accuracy. However, the other studied architectures also demonstrate competitive performance and are considered state-of-the-art automatic leaf deficiency detection tools. The proposed method can be a starting point to fine-tune machine vision-based solutions tailored for real-time monitoring of crop nutritional status.

Dynamic virtual testing by Hardware in the Loop (HIL) real time simulation systems is common to minimize physical tests to validate and verify control algorithms, logics and software, under normal and emergency conditions. The accurate but costly HIL models setup activities could have an extended use to simulate faulty conditions that are seldom observable in the real system, yet they must be detected in advance and recognized. Data driven diagnostic methods have reached a mature development, in various sectors, proving effective in early detecting slowly varying deviations from nominal patterns of signals, even without a priori knowledge of their nature and behavior. These methods rely on vast amount of data logged from real systems that are ever and ever richer of monitoring telemetries that are worth being exploited. However, due to the usually reliable and safe systems being managed, it is often difficult to collect enough data on anomalous situations to validate fault detection and isolation and limit false positives. HIL model-based simulations allow generating and observing operational domains or transients rarely observed in real operations. This allows identifying the signals that are most correlated to faults and that could be selected to setup data-based diagnostic models of parts or subsystems, which are more suitable than the whole HIL model for online diagnostics, as well as to identify the features and trends that are most symptomatic of anomalous conditions.

We extend the concept of metallic ratios to the real argument n considered as a dimension by analytic continuation showing that they are defined by an argument of a normalized complex number, and for rational n ≠ {0, ±2}, they are defined by Pythagorean triples. We further extend the concept of metallic ratios to metallic angles.