Artificial intelligence (AI) has been implemented in multiple fields of medicine to assist in the diagnosis and treatment of patients. AI implementation in radiology, more specifically for breast imaging, has advanced considerably. Breast cancer is one of the most important causes of cancer mortality among women, and there has been increased attention towards creating more efficacious methods for breast cancer detection utilizing AI to improve radiologist accuracy and efficiency to meet the increasing demand of our patients. AI can be applied to imaging studies to improve image quality, increase interpretation accuracy, and improve time efficiency and cost efficiency. AI applied to mammography, ultrasound, and MRI allows for improved cancer detection and diagnosis while decreasing intra- and interobserver variability. The synergistic effect between a radiologist and AI has the potential to improve patient care in underserved populations with the intention of providing quality and equitable care for all. Additionally, AI has allowed for improved risk stratification. Further, AI application can have treatment implications as well by identifying upstage risk of ductal carcinoma in situ (DCIS) to invasive carcinoma and by better predicting individualized patient response to neoadjuvant chemotherapy. AI has potential for advancement in pre-operative 3-dimensional models of the breast as well as improved viability of reconstructive grafts. Full article

The concept of symmetry has played a major role in Hilbert space setting owing to the structure of a complete inner product space. Subsequently, different studies pertaining to symmetry, including symmetric operators, have investigated real Hilbert spaces. In this paper, we study the solutions to multiple-set split feasibility problems for a pair of finite families of $\beta$-enriched, strictly pseudocontractive mappings in the setup of a real Hilbert space. In view of this, we constructed an iterative scheme that properly included these two mappings into the formula. Under this iterative scheme, an appropriate condition for the existence of solutions and strong and weak convergent results are presented. No sum condition is imposed on the countably finite family of the iteration parameters in obtaining our results unlike for several other results in this direction. In addition, we prove that a slight modification of our iterative scheme could be applied in studying hierarchical variational inequality problems in a real Hilbert space. Our results improve, extend and generalize several results currently existing in the literature. Full article

In brain tumor surgery, maximal tumor resection is typically desired. This is complicated by infiltrative tumor cells which cannot be visually distinguished from healthy brain tissue. Optical methods are an emerging field that can potentially revolutionize brain tumor surgery through intraoperative differentiation between healthy and tumor tissues. This study aimed to systematically explore and summarize the existing literature on the use of Raman Spectroscopy (RS), Hyperspectral Imaging (HSI), Optical Coherence Tomography (OCT), and Diffuse Reflectance Spectroscopy (DRS) for brain tumor detection. MEDLINE, Embase, and Web of Science were searched for studies evaluating the accuracy of these systems for brain tumor detection. Outcome measures included accuracy, sensitivity, and specificity. In total, 44 studies were included, covering a range of tumor types and technologies. Accuracy metrics in the studies ranged between 54 and 100% for RS, 69 and 99% for HSI, 82 and 99% for OCT, and 42 and 100% for DRS. This review provides insightful evidence on the use of optical methods in distinguishing tumor from healthy brain tissue. Full article

The advancement of novel water treatment technologies requires the implementation of both accurate data measurement and recording processes. These procedures are essential for acquiring results and conducting thorough analyses to enhance operational efficiency. In addition, accurate sensor data facilitate precise control over chemical treatment dosages, ensuring optimal water quality and corrosion inhibition while minimizing chemical usage and associated costs. Under this framework, this paper describes the sensoring and monitoring solution for a hybrid system based on a cooling tower (CT) connected to mechanical vapor compression (MVC) equipment for desalination and brine concentration purposes. Sensors connected to the data commercial logger solution, Almemo 2890-9, are also discussed in detail such as temperature, relative humidity, pressure, flow rate, etc. The monitoring system allows remote control of the MVC based on a server, GateManager, and TightVNC. In this way, the proposed solution provides remote access to the hybrid system, being able to visualize gathered data in real time. A case study located in Cartagena (Spain) is used to assess the proposed solution. Collected data from temperature transmitters, pneumatic valves, level sensors, and power demand are included and discussed in the paper. These variables allow a subsequent forecasting process to estimate brine concentration values. Different sample times are included in this paper to minimize the collected data from the hybrid system within suitable operation conditions. This solution is suitable to be applied to other desalination processes and locations. Full article

Based on 208 city-level data in China, this paper empirically analyzes the impact of ESG rating on carbon emissions through the SDM spatial metrology model, identifies the direct and indirect consequences and spatial spillover effects of ESG rating on carbon emissions, and compares the regional heterogeneity and city-size heterogeneity of such impacts. This paper draws three conclusions: (1) Empirical evidence shows that the ESG rating performance of enterprises has a significant inhibition effect on carbon dioxide emissions. Specifically, when the ESG rating performance increases by 1%, carbon emissions will decrease by 0.076; among other control variables, the effect of FDI on carbon emission reduction is that when ESG score performance increases by 1%, carbon emission decreases by 0.022. (2) In the decomposition of the total effects, indirect effects and direct effects have the same impact on carbon emissions, and the total effect is −0.393. (3) The inhibition effect is more significant in the Eastern Region and in megacities, where the effect of −0.096 in the Eastern Region is more obvious than that of −0.078 at the national level, and the effect of carbon reduction in megacities is significantly greater than 0.013 in big cities. This suggests regional heterogeneity in regards to the role of ESG ratings in reducing CO2 emissions. This paper reveals the specific effects and internal logic of the impact of ESG performance on CO2 emissions, which has certain implications for various regions to further promote the construction of an ESG system, according to local conditions, and to encourage enterprises to focus on emission reduction and high-quality development. Full article

Concept mapping is a valuable method to represent a domain of knowledge, also with the aim of supporting educational needs. Students are called upon to construct their own knowledge through a meaningful learning process, linking new concepts to concepts they have already learned, i.e., connecting new knowledge to knowledge they already possess. Moreover, the particular graphic form of a concept map makes it easy for the teacher to construct and interpret both. Consequently, for an educator, the ability to assess concept maps offered by students, facilitated by an automated system, can prove invaluable. This becomes even more apparent in educational settings where there is a large number of students, such as in Massive Open Online Courses. Here, we propose two new measures devised to evaluate the similarity between concept maps based on two deep-learning embedding models: InferSent and Universal Sentence Encoder. An experimental evaluation with a sample of teachers confirms the validity of one such deep-learning model as the baseline of the new similarity measure. Subsequently, we present a proof-of-concept dashboard where the measures are used to encode a concept map in a 2D space point, with the aim of helping teachers monitor students’ concept-mapping activity. Full article

This article presents an original method for minimising the energy expenditure of electric vehicles used in municipal service undertakings, taking into account the uncertainty in the functioning of their charging points. The uncertainty of the charging points’ operation was presented as the probability of the occurrence of an emergency situation hindering a point’s operation, e.g., a breakdown or lack of energy supply. The problem is how to calculate the driving routes of electric vehicles so that they will arrive at charging points at times at which there is a minimal probability of breakdowns. The second aspect of this problem to be solved is that the designated routes are supposed to ensure the minimum energy expenditure that is needed for the vehicles to complete the tasks assigned. The developed method is based on two heuristic algorithms, i.e., the ant algorithm and genetic algorithms. These algorithms work in a hybrid combination, i.e., the ant algorithm generates the initial population for the genetic algorithm. An important element of this method is the decision-making model for defining the driving routes of electric vehicles with various restrictions, e.g., their battery capacity or the permissible risk of charging point breakdown along the routes of the vehicles. The criterion function of the model was defined as the minimisation of the energy expenditure needed by the vehicles to perform their transport tasks. The method was verified against real-life data, and its effectiveness was confirmed. The authors presented a method of calibrating the developed optimisation algorithms. Theoretical distributions of the probability of charging point failure were determined based on the Statistica 13 program, while a graphical implementation of the method was carried out using the PTV Visum 23 software. Full article

Novel therapies for the treatment of familial dilated cardiomyopathy (DCM) are lacking. Shaping research directions to clinical needs is critical. Triggers for the progression of the disorder commonly occur due to specific gene variants that affect the production of sarcomeric/cytoskeletal proteins. Generally, these variants cause a decrease in tension by the myofilaments, resulting in signaling abnormalities within the micro-environment, which over time result in structural and functional maladaptations, leading to heart failure (HF). Current concepts support the hypothesis that the mutant sarcomere proteins induce a causal depression in the tension-time integral (TTI) of linear preparations of cardiac muscle. However, molecular mechanisms underlying tension generation particularly concerning mutant proteins and their impact on sarcomere molecular signaling are currently controversial. Thus, there is a need for clarification as to how mutant proteins affect sarcomere molecular signaling in the etiology and progression of DCM. A main topic in this controversy is the control of the number of tension-generating myosin heads reacting with the thin filament. One line of investigation proposes that this number is determined by changes in the ratio of myosin heads in a sequestered super-relaxed state (SRX) or in a disordered relaxed state (DRX) poised for force generation upon the Ca²⁺ activation of the thin filament. Contrasting evidence from nanometer–micrometer-scale X-ray diffraction in intact trabeculae indicates that the SRX/DRX states may have a lesser role. Instead, the proposal is that myosin heads are in a basal OFF state in relaxation then transfer to an ON state through a mechano-sensing mechanism induced during early thin filament activation and increasing thick filament strain. Recent evidence about the modulation of these mechanisms by protein phosphorylation has also introduced a need for reconsidering the control of tension. We discuss these mechanisms that lead to different ideas related to how tension is disturbed by levels of mutant sarcomere proteins linked to the expression of gene variants in the complex landscape of DCM. Resolving the various mechanisms and incorporating them into a unified concept is crucial for gaining a comprehensive understanding of DCM. This deeper understanding is not only important for diagnosis and treatment strategies with small molecules, but also for understanding the reciprocal signaling processes that occur between cardiac myocytes and their micro-environment. By unraveling these complexities, we can pave the way for improved therapeutic interventions for managing DCM. Full article

Molecular biomarkers are central to personalised medicine for human cancer patients. It is gaining traction as part of standard veterinary clinical practice for dogs and cats with cancer. Molecular biomarkers can be somatic or germline genomic alterations and can be ascertained from tissues or body fluids using various techniques. This review discusses how these genomic alterations can be determined and the findings used in clinical settings as diagnostic, prognostic, predictive, and screening biomarkers. We showcase the somatic and germline genomic alterations currently available to date for testing dogs and cats in a clinical setting, discussing their utility in each biomarker class. We also look at some emerging molecular biomarkers that are promising for clinical use. Finally, we discuss the hurdles that need to be overcome in going ‘bench to bedside’, i.e., the translation from discovery of genomic alterations to adoption by veterinary clinicians. As we understand more of the genomics underlying canine and feline tumours, molecular biomarkers will undoubtedly become a mainstay in delivering precision veterinary care to dogs and cats with cancer. Full article

Mesenchymal stem cells (MSCs) have garnered significant interest in the field of regenerative medicine for their ability to potentially treat various diseases, especially neurodegenerative disorders [...] Full article

The layered double hydroxides (LDHs) of transition metals are of great interest as building blocks for the creation of composite photocatalytic materials for hydrogen production, environmental remediation and other applications. However, the synthesis of most LDHs is reported only by the conventional coprecipitation method, which makes it difficult to control the catalyst’s crystallinity. In the present study, ZnCr- and NiCr-LDHs have been successfully prepared using a facile hydrothermal approach. Varying the hydrothermal synthesis conditions allowed us to obtain target products with a controllable crystallite size in the range of 2–26 nm and a specific surface area of 45–83 m²∙g⁻¹. The LDHs synthesized were investigated as photocatalysts of hydrogen generation from aqueous methanol. It was revealed that the photocatalytic activity of ZnCr-LDH samples grows monotonically with the increase in their average crystallite size, while that of NiCr-LDH ones reaches a maximum with intermediate-sized crystallites and then decreases due to the specific surface area reduction. The concentration dependence of the hydrogen evolution activity is generally consistent with the standard Langmuir–Hinshelwood model for heterogeneous catalysis. At a methanol content of 50 mol. %, the rate of hydrogen generation over ZnCr- and NiCr-LDHs reaches 88 and 41 μmol∙h⁻¹∙g⁻¹, respectively. The hydrothermally synthesized LDHs with enhanced crystallinity may be of interest for further fabrication of their nanosheets being promising components of new composite photocatalysts. Full article

Water availability is a local issue of growing importance in Mediterranean areas where water scarcity linked to climate change and population growth is already leading to increased competition for this resource. This study is aimed at the following: (i) assessing the water-related environmental impacts (water use, freshwater ecotoxicity and eutrophication, marine eutrophication, acidification, human toxicity, and ionizing radiation) along the production chain of cow milk in Catalonia, northeastern Spain; and (ii) addressing the issues encountered (modelling choices, data gaps and inconsistencies) which t can affect the quality of results when performing a water-footprint comprehensive assessment, focusing on water use and associated water scarcity impacts. The scope included the process from the extraction of raw materials up to the distribution of the packaged fat- and protein-corrected milk to the distribution centres of the supermarket chains and markets. Results showed the farm stage to be determinant (contributing to over 60% of the impact), due to the impact of feed production. Impact results were in the range of the European benchmark given by the Product Environmental Footprint Category Rules for dairy products, except for the water scarcity footprint which was one order of magnitude larger than the reference value, due to water scarcity in Spain. Considering compound feed ingredients with a lower water scarcity footprint, and research into slurry treatment for its use as irrigation and cleaning water (without compromising safety and health) could help reduce this impact. Water accounting and traceability along the production chain could support the dairy industry to take responsibility for the consequences of their production choices. Full article

The optimization of the affinity of monoclonal antibodies is crucial for the development of drug candidates, as it can impact the efficacy of the drug and, thus, the dose and dosing regimen, limit adverse effects, and reduce therapy costs. Here, we present the affinity maturation of an EGFR×PD-L1 Two-in-One antibody for EGFR binding utilizing site-directed mutagenesis and yeast surface display. The isolated antibody variants target EGFR with a 60-fold-improved affinity due to the replacement of a single amino acid in the CDR3 region of the light chain. The binding properties of the Two-in-One variants were confirmed using various methods, including BLI measurements, real-time antigen binding measurements on surfaces with a mixture of both recombinant proteins and cellular binding experiments using flow cytometry as well as real-time interaction cytometry. An AlphaFold-based model predicted that the amino acid exchange of tyrosine to glutamic acid enables the formation of a salt bridge to an arginine at EGFR position 165. This easily adaptable approach provides a strategy for the affinity maturation of bispecific antibodies with respect to the binding of one of the two antigens. Full article

We define the digital economy as all economic activities conducted through the use of information technologies, including activities to create new markets, expand old ones, and produce digital goods and services. The digital economy has become a major driver of sustainable development and the transition towards a greener economy. However, studies show an unequal level of progress among cities, regions, and countries. Consequently, this paper explores the associations between socio-cultural factors (such as attitudes towards marriage/raising a family) and components of the digital economy (such as expenses/investment in ICT and the proportion of personal computers and the Internet in households). This study specifically examines twenty-two ethnic minority regions in Russia with data covering a five-year period. Using the Pearson correlation coefficient, the results show that socio-cultural factors including a large urban population and high divorce rates were positively associated with the digital economy, whereas a large rural population, higher birth rates, and higher natural population growth were negatively correlated with the digital economy. Full article

Recent research has specifically targeted the decision-making process of eco-friendly individuals, emphasizing the significance of recycling and its impact on sustainability. Our study extends this inquiry by examining the correlation between recycling participation and pro-environmental behavior among consumers, integrating the concepts of self-efficacy, feelings of pride, and social pressure into our analysis. We utilized targeted sampling to collect data from a diverse sample of 378 participants, ensuring representation across key demographic groups. By employing Partial Least Squares–Structural Equation Modeling (PLS-SEM), we aimed to explore the intricate relationships underpinning recycling behaviors and pro-environmental actions. The results suggest that self-efficacy and feelings of pride significantly influence individuals’ recycling behaviors, highlighting the role of psychological and social factors in promoting environmental sustainability. It was concluded that social pressure did not have the expected moderating effect on increasing consumers’ feelings of pride and self-efficacy toward recycling activities. This study sheds light on the underlying mechanisms that drive pro-environmental actions, contributes to understanding sustainability promotion through recycling, and offers insights for policymakers and environmental advocates to help foster environmental responsibility and behavior change. The findings emphasize that individuals often value personal achievement and development more when addressing environmental responsibilities and that social pressure does not achieve its expected effects. Full article

Obtaining high-added value compounds from agricultural waste receives increasing attention, as it can both improve resource utilization efficiency and reduce waste generation. In this study, polysaccharides are extracted from the discarded roots of Abelmoschus manihot (L.) by the high-efficiency ultrasound-assisted extraction (UAE). The optimized condition was determined as solid–liquid ratio SL ratio = 1:20, temperature T = 30 °C and time T = 40 min, achieving an extraction yield of 13.41%. Composition analysis revealed that glucose (Glc, 44.65%), rhamnose (Rha, 26.30%), galacturonic acid (GalA, 12.50%) and galactose (Gal, 9.86%) are the major monosaccharides of the extract. The extract showed a low degree of esterification (DE) value of 40.95%, and its Fourier-transform infrared (FT−IR) spectrum exhibited several characteristic peaks of polysaccharides. Inspired by the wide cosmetic applications of polysaccharides, the skincare effect of the extract was evaluated via the moisture retention, total phenolic content (TPC) quantification, 2,2-Diphenyl-1-picrylhydrazyl (DPPH)-free radical scavenging activity, anti-hyaluronidase and anti-elastase activity experiments. The extract solutions demonstrated a 48 h moisture retention rate of 10.75%, which is superior to that of commercially available moisturizer hyaluronic acid (HA). Moreover, both the TPC value of 16.16 mg GAE/g (dw) and DPPH-free radical scavenging activity of 89.20% at the concentration of 2 mg/mL indicated the strong anti-oxidant properties of the extract. Furthermore, the anti-hyaluronidase activity and moderate anti-elastase activity were determined as 72.16% and 42.02%, respectively. In general, in vitro skincare effect experiments suggest moisturizing, anti-oxidant, anti-radical and anti-aging activities of the A. manihot root extract, indicating its potential applications in the cosmetic industry. Full article

Viral vector vaccines represent a substantial advancement in immunization technology, offering numerous benefits over traditional vaccine modalities. The Orf virus (ORFV) strain D1701-VrV is a particularly promising candidate for vaccine development due to its distinctive attributes, such as a good safety profile, the ability to elicit both humoral and cellular immunity, and its favorable genetic and thermal stability. Despite ORFV’s theoretical safety advantages, such as its narrow host range and limited systemic spread post-inoculation, a critical gap persists between these theoretical benefits and the empirical evidence regarding its in vivo safety profile. This discrepancy underscores the need for comprehensive preclinical validations to bridge this knowledge gap, especially considering ORFV’s use in humans. Our research introduces Prime-2-CoV, an innovative ORFV-based vaccine candidate against COVID-19, designed to elicit a robust immune response by expressing SARS-CoV-2 Nucleocapsid and Spike proteins. Currently under clinical trials, Prime-2-CoV marks the inaugural application of ORFV in human subjects. Addressing the aforementioned safety concerns, our extensive preclinical evaluation, including an environmental risk assessment (ERA) and detailed pharmacokinetic studies in rats and immunocompromised NOG mice, demonstrates Prime-2-CoV’s favorable pharmacokinetic profile, negligible environmental impact, and minimal ERA risks. These findings not only affirm the vaccine’s safety and efficacy but also pioneer the use of ORFV-based therapeutics, highlighting its potential for wider therapeutic applications. Full article

Sepsis is one of the major causes of morbidity and mortality in hospitals, especially in low- and middle-income countries, and represents a challenge to health care providers to carry out early detection, and accurate diagnosis and prognosis with cost-effective diagnostic tools. An observational prospective study was conducted from December 2021 to December 2022 to investigate the extended inflammatory parameters (EIPs) for sepsis management and analyze the survival of septic patients in the emergency unit, intensive care unit (ICU) and inpatient ward. Patients suspected of having sepsis underwent a sequential organ failure assessment (SOFA) evaluation and had blood drawn for complete blood counts (CBCs). Significant changes were observed in various CBC parameters and EIPs, and the sepsis group was followed up with for 30-day mortality. The study highlighted a significant difference yet strong discriminatory power to differentiate sepsis with an AUC of 0.924 against the non-sepsis group and an AUC of 0.991 against the healthy control group using combination of white blood cells and EIPs. Furthermore, the study showed good predictive ability for 30-day mortality with a hazard ratio of 2.311. In summary, this study provides evidence that the utilization of EIPs may be valuable in diagnosing and predicting patient outcomes, and thus will be beneficial for sepsis management in the hospital. Full article

In multi-agent systems, the Dynamic Distributed Constraint Optimisation Problem (D-DCOP) framework is pivotal, allowing for the decomposition of global objectives into agent constraints. Proactive agent behaviour is crucial in such systems, enabling agents to anticipate future changes and adapt accordingly. Existing approaches, like Proactive Dynamic DCOP (PD-DCOP) algorithms, often necessitate a predefined environment model. We address the problem of enabling proactive agent behaviour in D-DCOPs where the dynamics model of the environment is unknown. Specifically, we propose an approach where agents learn local autoregressive models from observations, predicting future states to inform decision-making. To achieve this, we present a temporal experience-sharing message-passing algorithm that leverages dynamic agent connections and a distance metric to collate training data. Our approach outperformed baseline methods in a search-and-extinguish task using the RoboCup Rescue Simulator, achieving better total building damage. The experimental results align with prior work on the significance of decision-switching costs and demonstrate improved performance when the switching cost is combined with a learned model. Full article

Greece has been malaria-free since 1974, after an intense malaria control program. However, as Greece hosts migrant populations from P. vivax malaria-endemic countries, there is a risk of introducing the disease to specific vulnerable and receptive areas of the country. Knowledge of the genetic diversity of P. vivax populations is essential for understanding the dynamics of malaria disease transmission in a given region. We used nine highly polymorphic markers to genotype 124 P. vivax-infected archived DNA samples from human blood specimens referred to the NMRL from all over Greece throughout 2015–2019. The genotypic variability of the samples studied was noted, as they comprised several unique haplotypes, indicative of the importation of a large number of different P. vivax strains in the country. However, only a few events of local transmission were recorded. Genotyping revealed and confirmed the same clusters as those identified through epidemiological investigation. In only one introduction event was the index case found. No sustained/ongoing malaria transmissions in/between the studied regions or during consecutive years or additional foci of local transmission were observed. Genotyping is an important component in assisting malaria surveillance, as it provides information concerning the patterns of introduction and the effectiveness of implemented malaria control and elimination measures. Full article

The effectiveness of newborn screening (NBS) for congenital hypothyroidism (CH) relies on timely screening, confirmation of diagnosis, and initiation and ongoing monitoring of treatment. The objective of this study was to ascertain the extent to which infants with CH have received timely and appropriate management within the first 3 years of life, following diagnosis through NBS in Alberta, Canada. Deidentified laboratory data were extracted between 1 April 2014 and 31 March 2019 from Alberta Health administrative databases for infants born in this time frame. Time to lab collection was anchored from date of birth. Timeliness was assessed as the frequency of monitoring of Thyroid Stimulating Hormone (TSH) and appropriateness as the frequency of children maintaining biochemical euthyroidism. Among 160 term infants, 95% had confirmation of diagnosis by 16 days of age. The cohort had a median of 2 (range 0–5) TSH measurements performed in the time interval from 0 to 1 month, 4 (0–12) from 1 to 6 months, 2 (0–10) from 6 to 12 months, and 7 (0–21) from 12 to 36 months. Approximately half were still biochemically hypothyroid (TSH > 7 mU/L) at 1 month of age. After becoming euthyroid, at least some period of hypo- (60%) or hyperthyroidism (TSH < 0.2 mU/L) (39%) was experienced. More work needs to be performed to discern factors contributing to prolonged periods of hypothyroidism or infrequent lab monitoring. Full article

The question of whether the early visual cortex (EVC) is involved in visual mental imagery remains a topic of debate. In this paper, I propose that the inconsistency in findings can be explained by the unique challenges associated with investigating EVC activity during imagery. During perception, the EVC processes low-level features, which means that activity is highly sensitive to variation in visual details. If the EVC has the same role during visual mental imagery, any change in the visual details of the mental image would lead to corresponding changes in EVC activity. Within this context, the question should not be whether the EVC is ‘active’ during imagery but how its activity relates to specific imagery properties. Studies using methods that are sensitive to variation in low-level features reveal that imagery can recruit the EVC in similar ways as perception. However, not all mental images contain a high level of visual details. Therefore, I end by considering a more nuanced view, which states that imagery can recruit the EVC, but that does not mean that it always does so. Full article