Low-lying coastal zones are highly subject to coastal hazards as a result of sea-level rise enhanced by natural or anthropogenic land subsidence. A combined analysis using sea-level data and remote sensing techniques allows the estimation of the current rates of land subsidence and shoreline retreat, supporting the development of quantified relative sea-level projections and flood maps, which are appropriate for specific areas. This study focuses on the coastal plain of Tavoliere delle Puglie (Apulia, Southern Italy), facing the Adriatic Sea. In this area, land subsidence is mainly caused by long-term tectonic movements and sediment compaction driven by high anthropogenic pressure, such as groundwater exploitation and constructions of buildings. To assess the expected effects of relative sea-level rise for the next decades, we considered the following multidisciplinary source data: (i) sea-level-rise projections for different climatic scenarios, as reported in the Sixth Assessment Report of the Intergovernmental Panel on Climate Change, (ii) coastal topography from airborne and terrestrial LiDAR data, (iii) Vertical Land Movement (VLM) from the analysis of InSAR and GNSS data, and (iv) shoreline changes obtained from the analysis of orthophotos, historic maps, and satellite images. To assess the expected evolution of the coastal belt, the topographic data were corrected for VLM values, assuming that the rates of land subsidence will remain constant up to 2150. The sea-level-rise projections and expected flooded areas were estimated for the Shared Socioeconomic Pathways SSP1-2.6 and SSP5-8.5, corresponding to low and high greenhouse-gas concentrations, respectively. From our analysis, we estimate that in 2050, 2100, and 2150, up to 50.5 km², 118.7 km² and 147.7 km² of the coast could be submerged, respectively, while beaches could retreat at rates of up to 5.8 m/yr. In this area, sea-level rise will be accelerated by natural and anthropogenic land subsidence at rates of up to −7.5 ± 1.7 mm/yr. Local infrastructure and residential areas are thus highly exposed to an increasing risk of severe inundation by storm surges and sea-level rise in the next decades. Full article

Training an automatic speech recognition (ASR) post-processor based on sequence-to-sequence (S2S) requires a parallel pair (e.g., speech recognition result and human post-edited sentence) to construct the dataset, which demands a great amount of human labor. BackTransScription (BTS) proposes a data-building method to mitigate the limitations of the existing S2S based ASR post-processors, which can automatically generate vast amounts of training datasets, reducing time and cost in data construction. Despite the emergence of this novel approach, the BTS-based ASR post-processor still has research challenges and is mostly untested in diverse approaches. In this study, we highlight these challenges through detailed experiments by analyzing the data-centric approach (i.e., controlling the amount of data without model alteration) and the model-centric approach (i.e., model modification). In other words, we attempt to point out problems with the current trend of research pursuing a model-centric approach and alert against ignoring the importance of the data. Our experiment results show that the data-centric approach outperformed the model-centric approach by +11.69, +17.64, and +19.02 in the F1-score, BLEU, and GLEU tests. Full article

Split variational inclusions are revealed as a large class of problems that includes several other pre-existing split-type issues: split feasibility, split zeroes problems, split variational inequalities and so on. This makes them not only a rich direction of theoretical study but also one with important and varied practical applications: large dimensional linear systems, optimization, signal reconstruction, boundary value problems and others. In this paper, the existing algorithmic tools are complemented by a new procedure based on a three-step iterative process. The resulting approximating sequence is proved to be weakly convergent toward a solution. The operation mode of the new algorithm is tracked in connection with mixed optimization–feasibility and mixed linear–feasibility systems. Standard polynomiographic techniques are applied for a comparative visual analysis of the convergence behavior. Full article

Major depressive disorder (MDD) and bipolar disorder (BD) with melancholia and psychotic features and suicidal behaviors are accompanied by activated immune-inflammatory and oxidative pathways, which may stimulate indoleamine 2,3-dioxygenase (IDO), the first and rate-limiting enzyme of the tryptophan catabolite (TRYCAT) pathway resulting in increased tryptophan degradation and elevated tryptophan catabolites (TRYCTAs). The purpose of the current study is to systematically review and meta-analyze levels of TRP, its competing amino acids (CAAs) and TRYCATs in patients with severe affective disorders. Methods: PubMed, Google Scholar and SciFinder were searched in the present study and we recruited 35 studies to examine 4647 participants including 2332 unipolar (MDD) and bipolar (BD) depressed patients and 2315 healthy controls. Severe patients showed significant lower (p < 0.0001) TRP (standardized mean difference, SMD = −0.517, 95% confidence interval, CI: −0.735; −0.299) and TRP/CAAs (SMD= −0.617, CI: −0.957; −0.277) levels with moderate effect sizes, while no significant difference in CAAs were found. Kynurenine (KYN) levels were unaltered in severe MDD/BD phenotypes, while the KYN/TRP ratio showed a significant increase only in patients with psychotic features (SMD= 0.224, CI: 0.012; 0.436). Quinolinic acid (QA) was significantly increased (SMD= 0.358, CI: 0.015; 0.701) and kynurenic acid (KA) significantly decreased (SMD= −0.260, CI: −0.487; −0.034) in severe MDD/BD. Patients with affective disorders with melancholic and psychotic features and suicidal behaviors showed normal IDO enzyme activity but a lowered availability of plasma/serum TRP to the brain, which is probably due to other processes such as low albumin levels. Full article

A lanthanum oxide (La₂O₃)-ZnO nanostructured material was synthesized in the proposed study with different La₂O₃ concentrations, 0.001 g to 5 g (named So to S7), using the combustion method. X-ray diffraction (XRD), scanning electron microscopy (SEM), and Fourier transformation infrared spectroscopy (FT-IR) were utilized for investigating the structure, morphology, and spectral studies of the La₂O₃- ZnO nanomaterials, respectively. The results obtained from previous techniques support ZnO’s growth from crystalline to nanoparticles’ fine structure by changing the concentrations of lanthanum oxide (La₂O₃) dopants in the host matrix. The percentage of ZnO doped with La- influences the ZnO photocatalytic activity. SEM analysis confirmed the grain size ranged between 81 and 138 nm. Furthermore, UV-Vis diffuse reflectance spectroscopy was performed to verify the effects of La₂O₃ dopants on the linear optical properties of the nano-composite oxides. There was a variation in the energy bandgaps of La₂O₃-ZnO nanocomposites, increasing the weight concentrations of lanthanum dopants. The AC electrical conductivity, dielectric properties, and current–voltage properties support the enactment of the electrical characteristics of the ZnO nanoparticles by adding La₂O₃. All the samples under investigation were used for photodegradation with Rhodamine B (RhB) and Methylene Blue (MB). In less than 30 min of visible light irradiation, S4 (0.5 g) La₂O₃-ZnO reached 99% of RhB and MB degradation activity. This study showed the best photocatalytic effect for RhB and MB degradation of 0.13 and 0.11 min⁻¹ by 0.5 g La₂O₃-ZnO. Recycling was performed five times for the nanocatalysts that displayed up to 98 percent catalytic efficiency for RhB and MB degradation in 30 min. The prepared La₂O₃-ZnO nanostructured composites are considered novel candidates for various applications in biomedical and photocatalytic studies. Full article

Retinal ischemia-reperfusion (I/R) injury often results in intractable visual impairments. The survival of retinal capillary endothelial cells is crucial for the treatment of retinal I/R injury. How to protect retinal endothelia from damage is a challenging work. Withaferin A, a small molecule derived from plants, has antibacterial and anti-inflammatory effects and has been used for about millennia in traditional medicine. The present study aimed to investigate the potential protective effect of withaferin A on retinal I/R injury. Methods: The drug-likeness of withaferin A was evaluated by the SwissADME web tool. The potential protective effect of withaferin A on the I/R-induced injury of human retinal microvascular endothelial cells (HRMECs) was investigated using multiple approaches. RNA sequencing was performed and associated mechanistic signaling pathways were analyzed based on the Kyoto Encyclopedia of Genes and Genomes data. The analytical results of RNA sequencing data were further validated by in vitro and in vivo experiments. Results: Withaferin A reduced the I/R injury-induced apoptotic death of HRMECs in vitro with a good drug-like property. RNA sequencing and experimental validation results indicated that withaferin A increased the production of the crucial antioxidant molecules heme oxygenase 1 (HO-1) and peroxiredoxin 1 (Prdx-1) during I/R. In addition, withaferin A activated the Akt signaling pathway and increased the expression of HO-1 and Prdx-1, thereby exerting an antioxidant effect, attenuated the retinal I/R injury, and decreased the apoptosis of HRMECs. The blockade of Akt completely abolished the effects of withaferin A. Conclusions: The study identified for the first time that withaferin A can protect against the I/R-induced apoptosis of human microvascular retinal endothelial cells via increasing the production of the antioxidants Prdx-1 and HO-1. Results suggest that withaferin A is a promising drug candidate for the treatment of retinal I/R injury. Full article

(1) Metabolic syndrome is a set of factors that considerably increase the risk of developing atherosclerosis, type 2 diabetes, and their cardiovascular complications. Studies show that menopause and the levels of elements may be significantly associated with increased risk of MetS. The present study evaluated the relationship between element levels (Ca, P, Na, K, Fe, Mg, Cu, Zn, Sr) and the incidence of MetS and concomitant metabolic disorders in peri-menopausal women. (2) The study involved 170 perimenopausal women. The methods used were: survey, anthropometric measurement (WC, height, BMI, WHtR), blood pressure measurement, and biochemical analysis of venous blood (lipid profile, glucose, insulin, HbA1C). (3) The study demonstrated statistically significantly higher WC, WHtR, SBP, and DBP values in women with pre-Mets than in those with Mets and the control group. Significantly higher FPG, TG, LDL, HbA1C, insulin, TG/HDL ratio, and TC/HDL ratio were recorded in the MetS group compared to the rest of respondents. In addition, post hoc analysis revealed statistically significant differences in mean K concentrations between pre-MetS and MetS women. (4) Low blood K levels in perimenopausal women are associated with an increased risk of MetS. Significantly higher Cu levels were observed in overweight women. The concentration of Cu negatively correlates with the values of TC, LDL, and SBP. Full article

Whale migrations are poorly understood. Two competing hypotheses dominate the literature: 1. moving between feeding and breeding grounds increases population fitness, 2. migration is driven by dynamic environmental gradients, without consideration of fitness. Other hypotheses invoke communication and learned behaviors. In this article, their migration was investigated with a minimal individual-based model at the scale of the Global Ocean. Our aim is to test if global migration patterns can emerge from only the local, individual perception of environmental change. The humpback whale (Megaptera novaeangliae) meta-population is used as a case study. This species reproduces in 14 zones spread across tropical latitudes. From these breeding areas, humpback whales are observed to move to higher latitudes seasonally, where they feed, storing energy in their blubber, before returning to lower latitudes. For the model, we developed a simplified ethogram that conditions the individual activity. Then trajectories of 420 whales (30 per DPS) were simulated in two oceanic configurations. The first is a homogeneous ocean basin without landmasses and a constant depth of −1000 m. The second configuration used the actual Earth topography and coastlines. Results show that a global migration pattern can emerge from the movements of a set of individuals which perceive their environment only locally and without a pre-determined destination. This emerging property is the conjunction of individual behaviors and the bathymetric configuration of the Earth’s oceanic basins. Topographic constraints also maintain a limited connectivity between the 14 DPSs. An important consequence of invoking a local perception of environmental change is that the predicted routes are loxodromic and not orthodromic. In an ocean without landmasses, ecophysiological processes tended to over-estimate individual weights. With the actual ocean configuration, the excess weight gain was mitigated and also produced increased heterogeneity among the individuals. Developing a model of individual whale dynamics has also highlighted where the understanding of whales’ individual behaviors and population dynamic processes is incomplete. Our new simulation framework is a step toward being able to anticipate migration events and trajectories to minimize negative interactions and could facilitate improved data collection on these movements. Full article

The El Niño–Southern Oscillation (ENSO) and the quasi-biennial oscillation (QBO) are two major interannual variations observed in the tropics, yet the joint modulation of the ENSO and QBO on the ozone valley over the Tibetan Plateau (TP) in summer has not been performed. This study investigates the combined effects of the ENSO and the QBO on the interannual variations of the ozone valley over the TP using the ERA5 reanalysis data from 1979 to 2021. The results show that the ENSO leads the zonal deviation of the total column ozone (TCO*) over the TP by about 6 months. This means the TCO* in the summer of the following year is affected by the ENSO in the current year. This is consistent with the theory of recharge oscillation. In terms of dynamic conditions, the anomalous circulation resulting from the combined effect of El Niño and the easterly phase of the QBO (EQBO) lead to strengthened and upward anomalies of the South Asian high (SAH) over the TP, followed by reduced ozone valley with more negative anomalies over the TP in summer. As to thermodynamic conditions, affected by both El Niño and the EQBO, the atmospheric stability shows positive anomalies from the lower troposphere to the upper troposphere, and the positive anomaly areas are larger than those in other conditions. These findings indicate an unstable atmosphere, where convection is more likely to cause ozone exchange. The turbulent mixing of ozone at low levels and high levels leads to the ozone valley over the TP, with more negative anomalies in the upper troposphere and lower stratosphere (UTLS). Full article

Based on animal long-term and short-term memory radial foraging techniques (or LMRFT and SMRFT), we devise a modelling approach that could capture the foraging behaviours of animals. In this modelling, LMRFT-based optimal foraging paths and SMRFT-based ones are constructed with respect to different levels of foraging strategies. Then, by a devised structural metric, we calculate the structural distance between these modelled optimal paths and the hypothetical real foraging paths taken by agents. We sample 20 foods positions via a chosen bivariate normal distribution for three agents. Then, we calculate their Euclidean distance matrix and their ranked matrix. Using LMRFT-based or SMRFT-based optimal foraging strategies, the optimal foraging paths are created. Then, foraging strategies are identified using optimal parameter learning techniques. Our results, based on the simulated foraging data, show that LMRFT-based foraging strategies for agent 1,2 and 3 are 3, 2 and 5, i.e., agent 3 is the most intelligent one among the three in terms of radial level. However, from the SMRFT-based perspective of strategies, their optimal foraging strategies are 5,5 and 2, respectively, i.e., agent 1 is as intelligent as agent 2 and both of them have better SMRFT-based foraging strategies than agent 3. Full article

The introduction of game-based learning techniques has significantly swayed learning, motivation, and information processing in both traditional and digital learning environments. This paper studies the footprint that the implementation of ten short-duration digital escape rooms has had on the creation of an environment of positive emotions in the educational field. The digital escape rooms were created by employing the Genial.ly platform and RPG Maker MZ software. A feelings/satisfaction questionnaire has been conducted to study what emotions students have experienced, as well as the students’ opinions about essential elements of digital escape rooms, to study whether positive feelings predominate in the performance of these activities. Results show a high incidence of positive emotions, and a very favorable opinion on the tools employed and the positive feelings on the acquisition of knowledge and skills. Full article

This review focuses on the evolving understanding that we have of tumor cell metabolism, particularly glycolytic and oxidative metabolism, and traces back its evolution through time. This understandng has developed since the pioneering work of Otto Warburg, but the understanding of tumor cell metabolism continues to be hampered by misinterpretation of his work. This has contributed to the use of the new concepts of metabolic switch and metabolic reprogramming, that are out of step with reality. The Warburg effect is often considered to be a hallmark of cancer, but is it really? More generally, is there a metabolic signature of cancer? We draw the conclusion that the signature of cancer cannot be reduced to a single factor, but is expressed at the tissue level in terms of the capacity of cells to dynamically explore a vast metabolic landscape in the context of significant environmental heterogeneities. Full article

Phenolic compounds are an important group of organic molecules with high radical scavenging, antimicrobial, anti-inflammatory, and antioxidant properties. The emerging interest in phenolic compounds in food products has led to the development of various analytical techniques for their detection and characterization. Among them, the coulometric array detector is a sensitive, selective, and precise method for the analysis of polyphenols. This review discusses the principle of this method and recent advances in its development, as well as trends in its application for the analysis of phenolic compounds in food products, such as fruits, cereals, beverages, herbs, and spices. Full article

The problem of interoperability is still open in fingerprint presentation attack detection (PAD) systems. This involves costs for designers and manufacturers who intend to change sensors of personal recognition systems or design multi-sensor systems, because they need to obtain sensor-specific spoofs and retrain the system. The solutions proposed in the state of the art to mitigate the problem still require data from the target sensor and are therefore not exempt from the problem of obtaining new data. In this paper, we provide insights for the design of PAD systems thanks to an overview of an interoperability analysis on modern systems: hand-crafted, deep-learning-based, and hybrid. We investigated realistic use cases to determine the pros and cons of training with data from multiple sensors compared to training with single sensor data, and drafted the main guidelines to follow for deciding the most convenient PAD design technique depending on the intended use of the fingerprint identification/authentication system. Full article

This paper investigates the problem of formation fault-tolerant control of multiple quadrotors (QRs) for a mobile sensing oriented application. The QRs subject to faults, input saturation and time-varying delays can be controlled to perform a target-enclosing and covering task while guaranteeing the state constraints will not be exceeded. A distributed formation control scheme is proposed, using a radial basis function neural network (RBFNN)-based time-delay position controller and an adaptive fault-tolerant attitude controller. The Lyapunov–Krasovskii approach is used to analyze the time-varying delay. Barrier Lyapunov function is deployed to handle the prescribed constraints, and an auxiliary system combined with a command filter is designed to resolve the saturation problem. An RBFNN and adaptive estimators are deployed to provide estimates of disturbances, fault signals and uncertainties. It is proven that all the closed-loop signals are bounded under the proposed protocol, while the prescribed constraints will not be violated, which enhances the flight safety and QR formation’s applicability. Comparative simulations based on application scenarios further verify the effectiveness of the proposed method. Full article

The objective of this paper is to study the specifics of the selection of renewables for regions of Azerbaijan with diverse conditions. Information is obtained through the analysis of the regions’ conditions and experts’ opinions. Analysis reveals that geographical position, diversity of natural resources, and a variety of other factors of the five economic regions of the country require subdivision of these regions in the selection of renewables. Given that the selection of renewables is a multi-criteria decision-making (MCDM) task under a high degree of uncertainty, Z-number-based models have been developed, and Z-extension of the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method has been used. Solutions have been derived based on direct calculations with Z-numbers. In this paper, results obtained for two regions are presented. In the case of one region, for the first part (mountains and foothill) of the Karabakh economic region, renewables are ranked as hydro, solar, and wind. For the second part (plain), the ranking is as follows: solar, hydro, and wind. For the Guba-Khachmaz economic region, the rankings of renewables for parts of the region are also different: the wind is preferable for the seaside, and solar is more appropriate for the foothills. Results show that in the case of uneven distribution of renewables and significant differences in factors influencing decision-making, it is necessary to subdivide economic regions and use different models for the selection of renewables. Full article

This paper aims to examine the interplay between the attributes of the FinTech ecosystem (input) and productive entrepreneurship (output) in Russian regions. A survey was used to gather data from FinTech representatives in ten selected regions located in Russia. The acquired responses allowed measuring the FinTech ecosystem attributes by calculating the FinTech ecosystem index. Correlation analysis was used to analyse the association between the FinTech ecosystem index and productive entrepreneurship, as measured by the number of FinTechs. Data envelopment analysis was used to determine regions with more productive entrepreneurship given the ecosystem attributes. The FinTech ecosystem index defines a similar environment in the analysed regions for financial sector entrepreneurship. The regions have high values of physical infrastructure, demand, and talent, while new knowledge and networks appear as weaknesses. Still, Moscow has the highest and Chelyabinsk the lowest FinTech ecosystem index. There appears a positive link between FinTech ecosystem attributes and productive entrepreneurship. The Moscow and Chelyabinsk regions are also revealed as the regions that effectively create an environment for productive entrepreneurship from the position of the Fintech ecosystem index. This study contributed to the existing literature by measuring FinTech ecosystem attributes and productive entrepreneurship, investigating the relationship between them and determining the territories with productive entrepreneurship. It also contributed to Russian FinTech literature by being the first to measure the environment for financial sector entrepreneurship. Full article

Climate change has a profound impact on the distribution of species on Earth. At present, there are two contrasting views explaining the direction of species range shifts. One is a single poleward (northward in the Northern Hemisphere) view, while the other is a multi-directional view (e.g., westward, southward, and eastward). Exploring the universality of these two views has become a key focus in climate change ecology. Here, we study the habitat range shift velocity of 99 tree species in China under future climate change scenarios using a bioclimatic envelope model (also called species distribution model) and a climate velocity method. A Monte Carlo method is used to test the consistency between the range shift pattern and stochastic process, and confusion matrices and kappa values are calculated to evaluate the consistency between the bioclimatic envelope model and climate velocity method. The results indicate that the tree species in China are generally expected to shift northwards, with northwest and northeast directions accounting for a larger proportion. The northward-shifting species are mainly distributed in the east monsoon region of China, while the multi-directional shifting species are mainly distributed in the alpine and arid regions of China. The shift directions described by the bioclimatic envelope model are inconsistent with those described by the climate velocity method. The results imply that the tree species in China support the view of the northward shift pattern but, more specifically, should be considered in terms of a multi-directional northward shift pattern. The results also emphasize that the inter-species variation in climate tolerance has been largely ignored in physical-based climate velocity methods. The development of a biological and vector operation-based climate velocity indicator may be more useful in characterizing the range shifts of species, compared to existing physical and scalar operation-based climate velocity indicators. This study provides favorable evidence for the pattern of climate change-induced range shifts in China, as well as in Eastern Asia. Full article

Scarce water resources present a major hindrance to ensuring food security. Crop water productivity (WP), embraced as one of the Sustainable Development Goals (SDGs), is playing an integral role in the performance-based evaluation of agricultural systems and securing sustainable food production. This study aims at developing a cloud-based model within the Google Earth Engine (GEE) based on Landsat -7 and -8 satellite imagery to facilitate WP mapping at regional scales (30-m resolution) and analyzing the state of the water use efficiency and productivity of the agricultural sector as a means of benchmarking its WP and defining local gaps and targets at spatiotemporal scales. The model was tested in three major agricultural districts in the Lake Urmia Basin (LUB) with respect to five crop types, including irrigated wheat, rainfed wheat, apples, grapes, alfalfa, and sugar beets as the major grown crops. The actual evapotranspiration (ET) was estimated using geeSEBAL based on the Surface Energy Balance Algorithm for Land (SEBAL) methodology, while for crop yield estimations Monteith’s Light Use Efficiency model (LUE) was employed. The results indicate that the WP in the LUB is below its optimum targets, revealing that there is a significant degree of work necessary to ameliorate the WP in the LUB. The WP varies between 0.49–0.55 (kg/m³) for irrigated wheat, 0.27–0.34 for rainfed wheat, 1.7–2.2 for apples, 1.2–1.7 for grapes, 5.5–6.2 for sugar beets, and 0.67–1.08 for alfalfa, which could be potentially increased up to 80%, 150%, 76%, 83%, 55%, and 48%, respectively. The spatial variation of the WP and crop yield makes it feasible to detect the areas with the best and poorest on-farm practices, thereby facilitating the better targeting of resources to bridge the WP gap through water management practices. This study provides important insights into the status and potential of WP with possible worldwide applications at both farm and government levels for policymakers, practitioners, and growers to adopt effective policy guidelines and improve on-farm practices. Full article

Building energy consumption in hot arid climates is dominated by air conditioning use. Therefore, using passive cooling methods could reduce this demand, improve resource efficiency, and decrease carbon emissions. In this study, an innovative configuration of a passive downdraught evaporative cooling (PDEC) tower is investigated numerically. The governing equations are solved using the finite element method (FEM), and the effects of inlet velocity (0.5 m·s⁻¹ ≤ u_in ≤ 3 m·s⁻¹) and temperature (35 °C ≤ T_in ≤ 45 °C) on the fluid structure, temperature field, and relative humidity are studied for three cases related to the position of the air outlet. The flow is considered as turbulent, and the building walls and the tower are assumed to be thermally well insulated. The PDEC tower is equipped with two vertical isotropic saturated porous layers. The results revealed that the inlet velocity and temperature play an essential role in the quality of the indoor temperature. In fact, the temperature can be reduced by about 7 degrees, and the relative humidity can be enhanced by 9% for lower inlet velocities. Full article

The supply chain for prefabricated buildings (PB) is vulnerable to the operation failure of node enterprises, with frequent damage occurring. Therefore, it is vital to establish an evaluation model of supply chain resilience (SCRE) to improve the ability to resist unanticipated risks. However, existing research falls short of explaining the hierarchy of the influential components. To fill this gap, this paper established an element-based system of PBSCRE affecting factors. The DEMATEL-ISM method, which combines Pythagorean fuzzy sets, was utilized to analyze the factors. The effectiveness of this framework was then verified via a case study. The results showed the following: the top six elements in terms of centrality were risk management level, inventory management, emergency response plan, visibility, environmental risk, and information technology level; all factors were divided into six levels: (1) factors in level 1 are surface direct influence factors, (2) factors in levels 2 to 5 are intermediate transfer factors, and (3) factors in level 6 are deep root factors. There are 4 root factors, namely, supplier level, environmental risk, information technology level, and visibility. The results indicate that the proposed model will assist managers in identifying critical aspects and achieving sustainable management. Full article

In the de Sitter gauge theory (DGT), the fundamental variables are the de Sitter (dS) connection and the gravitational Higgs/Goldstone field ${\xi }^A$, where A is a 5 dimensional index. Previously, a model for DGT was analyzed, which generalizes the MacDowell–Mansouri gravity to have a variable cosmological constant, $\Lambda =3/l^2$, where l is related to ${\xi }^A$ by ${\xi }^A{\xi }_A=l^2$. It was shown that the model sourced by a perfect fluid does not support a radiation epoch and the accelerated expansion of the parity invariant universe. In this paper, I consider a similar model, namely, the Stelle–West gravity, and couple it to a modified perfect fluid, such that the total Lagrangian 4-form is polynomial in the gravitational variables. The Lagrangian of the modified fluid has a nontrivial variational derivative with respect to l, and as a result, the problems encountered in the previous study no longer appear. Moreover, to explore the elegance of the general theory, as well as to write down the basic framework, I perform the Lagrange–Noether analysis for DGT sourced by a matter field, yielding the field equations and the identities with respect to the symmetries of the system. The resulted formula are dS covariant and do not rely on the existence of the metric field. Full article

Modern networks used for integrating custom Internet of Things (IoT) systems and devices have restrictions and requirements unique to their individual applications. These application specific demands require custom designed hardware to maximize throughput, security and data integrity whilst minimizing latency, power consumption, and form factor. Within this paper, we describe current, state-of-the-art works that utilize FPGAs for IoT network developments. We analyze two categories of works: those that prioritize reducing power consumption, and those that prioritize networking features. Further, we describe how future works can improve upon these designs and therefore improve the efficiency of resource-constrained IoT networks. Full article

Video-capsule endoscopy (VCE) reading is a time- and energy-consuming task. Agreement on findings between readers (either different or the same) is a crucial point for increasing performance and providing valid reports. The aim of this systematic review with meta-analysis is to provide an evaluation of inter/intra-observer agreement in VCE reading. A systematic literature search in PubMed, Embase and Web of Science was performed throughout September 2022. The degree of observer agreement, expressed with different test statistics, was extracted. As different statistics are not directly comparable, our analyses were stratified by type of test statistics, dividing them in groups of “None/Poor/Minimal”, “Moderate/Weak/Fair”, “Good/Excellent/Strong” and “Perfect/Almost perfect” to report the proportions of each. In total, 60 studies were included in the analysis, with a total of 579 comparisons. The quality of included studies, assessed with the MINORS score, was sufficient in 52/60 studies. The most common test statistics were the Kappa statistics for categorical outcomes (424 comparisons) and the intra-class correlation coefficient (ICC) for continuous outcomes (73 comparisons). In the overall comparison of inter-observer agreement, only 23% were evaluated as “good” or “perfect”; for intra-observer agreement, this was the case in 36%. Sources of heterogeneity (high, I² 81.8%­98.1%) were investigated with meta-regressions, showing a possible role of country, capsule type and year of publication in Kappa inter-observer agreement. VCE reading suffers from substantial heterogeneity and sub-optimal agreement in both inter- and intra-observer evaluation. Artificial-intelligence-based tools and the adoption of a unified terminology may progressively enhance levels of agreement in VCE reading. Full article

One of the primary causes of disability and mortality in the adult population worldwide is stroke. A person’s general health is significantly impacted by their oral and dental health. People who have poor oral health are more susceptible to conditions such as stroke. Stroke risk has long been linked to oral and dental conditions. The risk of stroke and its cost impact on the healthcare systems appear to be significantly reduced as a result of the decline in the incidence and prevalence of oral and dental illnesses. Hypothetically, better management of oral hygiene and dental health lead to reduced stroke risk. To the authors’ best knowledge, for the first time, the potential link between dental health and stroke were cross-examined. The most typical stroke symptoms, oral and dental illnesses linked to stroke, and the role of oral healthcare professionals in stroke prevention are revealed. The potential mediating processes and subsequent long-term cognitive and functional neurological outcomes are based on the available literature. It must be noted that periodontal diseases and tooth loss are two common oral health measures. Lack of knowledge on the effects of poor oral health on systemic health together with limited access to primary medical or dental care are considered to be partially responsible for the elevated risk of stroke. Concrete evidence confirming the associations between oral inflammatory conditions and stroke in large cohort prospective studies, stratifying association between oral disease severity and stroke risk and disease effects on stroke survival will be desirable. In terms of clinical pathology, a predictive model of stroke as a function of oral health status, and biomarkers of systemic inflammation could be useful for both cardiologists and dentists. Full article