Macromolecules with well-defined structures in terms of molar mass and monomer sequence became interesting building blocks for modern materials. The precision of the macromolecular structure makes fine-tuning of the properties of resulting materials possible. Conjugated macromolecules exhibit excellent optoelectronic properties that make them exceptional candidates for sensors construction. The importance of chain length and monomer sequence is particularly important in conjugated systems. The sequence lengths, monomer sequence and structural modification often influence the energy bang gap between HOMO and LUMO orbitals of the molecules that reflect in their properties. Moreover, the supramolecular aggregation that is often observed in oligo-conjugated systems is usually strongly affected by even minor structural changes that are used for sensor designs. This review summarizes the examples of well-defined conjugated macromolecules based on oligo(arylene ethynylene)s skeleton used for sensor applications. The sensing mechanisms and importance of uniformity of structure are discussed.

There is no well-defined threshold for intra-operative blood transfusion (BT) in advanced epithelial ovarian cancer (EOC) surgery. We developed a Machine Learning (ML)-driven prediction algorithm to trigger and explain a communication alert for BT based on anticipated peri-operative events irrespective of BT policies. We analysed prospectively collected data from 403 EOC patients who underwent cytoreductive surgery between 2014 and 2019. We calculated the estimated blood volume (EBV) using the formula EBV = weight x 80 and set off 10%EBV as threshold for individual intervention. Based on the known estimated blood loss (EBL) we identified two groups. We employed Receiver operating characteristic (ROC) curves for performance metrics. The model performance for the above threshold prediction was satisfactory (AUC 0.823, 95% CI 0.76-0.88). The top feature commonly shared between interrogators was operative time (OT). Intra-operative blood loss of at least 10%EBV was associated with OT>250 minutes, primary surgery, serous histology, performance status 0, R2 resection and surgical complexity score >4. Large bowel resection, stoma formation, ileocecal resection/right hemicolectomy, mesenteric resection, bladder and upper abdominal peritonectomy were amongst sub-procedures clearly associated with increased intervention risk. Precise prediction of blood requirements is not possible unless a rough estimate of OT is known in advance.

Polyhydroxyalkanotes (PHA) are bio-based microbial biopolyesters with stiffness, elasticity, crystallinity and degradability tunable by the monomeric composition, bio-production strategy and post-synthetic processing; they display biological alternatives for diverse technomers of petrochemical origin. This, together with the fact that their monomeric and oligomeric in vivo degradation products do not exert any toxic or elsewhere negative effect to living cells or tissue of humans or animals, makes them highly stimulating for various applications in the medical field. The article provides an overview of PHA application in the therapeutic, surgical and tissue engineering area, and reviews strategies to produce PHA at purity levels high enough to be used in vivo. Tested applications of differently composed PHA and advanced follow-up products as carrier materials for controlled in vivo release of anti-cancer drugs or antibiotics, as scaffolds for tissue engineering, as guidance conduits for nerve repair or as enhanced sutures, implants or meshes are discussed from both a biotechnological and a material-scientific perspective. Particular attention is devoted to the adaptation of traditional polymer processing techniques for production of medicine-related devices based on PHA, such as melt-spinning, melt extrusion, or solvent evaporation, and to emerging processing techniques like 3D-printing, computer-aided wet-spinning, laser perforation, or electrospinning.

Principal component analysis (PCA) is used to reduce the dimensionalities of high dimensional datasets in a variety of research areas. For example, biological macromolecules, such as proteins, exhibit many degrees of freedom, allowing them to adopt intricate structures and exhibit complex functions by undergoing large conformational changes. Therefore, molecular simulations of and experiments on proteins generate a large number of structure variations in high dimensional space. PCA and many PCA-related methods have been developed to extract key features from such structural data, and these approaches have been widely applied for over 30 years to elucidate macromolecular dynamics. This review mainly focuses on the methodological aspects of PCA and related methods, and their applications for investigating protein dynamics.

Grid modernization has been ushered in by rising electricity consumption, deteriorating infrastructure, and increasing reliability concerns for electric utilities. New advances, collectively referred to as the smart grid, include modern electronics, technology, telecommunications, and computing capabilities. Smart grid telecommunication frameworks provide two-way communication to support grid operations. Software-defined networking (SDN) has been proposed as a method of monitoring and controlling telecommunication networks, enabling increased smart grid visibility, control, and security. However, being connected to telecommunications infrastructure means that smart grid networks are exposed to cyber-attacks. Attackers may use unauthorized access to intercept messages, inject false data into system measurements, flood communication channels with false data packets, or target centralized controllers to cripple network control. Defense and security techniques against these threats are constantly evolving, necessitating an up-to-date, comprehensive study analyzing cyber attacks and defense methods for smart grid networks. Previous smart grid security surveys do not contain recent techniques and to our knowledge most, if not all, address only one type of attack type and/or one type of defense. This survey considers the latest security techniques, simultaneous multi-pronged cyber attacks and defensutilityes to meet the challenges of the next-generation SDN smart grid research with the goal of identifying future research needs, describing the open security challenges, and exposing both emerging threats and their potential impact on SD-SG deployment.

The prevailing interpretations of physics are based on deeply entrenched assumptions, rooted in classical mechanics. Logical implications include: the denial of entropy as a fundamental physical property, and the inability to explain irreversible change, random quantum measurements, or nonlocality without untestable and implausible metaphysical implications. We propose a conceptual model that is based on empirically justifiable assumptions and consistent with observations. The WYSIWYG Conceptual Model (WCM) assumes no hidden properties: “What You can See Is What You Get.” The WCM contextually defines a system’s state with respect to its actual ambient background, and it extends existing models of physical reality by defining entropy and exergy as objective contextual properties of state. The WCM establishes the irreversible dissipation of exergy and the Second law of thermodynamics as a fundamental law of physics, it recognizes physical randomness, and it provides a physical explanation for nonlocality, consistent with Special Relativity, without hidden variables, superdeterminism, or “spooky action.”

The conventional well placement was done manually by using a numerical reservoir simulator, and it required a lengthy trial-and-error process. It required great experience and expertise to manipulate the variables and uncertainties that lie on the reservoir to determine the best placement of the well. In addition, the traditional gradient-based methods such as Line-search and Trust-region were not viable in terms of maximum results obtained. Gradient-based methods were too dependent on the surface gradient of the solution and may only converge to local optima instead of global optima. Complex reservoirs have rough surfaces with high uncertainties, which hinders the traditional gradient-based method from converging to global optima. Thus, genetic algorithms were utilized to automate the manual trial-and-error process and to overcome the limitations of the traditional gradient-based method. The objectives of this study were to analyse the effect of different initial well placement distributions, the number of random solution sizes, and the crossover rate on cumulative oil production. A synthetic reservoir model built using CMG Builder was used as the testing platform for the optimization problems. Well-placement parameterization and optimization set-up were carried out using the CMG CMOST optimization tool. The integration of CMG IMEX and CMOST optimized cumulative oil production based on the objectives of the study. The results obtained showed that the higher number of random solutions used resulted in higher cumulative oil production, with more generations needed to reach the optimum solution. It can be concluded that the larger number of random solutions used increased the probability of reaching the optimum solution, but will take more generations.

We discuss a topological method of storing and retrieving information from flash memory. We first present a sensing method where the threshold voltage level, as represented by a sensing time, is extracted in one sensing cycle. The sense time distribution from one set of flash cells, e.g. one physical row, is then processed in software to decode the digital state of each cell. The decoding method uses topological constraints but no rigid or predetermined voltage thresholds to digitize the distribution. The software defined nature of the topologically defined flash (TDF) allows greater flexibility for allocating cells to arbitrary number of digital states.

In this paper, we study a one-dimensional Bresse-Cattaneo system with infinite memories and time-dependent delay term (the coefficient of which is not necessarily positive) in the internal feedbacks. First, it is proved that the system is well-posed by means of the Hille-Yosida theorem under suitable assumptions on the relaxation functions. Then, without any restriction on the speeds of wave propagations, we establish the exponential or general decay result by introducing suitable energy and Lyapunov functionals.

Data Meshes is an approach to data architecture and organization that treats data as a product and focuses on decentralizing data ownership and access. It has recently emerged as a field that presents quite a few challenges related to data ownership, governance, security, monitoring, and observability. To address these challenges, this paper introduces an innovative algorithmic framework leveraging data blueprints to enable the dynamic creation of Data Meshes and Data Products in response to user requests, ensuring that stakeholders will have access to specific portions of the Data Mesh as needed. Ownership and governance concerns are addressed through a unique mechanism involving Blockchain and Non-Fungible Tokens (NFTs). This facilitates secure and transparent transfer of data ownership, with the ability to mint time-based NFTs. By combining these advancements with the fundamental tenets of Data Meshes, this research offers a comprehensive solution to the challenges surrounding data ownership and governance. It empowers stakeholders to navigate the complexities of data management within a decentralized architecture, ensuring a secure, efficient, and user-centric approach to data utilization. The proposed framework is demonstrated using real-world data from a poultry meat production factory.

Background: This study aimed to identify the association between occupational stress and depression-well-being by proposing a comprehensive and flexible job burden-capital model with its corresponding hypotheses. Methods: For this research, 1618 valid samples were gathered from the electronic manufacturing service industry in Hunan Province, China; self-rated questionnaires were administered to participants for data collection after obtaining their written consent. The proposed model was fitted and tested through structural equation model analysis. Results: Single-factor correlation analysis results indicated that coefficients between all items and dimensions had statistical significance. The final model demonstrated satisfactory global goodness of fit (CMIN/DF=5.37, AGFI=0.915, NNFI=0.945, IFI=0.952, RMSEA=0.052). Both the measurement and structural models showed acceptable path loadings. Job burden and capital were directly associated with depression and well-being or indirectly related to them through personality. Multi-group structural equation model analyses indicated general applicability of the proposed model to basic features of such a population. Gender, marriage and education led to differences in the relation between occupational stress and health outcomes. Conclusions: The job burden-capital model of occupational stress-depression and well-being was found to be more systematic and comprehensive than previous models.

The study on graphs emerging from different algebraic structures like groups, rings, fields, vector spaces, etc. is a prominent area of research in mathematics, as algebra and graph theory are two mathematical fields that focuses on creating and analysing structures. There are numerous studies linking algebraic structures and graphs, which began with the introduction of Cayley graphs of groups. Several algebraic graphs have been defined on rings, which have huge-growing literature. In this article, we systematically review the literature on some variants of Cayley graphs that are defined on rings, to understand the research in this area.

Trends such as Industrial Internet of Things (IIoT) and Industry 4.0 have increased the need to use powerfull network technologies in industrial automation. The growing communication in industrial automation is harnessing the productivity and efficiency of manufacturing and process automation with minimum human intervention. Due to the ongoing evolution of industrial networks from Fieldbus technologies to Ethernet, the new opportunity has emerged to integrate the Software Defined Networking (SDN) technique. In this paper, we provide a brief overview of SDN in the domain of industrial automation. We propose a network architecture called Software Defined Industrial Automation Network (SDIAN), with the objective of improving network scalability and efficiency. To match the specific considerations and requirements of having a deterministic system in an industrial network, we propose two solutions for flow creation: Pro-active Flow Installation Scheme (PFIS) and Hybrid Flow-Installation Scheme (HFIS). We analytically quantify the proposed solutions in alleviating the overhead incurred from the flow setup cost. The analytical model is verified through monte carlo simulations. We also evaluate the SDIAN architecture and analyze the network performance of the modified topology using an emulator called Mininet. We further list and motivate SDIAN features and in particular report on an experimental food processing plant demonstration featuring Raspberry PIs (RPIs) instead of traditional Programmable Logic Controllers (PLCs). Our demonstration exemplifies the characteristics of SDIAN.

The digital society is an outcome of the Internet which has nearly made everything connected and accessible no matter where or when. Nevertheless, despite the fact that conventional IP networks are complicated and very hard to manage, they are still widely adopted. The already established policies make the network configuration/reconfiguration a complex process that reacts to errors, load, and modifications. The prevailing networks are vertically integrated which makes things more and more complicated: Data planes and control are strapped together. Software-defined networking is a model that is meant to solve this issue by splitting the vertical integration and detaching the network’s control logic from the implicit routers and switches; this could be achieved by reinforcing centralization of network control and making the network programmable. In this work, we worked to implement MPLS networks with SDN, to enhance the traffic engineering over the network, and to minimize the network delay and latency, with minimum cost using three of the different SDN networks. The experiment results showed the advantage of the proposed approach for reducing the network delay, comparing with previous studies. Where the average of network delay in our approach reaches to 3.01 milliseconds.

Complex-structured polymeric microparticles hold significant promise as advance in next-generation medicine mostly due to demand from developing targeted drug delivery. However, the conventional methods for producing these microparticles of defined size, shape and sophisticated composition often face challenges in scalability, reliance on specialized components such as micro-patterned templates, or have limited control over particle size distribution and cargo release kinetics. In this study, we introduce a novel and reliably scalable approach for manufacturing microparticles of defined structures and sizes with variable parameters. The concept behind this method involves the deposition of a specific number of polymer layers on a substrate with low surface energy. Each layer can serve as either the carrier for cargo or a programmable shell-former with predefined permeability. Subsequently, this layered structure is precisely cut into desired-sized blanks using a laser. The manufacturing process is completed by applying of heat to the substrate what results on sealing the edges of the blanks. The combination of the high surface tension of the molten polymer and the low surface energy of the substrate enables the formation of discrete particles, each possessing semi-spherical or other designed geometries determined by their internal composition. Such anisotropic microparticles are envisaged versatile applications.

Maize is an important staple food crop in sub-Saharan Africa (SSA). However, the average grain yield on farmers’ fields falls considerably short of the demand of the region’s population. In addition, the normal endosperm maize widely consumed in SSA is deficient in vitamin A. Drought, a consequence of climate change, is a major constraint to maize production, resulting in seasonal low grain yield in farmers’ fields. The objectives of this study were to assess the performance of newly developed extra-early maturing provitamin A hybrids under managed drought and well-watered conditions, compare the outcomes of multiple trait base-index and multi-trait genotype-ideotype distance index selection procedures, and identify drought-tolerant hybrids with stable performance across contrasting environments for commercialization in SSA. One hundred and ninety provitamin A hybrids and six checks were evaluated under managed drought and well-watered conditions at Ikenne for two seasons between 2021 and 2023. A 14*14-lattice design was used for the field evaluations under both research conditions. Drought stress was achieved by the complete withdrawal of irrigation water 25 days after planting. Results revealed significant differences among the hybrids under drought and well-watered conditions. Grain yield, ears per plant, and plant aspect under managed drought were correlated to the same traits under well-watered conditions suggesting that the expression of these traits is governed by common genetic factors. Twenty-nine hybrids were identified as top-performing drought-tolerant hybrids by the multiple trait base index and multiple-trait genotype–ideotype distance index. Of the selected outstanding 29 hybrids, 34% were derived from crosses involving the tester TZEEIOR 197, demonstrating the outstanding genetic potential of this inbred line. Further analysis of the 29 selected hybrids revealed TZEEIOR 509 × TZEEIOR 197 as the hybrid that combined the most drought-tolerant adaptive traits. However, the hybrids TZEEIOR 526 × TZEEIOR 97, TZEEIOR 384 × TZEEIOR 30, TZEEIOR 515 × TZEEIOR 249, TZEEIOR 510 × TZEEIOR 197, TZEEIOR 479 × TZEEIOR 197, and TZEEIOR 458 × TZEEIOR 197 were identified as the most stable hybrids across drought and well-watered conditions. These hybrids should be extensively tested in multi-location trials for deployment and commercialization in SSA.

Depression is considered a widespread mental health problem worldwide. Moreover, anxiety symptoms are very closely related to depression patients, and it is known that the coexistence rate of depression and anxiety diagnosed simultaneously is high. Treatment and preventive management of depression and anxiety are essential for public health. Forest healing is attracting attention as a form of low-cost preventive medicine that is safe and has no side effects. However, although the physiological and psychological effects have been scientifically proven, it is insufficient to reveal a direct relationship between forest healing and depression. This study investigated the benefits of an urban forest healing program on depression and anxiety symptoms of depressive disorders. We employed a randomized controlled trial design. Forty-seven depression patients were randomly divided into an urban forest healing program group and a control group. Measures included the Montgomery-Asberg depression rating scale (MADRS), the Hamilton Anxiety Rating Scale (HARS), and the State-Trait Anxiety Inventory (STAI) questionnaires. Our results revealed that the combination of general treatment and forest healing programs for patients with depression is more effective in improving depression and anxiety than routine treatment alone. We expect our work to serve as a starting point for more sophisticated research in discussing the availability of non-pharmacological treatments in forest healing.

Positively charged polyelectrolytes hold significant potential as materials for creating antibacterial coatings. Water-soluble macromolecules can be easily deposited onto a treated surface through various techniques, forming a film that provides antimicrobial properties to the surface through electrostatic interactions with bacterial membranes. The structural and molecular weight characteristics of the polymers play a crucial role in the physical and mechanical properties of the coatings. In this study, we investigated the properties of branched polyethyleneimine (PEI) and linear polydiallyldimethylammonium chloride (PDADMAC) coatings with different molecular weights of polymer samples to determine their suitability as stable coatings with antibacterial properties against foodborne bacteria. Using thermogravimetric analysis, dynamometry, and dynamic light scattering, we examined the physicochemical and mechanical properties of the macromolecules in water solutions and in coatings. Microbiological study was conducted to analyze the biocidal activity of the polycations in solutions and on the surface of coatings. Our findings showed that the moisture saturation of the polycationic coatings did not significantly depend on the chemical nature of charged groups or the molecular weight or architecture of macromolecules. Moreover, biocidal activity was not found to depend on the molecular weights of PEI and PDADMAC. However, the lowering of the molecular weight of polymers resulted in the loss of cohesive forces in the coatings and to dramatically loss of the stability towards wash-off with water. The diffusion coefficient (D0) of macromolecules was identified as a key parameter for the wash-off mechanism. Films formed by molecules with D0 below 1×10-7 cm2/s demonstrated high resistance to wash-off procedures. We demonstrated that PEI and PDADMAC samples with high molecular weights showed high antimicrobial activity towards L. monocytogenes. Our results highlight the importance of macromolecule characteristics in the development of new biocidal coatings based on polycations.

Due to the long duration and high cost of traditional pumping tests, the response of well water level to seismic wave, earth tide, and barometric pressure provides a feasible method for determining continuous changes in aquifer hydraulic parameters. Aiming at the problem that the response phase shift of well BB water level to tidal tide M2 is greater than that of tide O1, this paper preferentially calculated the time series changes of S, Be, n and BKu based on the response mechanism of well water level to barometric pressure and earth tide and with the help of smooth moving method. Then by using the mixed flow model, the variation of transmissivity and leakage coefficient over time were simultaneously obtained, and the evolution process and characteristics of aquifer parameters near well BB caused by the Wenchuan earthquake were ultimately discussed. The calculation results are basically consistent with the previous pumping test, and have been verified and compared by using other scholars' methods. This solving process avoids the problems such as excessive dependence on initial values, multiple solutions, and unstable tide O1, which has a promoting effect on the study of the impact of seismic activity on aquifer systems.

Purpose: To meet the challenges of the precision medicine era, quality assessment of shared sarcoma care becomes pivotal. The MDT approach is the most important parameter for succesfull outcome. Because of all MDTs disciplines surgery is the key step to render sarcoma patients disease free, defining the spectrum of a sarcoma surgeon is critical. To the best of the authors knowledge, a comprehensive interoperable digital platform to assess the scope of sarcoma surgery and the experience of a sarcoma surgeon in its full complexity is lacking. Methods: A web-based real-world data (RWD) registry on sarcoma surgery has been created to assess the clinical exposure, tumor characteristics, and surgical settings and techniques applied for both resections and reconstructions of sarcomas and thereby the surgical exposure of an individual surgeon over time. Results: During 10 years, there were 723 sarcoma board/MDT meetings discussing 3130 patients. A total of 1094 patients underwent 1250 surgical interventions on mesenchymal tumors by one single sarcoma surgeon. These included 615 deep soft tissue tumors (197 benign, 102 intermediate, 281 malignant, 27 simulator, 7 metastasis, 1 blood), 116 superficial soft tissue tumors (45 benign, 12 intermediate, 40 malignant, 18 simulator, 1 blood) and 519 bone tumors (129 benign, 112 intermediate, 182 malignant, 18 simulator, 46 metastasis, 14 blood and 18 sequelae of 1st treatment). Detailed types of resections and reconstructions were analyzed. Conclusion: A web-based RWD sarcoma surgeon registry with transparent real-time descriptive analytics is feasible and enables large scale definition of the surgical complexity and ultimately quality of sarcoma care.

In this paper, we investigate a new subclass of univalent functions defined by a generalized differential operator, and obtain some interesting properties of functions belonging to the class R^m λµ ( α, β, γ, υ ).

Carbon Capture and Storage (CCS) stands as a pivotal technological stride toward a sustainable future, with the practice of injecting supercritical CO2 into subsurface formations having already been an established practice for enhanced oil recovery operations. The overarching objective of CCS is to protract the operational viability and sustainability of platforms and oilfields, thereby facilitating a seamless transition towards sustainable practices. This study introduces a comprehensive framework for optimizing well placements in CCS operations, employing a derivative-free method known as Bayesian optimization. The development plan is tailored for scenarios featuring aquifers devoid of flow boundaries, incorporating production wells tasked with controlling pressure buildup and injection wells dedicated to CO2 sequestration. Notably, the wells operate under group control, signifying predefined injection and production targets and constraints that must be adhered to throughout the project’s lifespan. As a result, the objective function remains invariant under specific permutations of the well locations. Our investigation delves into the efficacy of Bayesian optimization under the introduced permutation invariance. The results reveal that it demonstrates critical efficiency in handling the optimization task extremely fast. In essence, this study advocates for the efficacy of Bayesian optimization in the context of optimizing well placements for CCS operations, emphasizing its potential as a preferred methodology for enhancing sustainability in the energy sector.

Optical networks offer a wide range of benefits to the telecommunication sector world- wide with its provision of higher bandwidth which leads to faster data speed, longer transmission distance, and improved latency. Currently, the complexity associated with advancements in optical networks poses problems to network flexibility, reliability, and quality of service. Over the years, many reviews and proposals have been implemented by several literatures to provide solutions for optical networks using software-defined networks and network service orchestrators. This paper reviews the significant challenges in current optical network applications, the various solutions rendered by software-defined networks as well as network service orchestration, the impediments, and gaps in these software – defined networks. This paper will go a step further to look into the various improvements and implementations of software-defined networks tailored to solve specific optical network problems. This paper further proposes a flexible orchestration architecture for software-defined networks for solving flexibility and scalability problems in optical networks. This proposal uses Open Network System (ONOS) SDN controller, leveraging on dockerisation as well as kubernetes clusterisation and orchestration. This solution presents a more flexible, reliable, customable, and higher quality of service which is an improvement upon current solutions in literature.

We investigate \texorpdfstring{$L_2$}{}-approximation problems in the worst case setting in the weighted Hilbert spaces \texorpdfstring{$H(K_{R_{d,\a,\g}})$}{} with weights \texorpdfstring{$R_{d,\a,{\bm \ga}}$}{} under parameters \texorpdfstring{$1\ge \ga_1\ge \ga_2\ge \cdots\ge 0$ and $1<\az_1\le \az_2\le \cdots$}{}. Several interesting weighted Hilbert spaces \texorpdfstring{$H(K_{R_{d,\a,\g}})$}{} appear in this paper. We consider the worst case error of algorithms that use finitely many arbitrary continuous linear functionals. Multivariate approximation; information complexity; tractability; weighted Hilbert spacesWe discuss tractability of \texorpdfstring{$L_2$}{}-approximation problems for the involved Hilbert spaces, which describes how the information complexity depends on \texorpdfstring{$d$}{} and \texorpdfstring{$\va^{-1}$}{}. As a consequence we study the strongly polynomial tractability (SPT), polynomial tractability (PT), weak tractability (WT), and \texorpdfstring{$(t_1,t_2)$}{}-weak tractability (\texorpdfstring{$(t_1,t_2)$}{}-WT) for all \texorpdfstring{$t_1>1$}{} and \texorpdfstring{$t_2>0$}{} in terms of the introduced weights under the absolute error criterion or the normalized error criterion.

This study investigated the effects of flamenco dance on mood and subjective well-being in older women. In a broader context, the question was raised about how participation in dance activities could influence the emotional well-being of this demographic group. Thirty-four older women, aged between 62 and 79 years, with a mean age of 70.11 years (SD = 5.13), voluntarily participated in the study after providing informed consent. All of them were enrolled in a 12-week flamenco dance workshop conducted by the Autoestima Flamenca Association, with one two-hour session per week. Mood measurements (sadness, anxiety, anger, and joy) were taken biweekly before and after each session, and subjective well-being assessments were conducted before and after the intervention. The results revealed significant improvements in the overall mood of the participants, as well as an increase in their subjective well-being. These improvements were observed at both the individual and group levels. In conclusion, participation in flamenco dance demonstrated a positive impact on the mood and subjective well-being of older women. These findings support the idea that physical and artistic activities, such as flamenco dance, can play an important role in promoting emotional well-being in this age group.

The accurate wellbore pressure control not only prevents from lost circulation/blowout and fracturing formation by managing density of drilling fluid, but also improves productivity by mitigating reservoir damage. The geothermal pressure calculated by constant parameters for geothermal well would bring big error easily, as the changes of physical, rheological and thermal properties of drilling fluids with temperature were neglected. This paper researches the wellbore pressure coupling by calculating the temperature distribution with existed model, fitting the rule of density of drilling fluid with temperature and establishing mathematical models to stimulate the wellbore pressures, which is expressed as the variation of Equivalent Circulating Density (ECD) under different conditions. With this method, temperature and ECDs in the wellbore of the first medium-deep geothermal well ZK212 Yangyi Geothermal Field in Tibet were determined, and the sensitivity analysis was simulated by assumed parameters, i.e. circulating time, flow rate, geothermal gradient, diameters of wellbore, rheological models and regimes, the results indicated the geothermal gradient and flow rate were the most influence parameters on the temperature and ECD distribution, and additives added in drilling fluid should be careful which would change the properties of drilling fluid and induce the temperature redistribution. To make sure the safe drilling, velocity of pipes tripping into the hole, depth and diameter of wellbore are considered to control the surge pressure.

A number of decision support tools facilitating the use of Electric Vehicles (EVs) have been recently developed. Due to the EVs’ limited autonomy, routing and path planning are the main challenges treated in such tools. Specifically, determining at which Charging Stations (CSs) to stop, and how much the EV should charge at them is complex. This complexity is further compounded by the fact that charging times depend on the CS technology, the EV characteristics, and follow a nonlinear function. Considering these factors, we propose a path planning methodology for EVs with user preferences, where charging is performed at public CSs. To achieve this, we introduce the Electric Vehicle Shortest Path Problem with time windows and user preferences (EVSPPWP) and propose an efficient solution algorithm for it. Given an origin and a destination, the algorithm prioritizes CSs close to Points of Interest (POIs) that match user inputted preferences, and user-defined time windows are considered for activities such as lunch and spending the night at hotels. The algorithm produces flexible solutions by considering clusters of charging points (CPs) as separate CSs. Furthermore, the algorithm yields resilient paths by ensuring that recommended paths have a minimum number of CSs in their vicinity. The main contributions of our methodology are: modeling user-defined time windows, including user-defined weights for different POI categories, creating CSs based on clusters of CPs with sufficient proximity, using resilient paths, and proposing an efficient algorithm for solving the EVSPPWP. To facilitate the use of our methodology, the algorithm was integrated into a web interface. We illustrate the use of the web interface, giving usage examples and comparing different settings.

We study factorization properties of continuous homomorphisms defined on subgroups (or submonoids) of products of (para)topological groups (or monoids). A typical result is the following one: Let $D=\prod_{i\in I}D_i$ be a product of paratopological groups, $S$ be a dense subgroup of $D$, and $\chi$ a continuous character of $S$. Then one can find a finite set $E\subset I$ and continuous characters $\chi_i$ of $D_i$, for $i\in E$, such that $\chi=\big(\prod_{i\in E} \chi_i\circ p_i\big)\hs1\res\hs1 S$, where $p_i\colon D\to D_i$ is the projection.

In this paper, we introduce two subclasses of analytic and Spirallike functions and investigate convolution properties, the necessary and sufficient condition, coefficient estimates and inclusion properties for these classes .

Predominantly rural areas make up half of Europe and account for about 20 per cent of the population. Yet most of them are among the least privileged regions in the European Union, with a GDP per capita significantly below the European average and with an average population age higher than in urban areas, although this gap will only slowly begin to narrow in the next decade. Together with a lack of connectivity, inadequate infrastructure, lack of diversified job opportunities and limited access to services, this makes rural areas a less attractive place to live and work. At the same time, however, rural areas actively participate in the EU's green and digital transition. Achieving the EU's digital goals for 2030 can offer more opportunities for the sustainable development of rural areas in areas other than agriculture, livestock and forestry, opening up new perspectives for the growth of manufacturing and, even more, service industries, and contributing to a better geographical distribution of services and industries. In this context, the objective of this work is the construction of a synthetic index of the welfare of European nations, through the Wroclaw taxonomic method and through the use of logit models, for the identification of best practices of local realities and the interpretation in a more im-mediated way of the fair and sustainable welfare of each European nation at a rural level

Dengue virus an arbovirus is endemic in an area that comprise almost half of the world's population, contrary to past beliefs that dengue virus differentiate from other neuroinvasive arbovirus due to its lack of neurological invasion and disease related neurological complications excluding hemorrhagic and thromboembolic , the body of evidence have grown to demonstrate a series of neurological manifestations linked to dengue virus with possible mechanisms involving direct virus invasion of the nervous system or immune mediated complications. In this review we provide a wide approach to this neglect but not so rare manifestations of a very common disease.

Ethiopia has decades of experience in implementing land and water management interventions. Nonetheless, there remains persisting challenges to follow an adaptive management (AM) approach in efforts of restoring and transforming agricultural landscapes. This review was carried out to synthesize evidences on the impact on agricultural landscapes following the implementation of land and water management practices and to evaluate the use of AM approaches. We explored how elements of the structures and functions of landscapes have been transformed, and how the components of AM, such as structured decision-making and learning processes, have been applied. Despite numerous environmental and economic benefits of land and water management interventions in Ethiopia, this review revealed gaps in AM approaches. These include: (i) insufficient efforts in relation to evidence based contextualization of interventions, (ii) insufficient efforts in monitoring of bio-physical and socio-economic processes and changes post implementation, (iii) lack of trade-off analyses, and (iv) inadequacy of local community engagement and provision of feedback. Given the many uncertainties we must deal with, efforts to restore and transform agricultural landscapes cannot follow a business-as-usual approach. Future investment, in AM approach, tailored to the needs and context would help to achieve the goals of sustainable agricultural landscape transformation. The success depends on three interdependent pillars of action: the ability to make a robust, co-developed plan of interventions, the ability to continuously monitor changes based on key variables, and to learn from the knowledge generated and apply the learning as implementation evolves.

In this paper for every number field K generated by a root α of a trinomial x⁷ + ax + b ∈ Z[x] and for every prime integer p, we calculate ν_p(i(K)), the highest power of p dividing the index i(K) of the field K. In particular, we calculate the index i(K). As application, when the index of K is not trivial, then K is not monogenic.

In this study, we introduce a new class of bi-univalent functions using q-Janowski Function. We derive the Fekete-Szegö functional problems for functions in this new subclass, as well as estimates for the Taylor-Maclaurin coefficients |α2| and |α3|. Furthermore, a collection of fresh outcomes are3 presented by customizing the parameters employed in our initial discoveries.

Scenario analysis is a widely employed method for addressing uncertainties when assessing the physical and socio-economic impacts if climate change. Global scenarios have been extensively used in this context. However, these scenarios are in most cases not suitable for supporting local analyses. On the other hand, locally developed scenarios may lack the global context, thus having limited comparability with or transferability to other locations. The Shared Socioeconomic Pathways, which have been primarily developed for climate impact research, provide the possibility to extend the existing global narratives and adapt them to local characteristics in order to develop locally relevant scenarios. Here, we propose a methodological framework for producing harmonized scenarios across different case studies. This framework was developed in the EVOKED project and combines elements of top-down and bottom-up approaches to develop local scenarios for five regions in northern Europe. We employ the SSP as boundary conditions and, in cooperation with stakeholders from these five regions, develop local scenarios for a range of SSP. The developed sets of scenarios are consistently informed by global developments and are therefore comparable with other downscaled scenarios developed in different regions. At the same time, they have been based on local participatory processes, thus being locally credible and relevant to the needs of stakeholders. The local scenarios constitute a climate service per se as they can raise stakeholder awareness of the processes that will drive risk, exposure, and adaptive capacity in the future and inform discussions on mitigation strategies and adaptation pathways.

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.

A software defined radio (SDR) is a communication system that makes use of components that can be configured through software, in contrast to traditional systems where these components are variable through hardware, these radio devices are much more versatile, this article describes the factors that must be considered when implementing a communication system based on Software Defined Radios (SDR), in order to reduce the attenuation factors and thus obtain the maximum distance for a transmission of data effectively in the UHF band. The calculations made for the first Fresnel zone and for the design of the Ground Plane type antennas used in the transmission/reception stages of the x40 bladeRF platforms are also presented. The tests were carried out at the facilities of the Huarangal Nuclear Center of the Peruvian Institute of Nuclear Energy, obtaining favorable results that allow ratifying the versatility and performance of the SDRs.

In this paper we use the additive thermodynamic formalism to obtain new bounds of the Hausdorff and box-counting dimension of certain non conformal hyperbolic repellers defined by piecewise smooth expanding maps on a $d$-dimensional smooth manifold $M$.

This work is concerned with the existence and uniqueness of boundary value problems defined on semi-infinite intervals. These kinds of problems seldom admit exactly known solutions and, therefore, the theoretical information on their well-posedness is essential before attempting to derive an approximate solution by analytical or numerical means. Our utmost contribution in this context is the definition of a numerical test for investigating the existence and uniqueness of solutions of boundary problems defined on semi-infinite intervals. The main result is given by a theorem relating the existence and uniqueness question to the number of real zeros of a function implicitly defined within the formulation of the iterative transformation method. As a consequence, we can investigate the existence and uniqueness of solutions by studying the behaviour of that function. Within such a context the numerical test is illustrated by two examples where we find meaningful numerical results.

Most recent university campuses follow the North American model, built on city limits or countryside, with large separate buildings in open green spaces. Studies suggest that prevalence and severity of mental health issues among university students are increasing over the past decade in most countries. University services were created to face this growing problem, however individual based interventions have limited effects on mental health and well-being of a large population. Our aim was to verify if and how the natural environment in Campuses is focused on programs to cope with the issue of mental health and well-being among students. Systematic review of literature was undertaken with search in Scopus and LILACS with the keywords “green areas” AND “well-being” AND “Campus”, following PRISMA guidelines. As a result, 32 articles were selected. Research on the topic is recent, mostly in the USA, Bulgaria, and China. Most studies used objective information on campuses’ greenness and/or university students’ perception. Mental health was usually measured by validated scores. Findings of all the studies indicated positive association between campus greenery and well-being of students. We conclude that there is a large potential for use of university campuses in programs and sites for students´ restoration and stress relief.

This paper examines the importance of choice of cooking fuels in wellbeing, analysing relationships between the proportion of population with primary reliance on different types of fuels for cooking (predictor variable), and key wellbeing indices (outcome variables) - Personal Health, Social Life, Civic Engagement, Life Evaluation, Negative Experience. By combining two global datasets from Gallup and WHO, the study adds to current evidence by taking a global perspective. Controlling for demographic factors such as income per capita, age, education level, employment, etc., regression modelling of these relationships show that clean cooking fuels are influential in all of the key wellbeing indices with the exception of the Life Evaluation Index. Among the key wellbeing indices, Personal Health and Negative Experience Indices are the most strongly influenced by choice of clean cooking fuels. By adding access to electricity as an additional predictor variable, the analysis highlights the potential for integrating eCooking into national electrification plans as part of sustainable energy transitions, given that health outcomes (Personal health and Negative experience indices) appear to be as closely linked to choice of cooking fuels as to access to electricity.

The clustering methods of Software Defined Networking (SDN) gained popularity due to their ability to offer improved scalability, consistency, dependability, and load balancing within overlay networks and SDN partitions. This paper delved into the effects of increasing the number of OpenFlow-enabled southbound devices on the establishment and coordination of SDN-Controller clusters. Specifically, we examined the volume of east-west cluster packet communication concerning the number of southbound devices within the topology. Many research studies focused on bandwidth and the number of bytes in East-West communication. While bandwidth referred to the maximum rate at which data could be transferred, and the number of bytes reflected the volume of data being transmitted, the number of packet communications directly influenced the efficiency and responsiveness of network operations. Our investigation encompassed the impact of SDN controllerto- controller communication within the cluster concerning the rising number of OpenFlow switches connected to various topologies, including tree (star-bus network), linear, and torus configurations. This study presented data on communication patterns within Open Network Operating Systems (ONOS) and OpenDaylight (ODL) clusters, revealing differing levels of controller communication with southbound network expansions. We evaluated the scalability of ODL and ONOS controllers by scrutinising the effect of increasing the number of southbound devices on control communication volume. Our analysis revealed varied communication patterns within ONOS and ODL clusters, resulting in different volumes of control communication with southbound expansions. The findings indicated that in small to medium-sized SDNs, ODL outperformed ONOS, notably with faster cluster discovery. Conversely, ONOS demonstrated greater efficiency in larger networks owing to its centralised communication architecture. Finally, we provided recommendations for selecting the most suitable controllers based on the size of southbound networks, aiming to provide practical guidelines for optimal network performance.

The Global Navigation Satellite Systems (GNSS) software-defined receivers offer greater flexibility, cost-effectiveness, customization, and integration capabilities compared to traditional hardware-based receivers, making them essential for a wide range of applications. The continuous evolution of GNSS research and the availability of new features require these software-defined receivers to upgrade continuously to facilitate the latest requirements. The Finnish Geospatial Research Institute (FGI) has been supporting the GNSS research community with its open-source implementations, such as a MATLAB-based GNSS software-defined receiver ’FGI-GSRx’ and a Python-based implementation ’FGI-OSNMA’ for utilizing Galileo’s Open Service Navigation Message Authentication (OSNMA). In this context, longer datasets are crucial for GNSS software-defined receivers to support adaptation, optimization and facilitate testing to investigate and develop future-proof receiver capabilities. In this paper we present an updated version of FGI-GSRx, namely FGI-GSRx-v2.0.0, which is also available as an open-source resource for the research community. FGI-GSRx-v2.0.0 offers improved performance as compared to its previous version, especially for the execution of long datasets. This is carried out by optimizing the receiver’s functionality and offering a newly added parallel processing feature to ensure faster capabilities to process the raw GNSS data. This paper also presents an analysis of some key design aspects of previous and current versions of FGI-GSRx for a better insight into the receiver’s functionalities. The results show that FGI-GSRx-v2.0.0 offers about 40% run time execution improvement over FGI-GSRx-v1.0.0 in case of sequential processing mode and about 59% improvement in case of parallel processing mode with 17 GNSS satellites from GPS and Galileo. In addition, an attempt is made to execute v2.0.0 with MATLAB’s own parallel computing toolbox. A detail performance comparison reveals an improvement of about 43% in execution time over v2.0.0 parallel processing mode for the same GNSS scenario.

In this paper, a geometric body-centered model to simulate the periodic structure of unidirectional fibrous composites is presented. To this end, three prescribed configurations are introduced to predict in a deterministic manner the arrangement of internal and neighboring fibers inside the matrix. Thus, three different representative volume elements (RVEs) are established. Furthermore, the concept of the interphase has been taken into account, stating that each individual fiber is encircled by a thin layer of variable thermomechanical properties. Next, these three unit cells are transformed in a unified manner to a coaxial multilayer cylinder model. This advanced model includes the influence of fiber contiguity in parallel with the interphase concept on the thermomechanical properties of the overall material. Then, by the use of this model, the authors propose explicit expressions to evaluate the longitudinal and transverse thermal conductivity of this type of composite. The theoretical predictions were compared with experimental results, as well as with theoretical values yielded by some reliable formulae derived from other workers, and a reasonable agreement was found.

Being forced to live in an area following a catastrophic landslide may adversely impact people's mental well-being. Unprivileged communities such as Adivasis, Dalits, plantation workers, and people with low incomes in Kerala's hilly districts are forced to live in landslide-affected areas despite their fear. This paper examines the fears and concerns of landslide survivors from the marginalized sections of society from a broader framework of the political economy of mental health. This approach aligns with the assertion made by the World Health Organisation that individual factors do not solely determine mental health but are intricately linked to broader social, political, and economic circumstances. Data were collected through in-depth interviews with fatal landslide survivors and key informants [ ]. The study employed thematic data analysis from in-depth interviews of various fatal landslide survivors since 2018. The three major themes unveiled in the analysis are: 1. post-disaster fears, 2. The factors that triggered fear and concern and 3. Socio-economic marginality and mental health. The study asserts that individuals who are poor and unprivileged are highly susceptible to mental health issues associated with landslides.

First, this paper broaches the epistemological status of scientific tenets and approaches: phenomenological (descriptive only), well-founded (solid first principles, conducive to deep understanding), provisional (can be falsified if universal and verified if existential), and imaginary (fictitious entities or processes, conducive to empirically unsupported beliefs). The ΛCDM “concordance model” involves such beliefs: the emanation of the universe out of a non-physical stage, cosmic inflation (invented ad hoc), Λ (fictitious energy), and exotic dark matter. Big Bang cosmology further faces conceptual and pragmatic problems in delimiting what expands from what does not. The problems dissolve after untying inertia from space. The cosmology that emerges appears immediately compatible with the considered observations and the ‘perfect cosmological principle’. Waves and field perturbations that propagate at c expand exponentially with distance (a gravitational effect). The cosmic web of galaxies does not. Potential -Φ varies as H/(cz) instead of 1/r. Inertial forces arise from the gravitational action of the rest of the universe. Due to dilatation, they are reduced disproportionately at low accelerations. A cut-off value a₀ = 0.168 cH is deduced. This explains the successful description of galaxy rotation curves by MoND. A fully elaborated physical theory is still pending. Wider implications are briefly discussed.

In the realm of digital transformation, effective leadership and motivation are pivotal for organisations navigating the complexities of today’s systems. This study explores the intersection of intrinsic motivation and mental well-being among mature students—an analogy that sheds light on strategies applicable to organisational contexts. In developed nations like the UK, mental health for mature students is increasingly recognised as a crucial component of their educational journey. Mature students, who typically enrol in higher education after an educational gap and upon turning 21, often face specific challenges that can impact their mental well-being while pursuing academic goals. The primary objective of our study was to assess the relationship between intrinsic motivation and the mental well-being of mature students. Our research revealed a significant positive correlation between these two variables. Confirmatory factor analysis (CFA) results supported a one-factor solution for the sample data from mature students. Additionally, we found that intrinsic motivation is a significant predictor of the mental well-being of mature students. Recognising and addressing the unique difficulties individuals encounter and providing appropriate support can enhance their well-being and contribute to the overall success of the higher education community.

With the advancement of the economy and society, policymakers acknowledge the significance of improving rural households' well-being as a crucial factor in promoting sustainable economic and social development. Based on the matching data of China Household Finance Survey and Digital Rural County Index, this study empirically examines the effect and mechanisms of digital village construction on subjective well-being of rural households. The results revealed that digital village construction has a significant improvement in their subjective well-being. The impact of digital village construction is particularly significant in rural areas located in the western regions of China, as well as among households possessing higher levels of human capital. The process through which digital village construction enhances the subjective well-being of rural households involves the augmentation of household income, the promotion of non-farm employment opportunities, and the enhancement of rural governance. This study provides robust micro-empirical evidence highlighting the positive welfare effects of digital rural construction. This study provides insights into the digital village construction within the happiness economy framework, offering a new perspective. The imperative to strengthen rural digital infrastructure and improve farmers' proficiency in modern information skills is a strategic policy aimed at enhancing well-being of rural households.

Emotional intelligence and educational level are commonly associated with success in life and well-being. While multiple studies have explored these concepts independently, few studies have examined the impact of educational level on emotional intelligence and associated variables, such as well-being. A total of N = 202 participants were recruited online. Participants completed measures of emotional intelligence, well-being (i.e., happiness, self-esteem, personal growth). Overall, participants who previously obtained a bachelor’s degree displayed higher levels of emotional intelligence, happiness, self-esteem, and personal growth compared to those without an undergraduate degree. However, no differences were observed on any variable between individuals currently enrolled in a university and non-students. The results suggest that, while completing a university degree increases emotional intelligence and well-being, the stress of being a student may negatively impact the benefits obtained from attending university. Limitations and possible directions for future research are discussed.

This review was written with the aim of examining the effects that caused an insult such as a wound to an organ such as the skin. Before examining the cellular mechanisms relating to wound healing, the reader is invited to read the structure of the skin as a necessary basis for understand-ing the final aim of this review. The structure of the skin as a basis for understanding the phe-nomena relating to wound healing is addressed taking into account updated literature that ad-dresses the numerous problems of the skin microenvironment. Starting from this awareness, the paragraph dedicated to wound healing becomes complicated when this phenomenon is not im-plemented and therefore the problems dedicated to chronic wounds, keloids and hypertrophic scars are addressed, pathologies that are still difficult to understand and treat today.

The energy-intensive sector of the cement industry needs to find technologically advanced methods to produce cement with as little energy as possible, without polluting the environment and without sacrificing the quality (fineness) of the cement. In addition, the stress on the machines changes the behavior of the data. By combining the k-means method, two (2) feature selection methods, nine (9) machine learning methods, and the differential evolution (DE) method, a dynamic system is created where the user determines the key performance indicators (KPIs) each time. The user has the potential to control the distribution of the data, the input of machine learning models, and the ability to switch the system to the suggested values without damage. The selection of the best-performing models is based on the normalized root mean squared error (NRMSE). The DE method optimizes the dynamic objective function. The optimal values of the manipulated variables are evaluated compared to the value of the objective function from the actual values of the variables. In all experiments, the recommendations are acceptable. The final results show an improvement in the operation of both the cement mill and kiln compared to the current operating condition.

Recent advancements in Software Defined Networking (SDN) makes it possible to overcome the management challenges of traditional network by logically centralizing control plane and decoupling it from forwarding plane. Through centralized controllers, SDN can prevent security breach, but it also brings in new threats and vulnerabilities. Central controller can be a single point of failure. Hence, flow-based anomaly detection system in OpenFlow Controller can secure SDN to a great extent. In this paper, we investigated two different approaches of flow-based intrusion detection system in OpenFlow Controller. The first of which is based on machine-learning algorithm where NSL-KDD dataset with feature selection ensures the accuracy of 82% with Random Forest classifier using Gain Ratio feature selection evaluator. In the later phase, the second approach is combined with Gated Recurrent Unit Long Short-Term Memory based intrusion detection model based on Deep Neural Network (DNN) where we applied an appropriate ANOVA F-Test and Recursive Feature Elimination feature selection method to improve the classifier performance and achieved an accuracy of 88%. Substantial experiments with comparative analysis clearly show that, deep learning would be a better choice for intrusion detection in OpenFlow Controller.

Within the Active Living and Well-Being Project (RRP3), funded by the Republic of Slovenia and the European Regional Development Fund Investing in Your Future programme, we aim to develop different approaches and prototypes to provide ICT solutions for the family in order to connect its members, communicate, promote quality family time, active life, a health-friendly lifestyle and well-being, and integrate various sensor and user-based data sources into a smart city ecosystem platform. A mixed methodology, combined qualitative and quantitative approaches, was selected to conduct a study. An online survey with a structured questionnaire as well as semi-structured interviews were performed. Through the analysis of the results we tried to establish a family-centred design approach that would be inclusive as much as possible, creating benefits for all generations in order to develop interactive prototypes that would allow us to further test and verify different use-case scenarios.

Purpose: Young transgender and non-binary are exposed to situations of discrimination and have a greater risk of violence. The purpose of this study is to analyze which protective, violence and health and well-being factors have more influence on transgender and non-binary people compared to cisgender people. Method: The sample comprised 856 people between 14 and 25 years old. A survey including questions about sociodemographic information and protective, violence and health and well-being factors was designed ad hoc for this study. Results: The results show non-binary group received the least support from family and friends, higher risk of suffering cyberbullying and a higher feel isolated and unhappy. Non-binary and transgender have suffered more verbal attacks both inside and outside their school and physical attacks at school than cisgender young. Conclusions: These results are important and may contribute to promote public policies and clinical interventions to favor the integration of non-binary and transgender people in our society.

To meet the calls of the International Labor Organization and National Institutes of Occupational Safety and Health, this paper discusses how to build Occupational, Health, Safety (OSH), and Well-Being competence by expanding education to non-traditional undergraduate disciplines. The authors provide (1) theoretical background on why this would benefit society as a whole, (2) learning theory strategies for teaching OHS and Well-being outside of traditional majors, (3) case studies of how this can occur in undergraduate classes and (4) opportunities and challenges for the future.

Spectral image analysis has the potential to replace traditional approaches for assessing plant responses to different types of stress including herbicide, through non-destructive and high-throughput screening (HTS). Therefore, this study was conducted to develop a rapid bioassay method using a multi-well plate and spectral image analysis for diagnosis of herbicide activity and mode of action. Crabgrass (Digitaria ciliaris) as a model weed was cultivated in multi-well plates and subsequently treated with 6 herbicides with different modes of action when they reached the 1-leaf stage, using only a quarter of the recommended dose. To detect plant response to herbicides, plant spectral images were acquired after herbicide treatment using RGB, infrared (IR) thermal, and chlorophyll fluorescence (CF) sensors and analyzed for diagnosing herbicide efficacy and mode of action. Principal Component Analysis (PCA) using all spectral data successfully distinguished herbicides and clustered depending on their modes of action. The performed experiments have shown that the multi-well plate assay combined with spectral image analysis can be successfully applied for herbicide bioassay. In addition, the use of spectral image sensors, especially in CF image, would facilitate HTS by enabling rapid observation of herbicide response, as early as 3 hours after herbicide treatment.

(1) Background: Psychological well-being (PWB) and female sexual health are two important areas for women’s quality of life and research, and they are closely related. The aim of this study was to conduct a systematic review of the existing literature to explore the association between PWB and sexual health in women. (2) Methods: This review was carried out following PRISMA. The inclusion criteria were studies with samples of adult women, that evaluated and associated sexual functioning and mental health. Scientific articles were identified on Web of Science, Scopus, EBSCO (PsycInfo, PsycArticles, and Psicodoc), ProQuest, and PubMed. The search was limited to years between 2010 and 2023. (3) Results: 14 selected articles were analyzed, in which population samples and variables related to mental and sexual health were examined. 42.9% of the studies included clinical samples, 71.4% focused on anxiety and depression as main mental health variables, and 50% examined female sexual functioning as a sexual health variable. (4) Conclusions: This review provides more up-to-date information about valuable insights into the possible determinants of female sexual health. The association between PWB and female sexual health has been demonstrated.

This paper focuses on the relationship between Mental Health and the Landscape. It aims to find out how people respond to Biophilic inspired landscape design in a healthcare setting. The focal point is not to cure diseases but to help them deal with the physiological, psychological, and psycho-social imbalance and provide a healing environment for the overall well-being of an individual. For this study, a Multispecialty Hospital was selected where an Indoor Healing Garden is used as a retrofitting tool to reduce stress and thus reconnect humans with nature. A multi-method approach is being used for this study. Initially, a questionnaire was conducted for the targeted users categorized into three types – patients, staff, and visitors to know their longing for the landscape. Based on this data and available literature, an evidence-based design was proposed. This conceptual design model is then shown to the targeted user and the response is recorded. The data has then collaborated with similar studies done earlier and design elements are highlighted which helps in creating a restorative environment by reducing stress and increasing recovery rate and thus approaching sustainable development.

At the level of the 50 U.S. states, an interconnected nexus of well-being variables exists. These variables have been shown to strongly correlate with estimates of state IQ in interesting ways. But the state IQ estimates (McDaniel 2006) are now more than 16 years old, and the state well-being estimates (Pesta et al., 2010) are over 12 years old. Updated state IQ and well-being estimates are therefore needed. I thus first created new state IQ estimates by analyzing scores from both the Program for the International Assessment of Adult Competency (for adults), and the National Assessment of Educational Progress (for fourth and eighth grade children) exams. I also created new global well-being scores by analyzing state variables from the following four well-being subdomains: crime, income, health, and education. When validating the nexus, several interesting correlations existed among the variables. For example, state IQ most strongly predicted FICO credit scores, alcohol consumption (directly), income inequality, and state temperature. Interestingly, state IQ derived here also correlated .58 with state IQ estimates from over 100 years ago. Global well-being likewise correlated with many old and new variables in the nexus, including a correlation of .80 with IQ. In sum, at the level of the U.S. state, a nexus of important, strongly correlated variables exists. These variables comprise well-being, and state IQ is a central node in this network.

Telecommuting is a flexible form of work that has progressively spread over the last 40 years and which has been strongly encouraged by the measures to limit the Covid19 pandemic. There is still limited evi-dence on the effects it has on workers' health. In this survey we invited 905 workers of companies that made a limited use of telework to fill out a questionnaire to evaluate: Intrusive leadership of managers (IL), the request for work outside traditional hours (OFF-TAJD), workaholism (BWAS), effort / reward imbalance (ERI), happiness and common mental issues (CMIs), anxiety and depression, assessed by the Goldberg scale (GADS). The interaction between these variables has been studied by structural equation modeling (SEM). Intrusive leadership and working after hours were significantly associated with occu-pational stress. Workaholism is a relevant moderator of this interaction: intrusive leadership significantly increased the stress of workaholic workers. Intrusive leadership and overtime work were associated with reduced happiness, anxiety and depression. These results indicate the need to guarantee the right to disconnect, to limit the effect of the OFF-TAJD. In addition to this, companies should implement policies to prevent intrusive leadership and workaholism.

In a software-defined radar (SDR) system, most of the signal processing usually implemented in hardware is implemented by software, thus allowing for higher flexibility and modularity compared to conventional radar systems. However, the majority of SDR demonstrators and proofs-of-concept reported in the open literature so far have been based on simple antenna systems. As a result, the full potentialities of an SDR approach have not been completely exploited yet. In this work, we propose a flexilbe antenna module to be integrated into an active electronically scanning array (AESA) with controlled sidelobe level over a wide angular range, exhibiting polarization reconfigurability with low cross-polarization level and high isolation. For this purpose, analytical and numerically efficient techniques for the synthesis of the aperture distribution and the correct evaluation of the radiating features (e.g., beamwidth, pointing angle, sidelobe levels, etc.) are presented in order to grant a real-time control of the digital beamforming network. A sub-array module demonstrator is fabricated and measured to corroborate the concept.

The results of applying drilling engineering tools in planned deviated and horizontal wells of oil and gas condensate fields have been examined. The basis for the implementation of a comprehensive approach was the information obtained from drilling horizontal wells in the West and East Siberia, Volga-Ural region, and Iraqi Kurdistan. A synthetic model is considered as an example of the data, incorporating geomechanical and geological properties. As a result of the conducted audit of the geomechanical model and drilling process, the methodologies used were further developed to obtain optimal drilling fluid densities, aiming to prevent cavity formation on well walls, hydraulic fractures, and other related issues. The implementation of the Python programming language was introduced in the stages of geomechanical model preparation, resulting in a time acceleration of up to 20%. During the pre-drilling stage, technological operations were synchronized with the geomechanical model, increasing the involvement of process participants through the synchronization of knowledge areas. The interrelation between drilling technology, drilling parameters, properties of flushing fluids, and rock stability analysis was established, ensuring a 5% increase in construction speed (through NPT reduction and modification of existing tools and technological operations) and accident-free drilling of complex deviated and horizontal wells, provided that the recommended drilling parameters are followed.

Drilling of wells for oil and gas production is a highly complex and expensive part of reservoir development. Thus, together with injury prevention, there is a goal to save cost expenditures on downtime and repair of drilling equipment. Nowadays companies have begun to look for ways to improve the efficiency of drilling and minimize non-production time with the help of new technologies. To support decisions in a narrow time frame, it is valuable to have an early warning system. Such a decision support system will help an engineer to intervene in the drilling process and prevent high expenses of unproductive time and equipment repair due to a problem. This work is describing a comparison of machine learning algorithms for anomaly detection during well drilling. Tested models classify drilling problems based on historical data from previously drilled wells. To validate anomaly detection algorithms, we use historical logs of drilling problems for 67 wells at a large brownfield in Siberia, Russia. Wells with problems were selected and analyzed. It should be noted that out of the 67 wells, 20 wells were drilled without expenses for unproductive time. Experiential results illustrated that a model based on gradient boosting can classify the complications in the drilling process best of all.

Well differentiated liposarcoma (WD-LPS) is a relatively rare tumour, with less than 50 cases occurring per year in the UK. These tumours are both chemotherapy and radiotherapy resistant and present a significant treatment challenge requiring radical surgery. Little is known of the molecular landscape of these tumours and no current targets for molecular therapy exist. We aimed to carry out a comprehensive molecular characterisation of WD-LPS via whole genome sequencing, RNA-sequencing and methylation array analysis. A recurrent mutation within exon1 of FOXD4L3 was observed (chr9:70,918,189A>T; c.322A>T; p. Lys108Ter). Recurrent mutations were also observed in Wnt signalling, immunity, DNA repair and hypoxia-associated genes. Recurrent amplification of HGMA2 was observed, although this was in fact part of a general amplification of the region around this gene. Recurrent gene fusions in HGMA2, SDHA, TSPAN31 and MDM2 were also observed as well as consistent rearrangements between chromosome 6 and chromosome 12. Our study has demonstrated a recurrent mutation within FOXD4L3, which shows evidence of interaction with the PAX pathway to promote tumorigenesis.

As Christopher Alexander discovered, all space or matter – either organic or inorganic – has some degree of order in it according to its structure and arrangement. The order refers to a kind of structural character, called living structure, which is defined as a mathematical structure that consists of numerous substructures with an inherent hierarchy. Across the hierarchy, there are far more small substructures than large ones, while on each level of the hierarchy the substructures are more or less similar in size. In this paper we develop a new approach to representing geographic space as a hierarchy of recursively defined subspaces for computing the degree of order. A geographic space is first represented as a hierarchy of recursively defined subspaces, and all the subspaces are then topologically represented as a network for computing the degree of order of the geographic space, as well as that of its subspaces. Unlike conventional geographic representations, which are mechanical in nature, this new geographic representation is organic, conceived, and developed under the third view of space; that is, space is neither lifeless nor neutral, but a living structure capable of being more living or less living. Thus, the order can also be referred to as life, beauty, coherence, or harmony. We applied the new representation to three urban environments, 253 patterns, and 35 black-white strips to verify it and to demonstrate advantages of the new approach and the new kind of order. We further discuss the implications of the approach and the order on geographic information science and sustainable urban planning.

In the realm of cement production, clinker-producing factories emerge as both energy and material-intensive entities, emitting a substantial array of primary pollutants into the environment compared to their non-clinker producing counterparts. Our study delves into Ethiopian clinker-producing cement factories, unraveling the concentration of primary pollutants and their repercussions on neighboring communities. Venturing beyond mere statistics, we meticulously measured particulate matter (PM2.5 and PM10) and gaseous emissions (CO2, N2O, SO2) at various units within the cement factories and in nearby residential areas. The findings reveal an ambient air quality riddled with concern; PM2.5 levels ranged from 137 to 814 μg/m3, PM10 from 195 to 886 μg/m3 within the cement factories, and PM2.5 (113 to 196 μg/m3) and PM10 (125 to 453 μg/m3) in the adjacent village. Alarmingly, these particulate matter emissions exceeded the limits set by Ethiopian ambient air quality guidelines (150 μg/m3). Unraveling the health implications, respiratory diseases were notably high among individuals aged 25 to 60, followed closely by those aged 6 to 24. In contrast, the age groups 0–5 and > 61 exhibited lesser susceptibility, as infants and the elderly spent more time at home, thus reducing exposure to emissions. Our study underscores the urgent need for legal measures, calling for the establishment of buffer zones between cement factories and settlements. This proactive step, if enforced, holds the promise of mitigating cement particulate emissions and safeguarding the well-being of communities residing in proximity to these industrial giants.

The well-being in the people is a key aspect of the field of psychology. Hence, it is important to an-alyse the variables that are related to life satisfaction and happiness as perceived by individuals and that, therefore, increase their overall well-being. The main objective of this study was to ana-lyse the predictive capacity of emotional intelligence and perceived social support on both the level of life satisfaction and perceived happiness. A total of 380 psychology students completed the Trait Meta Mood Scale, the Multidimensional Scale of Perceived Social Support, the Satisfaction With Life Scale, and the Subjective Happiness Scale. The results show that both emotional intelligence and social support are related to and predictive of subjective happiness and life satisfaction. The importance of developing the components of emotional intelligence and promoting an adequate social network in young people is highlighted.

The rapid growth of urban areas has led to a decline in the amount of green space available to residents. This has a number of negative consequences for human health and well-- being. Green spaces provide a number of benefits for human health, including improved physical, mental, and social health. They also have a number of economic benefits, such as increased property values and reduced crime rates. Given the many benefits of green spaces, it is clear that they are essential for the health and well-being of urban residents. Policymakers and planners should prioritize the creation and preservation of green spaces in urban areas.

The rise of multi-sided digital platforms has transformed the global economy, enabling individuals and companies to create, deliver, and capture value through innovative connections and network effects. While scholars have studied the core strategy concepts and proposed platform architectures, less attention has been paid to the long-term sustainability of these platforms. This paper addresses this gap by examining the relationship between sustainability and platform architecture. Specifically, it asks what mechanisms characterize digital platforms for sustainability, and whether there are design choices that optimize the business model for sustainability. Using a mixed-methods approach that draws on platform literature, business models, and sustainable innovation, the paper develops an integrative framework to identify elements and design choices in platform businesses which support sustainability outcomes. The framework is then used to classify the business models of the identified platforms, revealing specific design choices for platform architecture that can optimize their business models for sustainability. This contribution to existing literature provides an artifact that allocates key decisions on value creation, delivery, and capture that are key to platforms and includes an additional layer to optimize them for long-term sustainability. As digital platforms continue to drive the economy, this research is relevant not only to platform practitioners, but also to policy makers and society at large.

The objective of this study was to compare the mental well-being of French women who were and were not pregnant during the first COVID-19 pandemic lockdown. We performed a nationwide online quantitative survey including all women between 18 and 45 years of age during the second and third weeks of global lockdown (March 25–April 07, 2020). The main outcome measures was the mental well-being measured by the Warwick-Edinburgh Mental Well-Being Scale (WEMWBS). This study analysed 275 responses from pregnant women and compared them with those from a propensity score–matched sample of 825 non-pregnant women. The median WEMWBS score was 49.0 and did not differ by pregnancy status. Women living in urban areas reported better well-being, while those with sleep disorders or who spent more than an hour a day watching the news reported poorer well-being. During the first lockdown in France, women had relatively low mental well-being scores, with no significant difference between pregnant and non-pregnant women. More than ever, health-care workers need to find a way to maintain their support for women’s well-being. Minor daily annoyances of pregnancy, such as insomnia, should not be trivialised because they are a potential sign of poor well-being.

This study aims to assess using a smartphone app (DecibelX), as a noise measuring alternative to the more costly traditional use of measuring noise levels with a Sound Level Meter (SLM). The study compares the accuracy of the app to readings taken with a SLM and dosimeter, and also evaluates the app’s performance for pure tone and narrow band noise. And a usability study identifies strengths and weaknesses related to usability of the app.

This study examines the relationship between teleworking, gender roles and happiness of couples using data from the British Household Panel Survey (BHPS) and the Understanding Society Survey (USS) during the period 1991-2012. Various approaches are followed, including Probit-adapted fixed effects, multinomial Logit and Instrumental variables (IV). The results support that both men and women who are teleworkers spend more time on housework, while teleworking increases the probability that the household chores examined in this study, such as cooking, cleaning ironing and childcare, will be shared relatively to those who are non-teleworkers. In addition, women are happier when they or their spouse is teleworker, as well as, both men and women are happier when they state that the specific household chores are shared. Thus, women teleworkers may be happier because they can face the family demands and share the household chores with their spouse, increasing their fairness belief about the household division allocation and improving their well-being, expressed by happiness.

: Cybersecurity has become a critical area in the digital field in recent years. The expansion of networks has revolutionised the way network structures are organised and managed. However, with increased connectivity and the growing complexity of modern networks, the threat of cyber-attacks has become more intense. As technology continues to advance, it brings both opportunities and challenges. One of the major challenges is the need to secure networks and sensitive data from various malicious activities. Traditional networks have evolved to include Software Defined Network (SDN), which offers a more flexible and programmable framework. Researchers should focus on detecting attacks in SDN because SDN networks are becoming more popular and attractive targets for clients due to their programmability and dynamic nature. The centralised controller, known as the backbone of an SDN, becomes a single point of failure and a potential target for attackers if not properly secured. Researchers need to emphasise the detection of attacks in SDN in order to mitigate these risks. By understanding the potential vulnerabilities and attack methods specific to SDN, researchers can develop effective detection approaches and propose countermeasures. This methodology helps protect the network from potential threats and minimises the impact of successful attacks. Therefore, this survey paper provides a review of Intrusion Detection Systems (IDSs) in Software-Defined Networks (SDN) to provide a thorough understanding of SDN security issues.

The use of Information Communication Technologies (ICT) in education brings up new possibilities of promoting the learning and health experiences. In this sense, education contexts of 21st century must consider these two areas of knowledge, especially their integration. This article presents learning practices developed with mobile devices and games, in order to improve learning and well-being in children and adolescents undergoing cancer treatment in non-formal educational setting. The methodology is based on qualitative case studies with content-based data analysis, involving informal interviews and observation methods. The study considers data from 5 patients who participated in the research between 2015 and 2019. The results demonstrate a positive influence of the practices with mobile technologies and games in terms of learning and in the well-being feeling of patients during the treatment.

We calculate energies of shallow donors confined in a rolled-up quantum well in the presence of the electric field by solving numerically the Schrödinger equation in natural curvilinear coordinates. It is found that the curves of density of states (DOS) are very sensitive to the variation of the donor position, the geometry of the spiral and the applied electric field value. Novel results for dependencies of donor’s dipole moment and its polarizability on the electric field strength and its orientation, for different donor positions are presented. Also, we found that anisotropic Stark effect of the first order provides in this structure a dependency of the polarizability on the external electric field in a spike-like shape, giving rise to a sharp variation of the dipole moment.

This review paper gives Excel functions for highly precise Colebrook’s pipe flow friction approximations developed by users. All shown codes are implemented as User Defined Functions – UDFs written in Visual Basic for Applications – VBA, a common programming language for MS Excel spreadsheet solver. Accuracy of the friction factor computed using nine to date the most accurate explicit approximations is compared with the sufficiently accurate solution obtained through an iterative scheme which gives satisfying results after sufficient number of iterations. The codes are given for the presented approximations, for the used iterative scheme and for the Colebrook equation expressed through the Lambert W-function (including its cognate Wright ω-function). The developed code for the principal branch of the Lambert W-function has additional and more general application for solving different problems from variety branches of engineering and physics. The approach from this review paper automates computational processes and speeds up manual tasks.

Moral identity can promote people’s well-being, but existing research has paid little attention to the mechanism of the link between the two. The current study proposed that the eudaimonic identity function is a critical mechanism that links moral identity and well-being. Specifically, the quality of identity commitment mediates the link between subjective well-being and the two dimensions of moral identity, namely, internalization and symbolization. We examined these hypotheses in 419 participants, who completed the Self-importance of Moral Identity Questionnaire, Satisfaction with Life Scale, Scale of Positive and Negative Experience, and Questionnaire for Eudaimonic Well-being. Results from the obtained data confirmed our hypotheses: There is a significant correlation between moral identity and subjective well-being. Both the internalization and symbolization dimensions of moral identity promote subjective well-being through the mediating role of identity commitment quality. We discussed these findings with respect to implications and proposed research suggestions for future studies.

Solid-state lighting has been replacing conventional lighting in the market, raising concerns for implementing an efficient end-of-life management system. Since LED waste streams have not been quite dominant, characterization studies (product-level characteristics, component-wise information, bill of materials, diversity, and differences) are inconsistent and having substantial gaps. This study investigates the end-of-life LED lamp literature, focusing on the bill-of-materials, and reveals that the characterization procedure suffers from a severe lack of sample representativeness. Consequently, characterization results are widely varied and not generalizable. Moreover, most of the studies did not inform and document the detailed sample characteristics, precluding the possibility of identifying reasons for variation. Combining available information from the recent studies, we present a mass distribution at the component level, exemplifying the prospect for meeting EU regulatory limit and the need for more insight at the lamp and component level. To fill the disconnection between lamp level characteristics and component and material content, we propose a characterization protocol that carefully documents lamp, component, and material level information by establishing a lamp-component–material composition nexus. The protocol may help researchers, policymakers, and industrial stakeholders conduct a systematic characterization, analyze complexities and prepare for a sustainable solution.

This current research follows up on Greenleaf’s oft-quoted best test of servant leadership that calls for employees to be better off financially, emotionally, physically, psychologically, etc. because of the time spent with the servant leader. While oft-quoted, little empirical work exists to see if this is true. In this study, 170 participants provided their perception of their supervisors’ level of servant leadership, their perception of the organization’s support, and their self-report of their general well-being. Gender and age bracket information described the participants, and there were no significant differences between gender or age brackets for participants’ perception of their supervisors’ servant leadership. The analysis showed that there was a moderate positive correlation between servant leadership, perceived organizational support, and general well-being. A modification of an existing general well-being instrument provided a new eight-item general well-being scale with a Cronbach’s alpha of 0.956.

It is postulated in this research that the paradox of “advances in technology and management not keeping pace with the ever-increasing urban problems” is due to the poor understanding of person-focused governance of societal, environmental and economic entities. Therefore, the objective of this paper is to present an adaptive institutional model of person-driven effectiveness and ineffectiveness. The model proposes that human, ecologic and economic outcomes are heavily influenced by a complex system of systems, spanning from individually unique “non-physical influencers” to a broader set of social and environmental influencers that have a common impact on the larger society-environment-economy (SEE) system. At the heart of the model is an analytic formulation that explains the phenomena of non-physical blocker, enhancer and indifferent that are responsible for the adaptation and maladaptation of social agents, and accordingly for the sustainability and unsustainability of SEE systems. Examples are provided to illustrate the model applications: (a) the non-physical and maladaptive syndromes as antecedents of multi-morbidity and (b) the broadened and narrowed minds as sources of sustainability and unsustainability at the SEE system level within the context of emerging technologies such as engineered nanomaterials.

The mesoporous heteroatom molecular sieve MCM-41 bulk crystals with the crystalline phase were synthesized via a one-step hydrothermal method using an ionic complex as template. The ionic complex template was formed by interaction between cetyltrimethylammonium ions and metal complex ion [M (EDTA)]2- (M=Co or Ni ). The materials were characterized by X-ray diffraction, scanning electron microscopy, high-resolution transmission electron microscopy, N2 adsorption–desorption isotherms, and X-ray absorption fine structure spectroscopy. The results showed that the materials possess a highly ordered mesoporous structure with the crystalline phase and possess high uniform ordered arrangement channels. The structure is in the vertical cross directions with a crystalline size of about 12 µm and high specific surface areas. The metal atoms were incorporated into the zeolite frameworks in the form of octahedral coordinate and have a uniform distribution in the materials. The amount of metal complexes formed by metal ion and EDTA is an essential factor for the formation of the vertical cross structure. Comparing to Si-MCM-41, the samples exhibited better conversion, higher selectivity for cumene cracking.

Oxytocin (OT) is regarded as an extremely important prosocial neuropeptide that dramatically affects the establishment of social connections from infancy to adulthood. OT effects on the psychoemotional state are pretty individual and may be dependent on age, gender, ethnocultural factors, social environment, the presence of stress factors, and features of personality. The Strengths and Difficulties Questionnaire (SDQ) is a brief psychopathological screening tool and is recommended for the detection and classification of psychosocial problems in adolescents. The current field school-based study, conducted among urban Siberian adolescents (n = 298 aged 12–18) explored the relation of SDQ scales in relation to genotypes of CD38 gene that controls oxytocin release, rs3796863, and oxytocin receptor gene (OXTR), rs53576. The results of our study show that during the adolescence period, OT pathway high activity can cause some negative effects, such as emotional instability in young (aged 12–14) adolescent girls in the case of carriage of the rs3796863 A allele and emotional disturbances in older (aged 15–18) adolescent boys who are carriers of a GG variant of rs53576. Our results support the hypothesis of OT-mediated excessive social sensitivity which can lead to some age-sex depending psychosocial problems during adolescence.

The sexual health needs of female immigrant adolescents in Canada have been largely unmet and have increased in magnitude over the last few years. Evidence suggests that immigrant adolescents lack sexual and reproductive health knowledge and use fewer sexual health-related services and sex education resources than do non-immigrant youth. In Pakistani immigrant adolescents, this difference appears to be associated with socio-cultural and religious practices. This paper aims to describe how first-or-second generation Pakistani-descent female adolescents, living in Canada, describe their perspectives on developing sexuality and well-being. In addition, this paper explicates female adolescents’ perceptions of their needs to support their sexuality while going through the adolescence stage. Using a qualitative interpretive descriptive design, individual interviews were conducted in combination with drawing timelines. A purposive sample of 21 female adolescents who were first- or second-generation Pakistani-descent was obtained. A thematic analysis approach was used for data analysis. Findings suggest that immigrant female adolescents encounter mental health concerns as a result of confusing messages they received from their parents related to sexuality. Also, discrimination, exclusion from sex education classes, and lack of knowledge on sexual health can result in social exclusion, avoidance of health care, and poor mental health outcomes such as depression and anxiety. These participants related experiences are potentially contributed by the lack of communication with parents about sexuality and lack of health care providers who can understand and speak to their needs and realities as immigrant individuals. Female adolescents expressed their need to break the silence around the topic of sexuality, to have a non-judgemental and blame-free attitude from adults, and for open, honest, and stigma-free conversations. This study provides preliminary qualitative evidence of the interplay between experiences of developing sexuality and overall well-being, particularly psychological wellbeing in female adolescent immigrants. It is crucial to involve, listen to, and incorporate adolescent girls’ voices when planning and implementing interventions to support healthy sexuality among immigrant adolescents.

Although research has long established that the interaction with the natural environment is associated with better overall health and well-being outcomes, the Western model mainly focuses on treating the symptoms. In Aotearoa-New Zealand, the Indigenous Māori have long demonstrated significantly more negative health outcomes than non-Māori. Little research has examined the causes compared to Western populations or the role of the natural environment in health outcomes for Māori. An exploration of rongoā Māori (traditional healing system) was conducted to ascertain the importance of landscape in the process of healing. Eight rongoā healers or practitioners took part in semi-structured narrative interviews from June to November 2020. Transcribed interviews were analysed using an interpretative phenomenological analysis and Kaupapa Māori techniques. The findings show how rongoā is underpinned by a complex set of cultural values and beliefs, drawing from the connection to wairua (spirit), tinana (body), tikanga and whakaora (customs and healing), rākau (plants), whenua (landscape) and whānau (family). Incorporating such constructs into the landscape can foster our understanding of health and well-being and its implications for conceptualising therapeutic environments and a culturally appropriate model of care for Māori and non-Māori communities.

The next-generation "Industrial Internet of Things" (IIoT) will support "Machine-to-Machine" (M2M) communications for smart Cyber-Physical-Systems and Industry 4.0, and require guaranteed cyber-security. This paper explores hardware-enforced cyber-security for critical infrastructures. It examines a Quantum-Safe "Software-Defined Deterministic IIoT" (SDD-IIoT), with a new forwarding-plane (sub-layer-3a) for deterministic M2M traffic flows. A "Software-Defined-Networking" (SDN) control-plane controls many "SDD Wide Area Networks" (SDD-WANs), realized with FPGAs. The SDN control-plane provides an "Admission-Control/Access-Control" system for network-bandwidth, using collaborating Artificial Intelligence (AI) rule-based "Zero Trust Architectures" (ZTAs). Hardware-enforced access-control eliminates all congestion, BufferBloat, and DoS/DDoS attacks in the forwarding-plane, reduces buffer-sizes by 100,000+ times, and supports ultra-reliable and uItra-low-latency communications in the SDD-WANs. The SDD-WANs can: (i) Encrypt/Authenticate M2M flows using Quantum-Safe ciphers, to withstand attacks by Quantum Computers; (ii) Implement "Guaranteed Intrusion Detection Systems" in FPGAs, to detect cyber-attacks embedded within billions of IIoT packets/second; (iii) Provide guaranteed immunity to external cyber-attacks against critical infrastructure, and exceptionally-strong immunity to internal cyber-attacks; (iv) Save $US100s of billions annually by exploiting FPGAs; and (v) Enable "Quantum Key Distribution" (QKD) Networks by providing a programmable forwarding-plane with "authenticated classical channels" and full-immunity to DoS/DDoS attacks. Extensive experimental results for an SDD-WAN over the European Union are reported.

In this paper we investigate the optimal investment strategy for a defined contribution (DC) pension plan during the decumulation phrase which is risk-averse and pays close attention to inflation risk. The plan aims to maximize the expected constant relative risk aversion (CRRA) utility from the terminal wealth by investing the wealth in a financial market consisting of an inflation-indexed bond, an ordinary zero coupon bond and a risk-free asset. We derive the optimal investment strategy in closed-form using the dynamic programming approach by solving the corresponding Hamilton-Jacobi-Bellman (HJB) equation. Our theoretical and numerical results reveal that under some rational assumptions, an inflation-indexed bond do has significant advantage to hedge inflation risk.

Most of the educational interventions proposed so far in the field of mental well-being in education ‎usually address just students. In this study, we focused on teachers as the Covid-19 pandemic reiterated ‎the importance of their mental well-being during demanding times. We investigated whether ‎neurofeedback (NF) training can increase optimism, self-esteem, life satisfaction, and the ability to ‎cope with stressful events, reflecting on the research literature that emphasizes these four factors, ‎which affect the ability to be confident in dealing with uncertainty and distress. ‎ Forty teachers aged 35-55 participated in the study. The test group took part in 12 NF training sessions, ‎and the control group was not treated. Our findings indicate that compared to the control group, ‎measures of optimism, self-esteem, life satisfaction, and coping with stressful events improved ‎significantly in the test group.‎ To the best of our knowledge, this is the first attempt to test a mental welfare intervention program for ‎teachers through NF. This study responded to a call to develop teacher intervention programs using ‎physiological measurement and technological innovations to improve their mental health and allow ‎them to cope better with stressful teaching conditions.

Well-being is one of the pillars of positive psychology, which is known to have positive effects not only on the personal and professional lives of individuals, but also on teams and organizations. Understanding and promoting individual well-being is essential for staff health and long-term success, but current tools for assessing subjective well-being rely on time-consuming surveys and questionnaires, which limit the possibility of providing the real-time feedback needed to raise awareness and change individual behavior. This paper proposes a framework for understanding the process of non-verbal communication in teamwork, using video data to identify significant predictors of individual well-being in teamwork. It relies on video acquisition technologies and state-of-the-art artificial intelligence tools to extract individual, relative, and environmental characteristics from panoramic video. Statistical analysis is applied to each time series, leading to the generation of a dataset of 125 features, which are then linked to PERMA (Positive Emotion, Engagement, Relationships, Meaning, and Accomplishments) surveys developed in the context of positive psychology. Each pillar of the PERMA model is evaluated as a regression or classification problem using machine learning algorithms. Our approach was applied to a case study, where 80 students collaborated in 20 teams for a week on a team task in a face-to-face setting. This enabled us to formulate several hypotheses identifying factors influencing individual well-being in teamwork. These promising results point to interesting avenues for research, for instance fusing different media for the analysis of individual well-being in teamwork.

The abundance of information in academic articles, reports, and studies can make it challenging for researchers to gain insights from the existing literature. To address this issue, there is a growing demand for tools that can help researchers effectively parse and analyze large volumes of data. One such tool is DataDiscoveryLab, a software system that utilizes computer vision algorithms and NLP techniques to parse academic articles into text and figures, creating three separate databases. These databases allow researchers to quickly identify articles that may be relevant to their research questions, gain a deeper understanding of the research presented, and analyze visual data. The integration of article mining and computer vision in the DataDiscoveryLab software system provides researchers with a powerful tool for navigating the vast amount of scientific literature available today. Yet, as we will discuss in the latter papers these databases’ purpose is to create a bridge between researchers’ data and practically unlimited scientific publications. Yet, in this article, we will discuss how we plan to do that, and our efforts on integrating deep learning modes. After all, unlike already existing AI models, DataDiscoveryLab can be their combination and the first Generative AI in academia that can encompass every part of the natural sciences.

In this research, new setting is introduced for new SuperHyperNotions, namely, an SuperHyperStable and Neutrosophic SuperHyperStable. Two different types of SuperHyperDefinitions are debut for them but the research goes further and the SuperHyperNotion, SuperHyperUniform, and SuperHyperClass based on that are well-defined and well-reviewed. The literature review is implemented in the whole of this research. For shining the elegancy and the significancy of this research, the comparison between this SuperHyperNotion with other SuperHyperNotions and fundamental SuperHyperNumbers are featured. The definitions are followed by the examples and the instances thus the clarifications are driven with different tools. The applications are figured out to make sense about the theoretical aspect of this ongoing research. The ``Cancer's Recognitions'' are the under research to figure out the challenges make sense about ongoing and upcoming research. The special case is up. The cells are viewed in the deemed ways. There are different types of them. Some of them are individuals and some of them are well-modeled by the group of cells. These types are all officially called ``SuperHyperVertex'' but the relations amid them all officially called ``SuperHyperEdge''. The frameworks ``SuperHyperGraph'' and ``neutrosophic SuperHyperGraph'' are chosen and elected to research about ``Cancer's Recognitions''. Thus these complex and dense SuperHyperModels open up some avenues to research on theoretical segments and ``Cancer's Recognitions''. Some avenues are posed to pursue this research. It's also officially collected in the form of some questions and some problems. Assume a SuperHyperGraph. Then a``SuperHyperStable'' $\mathcal{I}(NSHG)$ for a SuperHyperGraph $NSHG:(V,E)$ is the maximum cardinality of a SuperHyperSet $S$ of SuperHyperVertices such that there's no SuperHyperVertex to have a SuperHyperEdge in common. Assume a SuperHyperGraph. Then an ``$\delta-$SuperHyperStable'' is a \underline{maximal} SuperHyperStable of SuperHyperVertices with \underline{maximum} cardinality such that either of the following expressions hold for the (neutrosophic) cardinalities of SuperHyperNeighbors of $s\in S:$ $~|S\cap N(s)| > |S\cap (V\setminus N(s))|+\delta,~|S\cap N(s)| < |S\cap (V\setminus N(s))|+\delta.$ The first Expression, holds if $S$ is an ``$\delta-$SuperHyperOffensive''. And the second Expression, holds if $S$ is an ``$\delta-$SuperHyperDefensive''; a``neutrosophic $\delta-$SuperHyperStable'' is a \underline{maximal} neutrosophic SuperHyperStable of SuperHyperVertices with \underline{maximum} neutrosophic cardinality such that either of the following expressions hold for the neutrosophic cardinalities of SuperHyperNeighbors of $s\in S:$ $~|S\cap N(s)|_{neutrosophic} > |S\cap (V\setminus N(s))|_{neutrosophic}+\delta,~ |S\cap N(s)|_{neutrosophic} < |S\cap (V\setminus N(s))|_{neutrosophic}+\delta.$ The first Expression, holds if $S$ is a ``neutrosophic $\delta-$SuperHyperOffensive''. And the second Expression, holds if $S$ is a ``neutrosophic $\delta-$SuperHyperDefensive''. It's useful to define a ``neutrosophic'' version of an SuperHyperStable. Since there's more ways to get type-results to make an SuperHyperStable more understandable. For the sake of having neutrosophic SuperHyperStable, there's a need to ``redefine'' the notion of an ``SuperHyperStable''. The SuperHyperVertices and the SuperHyperEdges are assigned by the labels from the letters of the alphabets. In this procedure, there's the usage of the position of labels to assign to the values. Assume an SuperHyperStable. It's redefined a neutrosophic SuperHyperStable if the mentioned Table holds, concerning, ``The Values of Vertices, SuperVertices, Edges, HyperEdges, and SuperHyperEdges Belong to The Neutrosophic SuperHyperGraph'' with the key points, ``The Values of The Vertices \& The Number of Position in Alphabet'', ``The Values of The SuperVertices\&The maximum Values of Its Vertices'', ``The Values of The Edges\&The maximum Values of Its Vertices'', ``The Values of The HyperEdges\&The maximum Values of Its Vertices'', ``The Values of The SuperHyperEdges\&The maximum Values of Its Endpoints''. To get structural examples and instances, I'm going to introduce the next SuperHyperClass of SuperHyperGraph based on an SuperHyperStable. It's the main. It'll be disciplinary to have the foundation of previous definition in the kind of SuperHyperClass. If there's a need to have all SuperHyperConnectivities until the SuperHyperStable, then it's officially called an ``SuperHyperStable'' but otherwise, it isn't an SuperHyperStable. There are some instances about the clarifications for the main definition titled an ``SuperHyperStable''. These two examples get more scrutiny and discernment since there are characterized in the disciplinary ways of the SuperHyperClass based on an SuperHyperStable. For the sake of having a neutrosophic SuperHyperStable, there's a need to ``redefine'' the notion of a ``neutrosophic SuperHyperStable'' and a ``neutrosophic SuperHyperStable''. The SuperHyperVertices and the SuperHyperEdges are assigned by the labels from the letters of the alphabets. In this procedure, there's the usage of the position of labels to assign to the values. Assume a neutrosophic SuperHyperGraph. It's redefined ``neutrosophic SuperHyperGraph'' if the intended Table holds. And an SuperHyperStable are redefined to an ``neutrosophic SuperHyperStable'' if the intended Table holds. It's useful to define ``neutrosophic'' version of SuperHyperClasses. Since there's more ways to get neutrosophic type-results to make a neutrosophic SuperHyperStable more understandable. Assume a neutrosophic SuperHyperGraph. There are some neutrosophic SuperHyperClasses if the intended Table holds. Thus SuperHyperPath, SuperHyperCycle, SuperHyperStar, SuperHyperBipartite, SuperHyperMultiPartite, and SuperHyperWheel, are ``neutrosophic SuperHyperPath'', ``neutrosophic SuperHyperCycle'', ``neutrosophic SuperHyperStar'', ``neutrosophic SuperHyperBipartite'', ``neutrosophic SuperHyperMultiPartite'', and ``neutrosophic SuperHyperWheel'' if the intended Table holds. A SuperHyperGraph has a ``neutrosophic SuperHyperStable'' where it's the strongest [the maximum neutrosophic value from all the SuperHyperStable amid the maximum value amid all SuperHyperVertices from an SuperHyperStable.] SuperHyperStable. A graph is a SuperHyperUniform if it's a SuperHyperGraph and the number of elements of SuperHyperEdges are the same. Assume a neutrosophic SuperHyperGraph. There are some SuperHyperClasses as follows. It's SuperHyperPath if it's only one SuperVertex as intersection amid two given SuperHyperEdges with two exceptions; it's SuperHyperCycle if it's only one SuperVertex as intersection amid two given SuperHyperEdges; it's SuperHyperStar it's only one SuperVertex as intersection amid all SuperHyperEdges; it's SuperHyperBipartite it's only one SuperVertex as intersection amid two given SuperHyperEdges and these SuperVertices, forming two separate sets, has no SuperHyperEdge in common; it's SuperHyperMultiPartite it's only one SuperVertex as intersection amid two given SuperHyperEdges and these SuperVertices, forming multi separate sets, has no SuperHyperEdge in common; it's a SuperHyperWheel if it's only one SuperVertex as intersection amid two given SuperHyperEdges and one SuperVertex has one SuperHyperEdge with any common SuperVertex. The SuperHyperModel proposes the specific designs and the specific architectures. The SuperHyperModel is officially called ``SuperHyperGraph'' and ``Neutrosophic SuperHyperGraph''. In this SuperHyperModel, The ``specific'' cells and ``specific group'' of cells are SuperHyperModeled as ``SuperHyperVertices'' and the common and intended properties between ``specific'' cells and ``specific group'' of cells are SuperHyperModeled as ``SuperHyperEdges''. Sometimes, it's useful to have some degrees of determinacy, indeterminacy, and neutrality to have more precise SuperHyperModel which in this case the SuperHyperModel is called ``neutrosophic''. In the future research, the foundation will be based on the ``Cancer's Recognitions'' and the results and the definitions will be introduced in redeemed ways. The recognition of the cancer in the long-term function. The specific region has been assigned by the model [it's called SuperHyperGraph] and the long cycle of the move from the cancer is identified by this research. Sometimes the move of the cancer hasn't be easily identified since there are some determinacy, indeterminacy and neutrality about the moves and the effects of the cancer on that region; this event leads us to choose another model [it's said to be neutrosophic SuperHyperGraph] to have convenient perception on what's happened and what's done. There are some specific models, which are well-known and they've got the names, and some SuperHyperGeneral SuperHyperModels. The moves and the traces of the cancer on the complex tracks and between complicated groups of cells could be fantasized by a neutrosophic SuperHyperPath(-/SuperHyperCycle, SuperHyperStar, SuperHyperBipartite, SuperHyperMultipartite, SuperHyperWheel). The aim is to find either the longest SuperHyperStable or the strongest SuperHyperStable in those neutrosophic SuperHyperModels. For the longest SuperHyperStable, called SuperHyperStable, and the strongest SuperHyperCycle, called neutrosophic SuperHyperStable, some general results are introduced. Beyond that in SuperHyperStar, all possible SuperHyperPaths have only two SuperHyperEdges but it's not enough since it's essential to have at least three SuperHyperEdges to form any style of a SuperHyperCycle. There isn't any formation of any SuperHyperCycle but literarily, it's the deformation of any SuperHyperCycle. It, literarily, deforms and it doesn't form. A basic familiarity with SuperHyperGraph theory and neutrosophic SuperHyperGraph theory are proposed.

As the structure of horizontal gas wells is more complicated than that of vertical wells, the form of the liquid-carrying in different sections does not well agree. This makes it problematic to apply the widely used liquid-carrying theory of vertical gas wells in horizontal gas wells. Since the theory focused on the critical gas flow rate, it cannot quantify how much liquid it can remove. Simultaneously, it ignores the fact that the liquid-carrying ability of gas flow is limited and the producing liquid has a certain amount of flowing energy. In this study, the gas-liquid flow law of horizontal gas wells and wellhead drainage stability in different tubing depths were firstly studied. Then, the stability of gas drainage for different tubing depths was analyzed and confirmed. Given the disadvantages of the typical theory of critical gas flow, the mathematical model of different tubing depths for gas drainage is established for horizontal gas wells. The innovative model could take the energy of gas flow and liquid flow into account, and quantify the liquid volume which was removed. By verifying the model with the experiments, the result showed that the relative error of the model is generally less than 10%. It shows the research could provide a scientific basis for the analysis and liquid-carrying capacity for horizontal gas wells.

Evolutionary perspectives have generated many questions and some answers in the study of human health and disease. The field of evolutionary medicine, and related analytics of evolutionary psychiatry and evolutionary psychology have extended and expanded the way health disorders are viewed by searching for why humans, as a species, are vulnerable to certain pathological conditions. The search is organized into four domains that apply proximate and evolutionary explanations to human traits and developmental sequences. This framework opens inquiry to the ontogeny, phylogeny, mechanism, and adaptive significance of human health conditions. In this paper I argue that evolutionary medicine seems to parallel biomedicine in its primarily pathogenic focus. That is, conditions of pain, suffering, and disorder have received the most attention. Some work has used the architecture of evolutionary medicine to take a salutogenic approach, evaluating the proximate and evolutionary explanations of human well-being. I propose that an evolutionary understanding of human well-being requires a survey of emotions and their relationship with neurobiology, language, and culture. My anthropology based, multidisciplinary review of biopsychosocial processes reveals the way evolution has shaped modern human understanding of well-being through sociolinguistic learning processes and thereby our individual experiences of well-being. These insights have the power to contextualize human suffering and flourishing as we progress toward the goal of attenuating the former and expanding the latter.

Langevin simulations are conducted to investigate the Josephson escape statistics over a large set of parameter values for damping and temperature. The results are compared to both Kramers and Büttiker-Harris-Landauer (BHL) models, and good agreement is found with the Kramers model for high to moderate damping, while the BHL model provides further good agreement down to lower damping values. However, for extremely low damping, even the BHL model fails to reproduce the progression of the escape statistics. In order to explain this discrepancy we develop a new model, which shows that the bias sweep effectively cools the system below the thermodynamic value as the potential well broadens due to the increasing bias. A simple expression for the temperature is derived, and the model is validated against direct Langevin simulations for extremely low damping values.

In only a few months after initial discovery in Wuhan, China, SARS-CoV-2 and the associated COVID-19 disease has become a global pandemic causing significant mortality and morbidity. In the absence of vaccines and effective therapeutics, reliable serological testing can be a key element of public health policy to control further spread of the disease and gradually ease quarantine measures. However, prior to launch of large-scale seroprevalence studies to assess herd immunity, it is critical to understand the limits and potential of current SARS-CoV-2 serological tests on the market. In this study, we provide an overview of serological testing and conduct a systematic review of independent evaluations of SARS-CoV-2 serological tests performance. Our findings show significant variability in the accuracy of marketed tests and highlight several lab-based and point-of-care rapid diagnostic tests with high performance level in detecting SRAS-CoV-2 specific antibodies. The findings of this review highlight the need for ongoing independent evaluations of commercialized COVID-19 diagnostic tests.

In response to a perceived epidemic of coronary heart disease, Ancel Keys introduced the lipid-heart hypothesis in 1953 which asserted that high intakes of total fat, saturated fat, and cholesterol lead to atherosclerosis and that consuming less fat and cholesterol, and replacing saturated fat with polyunsaturated fat, would reduce serum cholesterol and consequently the risk of heart disease. Keys proposed an equation that would predict the concentration of serum cholesterol (DChol.) from consumption of saturated fat (DS), polyunsaturated fat (DP), and cholesterol (DZ): ΔChol. = 1.2(2ΔS − ΔP) + 1.5ΔZ. However, the Keys equation conflated natural saturated fat and industrial trans-fat into a single parameter and considered only linoleic acid as the polyunsaturated fat. This ignored the widespread consumption of trans-fat and its effects on serum cholesterol and promoted an imbalance of omega-6 to omega-3 fatty acids in the diet. Numerous observational, epidemiological, interventional, and autopsy studies have failed to validate the Keys equation and the lipid-heart hypothesis. Nevertheless, these have been the cornerstone of national and international dietary guidelines which have focused disproportionately on heart disease and much less so on cancer and metabolic disorders, which have steadily increased since the adoption of this hypothesis.

This study investigates how students' well-being relates to sustainable development and education for sustainability at Prince Mohammad Bin Fahd University, Saudi Arabia. The authors endeavor to answer the question "How Does Students' Well-Being Relate to Sustainable Development Via Education for Sustainable Development?" and four sub-questions. Primary data were collected by semi-structured interviews exploring the viewpoints of twenty female and male students (n=26) aged between 18 and 26. The content analysis results have identified additional well-being and education for sustainability factors that influence sustainable education and, therefore, sustainable development. These antecedents include workload, transparency, grading criteria, fairness, belonging, work-life balance, mental health support, missing emotional intelligence factors, factors related to Education for Sustainable Development, such as instructors' role models, institutional commitment, leadership, and collaboration with government. In addition, the study developed a theoretical model for the relationship between antecedents for Education for Sustainable Development, Education for Sustainable Development, and Sustainable Development in the Saudi context. Finally, the study answers four research questions: What factors contribute to education for sustainable development? What are the antecedents of education for sustainable development? How do university educators contribute to sustainable education? How do the antecedents of education for sustainable development, education for sustainable development, and sustainable development relate?

The study explores how different dimensions of perfectionism influence psychological well-being (PWB) in emerging adults. Literature has deepened the relationships between maladaptive perfectionism (e.g., excessive self-criticism, perceived discrepancy from the standards) and low PWB. Less is known about whether and how adaptive perfectionism (e.g., pursuing personal standards) relates to PWB. Secondly, the study has investigated whether self-compassion (i.e., self-benevolence, seeing personal imperfections as a common condition) may mediate the relationships between adaptive/maladaptive perfectionism and PWB. Participants (N=217, 18-35 y. o.) completed self-report questionnaires measuring: adaptive/maladaptive perfectionism (Almost Perfect Scale-Revised, APS-R: high standards and order/discrepancy, respectively), PWB, and self-compassion (SCS). Adaptive perfectionism resulted associated with PWB, particularly higher presence of purpose in life, environmental mastery, self-acceptance, and personal growth. Conversely, discrepancy resulted the most robust predictor of low PWB (β=-.68), followed by high standards with a positive direction (β=.23; Rc²=.514, p&lt;.001). A strong negative association emerged between discrepancy and SCS (r=-.67, p&lt;.001). A mediation analysis shows that self-compassion has an indirect effect reducing the strength of the relationship between discrepancy and low PWB. Results suggest focusing on self-compassion as a buffer factor that reduces the negative impact of maladaptive perfectionism on psychological well-being. Implications for education and health psychology are discussed.

Using data from the China Family Panel Studies, this study examines the socioeconomic characteristics of Internet users, as well as the relationships between the dynamics of different forms of online activities and the subjective well-being of urbanites and rural migrants in urban China. The study finds that online behaviour may clearly reflect differences in individuals’ personal traits and socioeconomic positions. Patterns of the association between online activities and subjective well-being tend to differ among rural migrants and urbanites, especially in terms of depression. A difference-in-differences model is employed to estimate the impact of intensified engagement in online activities on depression and life satisfaction from 2010 to 2016. The results show that increased frequency of online entertainment exhibits a comparatively positive effect on depression and life satisfaction. Spending more time on online social networking has a similar impact on rural migrants, but not on urbanites. These findings suggest that the rapid development of urban China’s online community has important implications for residents’ subjective well-being.

In this paper, we study the well-posedness and asymptotic behaviour of solutions to a laminated beam in thermoelasticity of type III. We first give the well-posedness of the system by using the semigroup method. Then, we show that the system is exponentially stable under the assumption of equal wave speeds. Furthermore, it is proved that the system is lack of exponential stability for case of nonequal wave speeds. In this regard, a polynomial stability result is proved.

Motivated by the importance of entanglement and correlation indicators in the analysis of quantum systems, we study the equilibrium and the residual entropy in a two-species Bose Hubbard dimer when the spatial phase separation of the two species takes place. We consider both the zero and non-zero-temperature regime. We present different kinds of residual entropies (each one associated to a different way of partitioning the system), and we show that they strictly depend on the specific quantum phase characterizing the two species (supermixed, mixed or demixed) even at finite temperature. To provide a deeper physical insight into the zero-temperature scenario, we apply the fully-analytical variational approach based on su(2) coherent states and provide a considerbly good approximation of the entanglement entropy. Finally, we show that the effectiveness of residual entropy as a critical indicator at non-zero temperature is unchanged when considering a restricted combination of energy eigenstates.