Amyloids result from the aggregation of several unrelated proteins, due to either specific mutations or promoting intra- or extra-cellular conditions. Structurally, they are rich in intermolecular β-sheets and are the causative agents of several diseases, both neurodegenerative and systemic. It is believed that the most toxic species are small aggregates, referred to as oligomers, rather than the final fibrillar assemblies. Their mechanisms of toxicity are mostly mediated by aberrant interactions with the cell membranes, with resulting derangement of membrane-related functions. Much effort is being put in the search for natural antiamyloid agents, and/or in the development of synthetic molecules. Actually, it is well documented that the prevention of amyloid aggregation results in several cytoprotective effects. Here, we portray the state of the art in the field. Several natural compounds are effective antiamyloid agents, notably tetracyclines and polyphenols. They are generally non-specific, as documented by their partially overlapping mechanisms, and the capability to interfere with the aggregation of several unrelated proteins. Among rationally designed molecules, we mention the prominent examples of β-breakers peptides, whole antibodies and fragments thereof, and the special case of drugs contrasting transthyretin aggregation. In this framework, we stress the pivotal role of the computational approaches. When combined with biophysical methods, in several cases they have helped clarify in detail the protein/drug modes of interaction, which make it plausible that more effective drugs will be developed in the future.

This paper introduces a new rotor design for the easy insertion and removal of the rotor windings. The shape of the rotor is optimized based on surrogate method in order to achieve the lowest power loss under the maximum power output. The performance of the new rotor is examined in 2-D finite element software and validated by experiments. This rotor shows good potentials for reducing the maintenance and repair costs of synchronous machines, making it suitable for manufacturers within the mass production markets such as gen-sets, steam turbines, wind power generators and hybrid electric vehicles.

Dump design and scheduling are critical elements to effective mine planning, especially if several of them are required in large-scale open pit mines. Infrastructure capital and transportation costs are considerable from an early stage in the mining project, and through the life-of-mine as these dumps gradually become immense structures. Delivered mining rates, as well as certain spatial and physical constraints, provide a set of parameters of mathematical and economic relationship that creates opportunities for modelling and thus facilitates the measuring and optimization of ultimate dump design by using programming and empirical techniques while achieving economic objectives. This paper presents a methodology to model and optimize the design of a mine dump by minimizing the total haulage costs. The proposed methodology consists on: (i) Formulation of a dump model based on a system of equations relying on multiple relevant parameters; (ii) Solves by minimizing the total cost using linear programming and determines a ‘preliminary’ dump design; (iii) Through a series of iterations, modifies the ‘preliminary’ footprint by projecting it to the topography and creates the ultimate dump design. Finally, an example application for a waste rock dump illustrates this methodology.

Safety limits application has always been a traditional approach to ensure the safe operation of electro-mechanical systems within many industries including automated vehicles, robotics, aerospace, traditional automotive, railways, manufacturing, etc. In all of these applications, control and safety limits are usually hard-coded into the production firmware and are fixed throughout the entire product life cycle. Currently, due to the evolving needs of automated systems like automated vehicles and robots, this traditional approach does not address all the use cases and scenarios to ensure safe operation. Especially for data-driven machine learning applications that constantly evolve and learn over time, it is important to be able to adjust the safety limits application strategy to be more flexible and adaptable based on different Operational Design Domains (ODDs) and scenarios. Our ITSC conference paper ~\cite{4} introduced the concept of a new safety limits application strategy called the Dynamic Control Limits Application (DCLA) strategy that supports the flexible application of diverse limits profiles based on the parameters involved within the dynamic scenario at different layers of the Autonomy software stack.This paper extends the DCLA strategy to derive the complete methodology for safety limits application based on ODD elements, scenario identification and scenario classification using Decision Making Engines. It leverages the layered architecture introduced in the ITSC conference paper to implement the Decision Making (DM) algorithms. Another important extension is the use of cloud infrastructure that is based on the Vehicle-to-Infrastructure (V2I) technology to store the scenarios and the limits mapping to serve as a ground truth and/or a backup mechanism in case of errors or failures associated with the main Decision Making (DM) Engine. There is also a focus on providing a more comprehensive list of scenarios and a custom built experimental dataset to cover the maximum ODD elements, and multiple tables of safety limits to be chosen from, which eventually helps in creating different safety limits application profiles. These distinct safety limits application profiles are based on the scenario parameters that are perceived by the system upon which the Decision Making algorithms are applied or trained. This systematic approach can be used within the industry for any of the future automated vehicles and systems until Level 5 Autonomy.

In this study, an optimization of the first blade in new test rig presented. Blade tuning is conducted using 3D geometrical parameters. Sweep and dihedral play an essential role in this study. Compressor characteristics and blades vibrational behavior are the main objective of the evaluation. Here, the attachments are designed to isolate blade dynamics from Disk. So, the Vibrational behaviors of the one's blade are tuned based on the self-excited and forced vibration phenomenon. Using a semi analytical MATLAB code instability conditions are satisfied. The code takes advantages of whitehead and force response theory to predict classically and stall flutter speeds. Beside, Forced vibrations instability is controlled using a theory presented by Campbell. Aerodynamics of new blade geometry determined using multistage simulations Computational fluid dynamics (CFD) software. Numerical results show increasing performance near the surge line and working interval along with increasing mass flow.

Statistical modeling lies at the heart of product design and development throughout numerous engineering disciplines, especially since processing large amounts of data has become increasingly ubiquitous. While mathematical statistics provide elegant guidance pertaining to the question of whether or not some particular underlying modeling assumptions are justified and appropriate, when pursuing a more comprehensive assessment of product design and development other considerations often increase in significance. Therefore, we will examine and analyze the tedious interactions and implications of statistical modeling choices and product liability exposure. To the best of our knowledge, this paper is the first to draw attention to and explore some often overlooked or oversimplified dangers and pitfalls that enter the equation when product design heavily relies on statistical modeling. In particular, through a diligent analysis of both statistical and legal aspects we will explore how statistically optimal procedures may yield far from optimal outcomes in terms of product liability when applied to actual real life problems and why suboptimal nonparametric or robust approaches may constitute better alternatives.

End-to-end learned image compression codecs have notably emerged in recent years. These codecs have demonstrated superiority over conventional methods, showcasing remarkable flexibility and adaptability across diverse data domains while supporting new distortion losses. Despite challenges such as computational complexity, learned image compression methods inherently align with learning-based data processing and analytic pipelines due to their well-suited internal representations. The concept of Video Coding for Machines has garnered significant attention from both academic researchers and industry practitioners. This concept reflects the growing need to integrate data compression with computer vision applications. In light of these developments, we present a comprehensive survey and review of lossy image compression methods. Additionally, we provide a concise overview of two prominent international standards, MPEG Video Coding for Machines and JPEG AI. These standards are designed to bridge the gap between data compression and computer vision, catering to practical industry use cases.

This research article aims to examine the factors that influence behavioral intentions using the traffic accident claim system in Indonesia. This research uses the Theory of Planned Behavior, the Model of Technology Acceptance, and the Integrated Theory of Technology Acceptance and Use, as well as using the Structural Equation Modeling-Partial Least Squares. The questionnaire was distributed to 580 respondents from three institutions – police, hospitals, and state-owned insurance companies – using quota sampling techniques. The results showed that TPB, TAM, and UTAUT had a significant influence in encouraging behavioral intentions using the traffic accident claim system. Further, the study found that 21st-century digital skills have a moderate role in the impact of acceptance models, planned behavior, and technology use on behavioral intent. Although the study was conducted in Indonesia and is limited to three institutions, it provides strategic guidance for policymakers to improve the use of traffic accident claim systems and reduce Road Traffic Accidents. Further research is recommended to explore from different angles and focus on service providers/operators of traffic accident claim systems to refine the findings of this study. This study contributes to the literature by investigating the factors that influence behavioral intentions using traffic accident claim systems and has a high degree of accuracy of answers from the point of view of traffic safety officers.

Climate change is expected to affect the agricultural sector in ways that are often unclear to predict. If in the short- medium-terms farmers may adapt to climate change by adjusting agricultural practices, in the long-term these adjustments may become insufficient, forcing farmers to change their farming systems. The extent and direction in which these farming system transitions will occur is still a subject underexplored in the literature. We propose a new framework to explore the marginal effect of climate change on the choice of the farming system, while controlling the effect of other drivers known to also influence farming system choice. Using a spatial-explicit farming system choice-model developed by a previous study in an extensive agricultural region of southern Portugal, we applied a space-for-time approach to simulate the effect of climate change on the future dynamics of the farming systems in the study area. Results suggest that climate change will force many farmers to change the farming system in a foreseeable future. The extent of the projected changes in farming systems is likely to trigger significant social, economic, or environmental impacts, which should require early attention from policy makers.

The ageing transformation of digital health services faces issues of how to distinguish influencing factors, redesign services, and effectively promote measures and policies. In this study, in-depth interviews are conducted and grounded theory applied to open coding, main axis coding, and selective coding to form concepts and categories. Trajectory equifinality modeling clarified the evolution logic of digital transformation. Based on the theory of service ecology, a digital health service ageing model is constructed from the "macro-medium-micro" stages and includes governance, service, and technology transformation paths. The macro stage relies on organizational elements to promote the institutionalization of management and guide the transformation of governance for value realization, including the construction of three categories: mechanism, indemnification, and decision-making. The meso stage relies on service elements to promote service design and realize service transformation suitable for aging design, including the construction of three categories: organization, resources, and processes. The micro stage relies on technical elements to practice experiencing humanization, including the construction of three categories: target, methods, and evaluation. These results deepen the understanding of the main behaviors and roles of macro-organizational, meso-service, and micro-technical elements in digital transformation practice and have positive significance for health administrative agencies to implement action strategies.

Gender parity, is an important standard to be achieved by a society in which men and women are treated equally. The distinctions in the treatment may arise from psychology, biology, or cultural norms constructed by society. Studies show the different experiences of genders across many areas including health, education, personality, life expectancy, sports, interests, political empowerment, and careers. However, we are still far from reaching the objective, because there are conducts such as gender discrimination and expressions such as the purplewashing. In relation to feminism, purplewashing is used to define a diversity of marketing and political strategies intended at promoting people, companies, associations, and other organizations through an appeal to gender equality: they use only some of the feminist values at their convenience and in its actions, they are not really supportive of gender equality. In this opinion we aimed to address some of the reasons for inequality of opportunities based on gender; purplewashing is described as an expression that takes away the visibility of women's struggle. Additionally, we touch on some actions that promote gender equality in the family, educational, and work environments. Global leaders have an unprecedented opportunity to build gender-sensitive societies and economies. The challenges facing women today are essentially the same as they were a long time ago. It is time to break the bias.

Bacteria a Microscopic organisms are the most inexhaustible and flexible of microorganisms and constitute a huge division of the whole living earthly biomass, certain microorganisms were found to amass metallic components at a high limit Was Known as Bacterial Bio-sorption Due to their little size, capacity to become under controlled conditions, and their Accommodation to an extensive variety of ecological situations; Potent metal bio-sorbents among microorganisms, at low pH esteems, cell divider ligands are protonated and contend essentially with metals for official. With expanding pH, more ligands, such as amino and carboxyl groups, could be exposed, leading to attraction between these negative charges and the metals, and consequently increment bio-sorption onto the cell surface. Starting with Isolation and identification of heavy metal-resistant bacteria from rock Ore. Studying Factors Affecting Uranium Bio-sorption, Optimization of bacterial growth conditions and optimum for metal uptake by free and immobilized bacterial cells and Desorption ratio of uranium ions adsorbed by Coli. /alginate, All this evidence suggest that functions groups Represented in our study are responsible for metal uptake in our bacterial biomass beside change in peaks position which assigned for it's groups confirm bio-sorption of metal ions from waste due to ions charge interaction comparing with immobilized we found increase in no of binding sites indicate that immobilized bacterial have high efficiency for metal up take which also change in peaks position which assigned for its groups confirm bio-sorption of metal ions from waste due to ions charge interaction, Where the high bio-sorption yield obtained by bacteria, the Uranium & heavy metal bioremediation process expects microorganisms to be joined to a strong surface.

Microfluidic devices which integrate both rapid mixing and liquid jetting for sample delivery are an emerging solution for studying molecular dynamics via X-ray diffraction. Here we use finite element modelling to investigate the efficiency and time-resolution achievable using microfluidic mixers within the parameter range required for producing stable liquid jets. Three-dimensional simulations, validated by experimental data, are used to determine the velocity and concentration distribution within these devices. The results show that by adopting a serpentine geometry, it is possible to induce chaotic mixing, which effectively reduces the time required to achieve a homogeneous mixture for sample delivery. Further, we investigate the effect of flow rate and the mixer microchannel size on the mixing efficiency and minimum time required for complete mixing of the two solutions whilst maintaining a stable jet. In general, we find that the smaller the cross-sectional area of the mixer microchannel, the shorter the time needed to achieve homogeneous mixing for a given flow rate. The results of these simulations will form the basis for optimised designs enabling the study of molecular dynamics occurring on millisecond timescales using integrated mix-and-inject microfluidic devices.

Education is an imperative key to driving sustainability and gender equity. In addition to addressing well-known female deficiencies in leadership training, it is really important to develop initiatives in sustainable leadership education for women to acquire skills, competencies and tools on leadership and to increase their self-perceptions. The purpose of this study is to assess a Women’s Leadership Program for university students. The sample consisted of 50 students enrolled in the program. A mixed-method approach was applied. Quantitative methods with a survey were conducted to evaluate the training and the achievement of leadership skills. In the data analysis, a descriptive statistics variance analysis, using a Welch statistic and T2 Dunnett test, was applied. Qualitative research methods were conducted through three focus groups to evaluate personal changes in their own-perceptions and self-confidence. Results suggest that the female students in the program reached a level of leadership knowledge with practical tools for their future. The program inspired them and confirmed changes in their personal capacities or self-confidence, including reflection about facing challenges in the work environment. The findings support the effectiveness of the specific education in breaking two barriers shown by the literature for women to getting a managerial position: lack of training and female self-confidence.

Changes in curricula, publication policy and information technology, notably in China have led to concentrations in the role of STEM (science, technology, engineering and mathematics) education in early childhood and applauded to proliferations of imported up-to-date reading materials and mobile apps in English. This paper proposes a longitude study of a Chinese toddler learning STEM by reading picture books and playing with tablet and suggests new horizons in parenting and in STEM education during children's early years. The present study carried out from 2016, when the participant reached one year old, eligible to learn to speak and to concentrate on the picture books read by parents who had filled a language background questionnaire with information on themselves and the participant. Tablet playing brought about for the two-year-old toddler and collections of STEM books in English was added for the second year. Data collection lasted for two years with an iLab video camera, capturing utterances and motions for five minutes per week transcribed by VoiceScript software. Tests were given quarterly at private home by tapping in mobile app "Bilingual Child Learning" which consists of 20 basic STEM themes before scores were collected. Findings indicate that (1) it is accessible for children of very early years to be engaged in English STEM resources, (2) kids' limited English dominance does not impede learning STEM, (3) and to think in English in early STEM contributes to children's English.

BACKGROUND: Endoscopic placement of Self Expandable Metal Stents to relieve malignant colorectal obstruction has become a common therapeutic advancement in clinical practice. MATERIAL: In a 16 year period 167 patients had endoscopic placement of a Self Expandable Metal Stent in a center where gastroenterologists and surgeons cooperate in a daily basis, discussing indications. RESULTS: There was no operative mortality and no major complication in placement of the stent. Technical and clinical success was respectively 95.1% and 92.9%. Consultation among specialists changed the preoperative indication in 60 patients, during the same time period. CONCLUSIONS: Self expandable metal stents placement represents an important tool to treat patients with obstructing colorectal cancer and complications after colorectal resection . A proper training is required, and this training in operative endoscopy is not always available and possible. In this scenario, a close collaboration among specialists in selecting the most appropriate operative procedure is essential and brings to better results.

Achieving water security and availability for all is the main agenda of the UN-Sustainable Development Goals by the year 2030. To achieve the goal of water secure future in rapidly urbanizing cities, the sustainable water supplies are necessary. In the western part of India, the city of Surat is continuously growing and rapidly urbanized, which exerting massive pressure on groundwater water supply to meet increasing water demands. The study adopted the investigative approach, in which a total 33 groundwater samples were collected in and around the city from open, bore and dug wells and hand pumps. The selection of sampling sites was based on the land use signature, areas with a different depth of aquifers and different geological formations. After the hydrogeochemical analysis, the study evaluated the present state of the groundwater quality and determined the spatial distribution of groundwater quality parameters such as hardness, electrical conductivity, Cl −, pH, SO42-, and NO3 −  concentrations. An interpolation technique, known as ordinary kriging, was used to acquire the spatial distribution of parameters of groundwater quality parameters. The result showed that the groundwater quality falls under class I (>25%) and class II (25 to75%) category. The study recommends that the groundwater in the study area is not suitable for potable purposes, especially without any improved onsite water treatment facilities but it is appropriate for the irrigation purposes in City.

Manufacturing environments, characterized by rapid, unpredictable changes, uncertainties, risks, and uncontrollable fluctuations, pose significant challenges to minimizing disruptions in processes. This study introduces an innovative approach that prioritizes curbing risk propagation among processes to enhance robustness. It emphasizes the integration of engineering management principles and modular design within manufacturing. Adopting a system engineering perspective, all manufacturing process activities are viewed as interrelated components within a unified system. By employing Axiomatic Design (AD) theory and the Design Structure Matrix (DSM) method, manufacturing process architecture is modularized, yielding heightened robustness. The proposed mathematical model equips engineering and manufacturing managers with a potent tool for designing robust processes while adeptly managing system complexity. The study's outcomes underscore a substantial enhancement in modularization, leading to elevated overall robustness in manufacturing processes. To validate the methodology, the architectural design of manufacturing processes is examined in a real-case scenario, specifically the Barez Industrial Group in Iran. This verification substantiates the 'manufacturing processes' of the case, presenting an optimally modularized architecture. The results affirm the proposed approach's efficacy, demonstrating improved modularization that contributes to bolstered robustness in manufacturing processes.

This research explores the transformation of learning methodologies from traditional to modern approaches, focusing on the development of a gamified educational application with an Artificial Intelligence (AI) mentor for secondary school graduates preparing for Croatian state graduation exams. Traditionally, education has been marked by a passive student role and teacher-centric transmission of knowledge. In contrast, modern learning tools, such as gamified applications, introduce interactive and engaging elements. The purpose of this study is to identify user-centric learning approaches through a comprehensive survey of graduating students, assessing their readiness for exams, learning styles, and preferences. The research explores issues such as financial burdens on parents for preparatory courses and copyright concerns with external educational materials. In summary, the learning application should prioritise sustained knowledge retention, motivation, and stress reduction, offering an alternative to external preparatory courses. Conclusions underscore the importance of fostering an engaging learning environment, incorporating teacher-like elements, and aligning with user expectations. As digital technology positively impacts the learning experience, understanding user preferences is crucial in designing educational apps that cater to learners' needs. The study provides insights for developing a gamified learning application that not only prepares students for exams but also enhances long-term knowledge acquisition and engagement.

The A.C.Q.U.A. (Advisable Conscious Quality Use from Assisi) project, promoted by the Climate and Energy and Heritage Design courses of the Planet Life Design Master Program, addresses the theme of the recovery and regeneration of ancient wash-houses in the context of energy, environmental sustainability and innovation, a way of understanding cultural heritage in the wider sense of heritage community through the active participation of all the actors involved: universities, institutions, businesses, students and citizens. The proposal, tested in the municipalities of Assisi and Ruviano (ITALY), involves the creation of a "Community Wash House", a new way of carrying out the usual domestic act of washing clothes in the open air, next to the places where this rite was traditionally performed, in technologically innovative constructions that use renewable energy sources and encourage a reduction in household consumption of water and energy. This project is part of the training of professionals in the new inter-university course that combines knowledge of the tools of technical and scientific design with historical and cultural perspectives in a perspective of sustainable redevelopment of existing structures in the area and the use of alternative energy sources with low climate impact, calculated using the statistics of the Copernicus CDS.

This literature review offers a comprehensive analysis of antenna designs tailored for 6G applications and THz communications. Various antenna types, including elliptical lens, WHEMS, grid array, CP horn, Quasi Yagi-Uda, patch, transmit array, Vivaldi patch, SRR slotted waveguide array, RCA, and Cassegrain antennas, are scrutinized in terms of their dimensions, characteristics, frequency ranges, and materials. The study highlights existing works on antenna design for 6G applications, exploring different fabrication techniques like PCB technology, LCP technology, Topas fabrication, Wire-cutting EDM, 3D Printing, Laser-drilling processes, and CNC machining. Notably, PCB technology exhibited promise with antennas such as WHEMS, patch, and Vivaldi patch, achieving significant bandwidth and gain. However, gaps remain in research, urging further exploration into additional fabrication methods and antenna designs to meet the demands of 6G networks. The study underlines the need for advanced, intelligent antennas capable of higher bandwidth and better performance in view of future wireless communications technologies such as 6G.

Unmanned vehicles (UVs) have become increasingly important in various scenarios of civil and military operations. The present work aims at the conceptual design of a modular Amphibious Unmanned Ground Vehicle (A-UGV), that can be easily adapted for different types of land and/or water missions, with low monetary cost (<5k€, without sensors). Basing the design on the needs highlighted in the 2021 review of the Strategic Directive of the Portuguese Navy, the necessary specifications and requirements are established for two mission scenarios. Then a market research analysis focused on vehicles currently available, and their technological advances, is conducted to identify existing UVs solutions and respective characteristics/capabilities of interest to the current work. To study and define the geometry of the hull and the configuration of the A-UGV itself, preliminary computational structural and fluid analyses are carried out to ensure it complies with the specifications initially established. As a result, one obtains a fully electric vehicle, with approximate dimensions of 1050×670×450mm (length-width-height), enabled with 6×6 traction capable of reaching 20km/h in land, possesses amphibious capabilities of independent propulsion in water up to 8kts, and with an estimated autonomy of over 60 minutes.

Public housing stock, called Social Housing, in Italy developed between the 1950s and the 1980s. As of today, the first residential developments are almost nearing their end-of-life age, in need of urgent and intensive renovation. The European Commission, with the Renovation Wave, has set a goal of doubling the rate of building renovation over the next 10 years, reducing emissions, improving energy performance, and promoting decarburization. Renovation interventions, including structural, functional, energy, plant upgrading, etc., are to be preferred over integral demolition and reconstruction interventions, which have significant repercussions in terms of managerial and social discomfort. The case studies examined concern renovation interventions aimed at energy efficiency, functional adaptation of housing as well as facade restyling. The design variants analyzed were evaluated in terms of CO2e emissions, according to LCI (Life Cycle Inventory) and EPD (Environmental Product Declaration) approaches. This approach has a twofold purpose: to propose design guidelines, with low CO2e emissions, through hypotheses of variants to the case studies, and to propose, to the Economic Operators, economically advantageous bidding scenarios, in the procurement process.

The resolution of façade construction is not considered in the design process, as it can be expressed by complex technological innovations that emphasize the beauty of buildings. Nevertheless, resorting to this type of technology solution may not always be necessary. This study demonstrates this hypothesis through the investigation of five iconic case studies emphasizing the construction system analysis and the revelation of the brainwave idea. The brainwave idea defines the construction innovation that enables the detail by simplification rather than sophistication. Notable, unlike complex technological innovation, standard systems or elements applied strategically are considered little innovations to facilitate the resolutions of the façade complexity. Many of these innovations occur during the visual and constructive prototype progress required to validate the proposed solution and its performance. Therefore, real-scale prototype development that operates as a real-scale laboratory is necessary to correct and validate successive solutions.

This paper is an extended version of a previously reported conference paper regarding low power design for NAND Flash. As the number of bits per NAND Flash die increases with cost scaling, IO datapath speed increases to minimize the page access time with scaled CMOS in IOs. The power supply for IO buffers, namely VDDQ, has decreased from 3V to 1.2V, accordingly. In this paper, how a reduction in VDDQ can contribute to power reduction in BL path is discussed and validated. Conventionally, BL voltage of about 0.5V has been supplied from a supply voltage source (VDD) of 3V. BL path power can be reduced by a factor of VDDQ to VDD when BL voltage is supplied from VDDQ. To maintain a sense margin at sense amplifiers, the supply source for BLs is switched from VDDQ to VDD before sensing. As a result, power reduction and equivalent sense margin can be realized at the same time. The overhead of implementing this operation is an increase in BL access time of about 2% for switching the power supply from VDDQ to VDD and an increase in die size of about 0.01% for adding the switching circuit, both of which are not significant in comparison with a significant power reduction in BL path power of NAND die of about 60%. The BL path was designed in 180nm CMOS to validate the design. When the cost for powering SSD becomes quite significant especially for data center, an additional lower voltage supply such as 0.8V dedicated to BL charging for read and program verify operations may be the best option for the future.

AbstractCurrently, public health researchers are investigating several complex and multi-faced health problems that require mixed-method approaches (MMA) to clearly understand problems and design proper intervention approaches and policy formulation. Besides, a comprehensive comprehension of the complex operation of society is vital. The MMA helps in having a broader understanding of the functioning and structure of the community at large. MMA deliberately integrates qualitative and quantitative approaches carefully to build on the merits of each other and confirm that the findings of research are closer to the truth. Therefore, public health scholars must have an excellent comprehension of the MMA and its philosophical foundations for discovering the complex conditions that challenge public health nowadays. However, public health researchers do not clearly understand the theoretical underpinnings and practical application of MMA, despite its popularity in developing countries. Therefore, this article aimed to provide comprehensive evidence on the theoretical underpinnings and practical application of MMA.

The concept of the protein powder dispenser was developed on the basis of the results of analyses, studies and customer requirements. The dispenser was assembled using SolidWorks software, which consists of 63 elements, 14 of which are unique parts that are not available on the market. Each part of the dispenser was carefully designed to be injected into the plastic compound. Polypropylene is the perfect material for this dispenser as it is low density, waterproof, insoluble and extremely resistant to tension and bending. High purity propylene polymer can be processed into a tough, rigid and lightweight plastic with relatively low manufacturing costs, replacing expensive materials. The authors' original contributions are the design and manufacture of a dosing device for protein powder, adjustable in 3 heights to be able to dose in containers of different sizes; the design and integration of a mechanism with a precise dosing system, the components being designed so that the parts in contact with the shaft filled with protein powder form a perfectly closed space; the design and integration of the mechanism for adjusting the height of the dispenser.

Machine learning approaches are currently used to understand or model complex physical systems. In general, a substantial number of samples must be collected to create a model with reliable results. However, collecting numerous data is often relatively time-consuming or expensive. Moreover, the problems of industrial interest tend to be more and more complex and depending on a high number of parameters. High dimensional problems intrinsically involve the need of large data amount through the curse of dimensionality. That is why, new approaches based on smart sampling techniques are investigated to minimize the number of samples to be given to train the model, such as Active Learning methods. Here, we propose a technique based on a combination of Fisher information matrix and of Sparse Proper Generalized Decomposition that enables the definition of a new Active Learning informativeness criterion in high dimensions. We provide examples proving the performances of this technique on a theoretical 5D polynomial function and on an industrial crash simulation application. The results prove that the proposed strategy over-perform the usual ones.

This paper introduces the implementation of a genetic programming (GP)-based procedure to the automatic design and tuning of process controllers. The proposed approach makes a significant contribution to the field of artificial intelligence (AI) in control engineering. Unlike other controller design methods, the GP-based program handles the entire design in the time domain, including differential operations like derivatives and integrals, without the need for intermediate inverse Laplace transformation. This approach not only simplifies the design process but also ensures that all generated controllers are implementable in physical systems. Furthermore, GP’s functions set includes various mathematical operations beyond basic arithmetic operators, such as trigonometric, exponential, and logarithmic operators. The performance and validity of the resulting controllers generated by the proposed GP-based approach are evaluated by verifying whether the generator can replicate the structure and performance of those produced by traditional controller design methods and, in some cases, achieve even better results. As a result, the GP-based approach presents a promising solution for automating the controller design process and addressing control problems in various engineering applications.

Consideration of the individual bone characteristics of the wrist plays a key role in well-functioning biomedical devices and successful surgical procedures. Although geometric differences and individual bone sizes have been analyzed in the literature, detailed morphologic descriptions and correlations covering the entire wrist reported in a clinical context are lacking. This study aimed to perform a comprehensive and automatic analysis of wrist morphology using the freely available “Open Source Carpal Database” (OSCD). We quantified the dimensions of each of the individual carpal bones and their combination. These dimensions were extracted in n=117 datasets of the wrist of the OSCD in anatomical directions and analyzed using descriptive statics and correlation analysis to investigate morphological characteristics under gender-specific aspects. We found that there exist statistical differences between genders, and we concluded that gender specificity is an important variable affecting the utilization of biomedical device designs and clinical treatment.

Digital filtering is a fundamental technique in digital signal processing, which operates on a digital sequence without any information on how the sequence was generated. This paper proposes a methodology for designing the equivalent of digital filtering for neuromorphic samples, which are a low power alternative to conventional digital samples. In the literature, filtering using neuromorphic samples is done by filtering the reconstructed analog signal, which is required to belong to a predefined input space. We show that this requirement is not necessary, and introduce a new method for computing the neuromorphic samples of the filter output directly from the input samples, backed by theoretical guarantees. We show numerically we can achieve a similar accuracy compared to the conventional method. However, given that we bypass the analog signal reconstruction step, our results show significantly reduced computation time for the proposed method and good performance even when signal recovery is not possible.

Ternary blended cements such as limestone calcined clay cement (LC3) represent a strategic binder type for the mitigation of environmental impact associated with cement production and are estimated to reduce CO2 emissions by about 40% compared to ordinary Portland cement (OPC). In this paper we explore the possibility of producing such ternary blends by utilizing secondary raw materials that may be locally available. Specifically, the primary limestone that is commonly used in LC3 is here substituted by quarry dust obtained by sourcing of “kunkur”, a carbonate-rich sedimentary rock (also known as caliche) that can be locally utilized for the production of ordinary OPC clinker. To optimize the blending proportions of ternary cements consisting of OPC, calcined clay and kunkur fines, a Design of Experiment (DoE) approach was implemented, with the further goal of exploring the possibility of reducing the amount of the OPC fraction to values lower than 50%. The properties of the formulated blends were assessed by a combination of techniques that comprise mechanical strength testing, XRD time-dependent quantitative phase analysis, SEM-EDS microstructural and microchemical analysis. The results suggest that ternary blended cements based on kunkur fines form hydration products, such as hemicarboaluminates, which are also observed in LC3. This shows that such a waste material can potentially be used in sustainable cement blends, however, the presence of kaolinite in the kunkur fines seems to affect the development of strength when compared to both OPC and conventional LC3.

Multi-board electronic cases with high density and high power modules are widely used in industrial power supply management. With the improvement of case performance and miniaturization requirements, heat dissipation becomes one of the important factors to be considered in the design process. First,The existing small electronic thermal design methods focus on heat dissipation structure or heat source layout optimization,and ignores on-load test for modeling analysis. Second,The selected power module has on-load power consumption, resulting in relatively low calorific value and the effectiveness of thermal design cannot be verified. Third, The thermal lacks Intelligent monitoring and feedback control mechanism. In order to solve these problems, this paper designs a kind of heat dissipation case with intelligent temperature control based on high-power and high-density power supply array. Based on the extremely miniaturization design principle, we adopt the composite heat dissipation mode based on conduction and supplemented by forced air cooling . The case is made of magnesium and aluminum alloy with a perforated design. Finally, we compare and analyze with the existing cooling design. The results show that the case is smaller in volume, and the cooling performance parameters are slightly better than the existing case. Under the condition of high-density and high-power design, The output power of the whole system is not less than 10kw and the lowest packing-level density is not less than 47w/cm2 with high reliability, portability and practicability. It also provides technical support and prototype support for the standardized design of similar power arrays.

This paper presents a novel approach for individual design perception modeling using the YUKI-trained Fuzzy Inference System. The study focuses on understanding how individuals perceive design based on personality traits, particularly openness to experience. The proposed YUKI algorithm optimizes the FCM clustering algorithm, enhancing its ability to handle uncertain and imprecise data. The YUKI-trained FIS generates several Sugeno-type FIS models to predict design perception, to minimize the Root Mean Squared Error between the model prediction and the actual design perception of participants. The results demonstrate that the YUKI-trained FIS offers more accurate predictions compared to the traditional FCM-trained FIS, and the RMSE values for individual design perceptions fall within a satisfactory range of 0.84 to 1.32. The YUKI-trained FIS proves effective in clustering individuals based on their level of openness, providing insights into how personality traits influence design perception.

The rapid urbanization growth of Dubai has resulted in connectivity issues, considered tre-mendous development pressure. That leads the local authorities to set a vision for Dubai as a 15-20 minute city by 2040. The 15-minute city, where all services can be reached with minimum travel time using sustainable mobility means (walking, cycling, or electric bik-ing). This paper aims to assess the current walkability situation within 15 minutes in the most significant parts of Dubai. This study considered 13 communities; Bur-Dubai and Business Bay were selected to represent the ungated communities, and eleven major gated communities were considered to indicate the gated ones. Those neighborhoods are selected based on the developments' socio-economic status and population density. The assessment considered 14 essential services, categorized into five categories: educational, health, social, entertainment, and religious. The research methodology conducted desktop research, site visits, interviewing random residents to collect data, and then using ArcGIS to assess walk-ability. The results show (64.5%) of the ungated neighborhoods population which access essential services within 15 minutes, while most of the gated communities residents must use cars to access many services. Furthermore, services distribution patterns and walkability infrastructures outside these developments should be developed to obtain higher walkability indicators.

Accurate and reliable measurement of real-world walking activity is clinically relevant, particularly for people with mobility difficulties. Insights on walking can help understand mobility function, disease progression, and fall risks. People living in long-term residential care environments have heterogeneous and often pathological walking patterns, making it difficult for conventional algorithms paired with wearable sensors to detect their walking activity. We designed two walking bout detection algorithms for people living in long-term residential care. Both algorithms used thresholds on the magnitude of acceleration from a 3-axis accelerometer on the lower back to classify data as “walking” or “non-walking”. One algorithm had generic thresholds, while the other used personalized thresholds. To validate and evaluate the algorithms, we compared the classifications of walking/non-walking from our algorithms to the real-time research assistant annotated labels and the classification from an algorithm validated on a healthy population. Both the generic and personalized algorithms had acceptable accuracy (0.83 and 0.82 respectively). The personalized algorithm showed the highest specificity (0.84) of all tested algorithms, meaning it was the best suited to determine input data for gait characteristic extraction. The developed algorithms were almost 60% quicker than the previously developed algorithms, suggesting they are adaptable for real-time processing.

Silver nanoparticles from Origanum vulgare (Oregano) have been synthesized in the past. However, no investigation has been performed on the combined effects of independent factors that affect the synthesis. Silver nitrate and Oregano concentrations, incubation temperature and time, as well as pH can play crucial roles in synthesis. In this regard Full Factorial Design was applied. A Voigt function was fitted on the measured UV – Vis spectra. The fitting parameters of the Voigt function (peak wavelength, area, and Full Width at Half Maximum) were used as the responses. A quadratic model was fitted for the peak wavelength and area, and the pH proved the dominant factor on nanoparticle synthesis.

Numerical optimization methods are widely used for designing turbomachinery components due to the cost and time savings they can provide. In the available literature, shape optimization of radial compressors is mainly focused on improving the impeller alone. However, it is a well-established knowledge that the volute plays a key role in the overall performance of the compressor. The aim of the present paper is to perform the adjoint-based optimization of a volute that is designed for the SRV2-O compressor. The CAD model is first created, using a parametrization of 33 design parameters. Then, a butterfly topology is applied to mesh the computational domain with a multi-block structured grid, and an elliptic smoothing procedure is then used to improve the quality of the fluid grid. A steady-state RANS CFD solver with Spalart-Allmaras turbulence model is used to solve the Navier-Stokes equations, and flow sensitivities are computed with an adjoint solver. The objective function consists in minimizing the loss coefficient of the volute. The optimization is performed to obtain an improved design with 14% losses reduction. Detailed flow and design analysis is carried out to highlight the loss reduction mechanisms followed by the optimizer. Finally, the compressor map of the full stage is compared between the baseline and the optimized volute through CFD simulations using a mixing plane interface. This research demonstrates the successful use of a gradient-based optimization technique to improve the volute of a radial compressor and opens the door towards optimizing simultaneously the wheel and the volute.

Producing cherry tomatoes became interesting to know watering volume and growing design on growth, yield, and quality of cherry tomatoes. The research aimed to intend the best treatment for each treatment of watering volume and Growing design on the productivity and quality of cherry tomato cultivar Ruby. The study is an experimental exploration using RCBD factorial. The treatment factors include: Growing Design (greenhouse, Rain shelter, Screen house) and Watering Volume (100% Etc, 75% ETc, 50% ETc). The result showed that root dry weight and root-shoot ratio were found higher in the screen house design, while fruit firmness was higher in the rain shelter design. Considering the effect of watering volume, higher fruit diameter, heavier fruit, fruits per plant, ultimate fruit & biological yield per plant, higher root & shoot biomass, root-shoot ratio, leaf chlorophyll content, greater fruit skin firmness and elasticity was noted in the 100% ETc treatment. In contrast, the growth rate was higher in 50% ETc treatment. Cultivating cherry tomatoes in a greenhouse using a watering volume of 100% ETc under the results is recommended. These conditions have led to better growth, higher fruit yield, and improved fruit quality, making them favorable options for successful cherry tomato production.

The portal website of a university or a college usually represents the cultural characteristics and teaching advantages and plays a vital role in higher education, showing the style of the university or college to society and improving the admission rate. Mississippi State (MS) is bounded by the Mississippi River in the west and the Gulf of Mexico in the south, with a population of 3.1 million. It has a rich cultural heritage, and many universities, especially historically black colleges and universities (HBCUS), have strong scientific research strength in agriculture, medicine, petrochemicals and papermaking. Therefore, this article will analyze the design of the portal websites of four HBCUs in Mississippi from two aspects: user experience (UE) and functional architecture (FA), determine their advantages, disadvantages, similarities and differences, and propose some optimization suggestions.

In principle, modular or integral character of manufacturing lines depends on topological designs of products and determined operation tasks. On the other hand, in specific situations there is an articulated need for modular design in smart manufacturing systems, since modular layouts are a crucial step towards agile production via smart manufacturing. The aim of this paper is to explore how the modular layout relates to manufacturing lead time (MLT) and to operational complexity of smart manufacturing systems. For this purpose, topologically different models of alternative process layouts were simulated and tested, while MLT values were obtained using Tecnomatix Plant Simulation. Obtained positive findings of this research could be useful not only in selection of the most suitable process design from the alternative ones, but especially in deepening knowledge and better understanding of the concept of optimal network modularity.

The present paper deals with the complex study of the CO2 capture from combined heat power plant flue gases using the efficient technological scheme design – membrane cascade type of «Continuous Membrane Column». In contrast to well-known multi-step or multi-stage process designs, the cascade type of separation unit provides several advantages. That apparatus conceptually refers to the distillation columns. Here, the separation process is implemented in it by creating two counter current flows. In one of them is depleted by the high-permeable component in a continuous mode, meanwhile the other one is enriched. Taking into account, that the circulating flows rate overcome the withdrawn ones, there is a multiplicative growth in separation efficiency. A comprehensive study of the CO2 capture using membrane cascade type of «Continuous Membrane Column» includes the determination of optimal membrane material characteristics, the sensitivity study of the process and feasibility evaluation. It was clearly demonstrated that proposed process provides the efficient CO2 capture, which meets the modern requirements in terms of CO2 content (≥ 95 mol.%), recovery rate (≥ 90 %) and residual CO2 concentration (≤ 2 mol.%). Moreover, it was observed, that it is possible to process CO2 with purity up to 99.8 mol.% at the same recovery rate. This allows use of this specific process design in the CO2 pretreatment operations in the production of high-purity carbon dioxide.

The present paper deals with the investigation, at conceptual level, of the performance of short-medium-range aircraft with hydrogen propulsion. The attention is focused on the relationship between figures of merit related to transport capability, such as passenger capacity and flight range, and the parameters which drive the design of liquid hydrogen tanks and their integration with a given aircraft geometry. The reference aircraft chosen for such purpose is a box-wing short-medium-range airplane, object of study within a previous European research project called PARSIFAL, capable to cut the fuel consumption per passenger-kilometre up to 22%. By adopting a retrofitting approach, non-integral pressure vessels are sized to fit into the fuselage of the reference aircraft, under the assumption that the main aerodynamic, flight mechanic and structural characteristics are not affected. A parametric model is introduced to generate a wide variety of fuselage-tank cross-section layouts, from a single tank with the maximum diameter compatible with a catwalk corridor to multiple tanks located in the cargo deck , and an assessment work-flow is implemented to perform the structural sizing of the tanks and analyse their thermodynamic behaviour during the mission. This latter is simulated with a time-marching approach that couples the fuel request from engines with the thermodynamics of the hydrogen in the tanks, which is constantly subject to evaporation and, depending on the internal pressure, vent-ed-out in gas form. Each model is presented in detail in the paper and results are provided through sensitivity analyses to both the technology parameters of the tanks and the geometric parameters influencing their integration. The guidelines resulting from the analyses indicate that light materials, such as the Aluminium alloy AA2219 for tanks’ structure and polystyrene foam for the insulation, should be selected. Preferred values are also indicted for the aspect ratios of the vessel components, i.e. central tube and endcaps, as well as suggestions for the integration layout to be adopted depending on the desired trade-off between passenger capacity, as for the case of multiple tanks in the cargo deck, and achievable flight ranges, as for the single tank in the section.

Prospective end-users rated aptness, creativity, and innovativeness of biomimetic examples that featured different relationships to create combinations (e.g., used for) between nature and technology. Against common theorizing, similarity was not the most profound for creativity but rather appearance, being part_of, and property_of were. Creativity explained most of the variance in the level of innovation with aptness of the design in a strong supporting role. The focus of conceptualization shifted from ‘creation as new things coming from new ideas’ to ‘innovation as new ideas leading to new things.’ Results are interpreted in the Chinese context of utility. Both in education and industry, the use of 5*5 research grids with rating scales may work as a design method to develop and select functional variants during early design.

While many practitioners and experts understand the risks associated with low urban tree diversity, they often lack the ability to rectify issues they encounter on their own. The current system of tree production and procurement is complex – shaped by market pressures, nursery and site constraints, local governance, and differing professional objectives among those who grow, specify, and plant trees. To understand this complexity as well as constraints to- and opportunities for increasing urban tree diversity, we conducted a series of focus groups comprised of nursery growers, landscape architects, and urban foresters. Our results highlight a significant list of considerations and constraints to diversity (both shared among green industries and some specific to growers or purchasers). More importantly, in discussing our findings we outline actionable strategies for increasing urban tree diversity.

This paper presents an extension of the results obtained in previous work concerning the application of global optimization techniques to the design of finite strategic games with mixed strategies. In that publication the Fuzzy ASA global optimization method was applied to many examples of synthesis of strategic games with one previously specified Nash equilibrium, evidencing its ability in finding payoff functions whose respective games present those equilibria, possibly among others. That is to say, it was shown it is possible to establish in advance a Nash equilibrium for a generic finite state strategic game and to compute payoff functions that will make it feasible to reach the chosen equilibrium, allowing players to converge to the desired profile, con- sidering that it is an equilibrium of the game as well. Going beyond this state of affairs, the present article shows that it is possible to ”impose” multiple Nash equilibria to finite strategic games by following the same reasoning as before, but with a fundamental change: using the same fundamental theorem of Richard McKelvey, modifying the originally prescribed objective function and globally minimizing it. The proposed method, in principle, is able to find payoff functions that result in games featuring an arbitrary number of Nash equilibria, paving the way to a substantial number of potential applications.

Thermal simulations are an important part in the design of electronic systems, especially as systems with high power density become common. In simulation-based design approaches, a considerable amount of time is spent by repeated simulations. In this work, we present a proof-of-concept study of the application of convolutional neural networks to accelerate those thermal simulations. The goal is not to replace standard simulation tools but to provide a method to quickly select promising samples for more detailed investigations. Based on a training set of randomly generated circuits with corresponding Finite Element solutions, the full 3D steady-state temperature field is estimated using a fully convolutional neural network. A custom network architecture is proposed which captures the long-range correlations present in heat conduction problems. We test the network on a separate dataset and find that the mean relative error is around 2 % and the typical evaluation time is 35 ms per sample ( 2 ms for evaluation, 33 ms for data transfer). The benefit of this neural-network-based approach is that, once training is completed, the network can be applied to any system within the design space spanned by the randomised training dataset (which includes different components, material properties, different positioning of components on a PCB, etc.).

This review paper aimed at reviewing English language teaching articles on EFL teachers’ perceptions, practices and challenges towards communicative language teaching. In this review, two ELT articles, which have been conducted on teachers’ perceptions, practices and challenges towards communicative language teaching in EFL classes, were reviewed in detail. While reviewing the articles, the researcher adapted Rideley’s (2008) checklist to evaluate elements of article. Thus, articles were reviewed by focusing on the title, abstract, introduction, research questions, objectives, research design, participants, sample and sampling techniques, data collecting instruments, methods of data analyses, findings and references based on the checklist provided above. The review revealed that the articles had clear objectives, researchable questions, appropriate methods and inevitable conclusions. They tried to answer the questions which were raised in each article, and the objectives went along with the overall research findings. The review, on the other hand, revealed that the participants in the articles were not representative so as to conclude and generalize the overall population by taking only few participants which were selected even by using non probability sampling.

Molecular Dynamics (MD) simulations model motion of molecules in atomistic detail and aid in drug design. While simulations on large systems may require several days to complete, analysis of terabytes of data generated in the process could also be time consuming. Recent studies captured exciting and dramatic drug-receptor interactions under cell-like complex conditions. Such advances make simulations of biomolecular interactions more realistic, insightful, and informative and have potential to make drug design more realistic. However, currently available resources and techniques do not provide, in reasonable time, a comprehensive understanding of events seen in simulations. We demonstrate that big data approach results in significant speedups, and provides rapid insights into simulations performed. Advancing this improvement, we propose a scalable, self-tuning, and responsive framework based on Cloud-infrastructure to accomplish the best possible MD studies with given priorities and within available resources.

Progressive technologies and practices are shifting the possibilities of building design and improving work efficiency. Constantly changing site conditions require different procedures and designs that take into account these changing conditions, whether it is a design solution, a change in environmental conditions, or just sustainability factors. Adaptive building design offers opportunities to cope with changing factors to achieve the highest possible level of building quality. This case study deals with the topic of adaptive formwork design for building renovation, taking into account sustainability. Aim of the article is an investigation and demonstration of the building information modelling (BIM) environment used for the adaptive design of formwork elements for the building renovation in the context of sustainability. The object of the case study is a building in the center of Kosice, Slovakia. BIM environment allows prompt and correct adaptation of the formwork design to changing conditions of lighting, ventilation, heating and temperature during the design of the building.

The designs of two large arenas of different epochs are discussed, which are the most famous antique amphitheater the Roman Colosseum (Italy) and the modern Gazprom Arena stadium (St. Petersburg, Russia). 3D-computer models of the arenas have been built and evacuation of people has been simulated in the Sigma FS software (Russia). The arena designs are analyzed in terms of organizing pedestrian evacuation, a comparative analysis is made, and the specific characteristics affecting the evacuation time are established.

Creativity is fundamental to design problem-solving. This paper sets out a systematic review of the literature in relation to its role in the architectural design studio in order to identify central issues that impact upon this activity. Challenges and best practice in relation to systematic reviews are outlined, and the procedure followed in this context is set out in detail. This involves an iterative evaluation process that resulted in a pool of 17 papers for analysis. Eleven themes emerged in the analysis of the papers, which were organized into 5 key categories dealing with: pedagogy, cognitive approach, interaction and socialization, information representation, and measuring ideation and creativity. A discussion of these categories contributed to the comparison and connections between the selected papers, and the identification of critical issues and directions for promoting creativity in the architectural design studio.

The aim of this paper is to analyze the five grand parks in Dubai, United Arab Emirates (UAE) and provide a geoprocessing approach to different aspects such as sport, health, leisure, recreation, and public wellbeing. The study uses a hybrid of qualitative and quantitative approach as methodology. Sustainability offerings, accessibility for people of determination and special needs, typology and the geolocations of the grand parks plays crucial role in residents’ wellbeing. The paper concludes with recommendations for Dubai government to design new and innovative approaches to manage wellbeing of urban public places into the leisure environment for residents.

The commercial popularity of Virtual Reality attracted educators’ interest and brought new opportunities to the educational landscape. At the same time, Learning Analytics emerged with the promise to revolutionise the traditional practices by introducing ways to systematically assess and improve the effectiveness of instruction. However, the collection of ‘big’ educational data is mostly associated with web-based platforms as they offer direct access to learners’ activities with minimal effort. On the antipode, the nature of VR limits the opportunities for such data collection. Hence, in the context of this work, we present a four-dimensional theoretical framework, that accounts the information that can be gathered from VR-supported instruction, and propose a set of structural elements which can be utilised for the development of a Learning Analytics prototype system. The outcomes of this work are expected to support practitioners to maximise the potential of their interventions and provide inspiration for new ones.

The complexity of the design in high-rise residential projects is a challenge for the construction industry in completing projects that fit the needs of users. Performance-Based Building Design (PBBD) appears as a design concept that can describe these needs into performance requirements. In this case designing a building can be considered as an iterative process of exploration, where desired functional properties can be created, the shapes are suggested, and evaluation processes is used, so as to bring together the shapes and functions of the building. This concept is a container for designers to produce high-performance buildings. This study aimed to identify the performance-based building design factors applied by architect designers and engineers in high-rise residential building in Surabaya. As part of this study, primary data was collected based on surveys conducted through observation and questionnaire distributed to designers who had or were involved in the high-rise residential design process in Surabaya. A total of sixty-eight respondents were included in this study. Descriptive analysis through a mean and standard deviation scatter plot was used to rank the application of PBBD. Meanwhile, factor analysis was used in the analysis of PBBD application factors. From the results of the analysis, four factors were obtained for the application of PBBD in high-rise residential buildings in Surabaya, namely; the interests of occupants, the sustainability of building operations, the design collaboration process, and the risk of loss. Future research is the influence relationships and measure the success model of PBBD at a higher level into BIM (Building Information Modeling) interoperability.

This article presents a methodology for the design of rehabilitation devices that considers factors involved in a clinical environment. This methodology integrates different disciplines that work together. The methodology is composed by 3 phases and 13 stages with specific tasks, the first phase includes the clinical context considering the requirements of the patient and therapist during the rehabilitation, the second phase is focused in engineering based on the philosophy of digital twin, and in the third phase is evaluated the device. This article explains the characteristics of the methodology and how it was applied in the design of an exoskeleton for passive rehabilitation of the upper limb.

In this study, silver-strontium doped hydroxyapatite (AgSr-HA)/chitosan composite coatings were deposited on stainless steel (SS) substrate via electrophoretic deposition (EPD) technique. The EPD parameters such as the concentration of Ag Sr-HA particles in the suspension, applied voltage and deposition time were optimized on by the Taguchi Design of Experiment (DoE) approach. DOE approach elucidated that the “best” coating was obtained at; the deposition voltage of 20V, deposition time of 7 minutes, and at 5 g/L of Ag Sr-HA particles in the suspension. The optimum coatings were characterized by using scanning electron microscopy (SEM) and energy dispersive X-ray (EDX) spectroscopy. SEM images confirmed the deposition of chitosan/Ag Sr-HA on the SS substrate. The wettability studies indicated the hydrophilic nature of the chitosan/Ag Sr-HA coatings, which confirmed the suitability of the developed coatings for orthopedic applications. The average surface roughness of the chitosan/Ag Sr-HA coatings was in a suitable range for the attachment of bone marrow stromal cells. Chitosan/Ag Sr-HA coatings showed a potent antibacterial effect against the Gram-Positive and Gram-negative bacteria.

Objective: In low- and middle-income countries (LMICs), household survey data are a main source of information for planning, evaluation, and decision-making. Standard surveys are based on censuses, however, for many LMICs it has been more than ten years since their last census and they face high urban growth rates. Over the last decade, survey designers have begun to use modelled gridded population estimates as sample frames. We summarize the state of the emerging field of gridded population survey sampling, focussing on LMICs. Methods: We performed a systematic review and identified 43 national and sub-national gridded population-based household surveys implemented across 29 LMICs. Findings: Gridded population surveys used automated and manual approaches to derive clusters from WorldPop and LandScan gridded population estimates. After sampling, many surveys interviewed all households in each cluster or segment, though some sampled households from larger clusters. Tools to select gridded population survey clusters include the GridSample R package, Geo-sampling tool, and GridSample.org. In the field, gridded population surveys generally relied on geographically accurate maps based on satellite imagery or OpenStreetMap, and a tablet or GPS technology for navigation. Conclusions: For gridded population survey sampling to be adopted more widely, several strategic questions need answering regarding cell-level accuracy and uncertainty of gridded population estimates, the methods used to group/split cells into sample frame units, design effects of new sample designs, and feasibility of tools and methods to implement surveys across diverse settings.

Chiroptical responses have been an essential tool over the last decades for chemical structural elucidation due to their exceptional sensitivity to geometry and intermolecular interactions. In recent times, there has been an increasing interest for the search of more efficient sensing by the rational design of tailored chiroptical systems. In this Review article, advances on chiroptical systems towards their implementation in sensing applications are summarized. Strategies to generate chiroptical responses are illustrated. Theoretical approaches to assist in the design of these systems are discussed. Development of efficient chiroptical reporters in different states of matter, essential for the implementation in sensing devises, is reviewed. In the last part, remarkable examples of chiroptical sensing applications are highlighted.

Scouring is the most common cause of bridge failure. This study was conducted to evaluate the efficiency of the Artificial Neural Networks (ANN) in determining scour depth around composite bridge piers. The experimental data, attained in different conditions and various pile cap locations, were used to obtain the ANN model and to compare the results of the model with most well-known empirical, HEC-18 and FDOT, methods. The data were divided into training and evaluation sets. The ANN models were trained using the experimental data, and their efficiency was evaluated using statistical test. The results showed that to estimate scour at the composite piers, feedforward propagation network with three neurons in the hidden layer and hyperbolic sigmoid tangent transfer function was with the highest accuracy. The results also indicated a better estimation of the scour depth by the proposed ANN than the empirical methods.

The Middle East Respiratory Syndrome Coronavirus (MERS-CoV) was isolated in 2012 and is well known to cause the respiratory syndrome. The orf1ab gene is known to mediate MERS-CoV replication. In this study, we have discussed the in silico prediction of potential siRNAs targeting MERS-CoV-orf1ab gene for antiviral therapeutics. To identify the potential siRNAs, various factors were considered. We have excluded the siRNAs with off-target effects and potential binding with human mRNAs. By using available softwares, total twenty-one functional, off-target reduced potential siRNA were selected from four hundred and sixty-two siRNAs based on greater potency and specificity. We have tested only seven siRNAs initially to evaluate their performance by reverse transfection approach by lipofectamine mediated delivery in Vero cells. The evaluation results showed no cytotoxicity at various concentrations of siRNAs used. The results obtained in this study provided preliminary information about the cytotoxicity which will help us to further evaluate siRNAs in other cell cultures to find out the replication inhibition efficiency of MERS-CoV. Finally, it is concluded that the in silico prediction and designing resulted in filtration and selection of potential siRNAs with high accuracy, efficiency, and strength which can be further utilized for the development of oligonucleotide-based therapeutics.

Although significant efforts have been made to combat the spread of vector-borne diseases (VBDs), they still account for more than 17% of all infectious diseases. According to the World Health Organization (WHO), there were 216 million estimated cases in 2016, which is a 9.3% decrease from the estimated cases reported one decade earlier. It is known that the built environment, through features such as openings, can propagate the spread of malaria. There have been some significant efforts directed at addressing this risk. This notwithstanding, there are some knowledge gaps that have resulted in a missed opportunity for synergistically tackling the problem of vectors through leveraging design decisions made by built environment professionals. This work assesses the extent to which design decisions in the built environment can have a positive impact on the efforts directed at mitigating the risk of malaria based on selected cases from East Africa. Secondary data derived from relevant urban health journals as well as repositories curated by leading health agencies such as WHO were synthesized and analyzed using a web of causation approach. The outcome of the analysis is a schema of primary and secondary source (risk) factors. The use of the web of causation approach revealed the existing factor-to-factor interactions that could have a reinforcing effect. This information was used to identify the critical linkages and interdependencies across different factors. The outcome of the analysis was mapped against risk factors that can be linked to decisions made during the six primary phases of the construction life cycle: preliminary phase, conceptual design, detailed design, construction, facilities management, and end of life/disuse. The findings of the research have established that 1) there is, in fact, a built environment–related opportunity that can be leveraged to advance the impact of malaria mitigation effort; 2) cross-disciplinary synergies are critical to managing the interdependencies and complexity of malaria risk factors that have a reinforcing effect; and 3) a knowledge-management framework that serves as a decision support tool would be valuable for sharing data under a push-and-pull mechanism, in which data shared in real time can address the timeliness of mitigating the spread of malaria at the earliest stages for the greatest impact. Based on the findings, a conceptual architecture for a decision support framework has been proposed. This will be developed into a knowledge-management platform in subsequent efforts.

Objective: This paper aims to build an Effort Estimation Model for design, coding and testing Web Applications Based Fuzzy and Practical Models, which will help in optimizing the efforts in software development. Methods/Analysis: Soft computing approach is adopted and applied in the effort estimation and then compared with practical efforts in the development process with interpreting the historical data available for the existing functionalities. Findings: The effort estimation model presented in this paper focuses on the first level estimates published by Project Managers and the second level estimates presented by Project Leaders or Developers for any new requirement or enhancement for a web application built on 3-tier architecture using Microsoft technologies. The model considers the classification of each task as either Low or Medium or High complexity. These tasks pertain to the lowest level parts in bottom-up estimation. Efforts are estimated for designing, coding and unit testing of these tasks and the efforts are summed up to get the effort estimation for the higher level which is a feature to be implemented. Novelty/Improvement: The paper also discusses about the application of the effort estimation model by taking a new requirement as a case study. The first level estimates calculated using the effort estimation model has a variance of about 25% when compared with the actual effort. This variance is very much acceptable considering the fact that the first level estimates can be tolerable up to 35%. The proposed effort estimation tool would help the project managers to efficiently control the project, manage the resources effectively, and improve the software development process and also trade off analyses among schedule, performance, quality and functionality. Fuzzy logic is used to verify the claims made in efforts estimation. It is proposed a new relation between the number of data and efforts value membership for actual data. And converts it into crisp value in the range [0…1] which helps to classify the complexity of the task and subtask in the design, coding and testing phases.

To date, several independent methods and algorithms exist exploiting constraint-based stoichiometric models to find metabolic engineering strategies that optimize microbial production performance. Optimization procedures based on metaheuristics facilitate a straightforward adaption and expansion of engineering objectives as well as fitness functions, while being particularly suited for solving problems of high complexity. With the increasing interest in multi-scale models and a need for solving advanced engineering problems, we strive to advance genetic algorithms, which stand out due to their intuitive optimization principles and proven usefulness in this field of research. A drawback of genetic algorithms is that premature convergence to sub-optimal solutions easily occurs if the optimization parameters are not adapted to the specific problem. Here, we conducted comprehensive parameter sensitivity analyses to study their impact on finding optimal strain designs. We further demonstrate the capability of genetic algorithms to simultaneously handle (i) multiple, non-linear engineering objectives, (ii) the identification of gene target-sets according to logical gene-protein-reaction associations, (iii) minimization of the number of network perturbations, and (iv) the insertion of non-native reactions, while employing genome-scale metabolic models. This framework adds a level of sophistication in terms of strain design robustness, which is exemplarily tested on succinate overproduction in Escherichia coli.

Planning, development and design policies influence sense of safety of people touse the City centre or Central Business District (CBD) and therefore city centres can becomeactive and vibrant during the day and night. This paper reviews past and present planningpolicies relevant for feeling of personal safety in the context of housing, retail, amenities,street infrastructure, building design and transportation aspects. The past development trendsshow that insignificant attention has been paid to people's sense of safety when using publicspaces, particularly at night, a factor identified important in creating attractive city centressince 1960s. Local plans primarily refer to safety in relation to roads, accessibility andworkability. Local policies also show the dominance of CCTV since the 1990s has becomeubiquitous, but changes to sense of safety in urban spaces now may actually be a betterreflection of planning and design decisions made over the past 20 years.

Museums and Science Centres are informal education environments that intend to engage the visitors with their exhibits. We present an efficient design process that allows an improved working relationship between museum practitioners, exhibition designers, and visitors. We present the principles and a graphical representation based on the Engagement Profile from previous work. Elements of the design process are evaluated using a learning game at the science centre Engineerium. The evaluation is based on a study with over five hundred visitors to the science centre.

By using 0.35-um CMOS process, this work achieves a design of analogous band-gap reference voltage circuit with low temperature coefficient. The proposed circuit operates at 3V and generates a reference current of 44 uA. The HSPICE simulation results show the temperature coefficient of this circuit is 23 ppm/℃ at range of -10 ℃ to 100 ℃, and the line regulation (the ratio of output current variation to supply voltage variation) is estimated as 1.95 uA/V from supply voltage variation of 3 V to 5 V. The experimental chip is fabricated and measured. The circuit provides adjustable capability for output voltage among temperature variation of -10 - 100 ℃. The chip area is 534 × 695 um^2. In this new design, the operational amplifier is not necessary. The chip design effort can be great reduced.

Keywords: liquid alloys, microstratification, dispersed particles, spontaneous dispersion, criteria for true (entropic) spontaneous dispersion, mechanisms of quasi-spontaneous dispersion, methods and results for assessing size of dispersed particles.

Experiential learning can facilitate the development of transferrable skills necessary for success in attaining tenure and promotion in academia. In this article, we discuss the benefits of designing and implementing an individualized professional development experience or practicum. By doing this, we describe the experiential learning component of the Accomplishing Career Transitions (ACT) Program of the American Society for Cell Biology. The ACT program aims to assist postdoctoral trainees and junior faculty from backgrounds underrepresented in STEM as they strive to transition into tenure-track positions and ultimately attain tenure at research-intensive or teaching-intensive academic institutions.

How crucial is big data in contemporary molecular design? In this publication we elucidate fundamental concepts and terminology in this field, critically addressing overlooked issues. We thoroughly examine the size, accessibility, quality, and structural aspects of big data alongside the primary methodologies employed for their analysis. Within chemical compounds, properties and descriptors represent two distinct data types, forming the basis for categorizing molecular big data. The primary objective of chemistry is property production, which means we are searching for novel drugs or materials rather than chemical compounds, and big data is the central issue of this philosophy. The increasing availability of data in computer-aided technology propels advancements in artificial intelligence (AI), machine learning (ML), and deep learning (DL). Accordingly, a broad chemical audience must comprehend these methods to understand data-centered chemistry. Thus, we aim to systemize big data issues through a simple illustrative framework with fundamental descriptor categories: coding, computer-generated descriptors, and property correlates. Although we employ computer-generated descriptors as big data for predictions, the measured data are irreplaceable for achieving high-quality and reliable outcomes and controlling molecular effects. The scarcity of property data remains a significant hurdle limiting comprehensive studies on the structure-property relationships within big data. Accordingly, guided by pragmatics not-so-big data is an option for drug design. We presented also a brief review of the recent big data literature.

Today, numerous studies have shown that the physical environment in hospitals can significantly influence patients' well-being, comfort, and recovery. However, this is currently neglected in hospitals in the Global South. Therefore, there is an urgent need to increase the awareness to make it more applicable worldwide. Thus, this study focuses on improving the healing environment standards, by exploring the impact of evidence-based design and patient-centred care in hospitals for cancer patients; particularly the architectural space quality, on patient health outcomes as well as hospital staff health and wellbeing. In Global North countries, such as the UK, the Achieving Excellence Design Evaluation Toolkit (AEDET), is used by its National Health Services, to assess the effectiveness of various environmental attributes. However, these toolkits have not been designed for and do not work well within Global South countries, such as Northern Cyprus. To examine and compare the effectiveness of different physical environmental attributes and to evaluate user responses, the Post-Occupancy Evaluation Method and the AEDET toolkit have been used in the study. These were applied to both public and private hospitals in Northern Cyprus, involving cancer patients, staff, and professionals (n=220). The findings reveal the strength and weaknesses in terms of environmental comfort based on the aspects of evidence-based design of the hospitals such as natural light, air quality, noise, view, infection control, etc., to create a more optimal physical environment for better psychological outcomes. This is the first study to propose an adaptation of the AEDET toolkit to assist architects in designing healthcare facilities that are responsive to the requirements of hospital patients and staff; and to promote the quality of healing environment for improved health and well-being outcomes.

Buildings can generate heats which are mostly generated from the machinery using inside the buildings, and these heats generally released to the atmosphere. Buildings can also block the wind flow by their canopies and trap the heat by using low albedo materials. These causes pointedly contribute to urban heat island and greenhouse effects. Likewise, urban development and building construction in Cambodia are growing rapidly. The construction has been recognized as a key development sector while thousands of buildings are being built and have been operated in the main cities. However, those buildings mostly have not been considered to incorporate sustainability concepts while the major final energy consumers in the country are buildings. The buildings’ energy consumption is also projected to increase more than double until 2040. Hence, sustainable building promotion in Cambodia is necessary, and sustainable building criteria are completely required. This research aims to find out significant sustainable building criteria for Cambodia and focused on planning and design criteria because having proper planning and design is a smart start leading to achieving building sustainability in all stages. This research used the Delphi methods to validate the relevant sustainable building criteria available in the literature and then select the significant ones for Cambodia based on the Delphi consensus. The results showed that ninety-nine consensus planning and design criteria were found to be significant for sustainable buildings in Cambodia.

A particular challenge in the conceptual design of direct-from orbit delivery systems is the seemingly well-known kinematics retain fallacies whose efficacies are reduced over great distances. Rotation about the local wing of an aerospace vehicle is almost never the pitch angle, yet modern application of kinematics often assumes such (with accompanying angular error). The same assertion is usually true about the nature of roll and yaw angles. Expressing motion in coordinates of rotating reference frames necessitates transformation between reference frames, and one such transformation is embodied in the Direction Cosine Matrices (DCM) formed by a sequence of three successive frame rotations. One of two ubiquitous sequences of three rotations used to construct the DCM involves first a rotation around the inertial z-axis, then intermediate y-axis, then finally about the body’s x-axis; a sequence commonly called the “aerospace sequence” or the a “3-2-1 rotation sequence”. The second ubiquitous sequence is the so-called “orbital sequence” or “3-1-3 rotation sequence” with rotations about the inertial z axis first, then about the intermediate x-axis, then finally about the body z-axis. This manuscript evaluates which sequence is the most advantageous for an object starting in space and then travels through the atmosphere to a target on the Earth’s surface. Six degrees of freedom of vehicle motion were simulated starting in orbit with a given thrust and commanded maneuver. The simulation performs all twelve possible rotation sequences (transforming inertial coordinates to body coordinates) with comparison by computational burden and error representing rotations about body axes (roll, pitch, and yaw respectively). Simulation precision is validated using the quaternion normalization condition indicating near machine precision (0.9\times{10}^{-15}) and reveals the so-called 132 rotation is the most accurate with an average error of 0.14° and a computational time of 0.013 seconds: resulting in a 97.95% increase in accuracy over the so-called 321 rotation and a 99.84% increase over the so-called 313 rotation.

This article develops duality principles and numerical results for a large class of non-convex variational models. The main results are based on fundamental tools of convex analysis, duality theory and calculus of variations. More specifically the approach is established for a class of non-convex functionals similar as those found in some models in phase transition. Finally, in the last section we present a concerning numerical example and the respective software.

Preterm birth accounts for about 10% of births worldwide. Studying risk factors for perinatal brain damage is essential, as findings suggest that almost 20% of disabilities are linked to risks in the early stages of development. This research aimed to study longitudinal changes in intelligence from 6 to 8 years of age in a sample of 39 preterm children with a history of risk of brain damage and a control group of 35 children born at term. The Wechsler Intelligence Scale (WISC-IV) was used for cognitive measurement. The results showed that the preterm group obtained significantly lower scores than the control group. The working memory indicator significantly affected the interaction between age and prematurity. We consider that it is crucial to expand the knowledge we have about the neurocognitive development of premature infants both in specific cognitive domains and in age ranges so that the information obtained helps to predict the probability of presenting cognitive alterations from early stages and, therefore, to implement intervention strategies and programs based on scientific evidence and complemented in their design by clinical experience, empirical and theoretical knowledge of the different professionals involved in infant cognitive intervention.

In this paper we introduce an ODE system to model the interaction between nature resources and human exploitation in a rich consumeristic society. In this model the rate of change of population depends on wealth per capita, and the rate of consumption has a quadratic growth with respect to population and wealth. As in our previous work \cite{BaCra_1}, we distinguish between renewable and non renewable resources, and we introduce a replenishment term for non renewable resources. We first get some information on the asymptotic behaviour of wealth and population, then we compute all the equilibria of the system and we study their stability when the parameter of exploitation of resources is small. Some numerical simulations confirm the theoretical results, and give suggestions for future research.

In Mexico, the evaluations of environmental flows are regulated by the Mexican Norm NMX-AA-159-SCFI-2012 and they warrant the establishment of water reserves for the environment. Yet, the pressure for water use limits the establishment of said reserves. This research aimed to evaluate the changes through time of the variables that serve as a basis for the implementation strategy by the Mexican government. A geographical information system was built with updated variables, the desired conservation status was analyzed, and the potential reserves were estimated based on the reference values for all basins nationwide. The results were examined according to their historical, current, and potential contribution to the conservation of natural protected areas and their connectivity. The outcomes point towards an administrative implementation strategy with positive outcomes despite the growing pressure for water use, with a change rate higher than the one for the creation of new protected areas. Currently, basins with low pressure and high conservation value have the potential to contribute to 86–88% of the goal set by the present administration without affecting water availability. Finally, reserving water in the priority basins would guarantee the legal protection of the flow regime in 48–50% of the hydrographic network in a desired conservation status, 45–49% of wetlands of international importance, and other natural protected areas in 85–89% of the global ecoregions represented in Mexico.

The task of conveying scientific research to individuals with varying levels of knowledge and understanding can prove to be quite challenging for a research scientist. The difficulty is further compounded when the exchange of information must be conducted within a limited timeframe. Notwithstanding, the 'elevator pitch' is a valuable tool that enables researchers to navigate these potential obstacles. An effective elevator pitch not only facilitates the communication of a researcher's scientific findings but also highlights the individual's skills and the significance of their research. Moreover, a well-crafted elevator pitch is a critical career development tool, serving as a means of networking and paving the way for future communications, scientific collaborations, and funding opportunities. This article examines the value of a scientific elevator pitch and provides step-by-step guidelines for developing and constructing an impactful pitch. Furthermore, we provide resources and an example of a successful elevator pitch delivered by a Fellow from the NIH-funded Accelerating Career Transitions (ACT) program, a professional development program established and managed by the American Society for Cell Biology (ASCB).

The preservation of biodiversity has become a major concern in contemporary society. It is essential to understand teachers' representations of biodiversity to effectively guide educational efforts because of the significant role of education in raising awareness and promoting sustainable behavior. Through a survey of a sample of 118 teachers, we adopted a mixed-method approach combining both a closed questionnaire and interviews. We used these methods to explore teachers' representations of the concept of biodiversity as an integral part of the school curriculum, as well as to gather their views on certain features of its teaching. The results state that the majority of teachers perceive biodiversity as a whole and in its most complex relationships. During their professional experience, they have developed a biocentric and anthropocentric conception of biodiversity. This study provides valuable information to guide future pedagogical practices and educational policies in sustainable education.

The Dubai Digital Government launched its recent guidelines, which call for artificial intelligence systems to be subject to legal accountability. This study discusses the extent to which autonomous robots can be granted legal personality in UAE law and the consistency of this approach with the provisions of Islamic jurisprudence. This research paper answered two main questions: First, the extent to which these guidelines are considered the beginning of work on granting legal personality to AI systems in the UAE. Second, what form of legal personality can be given to autonomous robots in UAE law to be consistent with the provisions of Islamic jurisprudence as a primary source of legislation in the country? The research concluded the impossibility of considering autonomous robots as a "thing" and classifying them within the concept of "persons." It also concluded that it is possible to give them legal personality according to two legislative solutions: granting them partial or incomplete performance eligibility like minors.

The paper presents the conceptualization and realization of a novel platform for additive manu-facturing, an industrial robot arm-based system for additive manufacturing applications. Tradi-tional 3D printers, especially those employing fused deposition modelling (FDM) processes, are restricted to depositing material in a single toolpath plane (e.g. x-y plane). The focus of this study was to explore the feasibility of integrating commercial off the shelf (COTS) additive manufac-turing technologies with a six degree of freedom industrial robot arm to yield a 3D additive manufacturing system with the capability to perform free-form six degree of freedom fused deposition modelling. The present paper presents the development of a platform from stage 0, i.e. materials to its use, and finally a printed product with the developed extruder.

Through an ambitious development blueprint called Agenda 2063, Africa is on a mission to creating the ‘Africa We Want’ by the year 2063, centred on science, technology, and innovation. While the 2063 development agenda portends attainment of socio-economic development and prosperity in Africa, it brings with it an enormous need for strategic investment in research to ensure that no one is left behind. This paper presents insights from the African Research Initiative for Scientific Excellence (ARISE) programme on inclusive research capacity strengthening investment in Africa. The insights are drawn from a comprehensive candidate selection process for ARISE, from which 45 researchers (from a pool of 929 applicants) are recruited for ARISE Fellowships. The 45 early-to-mid-career researchers, 37% of which are women, are hosted in 45 institutions of higher learning located in 38 countries across Africa, conducting 5-year research fellowships with grants of up to €500,000 each. The insights from the ARISE programme contribute to the debate on effective approaches to programme scoping, design, and delivery, underscoring the need for consideration of scientific excellence in the context of diversity in research support capacity and investments across Africa.

Silicon nanoparticles (SiNPs) are highly promising for biological and biomedical applications, including bioimaging, due to their unique opltical properties (i.e. strong fluorescence and very high photostability). Their low or negligible in vitro toxicity has been reported, but in vivo toxicity and biological effects of SiNPs are still uncertain. Uncoated SiNPs were dispersed in distilled water via sonication, and their rapid aggregation was observed (319.0 ± 2.4 nm particle size). In vivo toxicity was studied using Danio rerio embryos and larvae. Rapid aggregation in their incubation medium was observed; besides that, SiNPs at 25 mg/L or higher concentration induced swim bladder malformation and/or death of the fish. The estimated LC50 value for 7-day larvae was 180 mg/L. This is the first in vivo toxicity study of uncoated and unfunctionalized SiNPs. To achieve better stability in biological media and lower toxicity, SiNPs should be covered with hydrophilic layers, but their absorption by cellular membranes may be weaker in this case.

The two major global immunisation agenda framings (Missed Opportunity for Immunisation, MOI vs Immunisation Defaulting) are interchangeably and inappropriately used in public health research and practice with flawed or misleading strategies recommended and adopted in various settings globally. This is evident in the fact that many opportunities to adopt evidence/findings from immunisation coverage research in policy are grossly missed. Ineffectiveness of inappropriate interventions from biased evidence can discourage and mislead the governance to make radical decisions by discretion. This could be the reason for the inability of low-and middle-income countries to vaccinate 80% of their children and otherwise; this also poses a global health threat to capable nations. The current guideline and information on MOI and immunisation defaulting appear insufficient and a little clarification on it would assist forerunners in immunisation to achieve measurable progress in ensuring good coverage especially in low-and middle-income countries. Consequently, this paper is aimed at addressing this issue in immunisation practice with appropriate recommendations. Optimistically, this will stimulate further discussions, streamline differences, and gear global immunisation governance on the subject matter, to achieve the target coverage by 2030 in low-and middle-income countries.

A new teaching method under the name of STEM, integrating the disciplines of Science, Technology, Engineering, and Mathematics, is now taught by teachers in their classes. Considering that the generation that grows up in the 21st-century has grown up with technology, it is thought that integrating technology into lessons helps students learn the subject. The study aims to develop five STEM activities for the human body systems lesson by integrating the coding-based Arduino into STEM education. The activities were implemented to 6th-grade students for seven weeks and the effects on students' skills of establishing a cause-effect relationship. The study method was pre-test-post-test quasi-experimental design, and the cause-effect relationship scale was used as a data collection tool. As a result of the study, a significant difference was found between the Arduino-supported STEM activities developed and the students' skills of establishing a cause-effect relationship.

Magnetic force microscopy (MFM) is a widespread technique for imaging magnetic structures with a resolution of some 10 nanometers. MFM can be calibrated to obtain quantitative (qMFM) spatially resolved magnetization data in units of A/m by determining the calibrated point spread function of the instrument, its instrument calibration function (ICF), from a measurement of a well-known reference sample. Beyond quantifying the MFM data, a deconvolution of the MFM image data with the ICF also corrects the smearing caused by the finite width of the MFM tip stray field distribution. However, the quality of the calibration depends critically on the calculability of the magnetization distribution of the reference sample. Here, we discuss a Ti/Pt/Co multilayer stack which shows a stripe domain pattern as a suitable reference material. A precise control of the fabrication process combined with a characterization of the sample micromagnetic parameters allows to reliably calculate the sample’s magnetic stray field, proven by a very good agreement between micromagnetic simulations and qMFM measurements. A calibrated qMFM measurement using the Ti/Pt/Co stack as a reference sample is shown and validated and the application area for quantitative MFM measurements calibrated with the Ti/Pt/Co stack is discussed.

This paper describes how to construct a low-cost magnetic levitation system (MagLev). The MagLev has been intensively used in the engineering education, allowing instructors and students to learn through hands-on experiments essential concepts, such as electronics, electromagnetism, and control systems. Built from scratch, the proposed MagLev depends only on simple, low-cost components readily available on the market. In addition to showing how to construct the MagLev, this paper presents a semi-active control strategy which seems novel when applied in the MagLev. Experiments performed in the laboratory have compared the proposed control scheme with the classical PID control. The corresponding real-time experiments illustrate both the effectiveness of the approach and the potential of the MagLev for education.

In the Italian context, the diffusion of online fake news about food is becoming increasingly fast-paced and widespread, making it more difficult for the public to recognize reliable information. Moreover, this phenomenon is deteriorating the relation with public institutions and industries. The purpose of this article is to provide a more advanced understanding of the individual psychological factors and the social influence contribute to the belief in food-related online fake news and the aspects that can increase or mitigate this risk. Data were collected with a self-report questionnaire between February and March 2019. We obtained 1004 valid questionnaires filled out by a representative sample of Italian population, extracted by stratified sampling. We used structural equation modelling (SEM) and the multi-group analyses to test our hypothesis. The results show that self-evaluation negatively affects the social-influence, which in turn positively affects the belief in online fake news. Moreover, this latter relationship is moderated by the readiness to change. Our results suggest that individual psychological characteristics and social influence are important to explain the belief in online fake news in the food sector; however, a pivotal role is played by the motivation of change lifestyle. This should be considered to engage people in clear and effective communication.

Efficient and uninterrupted energy supply plays crucial role in the quality of the modern daily life, while it is obvious that the efficiency and performance of energy supply companies has significant impact on energy supply itself, and on determining and finetuning the future roadmap of the sector. In this study, the performance and efficiency of energy supply companies with respect to productivity is investigated over a case study of an electricity distribution company in Turkey. The factors affecting the company’s performance and their corresponding weights have been determined and elicited using analytical hierarchy process (AHP) and the Fuzzy AHP methods, as two well-known multi-criteria decision-making methods, which are two well-known prominent methods widely used in the literature. The results help demonstrate that the criteria elicited to evaluate the company’s energy supply performance plan a crucial role in developing strategies, policies and action plans to achieve continuous improvement and consistent development.

The present research is embedded in the professional development and research line and in the needs of secondary education and first-year university teachers. We focussed on evidencing the importance of teachers’ professional training to include some specific adaptation and skills in intercultural dialogue and understanding -often called Intercultural Competence- because of its direct impact on the sustainable development of human beings, groups, and ecosystems. We investigated the role played by each of the main competencies linked to the following intercultural dimensions: Professional Identity, Ethics and Axiology, Methodology, and Inclusive Education. We used an integrated methodology and a cross-study of data, performed after the obtention of a three-cornered evaluation of results collected in focus groups, interviews, and questionnaires. We were able to show the impact of intercultural dialogue and understanding in the education for a sustainable development pattern. This is fundamental to set up a new ecology of forms, knowledge, attitudes, and educational meanings, further used to update teachers and students’ training in sustainable ecology and cultural diversity. Progress made in these complementary competencies -Professional Identity, Ethics and Axiology, Methodology- were appraised by teachers participating in the present study; the latter showing an increased interest and demand for the intercultural competence, after increasing their proficiency in the other complementary competencies.

This study uses a recently developed theory and technique to examine post-acquisition evidence as to the motives for mergers and acquisitions(M&As), and decomposed the M/B ratio into three components: firm-specific error, time-series sector error, and long-run value-to-book. We make a multidimensional grouping according to the frequency of M&As , payment method, proportion of shares acquired, M/B ratio before the merger and total assets of the acquirers before the merge. The results confirm that M&As involve multiple motives, such as market timing, industry and economic shocks, agency and hubris. Using a sample of 2,035 M&As in China, we find that 59% are related to market timing, 68% are related to agency and hubris, 21% are related to industry and economic shocks, 51% are related to multiple motives. Our empirical research finds that the main motives for M&As of listed companies in China are value-decreasing, which have negative impact on the acquirers‘ sustainable development.

Modern gas turbines firing temperatures (1500-2000K) are well beyond the maximum allowable blade material temperatures. Continuous safe operation is made possible by cooling the HP turbine first stages -nozzle vanes and rotor blades- with a portion of the compressor discharge air, a practice that induces a penalty on the cycle thermal efficiency. Therefore, a current issue is to investigate the real advantage, technical and economical, of raising maximum temperatures much further beyond current values. In this paper, process simulations of a gas turbine are performed to assess HP turbine first-stage cooling effects on cycle performance. A new simplified and properly streamlined model is proposed for the non-adiabatic expansion of the hot gas mixed with the cooling air within the blade passage, which allows for a comparison of several cycle configurations at different TIT (turbine inlet temperature) and max (total turbine expansion ratio) with a realistically acceptable degree of approximation.. The calculations suggest that, at a given max, the TIT can be increased in order to reach higher cycle efficiency up to a limit imposed by the required amount and temperature of the cooling air. Beyond this limit, no significant gains in thermal efficiency are obtained by adopting higher max and/or increasing the TIT, so that it is convenient in terms of cycle performance to design at lower rather than higher max. The small penalty on cycle efficiency is compensated by lower plant cost. The results of our model agree with those of some previous much more complex and computationally expensive studies, so that the novelty of this paper lies in the original method adopted on which the proposed model is based, and in the fast, accurate and low resource intensity of the corresponding numerical procedure: all advantages that can be crucial for industry needs. The presented analysis is purely thermodynamic, with no investigation on the effects of the different configurations on plant costs, so that future work addressing a thermo-economic analysis of the air-cooled gas turbine power plant is the next logical step.

The Medi-test system we developed was motivated by the large number of resources available for the medical domain, as well as the number of tests needed in this field (during and after the medical school) for evaluation, promotion, certification, etc. Generating questions to support learning and user interactivity has been an interesting and dynamic topic in NLP since the availability of e-book curricula and e-learning platforms. Current e-learning platforms offer increased support for student evaluation, with an emphasis in exploiting automation in both test generation and evaluation. In this context, our system is able to evaluate a student’s academic performance for the medical domain. Using as input medical reference texts and supported by a specially designed medical ontology, Medi-test generates different types of questionnaires for Romanian language. The evaluation includes 4 types of questions (multiple-choice, fill in the blanks, true/false and match), can have customizable length and difficulty and can be automatically graded. A recent extension of our system also allows for the generation of tests which include images. We evaluated our system with a local testing team, but also with a set of medicine students, and user satisfaction questionnaires showed that the system can be used to enhance learning.

The paper presents the results of the theoretical and practical research on developing the infrastructure for assessment of overall risk (explosion / occupational / terrorist attack) associated with unwanted events such as major accidents that can occur at explosive storehouses for civilian use. The scientific research outlined in this article was carried out within the Nucleu Project PN 16 43 02 15 - “Research on increasing safety levels at technical facilities for storage of explosives for civil use”.

In photolithography process, nanometer level precise, wavefront aberration models enable the machine to be able to meet the overlay (OVL) drift and critical dimension (CD) specifications. Software control algorithms take as input these models and correct any expected wavefront imperfections before reaching the wafer. In such way a near optimal image is exposed on the wafer surface. Optimizing the parameters of these models though, involves several time costly sensor measurements which reduce the throughput performance, in terms of exposed wafers per hour, of the machine. In that case, photolithography machines come across the trade-off between throughput and quality. Therefore one of the most common Optimal Experimental Design (OED) problems in photolithography machines (and not only) is how to choose the minimum amount of sensor measurements that will provide the maximum amount of information. Additionally, each sensor measurement corresponds to a point on the wafer surface and therefore we must measure uniformly around the wafer surface as well. In order to solve this problem, we propose a Sensor Marks Selection Algorithm which exploits Genetic Algorithms. The proposed solution first selects a pool of points that qualify as candidates to be selected in order to meet the uniformity constraint. Then, the point that provides the maximum amount of information, quantified by the Fisher based criteria of G, D and A-Optimality, is selected and added to the measurement scheme. This process though is considered "greedy", and for this reason Genetic Algorithms (GA) are exploited to further improve the solution. By repeating in parallel the "greedy" part several times we get an initial population that will be the input to our GA. This meta-heuristic approach outperforms the "greedy" approach significantly. The proposed solution is applied in a real life semiconductors industry use case and achieves interesting industry and academical results as well.

Obstructive Sleep Apnea (OSA) is nowadays one of the respiratory pathologies with a higher in-cidence globally in developed countries. This situation led to an increase in the demand for medical appointments and diagnostic studies related to that condition, especially those based on poly-somnographies and cardiorespiratory polygraphies. These studies are limited in resources, causing long waiting lists with the subsequent impact on the patients’ health. Furthermore, it is necessary to mention that OSA’s symptomatology is not very specific, and it is typically present in the general population (excessive sleepiness, snore, etc.). In this regard, this paper proposes a novel intelligent clinical decision support system for the diagnosis of OSA which could be used to help medical teams, both in primary care settings and in units specialized in respiratory pathologies. The aim of the proposed system is to help discriminate the patients suspected of suffering from the pathology from those who are not. To this end, two types of information sets of heterogeneous nature are consid-ered. The first one encompasses objective data, related to the patient's health profile with infor-mation usually available in electronic health records. The second type comprises subjective data, referred to the symptomatology reported by the patient in a previous interview. To process the first group of information, a Machine Learning classification algorithm is used, Bagged Trees in this case. For processing the second information set, related with the symptomatology of the patient, a col-lection of expert systems based on fuzzy inferential systems arranged in cascade are employed. As a result, the system is able to determine two risk indicators related to the patient's risk of suffering from OSA: the Statistical Risk and the Symbolic Risk respectively. Subsequently, by interpreting both risk indicators mentioned it will be possible to determine the severity of the patients’ health, proposing a preliminary evaluation on their condition. For the initial tests of the system, a software artifact has been built using a dataset with 4,978 selected patients, suspected of suffering from OSA, from the Álvaro Cunqueiro Hospital in Vigo. The results obtained are promising, demonstrating the potential usefulness of this type of tools in medical diagnosis. Once the system has been validated with new data from clinical environments, it is considered as possible to obtain a relevant improvement in the quality of the healthcare services, and a reduction in the associated costs.

The built environment sector’s growing impact on climate change is becoming increasingly important due to its share in energy consumption and greenhouse gas emissions. Global efforts have been undertaken to design and develop residential dwellings that aim towards zero energy and carbon emission, but there remains a multitude of obstructions to efficient construction processes. This study is focused on the gaps and barriers that have emerged during the pre-construction phase of a low-environmental-impact Passive House in Fayetteville, Arkansas. The technical, management, regulatory, and supply chain obstacles to the construction of a new three-story residential Passive House are documented to engage knowledge transformation in the design and construction of sustainable buildings of interest to developers and property owners. Primary data are collected by direct observation as well as open-ended interviews and secondary data collected through a literature review to understand the barriers and gaps faced by different key actors during the pre-construction phase in different regions. This local study highlighted the lack of interest, knowledge, and experience in sustainable building design among professionals having a significant influence on the project goals and timeline and was mentioned by participants as a common barrier as well as the inconsistency and inadequacy of regulatory framework of existing building codes to implement sustainable building design. These barriers along with other identified barriers are discussed and recommendations to overcome these barriers are provided.

Compact solar-powered plasma water generator: enhanced on-site aged seed germination with the corona dielectric barrier discharger

The acoustic environment in learning spaces significantly influences learning effectiveness and occupant well-being. Recent studies have shown that a series of architectural factors within physical learning environments can impact students' educational experiences. This research delves into the relationship between architectural characteristics and the perceived acoustic environment among 467 primary students in 19 learning spaces across 9 schools in Chile. The survey comprises a student questionnaire, a checklist evaluating space characteristics, and acoustic measurements of indoor noise levels during occupied conditions. Examined topics include Indoor Environmental Quality (IEQ) comfort perception, noise annoyance, hearing ability, and acoustic preference. Architectural characteristics considered encompass flexible and acoustic space design parameters. The results indicated that noise discomfort was a common issue, especially in traditional learning spaces without acoustic treatment. The type of learning space (traditional or flexible settings) has a greater impact on acoustic perception particularly concerning noise discomfort and acoustic preference. However, poorly acoustic spaces lacking absorbing materials or exhibiting lower spatial density (m2 per student) contribute to increased indoor noise levels affecting noise annoyance caused by children's talking inside. The study emphasizes the importance of considering both architectural design and acoustic conditioning for optimizing the acoustic experience in educational spaces.

Buildings consume 30% of the total energy consumption around the globe and 29% of the energy consumption in Egypt which in 2022 had a total population of 102 million, out of which 43 % live in urban areas . The operation of buildings contributes to around 30% of global CO2 emissions due to their high energy consumption (IEA, 2022a). Among the efforts made towards improving the energy efficiency of buildings are Advanced Energy Design Guides (AEDGs), building rating systems, codes, and standards. Furthermore, numerous research studies that are either literature review studies, experimental studies, or computational studies addressed the topic of energy efficiency in buildings. These are all examined in this literature review with the purpose of identifying the research gap in available research with a focus on Egypt. The identified gap is the development of a prescriptive path for the GPRS energy efficiency category based on whole building energy simulations.