Species distribution models (SDMs) are usually used to predict current species’ geographic distributions and to forecast the impact of climate change, with different aims, such as conservation, and biodiversity management. SDMs use has been increasing in the last decades, however, they are vulnerable to parametrization and data quality input. Thus, inappropriate input can lead to potential unreliability in results. In this context, the most used data and methodologies in SDM, and putative deviations from the consensual best practices, were identified, by analysing recent literature (2018 to 2022). Results show that the parameters presented more consistently are the chosen algorithm (MaxEnt was used in 98% of the studies), the accuracy measures, and the time windows. Many papers fail to specify other parameters, limiting the reproducibility of the studies. Some papers also fail to provide information about the target species: only a fraction of the species' range is considered, or no justification for including specific variables in the model is provided. These options can decrease reliability in predictions under future scenarios since data provided to the model is inaccurate from the start or there is insufficient information for outputs discussion.

Springs play a significant role in maintaining hydrological balance in the mountain ecosystem. The communities living in the mountain tops rely entirely on spring water for their daily needs. In recent decades, spring water discharges have decreased drastically in the Himalayan regions and become seasonal. Remote sensing and geographical information system techniques have proved to be essential for understanding the sustainable development of groundwater, particularly where people rely solely on spring water in the mountainous regions of the Himalayas. This study employs the Analytical Hierarchy Process (AHP) to identify groundwater potential zones. It involves overlaying seven thematic layers concerning elements of physical features and land-use/land-cover of the region, using the weighted overlay toolbox in ArcGIS, with each layer being assigned a weight based on its importance. Based on the results, groundwater potential zones have been classified into five categories: poor, fair, good, very good, and excellent. The study found that poor groundwater potential zones cover 1.1% of the area, fair zones cover 27.8%, good zones cover 23.3%, very good zones cover 26.6%, and excellent zones cover 21.2% of the total area. The excellent to very good potential zones are associated with perennial springs that have higher discharge (4.30-30.92 l/m), lineaments, rainfall, forested land, and porous soils, favoring the potentiality of the springs. The fair and poor groundwater potential zones are associated with seasonal flowing springs, consisting of barren land, less rainfall, and low fracture density are influencing the potentiality groundwater. The validation of the groundwater potential zones indicated an Area Under Curve (AUC) value of 0.88, which shows good agreement with observed spring water locations. The identified groundwater potential zones are valuable for prioritizing the area for the sustainable development of spring water. Particularly, it is helpful for the stakeholder departments to involved in developing strategies for sustainable water management at the micro-watershed level and safeguarding spring water resources using integrated watershed management.

This study explores the potential of digital technologies for preserving cultural heritage through the case study of the Raya Gopura, an incomplete monument in Melukote, India. Employing a combination of terrestrial photogrammetry, drone-based photogrammetry and terrestrial laser scanning, the research team captured highly detailed 3D models of the structure. This non-destructive approach offers a comprehensive digital record for future research and preservation. Furthermore, for the conjecture for the Raya Gopura two possible purposes: an entrance to a planned fort or a gateway to the temple are perceived through the collective intelligence (CI) approach. These insights inform a conjectural architectural drawing of the potentially completed monument. The 3D models hold significant potential for various applications, including tourism, education, and architectural research, with the potential for immersive experiences through VR and AR technologies. The study demonstrated the effectiveness of digital tools in heritage preservation, not only safeguarding the Raya Gopura but also offering valuable in-sights for future research and public engagements.

With the increasing incidents of fatal road injuries, there is an urgent need for developing effective road safety management systems. The study aims to develop predictive models based on machine learning to forecast the likelihood of road collisions depending on factors like weather, road condition, time, and driver behaviour in Chicago, USA. A machine learning approach has been applied to the crash dataset to evaluate the factors affecting the prevalence of road accidents. Python programming and the Jupyter Notebook platform have been used for performing descriptive statistics, correlation and three classification algorithms (Random Forest, K-Nearest Neighbor (KNN), Decision Tree and MLP Classification). Obtained accuracy of the KNN classifier is slightly higher than the other two classification models. The research explored insights into collision patterns related to roads, locations, and intersections. The study helps to increase road safety through targeted interventions with resource prioritisation, reducing the frequency and severity of traffic incidents by leveraging historical accident data with diverse spatial analysis techniques.

As an important part of coastal wetlands, tidal flats provide unique ecosystem services and functions. China's tidal flats are significantly threatened by industrialization, urbanization, aquaculture expansion and coastline reconstruction, and there is an urgent need for sustainable strategies to balance the protection and utilization of tidal flats. Remote sensing technology can realize large-scale spatiotemporal research of tidal flats, comprehensively improve the ecological environment of coastal zones, and help achieve the overall planning goals of major projects for the protection and restoration of important ecosystems in China. In this study, based on GEE (Google Earth Engine) platform, Sentinel-2 (MSI), Landsat 8 (OLI) and Landsat 9 (OLI-2) remote sensing images were used to construct multi-source intensive time series remote sensing image collection, combined with MSIC-OA algorithm. The tidal flat data of China in 2018 and 2023 are extracted and analyzed. The results show as follows: 1) The overall classification accuracy of the tidal flat in 2023 is 95.19%, and the Kappa coefficient is 0.89; In 2018, they were 92.77% and 0.83 respectively. 2) The total tidal flat area in 2018 and 2023 is 8300.34km2 and 8151.54km2, respectively, a decrease of 148.80km2; 3) In 2023, estuarine and bay tidal flats will account for 54.88% of the total area, and most of the tidal flats will be distributed near river inlets and bays; 4) In 2023, the total length of the coastline adjacent to the tidal flat is 10196.17km, of which the artificial shoreline accounts for 67.06%, and the development degree of the tidal flat is 2.04, indicating that most of the tidal flat has been developed and utilized. The research results provide valuable reference for the scientific planning and rational utilization of tidal flat resources in China.

Purpose: To evaluate prognostic factors for visual outcome in patients with diabetes who have undergone vitrectomy (PPV) for severe proliferative diabetic vitreo-retinopathy (PDVR) in at least one eye in the past 15 years. Methods: Medical records of 132 eyes of 66 patients were analyzed (median age 52ys 21-80; patients with type 1/2 diabetes 40/26, median follow-up 38 months 9-125). Correlation between final good visual outcome defined as 0.5≤ best corrected visual acuity (BCVA) and prognostic factors (age, sex, type and duration of diabetes, metabolic status, BCVA, diabetic retinopathy status, data of preoperative management, data of vitrectomy, postoperative complications) were analyzed. Results: BCVA improved significantly in the entire study cohort (from median 0.05 min-max 0.001-1 to 0.32 0.001-1, p <0.000). Visual stabilization was achieved in the majority of patients, and relatively good visual acuity (0.5≤BCVA) was maintained in more than one third of eyes. Multivariable GEE statistics showed that in addition to duration of diabetes and stable HbA1c values, only preoperative tractional macular detachment proved to be an independent significant predictor of visual outcome. Conclusions: Pars plana vitrectomy is a useful tool when performed early before tractional macular detachment. However, long-term visual stability can only be achieved with good metabolic control.

This qualitative research explores the impact of Supplier Relationship Management (SRM) on e-commerce brand reputation, focusing on the strategic imperatives, operational challenges, and economic implications within digital supply chains. Trust emerges as a foundational element in effective SRM practices, facilitating consistent product quality, timely delivery, and consumer trust, thereby enhancing brand credibility and loyalty. Strategic alignment of SRM with organizational goals enables e-commerce brands to leverage supplier capabilities for mutual growth and innovation. Operational challenges such as technological constraints and logistical complexities underscore the importance of digital integration and proactive risk management strategies to optimize SRM effectiveness. Digital technologies, including AI and blockchain, play a transformative role in enhancing transparency, efficiency, and resilience in SRM strategies, enabling e-commerce firms to mitigate risks and capitalize on market opportunities. Emotional intelligence (EI) competencies among supply chain professionals facilitate effective communication, conflict resolution, and sustainable supplier relationships that bolster brand reputation resilience. Economically, effective SRM practices yield cost efficiencies, improved financial performance, and resilience against supply chain disruptions, supporting sustainable growth in competitive digital markets. This study contributes valuable insights for practitioners and scholars aiming to enhance SRM strategies, optimize supplier relationships, and strengthen brand reputation management in e-commerce. By prioritizing trust, strategic alignment, digital innovation, EI competencies, and proactive risk management, e-commerce brands can navigate complexities, capitalize on opportunities, and foster positive brand reputations in the evolving landscape of digital commerce.

Laser Powder Bed Fusion (L-PBF)-based manufacturing is a growing area of research, with a particular focus on evaluating constraints in printed products. This research emphasises the importance of considering various factors—including mechanical properties and support structures—that influence the final product during the design phase. Specifically, the design of microchannel heat exchangers is highlighted, where all constraints are critical. This article will present a method for analysing channel pressure limitations and report findings about mechanical properties loss from examining tube porosity. This includes a summary of results and the establishment of an experimental device system.

Let R be a commutative ring and m, n be positive integers. We define a proper submodule N of an R-module M to be (m,n)-closed if for r∈R and b∈M, r^{m}b∈N implies rⁿ∈(N:_{R}M) or b∈N. This class of submodules lies properly between the classes of prime and primary submodules. Many characterizations, properties and supporting examples concerning this class of submodules are provided. The notion of (m,n)-modules is introduced and characterized. Furhermore, the (m,n)-closed avoidance theorem is proved. Finally, the (m,n)-closed submodules in amalgamated modules are studied.

This qualitative research explores Supplier Relationship Management (SRM) within the context of subscription-based e-commerce models. Through in-depth interviews and thematic analysis, the study investigates key elements such as trust, collaboration, technology integration, sustainability, risk management, cultural alignment, innovation, cost management, globalization, supplier selection, and performance measurement. Findings reveal that trust is foundational in fostering reliable interactions and open communication between e-commerce businesses and suppliers. Collaboration emerges as crucial for innovation and operational efficiency, facilitating co-development and shared risk management. Technology integration, including AI and blockchain, enhances supply chain visibility and decision-making capabilities. Sustainability considerations drive businesses to engage with suppliers adhering to environmental standards, enhancing brand reputation and consumer loyalty. Effective risk management strategies mitigate disruptions and ensure supply chain resilience. Cultural alignment fosters harmonious partnerships and mutual understanding across diverse global markets. Innovation through supplier collaboration drives product development and market responsiveness. Cost management practices optimize operational efficiency and strategic supplier relationships. Globalization necessitates adaptive strategies to manage diverse cultural and regulatory landscapes. Strategic supplier selection and continuous performance measurement drive ongoing improvement and alignment with business objectives. This study contributes empirical insights and practical implications for enhancing SRM in subscription-based e-commerce, informing strategies to navigate challenges and leverage opportunities in a competitive marketplace.

The accumulation of space debris, including defunct satellites, rocket stages, and fragments, poses a severe threat to current and future space operations. Addressing this issue requires innovative approaches for active debris removal. This paper presents a new method for detumbling and deorbiting large, non-cooperative tumbling debris, such as those from Russian 'Kosmos 3M' launchers. We propose a detumbling device combining three harpoons with a nanosatellite, which attaches to debris and uses thrusters to reduce its angular velocity, facilitating subsequent removal. A high-fidelity coupled dynamics model of the system is developed to account for external disturbances and inertial changes due to fuel consumption. Additionally, an adaptive sliding mode control strategy with pulse-width pulse-frequency (PWPF) modulation is proposed to manage uncertainties and disturbances during the detumbling process. Numerical simulations demonstrate the effectiveness and robustness of the proposed method, achieving successful detumbling within 4000 seconds.

Soft robotic manipulators consisting of serially-stacked segments combine actuation and structure in an integrated design. This design can be miniaturised while providing suitable actuation for applications such as minimally invasive surgery and for inspections in confined environments. The control of these robots, however, remains challenging, due to the difficulty in accurately modelling the robots, in coping with their redundancies, and in solving their full inverse kinematics. In this work, we explore a hybrid approach to control serial soft robotic manipulators that combines machine learning (ML) to estimate the inverse kinematics with a closed-loop control to compensate the remaining errors. For the ML part, we compare various approaches, including both kernel-based learning and more general neural networks. We validate the selected ML model experimentally. For the closed-loop control part, we first explore Jacobian formulations using both synthetic models and numerical approximations from experimental data. We then implement integral control actions using both these Jacobians, and evaluate them experimentally. In an experimental validation, we demonstrate that the hybrid control approach achieves setpoint regulation in a robot with 6 inputs and 4 outputs.

We present a cyclic symmetry type II vacuum spacetime admitting closed timelike curves (CTCs) which appear after a certain instant of time, i.e., a time-machine spacetime. The various authors in past have considered the 2D and 4D flat generalization of Misner space, but in the present work, we have considered the curved spacetime generalzations of 4D Misner space, and is asymptotically flat radially

New q-series in the spirit of Jacobi have been found in a publication rst published in 1884 written in Russian and translated into English in 1928. This work was found by chance and appears to be almost totally unknown. From these entirely new q-series, fresh lattice sums have been discovered and are presented here.

This paper offers a novel geometric and visual approach to the renowned Four Color Map Theorem and K5 non-planarity problem while unveiling their profound connection to the "kissing number" problem in 2D. We represent planar graphs through circles and tangents, simplifying complex structures and shedding light on these classic problems. Our proofs by contradiction, rooted in the kissing number concept, reveal that both the Four Color Map Theorem and K5 non-planarity are fundamentally linked, as they pivot around the concept of coloring. This study bridges the realms of geometry and graph theory, providing fresh insights and emphasizing the significance of the kissing number problem in various fields.

In analogy with entanglement in physics, the concept of entanglement has been developed in mathematics as a symmetry to build upon as a tool to study 'proximity' relations between different number sequences and series in a unifying way. Examples of entanglement are shown. A general algorithm for detecting entangled sequences/series is given in the appendix. The novelty of this paper is to propose the concept of entanglement as a tool to study different sequences and se-ries-series phenomena. To enable useful treatment suggested by Poincaré.

The Konya Closed Basin (Quaternary, Central Turkey) is a graben basin which expands toward the east-west and it is controlled by faults on three sides: The Konya fault zone in the west, the Divanlar fault zone in the east and the Karaömerler fault zone in the north. Calcretes developed in relation to fault systems in the Konya region are concentrated in areas where faults cut Quaternary aged terrestrial deposits. In this study, it is aimed to elucidate the deposition conditions, geochemistry and age (with ESR method) of the calcareous deposits associated with faults in the Konya Closed Basin. Calcretes in the region existing as coatings, dust, nodules and layers are in the form of dolocrete and clayey calcrete. Dolocretes were deposited in the Quaternary terrestrial sediments on the ophiolitic rocks and geochemical data point to an ultramafic source. Bacterial community, clay, quartz minerals and calcite cement are observed in the calcretes formed in areas with limestone basement. According to the results of ICP-MS analysis of samples taken from Konya calcretes, the %MgO contents are between 0.99 and 7.7; CaO%: between 34.71 and 50.71; %SiO2 between 3.22 and 20.59. %MgO in dolocretes are between 11.65 and 21.01; %CaO between 8.44 and 29.57; %SiO2 values between 4.48 and 9.17 The δ13C and δ18O isotope values of calcretes range from -3.87 to -7.62 and from -3.62 to -7.45 respectfully. Average δ13C values indicate that calcrete formation took place under pedogenic condition or in shallow groundwater. The calcretes deposited in 3 locations around the city of Konya (on the Konya fault zone) were dated by using the Electron Spin Resonance (ESR) method and ages between 217.47 and 389.85 ky were obtained. The calcrete samples taken from the fault planes (dip-slip normal fault bordering the Upper Cretaceous Ophiolitic Mélange and the Quaternary Karahüyük Formation) gave a relative age for faulting as being 292.86 ky. This first dating study conducted in the Konya Fault Zone has provided important clues to elucidate the formation history of Konya Closed Basin (KCB) and the paleo-seismological past of Konya.

In view of the floating rectangular aerostatic guideway problem of low load capacity and stiffness, this paper puts forward a kind of closed rectangular aerostatic guideway and its optimized design. Firstly, the analytic calculation formula of a closed rectangular aerostatic guideway was deduced. The use of MATLAB software for the numerical simulation and the parameter influence analyses was carried out in terms of the gas supply pressure on load capacity and stiffness. A simulation model of the rectangular air bearing was also built using the Fluent software, and the model was used for simulation calculations. Secondly, the static performance of the rectangular air bearing was analyzed by analyzing the distribution position and number of orifices on its load capacity and stiffness. On this basis, the response surface optimization design method is used to analyze the variation law of the load capacity and stiffness of the air bearing under different restrictor structural parameters. Finally, the optimal design parameters for the rectangular air bearing are obtained. The simulation results show that the optimized rectangular air bearing designed in this paper has a good load capacity and stiffness of 644.58N and 63.405N N∙μm^(-1).

We apply the Ramsey theory to the analysis of geometrical properties of closed contours. Consider a set of six points placed on a closed contour. The straight lines connecting these points are yikx=αikx+βik i,k=1...6, αik≠0. We color the edges connecting the points for which αik&gt;0 holds with red, and the edges for which αik&lt;0 with green with red. At least one monochromic triangle should necessarily appear within the curve (according to the Ramsey number R3,3=6). This result is immediately applicable for the analysis of dynamical billiards. The second theorem emerges from the combination of the Jordan curve and Ramsey theorem. The closed curve is considered. We connect the points located within the same region with green links and the points placed within the different regions with red links. In this case, transitivity/intransitivity of the relations between the points should be considered. Ramsey constructions arising from the differential geometry of closed contours are discussed.

Background: Ankle fractures, comprising about 10% of musculoskeletal injuries, pose a significant healthcare burden with an increasing incidence, particularly among an aging population. This study focuses on isolated Danis-Weber type B fractures. Recent trends lean towards surgical intervention for anatomical restoration, quicker recovery, albeit with associated complications. This report aims to assess the safety and efficacy of NewClip narrow locking plate system with early weight bearing in treating isolated fibular fractures. Methods: The study includes patients with Danis-Weber type B fractures surgically treated with NewClip narrow locking plate system. Exclusions involved nondisplaced fractures, open fractures, or those requiring additional fixation.Results: Fifteen patients were enrolled in this study. Minor complications, including wound swelling, were observed in two cases. The Visual Analogue Scale (VAS) for pain exhibited a steady decline postoperatively, with almost complete resolution by the third month. At three months, the FAOS demonstrated excellent results, and final follow-up at twelve months revealed complete osseous healing without complications.Conclusions: The use of this type of plates in treating isolated fibular fractures with early weight bearing shows promising results in terms of fracture healing, pain resolution, and functional outcomes warranting further investigation with larger cohorts.

Ranging from traditional food packaging, clothing, and furniture to the current small and large electronic devices and automobiles, plastics serve to fulfill diverse demands in our daily lives. However, the global plastic waste generation is dramatically escalating, currently standing at approximately 150 million metric tonnes annually. While some of regenerated plastics recycled by mechanical methods can be used as their parent plastics, cost and energy savings are limited by multiple preliminary processes such as plastic sorting, shredding, washing, and drying. Moreover, the continuous mechanical recycling process degrades the physical properties of the materials. In this context, chemical recycling is emerging as a promising alternative method due to its high efficiency, simple preliminary steps, reducing reliance on fossil resources, and conversion of plastic waste into value-added chemicals. This review provides a state-of-the-art overview of contemporary chemical recycling of polymeric materials via i) depolymerization: “polymers to small valuable molecules” and ii) closed-loop cycles: “polymers to monomers, and/or to polymers”, by encompassing both traditional/advanced depolymerization chemistries and the remaining challenges. These recycling approaches are contextualized within the present industrial technologies, key design principles, and specific recycling case studies related to distinct polymeric materials.

Although the effect of thermal modification (TM) on teak wood color is well documented, a few studies were carried out in closed system processes, as well as it remains unclear the effect of different processes on the same material. This work aimed to verify the effect of closed and open system processes of TM on the color of fast-growing teak wood. Thermally modified wood was evaluated in a closed system at 160 °C (CS160) and in an open system at 185 °C and 210 °C (OS185 and OS210). We measured the moisture content (initial and final) of wood, and the corrected mass loss (CML). The chemical analyses encompassed the contents of alpha-cellulose, hemicelluloses, lignin, and extractives (total, in acetone and dichloromethane). Wood color was measured before and after TM according to the CIEL*a*b* color space. It was possible to achieve the same color using different processes of thermal modification (CS160 and OS210). TM reduced wood lightness (L*), red-green chromaticity coordinate (a*), and yellow-blue chromaticity coordinate (b*). L* and a* had the bigger and lower variations, respectively. The color of thermally modified wood was significantly changed, even at the mildest condition tested (OS185, 0.33% CML).

This short paper reveals a simple methodology to create local-correlation models suitable for the closed-form pricing of multi-asset financial derivatives. The multivariate models are built to ensure two conditions, first, marginals follow desirable processes, e.g. we choose the Geometric Brownian Motion (GBM), popular for stock prices. Second, the payoff of the derivative should follow a desired one dimensional process. These conditions lead to a specific choice of the dependence structure, in the form of a local-correlation model. Two popular multi-asset options are entertained, a spread option and a basket option.

In this paper, an analytical form of the Unit Step Function (or Heaviside Step function) is presented. This important function constitutes a fundamental concept of Operational Calculus and is also involved in many other fields of applied and engineering mathematics. In particular, Heaviside Step Function is performed in a very simple manner by the use of a finite number of standard operations, as the summation of six inverse tangent functions. The novelty of this work when compared with other analytical expressions, is that the proposed exact formula contains two arbitrary single - valued continuous functions which satisfy only one restriction. In addition, the proposed representation is not exhibited in terms of miscellaneous special functions, e.g. Bessel functions, Beta function, Logistic function. Besides, it is neither the limit of a function, nor the limit of a sequence of functions with point – wise or uniform convergence. Hence, this formula may be much more practical, flexible and useful in the computational procedures which are inserted into Operational Calculus techniques and other engineering practices.

Closed timelike curves (CTCs), non-intuitive theoretical solutions of general relativity field equations can be modelled in quantum mechanics in a way, known as Deutsch-CTCs, to circumvent one of their most paradoxical implications, namely, the so-called grandfather paradox. An outstanding theoretical result of this model is the demonstration that in the presence of a Deutsch-CTC a classical computer would be computationally equivalent to a quantum computer. In the present study, the possible implications of such a striking result for the foundations of quantum mechanics and the connections between classicality and quantumness are explored. To this purpose, a model for fundamental particles that interact in physical space exchanging carriers of momentum and energy is considered. Every particle is then supplemented with an information space in which a probabilistic classical Turing machine is stored. It is analysed whether, through the action of Darwinian evolution, both a classical algorithm coding the rules of quantum mechanics and an anticipation module might plausibly be developed on the information space from initial random behaviour. The simulation of a CTC on the information space of the particle by means of the anticipation module would imply that fundamental particles, which do not possess direct intrinsic quantum features from first principles in this information-theoretic Darwinian approach, could however generate quantum emergent behaviour in real time as a consequence of Darwinian evolution acting on information-theoretic physical systems.

Sensor fusion technology is one of extensive used methods in the field of robot, aerospace and target tracking control. In this paper, the generalized sensor fusion framework, named the closed-loop fusion (CLF) is analyzed and the optimal design principle of filter is proposed in detail. Fusion error optimization problem, which is the core issue of fusion design, is also solved better through the feedback compensation law of CLF framework. Differently from conventional methods, the fusion filter of CLF can be optimally designed and the determination of superposition of fusion information is avoided. To show the validity, simulation and experimental results are to be submitted.

Electroencephalography (EEG) is a crucial tool in cognitive neuroscience, enabling the study of neurophysiological function by measuring the brain's electrical activity. Its applications are included perception, learning, memory, language, decision-making and neural network mapping. Recently, interest has surged in extending EEG measurements to domestic environments. However, the high costs associated with traditional laboratory EEG systems have hindered accessibility for many individuals and researchers in education, research, and medicine. To tackle this, a mobile-EEG device named "DreamMachine” was developed. A more affordable alternative to both lab-based EEG systems and existing mobile-EEG devices. This system boasts 24-channels, 24-bit resolution, up to 6 hours of battery life, portability and a low price. Our open-source and open-hardware approach empowers cognitive neuroscience, especially in education, learning, and research, opening doors to more accessibility. This paper introduces the DreamMachine's design and compares it with the lab-based EEG system "asalabTM" in an eyes-open and eyes-closed experiment. The Alpha band exhibited higher power in the power spectrum during eyes-closed conditions, whereas the eyes-open condition showed increased power specifically within the Delta frequency range. Our analysis confirms that the DreamMachine accurately records brain activity, meeting the necessary standards when compared to the asalabTM system.

Thermal-based actuators are known for generating large force and displacement strokes at mesoscale (millimeter) regime. In particular, two-phase thermal actuators are found to benefit from the scaling laws of physics at mesoscale to offer large force and displacement strokes; but they have low thermal efficiencies. As an alternative, a combustion-based thermal actuator is proposed and its performance is studied in both open and closed cycle operations. Through a physics-based lumped-parameter model, we investigate the behavior and performance of the actuator using a spring-mass-damper analogy and taking an air standard cycle approach. Three observations are reported: (1) the mesoscale actuator can generate peak forces of up to 400 N and displacement strokes of about 16 cm suitable for practical applications; (2) an increase in heat input to the actuator results in increasing the thermal efficiency of the actuator for both open and closed cycles; and (3) for a specific heat input, both the open and closed cycle operations respond differently \textemdash different stroke lengths, peak pressures, and thermal efficiencies.

We obtain two generalizations of a known theorem of A. Alam and M. Imdad (Fixed Point Theory Appl. 17 (2015) 693–702) showing that some standard proofs can be obtained involving only Cauchy sequences of the successive approximations instead of the usual successive approximations sequences. Suitable examples prove the effective generalization of our results in metric spaces not necessarily complete.

In the paper, the authors nd a new closed expression for the Fibonacci polynomials and, consequently, for the Fibonacci numbers, in terms of a tridiagonal determinant.

This paper evaluates the open and closed loop DC-DC converter operation within a DC coupling multilevel inverter architecture to obtain an infinite level stepped sinusoidal voltage. Adding a cascade controller to the DC-DC converter should reduce the settling time and increase the number of levels in the output voltage waveform, it could decrease the speed error and phase shift concerning the sinusoidal reference signal. The proposed methodology consists of implementing an experimental multilevel inverter with DC coupling, through a single-phase bridge inverter energized from a BUCK converter, trigger signals for the two converters are obtained from a control circuit based in an ATMEGA644P microcontroller, and a digital controller is also implemented to evaluate the operation of the BUCK converter in open and closed loop and observe its influence in the stepped sinusoidal output voltage. The evaluation is performed to energize a resistive load with common output voltage in multilevel inverters, that is 3, 5, 7, 11, and infinity levels. Results show that during the design stage, fast dynamic elements, like the storage capacitor, can be used to obtain a minimum THD because the settling time is sufficiently fast and the speed error remains small and there isn’t a need for a controller. A digital controller requires processing time and although in theory, it can reduce the settling time to a minimum, the processor introduces latency in the control signals generation, producing the opposite effect. Controller complexity of the digital controller must be considered because it increases processing time and influences the efficiency of the closed-loop operation.

Chipman contends, in stark contrast to the conventional view, that utility is not a real number but a vector and is inherently lexicographic in nature. According to these views, it will be proved that, for every preordered topological space (X,≾,t), the assumption t to be finer than the order topology t≾ on (X,t), i.e. t⊇t≾, and the assumption the quotient topology t∣∼≾ that is defined on the preordered set (X∣∼,≾∣∼) of indifference classes of ≾ to be Hausdorff imply that a cardinal number κ and a (complete) preorder ≲ on {0,1}κ that is coarser than the lexicographical ordering ≤lex on {0,1}κ, i.e. ≤lex⊂≲, can be chosen in such a way that there exists a continuous order-embedding ϑ:(X,≾,t)⟶({0,1}κ,≲,t≤lex). This theorem will be compared with a theorem that, in particular, describes necessary and sufficient conditions for ≾ to have a continuous multi-utility representation.

(1) Background: Presentation of the method of increasing the competitiveness of the mining industry through the demonstration of the possibility and potential in closing the loop of supply chains through waste management; (2) Methods: The source literature analysis and an arithmetic analysis of the data of statistical materials and data obtained from business in static and dynamic perspectives; (3) Results: According to the latest data available, in Poland, mining wastes account for over a half of industrial wastes, while the annual growth of mining wastes is on the level of 4%. The recorded recovery of mining wastes is on the level of ca. 19%. The exemplary company that deals with the recovery of carbon wastes recovers ca. 80% of material, which is handed over for utilization (4) Conclusions: It has been found that the structure of the level of mining wastes and the level of their recovery rates demonstrate a large potential of closing the loop of chains in this industry and, at the same time, a potential to extend the chains through directing the material from recovery to various sectors. This constitutes an example of the direction of activities that are in line with the EU strategies for the economies of other states which possess this type wastes.

Due to constraints in launch platform and cost, the maneuverability of gliding-guided projectiles is limited, necessitating a rational design of their trajectory schemes. To reduce the sensitivity of trajectory schemes to uncertainties while ensuring compatibility between flight schemes and guidance control systems, and fully exploiting the control capability of the projectile, a closed-loop robust trajectory planning method is proposed. Models of major uncertain factors and states deviation at the control-start point are established. Based on the NIPCE method, the stochastic dynamic model is transformed into a high-dimensional deterministic model with PCE coefficients as state variables, and the uncertainty propagation law is obtained. A PID algorithm is employed to design a tracking guidance law based on position error feedback, and open-loop and closed-loop robust trajectory planning models are established accordingly. The optimal control problem is solved by transforming it into a nonlinear programming problem using the direct shooting method. Simulation results indicate that the NIPCE method can significantly improve the computational efficiency of uncertainty propagation while ensuring accuracy. Open-loop robust planning can effectively mitigate the sensitivity of gliding trajectories to uncertainties but cannot completely eliminate terminal dispersion. Closed-loop robust planning effectively improves control effort consumption on the basis of open-loop planning.

Background/Objectives: We defined the value of a machine learning algorithm to distinguish between the EEG response to no light or any light stimulation, and between red or green light stimulation in awake volunteers with closed eyelids. This new method of EEG analysis is visionary in the understanding of visual signal processing and will facilitate anaesthetic depth research. Methods: X-gradient boosting models were used to classify the cortical response to VEP stimulation (no light vs. any light stimulation; red vs. green light stimulation). For each of the two classifications, three scenarios were tested: training and prediction in all participants (all), training and prediction in one participant (individual), training across all but one participant with prediction in the participant left out (one out). Results: Ninety-four Caucasian adults were included. The machine learning algorithm had a very high predictive value and accuracy in differentiating between no light and any light stimulation (AUCROCall: 0.96; accuracyall: 0.94; AUCROCindividual: 0.96±0.05, accuracyindividual: 0.94±0.05; AUCROConeout: 0.98±0.04; accuracyo-neout:0.96±0.04). The machine learning algorithm was highly predictive and accurate in distinguishing between green and red colour stimulation (AUCROCall: 0.97; accuracyall: 0.91; AUCROCin-dividual: 0.98±0.04, accuracyindividual: 0.96±0.04; AUCROConeout: 0.96±0.05; accuracyoneout: 0.93±0.06). The predictive value and accuracy of both classification tasks was comparable between males and females. Conclusions: Machine learning algorithms could almost continuously and reliably differentiate between the cortical EEG responses to no light or any light stimulation and between green or red colour stimulation using VEPs in awake female and male volunteers with eyes closed. Our findings may open new possibilities for using VEPs in the intraoperative setting.

Permafrost covers about 23% ~ 25% of the land in the northern hemisphere, mainly in Russia, Canada, Alaska, Northeast and Qinghai Tibet Plateau (QTP) in China. Many engineering especially the transportation has been in the permafrost regions above. Under the action of highways construction and global warming, permafrost under infrastructures is degraded and causes serious damage. Two phases closed thermosyphon (TPCT) is a widely accepted green countermeasure against the problem in permafrost regions. Although it has been applied to prevent permafrost degradation, their application presents significant challenges on account of the stronger endothermic action of asphalt pavement. This paper focused on the thermosyphon technology and application in the permafrost. Moreover, the article highlighted the excellent working performance of the TPCT that improving the stability of the infrastructures and prevent it degrading due its excellent efficiency of heat transfer. The industrial applications of the TPCT were also summarized, along with their limitations. Finally, the results reported in this paper can provide a valuable guidance for the design of the TPCT and construction of the permafrost regions in the future.

Our starting point is the covariant coordinate transformation equation of a relativistic positioning system in Minkowski space-time, which maps the receiver’s emission coordinates (proper times broadcast by the emitters) to its coordinates in some inertial reference frame. Bancroft’s analytical (closed-form) solution to the basic pseudorange navigation equations with four emitters is recovered and the subjacent elements are geometrically interpreted. The case of four static beacons is analized as a clarifying situation.

The rapid advancement of technology has led to increased electronic consumption and a corresponding rise in e-waste generation. To address this issue, this study develops a low-carbon e-commerce closed-loop supply chain (LCE-CLSC) system with remanufacturer, platform, and the government as key stakeholders. An evolutionary game approach is employed to investigate the system's dynamics, analyzing the impact of stakeholder strategies on system equilibrium. Numerical simulations reveal important findings: Firstly, government initiatives promoting recycling, carbon taxes on traditional products, can incentivize remanufacturers to produce low-carbon items and encourage platform investment in recycling services. Secondly, higher sales revenues motivate remanufacturers to produce low-carbon products. Thirdly, consumer sensitivity to recycling services strengthens waste recovery when platforms increase investments in these services, leading to remanufacturers choosing low-carbon production. Lastly, government subsidies may become ineffective if the cost of remanufacturers' carbon reduction and platforms' recycling services exceeds their affordability. These findings offer insights for the sustainable development of obsolete electronic product recycling systems.

Leasing and recycling are important issues to achieve low-carbon sustainable development of construction machinery industry, however there are some dilemmas bothering which is caused by excessive restriction of product service life. Focusing on the problem of pricing and coordination, a two-stage model of leasing closed-loop supply chain based on the Industrial Internet platform practical application was proposed. Under the centralized and decentralized decision-making scenarios, the price of leasing and selling, maintenance effort and recovery rate are calculated respectively. By using the Shapley value method to optimize the selling price, and the two-part pricing contract to calculate the compensation fee, the global profit is reasonably distributed, while the supply chain achieving Pareto optimality. The performance of different contracts on the improvement of supply chain profit was investigated. And the correlation among parameters was also explored through sensitivity analysis and numerical simulation. The findings showed that maintenance and recycling of construction machinery can be improved with the advantage of the Industrial Internet platform, while achieving the supply chain coordination by contracts. The enhancement of maintenance effort can decrease the remanufacturing cost which is positively correlated to the selling price and leasing price of product, furthermore promoting the recovery rate of used products. In the future, reasonable control of platform cost can help improve the recycling of construction machinery.

Trace metals can enter some natural regions with low human disturbance from atmospheric circulation, but little information is available regarding how the canopy can retained trace metals. Therefore, a representative sub-alpine spruce plantation was selected to investigate the net throughfall fluxes of eight trace metals (Fe, Mn, Cu, Zn, Al, Pb, Cd and Cr) of closed canopy and gap-edge canopy from August 2015 to July 2016. Over a one-year observational period, the annual fluxes of Al, Zn, Fe, Mn, Cu, Cd, Cr and Pb were 7.29 kg·ha^-1, 2.30 kg·ha^-1, 7.02 kg·ha^-1, 0.16 kg·ha^-1, 0.19 kg·ha^-1, 0.06 kg·ha^-1, 0.56 kg·ha^-1 and 0.24 kg·ha^-1, respectively, in the deposited precipitation. The annual net throughfall fluxes of these trace metals were 1.73 kg·ha^-1, 0.9 kg·ha^-1, 1.68kg·ha^-1, -0.032 kg·ha^-1, 0.04 kg·ha^-1, 0.018 kg·ha^-1, 0.093 kg·ha^-1 and 0.087kg·ha^-1, respectively, in the gap-edge canopy and -1.6 kg·ha^-1, 1.13 kg·ha^-1, 1.65 kg·ha^-1, -0.10 kg·ha^-1, 0.05 kg·ha^-1, 0.03 kg·ha^-1, 0.26 kg·ha^-1 and 0.15 kg·ha^-1, respectively, in the closed canopy. The closed canopy displayed a greater filter effect on the trace metals from precipitation than did the gap-edge canopy in the sub-alpine forest. In the rainy season, the net filtering ratio of trace metals ranged from -66%-89% in the closed canopy and from -52% to 25% in the gap-edge canopy. However, the net filtering ratio of all trace metals was greater than 50% in the closed canopy in the snowy season. Therefore, the results suggested that the most trace metals moving through the forest canopy are taken up rather than by rainfall leaching; moreover, the closed canopy can efficiently take up trace metals in the snowy season.

Free axisymmetric and non-axisymmetric vibration analysis of the unsaturated porous functionally graded circular plates has been presented on the basis of classical plate theory. The defined coupled equations of motion for the porous functionally graded circular plate were decoupled based on the properties of the physical neutral surface. The one general solution of the decoupled equation of motion was obtained as linear combinations of the multiparametric special Bessel functions for the functionally graded circular plate with even and uneven porosity distributions. The influences of the even and uneven distributions of porosity, gradient index, diverse boundary conditions and the negligible effect of the coupling in-plane and transverse displacements on the dimensionless frequencies of the circular plate were comprehensively studied. The obtained numerical results show the differences and significant effect of considered types of distributions of porosities, values of the gradient index and the porosity volume fraction on the distribution of eigenfrequencies of the circular plates. Additionally, the obtained multiparametric general solution of the defined differential equation will allow to study the influences of diverse additional complicating effects such as stepped thickness, cracks, additional mounted elements expressed by only additional boundary conditions on the dynamic behavior of the porous functionally graded circular/annular plates. The formulated boundary value problem, the method of solution and the obtained numerical results for the perfect and imperfect functionally graded circular plates have not yet been reported. The present paper fills this void in the literature.

This paper introduces a sliding mode control (SMC) based equivalent control method to a novel high output gain Cuk converter. An additional inductor and capacitor improves the efficiency and output gain of the classical Cuk converter. Classical PI controllers are widely used in DC-DC converters. However, it is a very challenging task to design a single PI controller operating in different load and disturbances. SMC based equivalent control method which achieves a robust operation in a wide operation range is also proposed. Switching frequency is kept constant in appropriate interval in different loading and disturbance conditions by implementing a dynamic hysteresis control method. Numerical simulations conducted on Matlab/Simulink confirm the accuracy of analytical analysis of high output gain modified Cuk converter. In addition, proposed equivalent control method is validated in different perturbations to demonstrate the robust operation in wide operation range.

Let R be a commutative ring with identity and m, n be positive integers. In this paper, we introduce the class of (m,n)-prime ideals which lies properly between the classes of prime and (m,n)-closed ideals. A proper ideal I of R is called (m,n)-prime if for a,b∈R, a^{m}b∈I implies either aⁿ∈I or b∈I. Several characterizations of this new class with many examples are given. Analougus to primary decomposition, we define the (m,n)-decomposition of ideals and show that every ideal in an n-Noetherian ring has an (m,n)-decomposition. Furthermore, the (m,n)-prime avoidance theorem is proved.

Environmental responsibility and economic benefits have promoted the development of closed-loop supply chain (CLSC), and shortages and channels are considered to be two important issues in CLSC. This paper explores ordering and channel decisions in CLSC with new and differentiated remanufactured products, and considers the price and sales effort-dependent demands, as well as the proportion of emergency orders determined by emergency order costs and backorder losses, and establishes an integrated and decentralized CLSC game models. We introduce a stochastic sales effort, which affects two types of products. Numerical results show that sales effort and the order quantity of new and remanufactured products exhibit concave and convex functions, respectively. Wherein, the upper limit of sales effort has a greater impact on supply chain decisions. High sales efforts can serve as a means of coordinating dispersed supply chains. Moreover, in different cases, decisions of integrated channel are better than those of decentralized channel. Finally, whether the supply chain adopts an emergency order strategy depends on the relative cost of emergency orders and out of stock costs. According to the research in this article, some management insights are also provided.

Based on the elasticity theory, this paper deals with the static analysis of a cracked double beam system in presence of a Winkler medium. The double-beam system is also supposed to be constrained at both ends by elastically flexible springs, with transverse and rotational stiffness. Using a variational formulation, the static governing equations are derived and solved by using analytical and numerical approaches. In the first approach, the closed-form solutions for the displacements functions are obtained based on the Euler-Bernoulli beam theory. In the second approach, the Cell-Discretization Method (CDM) is performed, according to which the two beams are reduced to a set of rigid bars linked together by means of elastic constraints, where the bending stiffness of the bars is concentrated. The resulting stiffness matrix is easily deduced, and the governing equations of the static problem can be immediately solved. A comparative analysis is performed in order to verify the accuracy and validity of the proposed method. This study focuses on the effect of various parameters including the crack depth and position, boundary conditions, elastic medium and slenderness. The validity of the proposed analysis is confirmed by comparing the present results with those obtained from the other approach. In particular, the results obtained by closed-form solution and Cell-discretization method (CDM) are compared by Finite element method (FEM). Accuracy of the results has been evaluated by making comparisons with the results in literature and reported in bibliography. It is demonstrated that the proposed algorithm provides a simple and powerful tool in dealing with the static analysis of a double-beam system. Finally, some concluding remarks are made.

In particle physics, spin is an intrinsic form of angular momentum carried by the elementary particles. It is believed that spin is a solely quantum-mechanical phenomenon, which does not have a counterpart in classical mechanics. We have derived the simplest equations of spin and magnetic moment of a charged elementary particle. These formulas enable us to understand the physical nature of the spin and the structure of elementary particles. It is shown that the electron and muon are in the shape of a thin ring with a circular cross section (torus), and the proton is in the form of a ring with a non-circular cross section (toroid). The connection between the photon’s spin of and the propagation of electromagnetic waves is considered.

This paper develops a chemical model for a closed constant volume combustion of gaseous mixtures of methane and hydrogen. Since the combustion is strongly depending on temperature, pressure and fuel composition, they were chosen the actual corresponding thermodynamic systems using this kind of combustion, respectively the spark ignition reciprocating engines in order to evaluate the combustion parameters and exhaust flue gases composition. The actual cycles impose extra restrictive operational conditions through the engine volumetric compression ratio, the geometry of combustion volume, the mode to prepare the mixture of methane and hydrogen, the cooling system and the delivered power. The chemical model avoided the unknown influences in order to explain accurately the influence of hydrogen upon the constant volume combustion and flue gases composition. The model adopted simplifying hypotheses, respectively isentropic compression and expansion processes, closed constant volume combustion developed by two successive steps obeying to the energy and mass conservation laws and, flue gases exhaust described also by two steps, i.e. an isentropic expansion through the flow section of exhaust valves followed by a constant pressure stagnation (this succession is corresponding in fact to a throttling direct process). The chemical model supposed the homogeneous mixtures of gases with variable heat capacities function of temperatures, the Mendeleev - Clapeyron ideal gas state equation and, the variable chemical equilibrium constants for chosen chemical reactions. It was assumed that the flue gases chemistry is prevailing during the isentropic expansion and flue gases exhaust and has mainly a thermal ground. The chemical model allowed evaluation of flue gasses composition and of noxious emissions.

The current work aims to develop an approximation of the slice of Minkowski sum of finite number of ellipsoids, sliced up by an arbitrarily oriented plane in Euclidean space $\mathbb{R}^3$ that, to the best of the author's knowledge, has not been addressed yet. This approximation of the actual slice is in a closed form of an explicit parametric equation in the case that the slice is not passing through those zones of the Minkowski surface with high curvatures, namely the "corners". At corners with high curvatures an alternative computational algorithm is introduced in which a family of ellipsoidal inner and outer bounds of the Minkowski's sum are used to construct a "narrow strip" for the actual slice of Minkowski sum. This strip can narrow persistently for a few more number of constructing bounds to precisely coincide on the actual slice of Minkowski sum. This algorithm is also applicable to the cases of slice of Minkowski sum of ellipsoids with high aspect ratio. In line with the main goal, some ellipsoidal inner and outer bounds of the Minkowski sum are reviewed, including the so called "Kurzhanski's" bounds. Also some ellipsoidal approximations are suggested for the Minkowski sum, which they can be used, as well as the inner and outer bounds, in calculation of the suggested parametric approximation of the slice of Minkowski sum.

Nutrient regulation in aquaponic environments has been the topic of research for many years. Most have focused on appropriate control of nutrients in an aquaponic set-up, but very little research has been done on commercial scale applications. In our model, the input data was sourced on a weekly basis from three commercial aquaponic farms in South-East Texas over the course of a year. Due to limited number of data points, dimensionality reduction techniques like pair-wise correlation matrix was used to remove the highly correlated predictors. Feature selection techniques like the XGBoost classifier and Recursive Feature Elimination with ExtraTreesClassifier were used to rank the features in order of their relative importance. Ammonium and calcium were found to be the top two nutrient predictors and based on the months in which lettuce was cultivated, the median of these nutrient values from the historical dataset served as the optimal concentrations to be maintained in the aquaponic solution. To accomplish this, Vernier sensors were used to measure the nutrient values and actuator systems were built to dispense the appropriate nutrient into the ecosystem via a closed loop.

Null-flux Electro-dynamic suspension (EDS) system promises to be one of the feasible high-speed maglev systems above 600 km/h. On account of its greater current-carrying capacity, superconducting magnet can provide super-magnetomotive force that is required for null-flux EDS system and cannot be provided by electromagnets and permanent magnets. There is already a relatively mature high-speed maglev technology with low temperature superconducting (LTS) magnets as the core, which works in the liquid helium temperature region (T≤4.2 K). 2-Generation high temperature superconducting (HTS) magnet winded by REBa2Cu3O7−δ (REBCO, RE=rare earth) tapes works above 20 K region and do not need to count on liquid helium which is rare on earth. This paper designed HTS no-insulation closed-loop coils applied for EDS system and energized with persistent current switch. The coils can work at persistent current model and has premier thermal quench self-protection. Besides, a full size double-pancake module was designed and manufactured in this paper, and it was tested in liquid nitrogen. The double-pancake module’s critical current is about 54 A and it is capable of working at persistent current model, whose average decay rate measured in 12 hours is 0.58%/day.

Religious and spiritual struggles are typically assessed by self-report scales using closed-ended items, yet nascent research suggests that using open-ended items may complement and advance assessment. In the current study, undergraduate participants (N = 976) completed open-ended descriptions of their religious and spiritual struggles, the Religious and Spiritual Struggles Scale (RSS), and a standardized measures of religious belief salience. Qualitative coding showed that the themes emerging from open-ended descriptions generally fell within the broad domains of the RSS though some descriptions reflected more contextualized struggles. Scores derived from the open-ended responses to assess RSS domains achieved evidence of reliability as well as convergent and discriminant validity with the RSS . Correlations revealed a mix of similar and divergent associations between methods of assessing religious and spiritual struggles and religious belief salience. Open-ended descriptions of religious and spiritual struggles may yield reliable and valid information that is related to but distinct from assessments relying on closed-ended items.

Recycling waste products is an environmental-friendly activity that can bring benefits to accompany, saving manufacturing costs and improving economic efficiency. For the beer industry, recycling bottles can reduce manufacturing costs and reduce the industry's carbon footprint. This paper presents a model for a multi-objective collection-distribution center location and allocation problem in a closed loop supply chain for the beer industry, in which the objective is to minimize total costs and transportation pollution. Uncertainties in the form of randomness and fuzziness are jointly handled in this paper to ensure a more practical problem solution, for which returned bottle sand unusable bottles are considered fuzzy random variables. A heuristic algorithm based on priority-based global-local-neighbor particle swarm optimization (pb-glnPSO) is applied to ensure reliable solutions for this NP-hard problem. A case study on a beer operation company is conducted to illustrate the application of the proposed model and demonstrate the priority-based global-local-neighbor particle swarm optimization.

In the paper, the authors find closed forms for derangement numbers in terms of the Hessenberg determinants, discover a recurrence relation of derangement numbers, present a formula for any higher order derivative of the exponential generating function of derangement numbers, and compute some related Hessenberg and tridiagonal determinants.

Electric tractors have many advantages, including high torque, excellent controllability, energy efficiency, simple structure, and electric interface for expansion. However, a significant limitation lies in their endurance. This study presents the design of an extended-range power supply system to ensure continuous endurance of electric tractor. The objective is to provide a continuous power source for our self-developed electric tractor while preserving the benefits of electric propulsion. Extended-range power systems utilize a primary mover, typically an oil-fueled internal combustion engine, to drive the generator for electricity generation, and the generated AC form electricity is subsequently converted into stable DC bus voltage by a power electronic converter. The hardware and control design of the extended-range power supply system have been finalized and validated through experimental trials. Results demonstrate the system’s capability to sustain a stable DC bus voltage amidst disruptions such as sudden load shifts and fluctuations in prime mover speed. Even with 50% sudden load change, the voltage drop is within 12% and could recover to ±3% within 4 seconds. The range extender can be used alone without battery to power the electric tractor, or it can used in parallel with other extended-range extenders or battery thanks with the droop control ability for power sharing.

This study examines geothermal energy extraction potential from the basement rock within the Denver-Julesburg (DJ) Basin, focusing on flow performance and heat extraction efficiency of different geothermal well configurations. It specifically compares U-Shaped, V-Shaped, Inclined V-Shaped, and Pipe-in-Pipe configurations against Enhanced Geothermal Systems (EGS) setups. Through numerical modeling, we evaluated the thermal behavior of these systems under various operational scenarios and fracture conditions. Results suggest that while closed-loop systems offer moderate temperature increases, EGS configurations show substantial potential for high-temperature extraction. This underscores the importance of evaluating well configurations in complex geological settings like the DJ Basin. The insights from this study aid in strategic geothermal energy planning and development, marking significant advancements in geothermal technology and setting a foundation for future explorations and optimizations.

Agriculture is the main driver of depletion resources worldwide, and its duty is to ensure food security within a rapidly increasing demographic and urbanization, so it is important to transition to sustainable production systems. Vertical crops (VCs) can reduce the pressure on conventional agriculture because they save water and nutrients and increase crop yield. Therefore, this study aimed to validate a proposed predictive model (PM) to simulate water and nutrient uptake in vertical crops under greenhouse conditions. Based on the Penman-Monteith equation, PM estimates transpiration, while nutrient uptake was estimated using the Carmassi-Sonneveld submodel. PM was experimentally evaluated for vertically grown lettuce under Mediterranean greenhouse conditions, during spring 2023. The irrigation technique was a closed-loop fertigation circuit. The experimental consisted of testing two densities (50 and 80 plants·m-2), where each unit of the experiment unit was divided into three heights (low, medium, and upper). It performed ANOVA with a value of p &lt; 0.05 and R2 to assess PM performance. The results suggest a high degree of PM, since R2 ranged from 0.7 to 0.9 for the uptake of water and nutrients. Both densities had a yield between 17-20 times higher than conventional lettuce production and significant savings in water, between 85-88%. In this sense, PM has great potential to intelligently manage VC fertigation, saving water and nutrients, which represents an advance towards reaching SDG 6 and SDG 12, within the 2030 Agenda.

Deep-Brain Stimulation (DBS) is a a highly effective and safe medical treatment that improves the lives of patients with a wide range of neurological and psychiatric deceases, and has been consolidated as a first-line tool in the treatment of these conditionsin the last two decades. Closed Loop Deep-Brain Stimulation (CLDBS) pushes this tool further by automatically adjusting the stimulation parameters to the brain response in real time. In this context, this paper presents a Low-Noise Amplifier (LNA) and a Neurostimulator circuits fabricated in the low-power/low-voltage 65 nm CMOS process from the TSMC, which were designed targeting implantable applications. To achieve the best trade-off between input-referred noise and power consuption, metaheuristic algorithms were employed to determine and optimizes the dimentions of the LNA devices during the design phase. The measurement results showed that the LNA had a gain of 40.6 dB, a 3 dB bandwidth spanning over three decades from 10 Hz to 8.6 kHz, and a power consumption of 6.19 uW. Simulations results indicated an input-referred noise of 4.86 uVrms for the LNA. The circuit of the Neurostimulator is a programmable Howland Current-Pump, whose measurements showed its ability to generate currents with arbitrary shapes ranging from between 325 uA to +318 uA. The simulations showed a quiescent power consumption of 0.13 W with a zero neurostimulation current. The LNA and the Neurostimulator circuits are supplied with 1.2 V voltage and occupy a microdevice area of 145 um x 311 um and 88 um x 89 um, respectively, making them suitable for implantation in applications involving Closed Loop Deep-Brain Stimulation.

In this paper, we introduced a generalized ∆-implicit locally contractive condition and give some examples to support it and to show its significance in fixed point theory. We prove that the mappings satisfying generalized ∆-implicit locally contractive condition admits a common fixed point, where, the ordered multiplicative GM−metric space is chosen as underlying space. The obtained fixed point theorems generalize many earlier fixed point theorems on implicit locally contractive mappings. In addition, some nontrivial and interesting examples are provided to support our findings. To demonstrate the originality of our new main result, we apply it to show existence of solutions to a system of nonlinear -Volterra type- integral equations.

Sinkhole flooding is an essential hydrological process to recharge karst aquifer in arid to dry sub-humid regions. On the other hand, the increase of rain extremes is one of the major consequences of the global warming, together with the expansion of drylands. Thus, appropriate runoff regulation in endorheic karst basins in order to reduce the risk of flooding and improve the quantity and quality of the water drained by sinkholes will be more and more crucial. With these premises, a systematic review was performed by using WoS engine to infer the best practices for the karst water management in regions actually or potentially affected by water scarcity. Hydrological models are essential to manage the consequences of climate change on karst water resource, however the review shows that providing the tools necessary for reliable modeling is still challenging. Finally, due to the intrinsic vulnerability of the karst aquifers, pollution reduction and wastewater recycling policy will play key role in the next decades.

In the paper, by virtue of the Faá di Bruno formula and two identities for the Bell polynomial of the second kind, the authors find a closed form for the Stirling polynomials in terms of the Stirling numbers of the first and second kinds.

Abstract: The traditional model of closed circuit ball milling systems has been used for several decades, however, if the classifier of the closed circuit ball mill system performs the duties of both pre-classification and check-classification, the characterization error of the traditional model is large. To address this problem, a new model is obtained by modifying and supplementing the traditional one. The most important feature of the new model compared to the traditional model is that the circulating load is considered to be the fresh feed for the entire system rather than the ball mill. The error between the slurry level height calculated using the traditional model and the actual is 52.31%, which is 13.77 times higher than that of the new model. When the relative capacity varies greatly, that of the ball mill calculated by the traditional model fluctuates between 0.95 and 1.15, while the new model is 0.6 to 1.4. The new model has a higher accuracy than the traditional model in characterizing the production status of the grinding system, which is of some significance for industrial production.

Deep brain stimulation (DBS) is an effective and safe medical treatment that improves the lives of patients with a wide range of neurological and psychiatric diseases, and has been consolidated as a first-line tool in the last two decades. Closed loop deep brain stimulation (CLDBS) pushes this tool further by automatically adjusting the stimulation parameters to the brain response in real-time. This paper presents a CLDBS with 2 stimulation channels and 2 acquisition channels. Each channel has a low-noise amplifier (LNA) buffer in differential configuration to eliminate the DC signal component of the input. Energy management is efficiently done by the control and communication unit. The battery supports almost 9 hours with both the acquisition and stimulation circuits active. If only the stimulation circuit is used as an Open Loop DBS (OLDBS), the battery can hold sufficient voltage for 24 hours of operation. The whole system is low-cost and portable and therefore it could be used as a wearable.

Finding sustainable renewable energy sources for energy conversion and management is still an obscure topic. This paper presents a model-based simulation for an energy conversion system using piezoelectric energy harvester (PEH) technology. A dynamic mathematical model of a PEH device consists of a piezoelectric transducer, a controlled PWM rectifier, and a closed-loop buck boost converter is developed. A piezoelectric transducer converts mechanical vibrations from a wind force into an oscillating train of electrical charges. The sinewave peak-to-peak level relationship describes the changeable values of these charges, which depend on the severity of the wind vibration. The controlled PWM rectifier, in conjunction with a closed-loop buck-boost converter, converts this train of sinewave cycles into DC voltages. The control blocks of the closed-loop buck-boost converter use the perturbation and observation (P&amp;O) algorithm based on maximum power point tracking (MPPT), which adapts the operational voltage of the piezoelectric source to deliver the maximum power to load and improves the PEHS output voltage stability. A simulation program is employed to perform mathematical analysis on various wind vibration scenarios, piezoelectric sources without PWM converters, and piezoelectric vibration sources connected to a closed-loop P&amp;O converter. The crucial results of this paper demonstrate that the proposed dynamic PEHS model effectively feeds low-power electronic loads by directly adjusting the output voltage level to the set voltage, even under different vibration severity levels. As a result, the proposed PEHS dynamic model serves as a guideline for researchers in the development of self-powered sensors, which contributes to understanding sustainable energy alternatives.

Machine learning has gained significant recognition within healthcare organizations as a potent technology for medical image analytics. Among various medical image modalities, Contrast-Enhanced CT (CECT) is widely utilized to acquire additional diagnostic information that can help to better visualize and evaluate certain structures or abnormalities in the human body. Accordingly, there is an increasing demand for machine learning systems for disease analytics using CECT. However, developing such systems presents two significant challenges: high technical complexity and high development effort. This paper presents a software platform that can effectively remedy these challenges. This platform embodies a unified software process for CECT-specific disease diagnosis including oncological diseases, cardiovascular diseases, and gastrointestinal diseases. It integrates multiple types of machine learning models into the disease diagnosis process, where the models can diagnose lesions, malignancies, tumors, medical features of tumors, temporal transitions with a contrast agent, and disease progress. The platform has been implemented in Python using Scikit-learn and TensorFlow libraries. To validate its applicability and reusability, a Hepatocellular Carcinoma (HCC) diagnosis system has been implemented.

Qualtra, an innovative 10 MW geothermal power plant proposal, employs a closed-loop design to mitigate emissions, ensuring no direct release into the atmosphere. A thorough assessment utilizing energy and exergy analysis, Life Cycle Assessment (LCA), Exergo-economic and Exergo Environmental Analysis (EevA) was conducted. The LCA results, utilizing the ReCiPe 2016 midpoint methodology, encompass all the spectrum of environmental indicators provided. The technology implemented makes it possible to totally avoid direct atmospheric emissions from the Qualtra plant, so the environmental impact is mainly due to indirect emissions over the life cycle. The results obtained for the Global Warming Potential indicator is about 6.6 g CO2/kWh, notably lower compared to other conventional systems. Contribution analysis reveals that the construction phase dominates, accounting for over 90% of the impact in all LCA MidPoint categories. At the component level, a single score calculation incorporating normalization and weighting was executed. The resulting single score is then used into Exergo-Environmental Analysis (EEvA), highlighting the well system as the most impactful contributor, constituting approximately 45% of the total impact. Other substantial contributions to the environmental impact include the condenser (21%), the turbine (17%), and the HEGeo (14%). The Exergo-Economic analysis assesses cost distribution across major plant components, projecting an electricity cost of about 8.3 c€/kWh.

Deep learning is based on matrix computing with a large amount of hidden parameters that is not visible outside the computing module. Deep learning is a non-linear system and a linear approach is not possible. It is natural for people to visualize the algorithm and to follow some hidden parameters. In this paper, we propose a simple graphical programming of a nonlinear system based on drawing the simplest unit, such as a single neuron model. A more complex scheme of a classical neural network is obtained by commands copy-move-place of one neuron. The number of neurons and layers can be chosen arbitrarily. Once the scheme is complete, the implementation code is evaluated with symbolic parameters and nonlinear activation functions. This cannot be done manually. With the symbolic expression of outputs in terms of inputs and symbolic parameters, including symbolic activation pure functions, some other properties can be derived in closed form. This unique original approach can help scientists and developers and design numerical algorithms for machine learning and to understand how deep learning algorithms work.

The purpose of this study is to apply the convergence-confinement method (CCM) based on the assumption of hydrostatic stress to the surrounding rock excavated in a circular tunnel whose rock mass characteristics meet the requirements of the non-linear Hoek-Brown failure criterion. Based on a consistent and rigorous method of theoretical analysis, a closed-form analytical solution for the stress/displacement of the ground reaction induced by the advancing excavation of the tunnel, especially in the elastic and plastic regions, is derived and investigated under the condition of an isotropic stress state. By taking the value of a confinement loss as an explicit analysis process in an incremental manner, not only is the computationally executable analytical solution achieved, but it can also be performed using a simple spreadsheet. The validity of the analytical solution implemented by the incremental procedure was examined with published data to study the effect of nonlinear failure criteria on the ground reaction curve; in particular the mechanical behavior at the intrados of the tunnel, and the distribution of stress/displacement on the cross-section of the tunnel. A comparison between the published results and the solution proposed in this study, which interprets the closed-form by the incremental procedure, shows consistent and favorable trends.

This paper presents an exact solution to the Timoshenko beam theory (TBT) for first-order analysis, second-order analysis, and stability. The TBT covers cases associated with small deflections based on shear deformation considerations, whereas the Euler–Bernoulli beam theory (EBBT) neglects shear deformations. Thus, the Euler–Bernoulli beam is a special case of the Timoshenko beam. The moment-curvature relationship is one of the governing equations of the EBBT, and closed-form expressions of efforts and deformations are available in the literature. However, neither an equivalent to the moment-curvature relationship of EBBT nor closed-form expressions of efforts and deformations can be found in the TBT. In this paper, a moment-shear force-curvature relationship, the equivalent in TBT of the moment-curvature relationship of EBBT, was presented. Based on this relationship, first-order and second-order analyses were conducted, and closed-form expressions of efforts and deformations were derived for various load cases. Furthermore, beam stability was analyzed and buckling loads were calculated. Finally, first-order and second-order element stiffness matrices were determined.

Assuming a geometrically closed universe, we predict a value for the cosmic curvature, , a value within current observational bounds. We also propose a thermodynamic heat engine model for the universe, which bypasses the need for an inflaton field. Our model is based on a Carnot Cycle where we have isothermal expansion, followed by adiabatic expansion, followed by isothermal contraction, followed by adiabatic contraction, bringing us back to our original starting point. For the working substance, we focus specifically on the CMB radiation filling the collective voids in the universe. Using this construct, we identify cosmic inflation as the isothermal expansion phase, which lasts just under, . The collective CMB volume we see today only increases by a factor of 5.65 times during this process, and homogeneity and perturbations in the CMB are explained. The singularity problem is avoided and we have a clear mechanism for the work done by the cosmos in causing expansion, and later contraction. For scaling laws with respect to the density parameters in Friedmann’s equations, we will assume a susceptibility model for space, where, , the smeared cosmic susceptibility, decreases with increasing cosmic scale parameter, . Within this framework, we can predict a maximum Hubble volume with minimum CMB temperature for the voids before contraction begins, as well as a minimum volume with maximum CMB temperature when expansion starts. The thermodynamic heat cycle deviates from efficiency in converting heat energy into mechanical energy (expansion) by a minuscule amount, namely, . The significance of this number is not known.

The study aims to utilize the convergence-confinement method (CCM) by considering non-hydrostatic stress assumptions in the analysis of the surrounding rock in a circular tunnel. The rock mass properties should adhere to the criteria of the non-linear Hoek-Brown failure criterion. Through a thorough theoretical analysis approach, an analytical solution is derived to determine the stress and displacement induced by tunnel excavation, particularly in the elastic and plastic zones. This solution, applicable under anisotropic stress conditions, involves accounting for confinement loss incrementally for computational feasibility. The implementation of this analytical solution, facilitated by a straightforward spreadsheet, was validated against existing data to evaluate the impact of non-linear failure criteria on ground reaction behavior. The study scrutinizes the mechanical response at the tunnel's inner curve and assesses stress-displacement distribution across the tunnel cross-section. A comparison between the proposed solution and published results demonstrates a consistent and promising correlation.

The complexity of plastic polymers and even more so of additives has increased enormously in recent years. This makes the high-quality recycling of mixed plastic waste considerably more difficult. Some additives have now been strictly regulated or even completely banned for good reasons ('legacy additives'). Material or mechanical recycling generally utilises old plastics that still contain these substances. Consequently, products that are manufactured using such recyclates are contaminated with these harmful substances. We therefore recommend avoiding the use of these recyclates for products with intensive contact with consumers until further notice. We also show that the climate policy challenges for the plastics (and chemical) industry necessitate a defossilisation ('feedstock change'). This turnaround can only succeed if solely high-quality recycling takes place in future; recyclates should primarily replace virgin plastics. This can only work if used plastics with a high degree of homogeneity and known formulation are collected separately, as is already the case today with PET bottles. In this context, we would like to point out inconsistencies in the current legislation on the European emissions trading system.

Abstract: In recent years, low frequency (LF) electroencephalogram (EEG) signals have been decoded to obtain kinematic trajectories with the aim of achieving closed loop natural control. However, decoded trajectories suffer variability and low correlation against the measured movement. This paper suggests that if EEG features of motor intents are directly associated with fixed points along a given range of motion, then the natural kinematic parameters can be quantified. A novel classification method is proposed to evaluate this hypothesis along with equations for obtaining the movement parameters (velocity, acceleration). Furthermore, this implies that the force of an end-effector and work done in moving the end-effector may be computed, leading to natural control of EEG-based robotic arms and neuroprostheses. Finally, expectations are that combining the proposed method with existing classification methods will increase the accuracy and scalability of brain-computer interface (BCI) applications.

The use of the commercial simulator Aspen Plus® could bring an amelioration in the accuracy of the predictions of the chemical species composition in the output streams of the anaerobic digestion process, due to availability of a broad library of thermodynamic and phenomena transport properties in this commercial package. In the present investigation, the process simulation model for anaerobic digestion, which was originally developed by Rajendran et al. [1], has been modified by including a stoichiometric-equilibria reactor to calculate the extent of the ionization of the molecules present in the anaerobic digestate. The refined model offers a more accurate prediction of the composition of the biogas because it delves on the chemical equilibrium of the gaseous stream and the anaerobic digestate. Additionally, the refined model allows to assess the possibility of upgrading the gaseous stream to biomethane degree via manufacturing of ammonium bicarbonate. This processing pathway relies on the stabilization of the anaerobic digestate by means of biomass ash-based treatment. First of all, the titration of the manure digestate with the hydrochloric acid showed that a dose of 3.18 mEq/g would be required to attain the targeted pH of zero-point charge, upon addition of the sewage sludge ash in a ratio to the manure digestate of 0.6 ± 0.2 %. Secondly, the profiles of ammonia, carbon dioxide, and methane found in the biogas agree with both the pH of the treated digestate and the processes described in for the simultaneously upgrading the biogas and the production of ammonium bicarbonate. The refined Aspen Plus® model presented in this article needs to be further developed to ensure the standards are attained in all output streams of stabilized anaerobic digestate, biomethane, and isolated added-value chemical fertilizers.

Approximately 240 million people are chronically infected with hepatitis B virus (HBV), despite four decades of an effective HBV vaccine. During chronic infection, HBV forms two distinct templates responsible for viral gene transcription: (1) episomal covalently closed circular (ccc)DNA and (2) host-genome integrated viral templates. Multiple ubiquitous and liver-specific transcription factors are recruited onto these templates and modulate viral gene transcription. This review details the latest developments in antivirals that inhibit HBV gene transcription, and their impact on the stability of viral transcripts. Notably, nuclear receptor agonists exhibit potent inhibition of viral gene transcription from cccDNA, small molecule inhibitors repress HBV X protein-mediated transcription from cccDNA and small interfering RNAs and single-stranded oligonucleotides result in transcript degradation from both cccDNA and integrant templates. These antivirals mediate their effects by reducing viral transcripts abundance, eventually leading to loss of surface antigen expression, and can potentially be added to the arsenal of drugs with demonstrable anti-HBV activity. Thus, these candidates deserve special attention for future repurposing or further development as anti-HBV therapeutics.

In this paper, we introduce a comprehensive solution aimed at enhancing the understanding of three-dimensional atmospheric pollutant dispersion. This innovative solution develops a generalized model that extends previous research and is applicable to all parameterization schemes of the equation, including wind speed profiles and turbulent diffusion coefficients, while incorporating the dry deposition criterion. Our methodology involves subdividing the atmospheric boundary layer into distinct sublayers, which facilitates a detailed examination of pollutant dispersion dynamics. Extensive validation with data from the Hanford experiment has demonstrated the accuracy of this solution in simulating pollutant concentrations. The results exhibit a strong correlation between projected and observed concentrations, underscoring the statistical reliability of our approach. This validation situates the statistical indices of our solution within an acceptable range, confirming its accuracy in predicting atmospheric pollutant dispersion. These findings thus establish our solution as a valid and effective method for studying complex environmental phenomena.

In this review, we explore a broad-based view of technologies for supporting human activities on the Moon. Primarily, we assess the state of life support systems technology beginning with physicochemical processes, waste processing, bioregenerative methods, food production systems and the robotics and advanced biological technologies that support the latter. We observe that the Moon possesses in-situ resources but that these resources are of limited value in CELSS – indeed, CELSS technology is most mature in recycling water and oxygen, the two resources that are abundant on the Moon. This places a premium on developing CELSS that recycles other elements that are rarified on the Moon including C and N in particular but also other elements such as P, S and K which might be challenging to extract from local resources. Although we focus on closed loop ecological life support systems, we also consider related technologies that involve the application of biological organisms to bioregenerative medical technologies and bioregenerative approaches to industrial activity on the Moon as potential future developments.

A variety of techniques have been utilized in metal additive manufacturing (AM) for melt pool size management, including modeling and feed-forward approaches. In a few cases, closed-loop control has been demonstrated. In this research, closed-loop melt pool size control for large-scale, laser-wire based Directed Energy Deposition is demonstrated with a novel modification: site-specific changes to the controller set-point were commanded at trigger points, the locations of which were generated by the projection of a secondary geometry onto the primary 3D-printed component geometry. The present work shows that, through this technique, it is possible to print a specific geometry that occurs beyond the actual toolpath of the print head. This is denoted as an extra-toolpath geometry and is fundamentally different from other methods of generating component features in metal AM. A proof-of-principle experiment is presented in which a complex oak leaf geometry was embossed on an otherwise ordinary double-bead wall made from Ti-6Al-4V. The process is introduced and characterized primarily from a controls perspective with reports on the performance of the control system, the melt pool size response, and the resulting geometry. The implications of this capability, which extend beyond localized control of bead geometry to the potential mitigations of defects and functional grading of component properties, are discussed.

The complexity of software is increasing day by day due to the increase in the size of the projects being developed. For better planning and management of large software projects, estimation of software quality is important. During the development processes, complexity metrics are used for the indication of the attributes/characteristics of the quality software. There are many studies about the effect of the complexity of the software on the cost and quality. In this study, we discussed the effects of software complexity on the quality attributes of the software for open source and closed source software. Though, the quality metrics for open and closed source software are not distinct from each other. In this paper, we comparatively analyzed the impact of complexity metrics on open source and private software. We also presented various models for the management of the project complexity such as William’s Model, Stacey’s Agreement and Certainty matrix, Kahane’s Approach and UCP Model. Quality metrics here refer to the standards for the measurement of the quality of software which contains certain attributes or characteristics of the software that are related to the quality of the software. Certain quality attributes addressed in this study are Usability, Reliability, Security, Portability, Maintainability, Efficiency, Cost, Standards and Availability, etc. Both Open source and Closed source software are evaluated on the basis of these quality attributes. This study also recommended future approaches to manage the quality of project Open source and Closed source software and specify which one of them is mostly used in the industry.

Most of the research in data mining concentrated on finding the positive associations that exist in frequent patterns. Frequent patterns have no bearing on the time duration and, therefore, lose interestingness. The Regularity of an itemset is related to the time at which the transaction occurred and the time distance between the transactions. Frequent Regular item sets can be generated considering the Frequency and the Regularity of the occurrence of the Item Sets. The frequent and regular Item sets will be so huge that they cannot be handled in real time. The count of Frequent and regular item sets gets reduced drastically when the properties “closed” and “Maximality” are applied. Finding negative associations among such patterns are important in the field of medicine. Many drugs administered to cure some diseases have counter reactions leading to many other diseases. Negative associations among the mined patterns are important as they reveal significant contradictions frequently among medical drugs administered by medical practitioners to cure some diseases. This paper proposes a method that mines medical databases to find regular, frequent patterns applied with closed and maximal properties and find negative associations among those patterns. The proposed algorithm is accurate to 98% and performs 9% more efficiently than the other algorithms presented in the literature.

This exploratory study investigates the use of Generative Artificial Intelligence (GenAI) tools in developing strategy practices for nanostores — i.e., small independent grocery retailers — to enhance their competitiveness while contributing to community sustainability. Nanostores, particularly in emerging countries, face intense competition and rapidly changing trends. By leveraging their proximity to consumers in neighbourhoods, these stores adopt various strategies, such as offering complementary services, integrating technology, and adapting business models. While existing literature highlights the broader economic, social, and environmental roles of nanostores, there is limited comprehensive research on how they may simultaneously contribute to their competitiveness and communities’ sustainability. This study employs a 'thing ethnography' approach, using GenAI tools —i.e., ChatGPT 3.5 and Microsoft Copilot— to explore potential strategy practices for these shops, and reflect on their possible use for strategy ideation and implementation. Key findings suggest that prioritising local sourcing, understanding local preferences, flexible inventory management, efficient retail operations, in-store sustainable practices, promoting healthy lifestyles, and diverse community engagement are crucial for success. However, the study also acknowledges the limitations of GenAI tools, including possible bias and the need for result validation. By aligning with these evolving requirements, nanostores can strive in neighbourhoods and decisively promote sustainable communities.

This paper aims to outline the effectiveness of modern universal gate quantum computers when utilizing different configurations to solve the B-SAT(Boolean Satisfiability) problem. The quantum computing experiments are performed using Grover’s Search algorithm to find a valid solution. The experiments are performed under different variations to demonstrate their effects on the results. Changing the number of shots, qubit mapping, and using a different quantum processor are all among the experimental variables. The study also branches into a dedicated experiment highlighting a peculiar behavior that IBM quantum processors exhibit when running circuits with a certain number of shots.

Currently, Korea is experiencing localized extreme rainfall, which accounts for more than 80% of flood-related disasters, and is increasing in small river basins, where more than 60% of flood-related casualties occur. These events are caused by climate change and geological factors and their impact is becoming more severe. As a result, an effective measurement system is required to mitigate their impact, particularly in small stream basins that are especially vulnerable due to their steep slopes, small catchment areas, and lack of maintenance and management capacity. In addition, a Flood Early Warning Framework (FEWF) that forecasts discharge and depth during flood events is crucial for reducing casualties. Therefore, this research is focused on developing the FEWF using the nomograph and rating curve methods, which are established by the robust constrained nonlinear equation solver and are suitable for small streams. The FEWF is evaluated using real-time data observed over 7-years period from the Closed-circuit Television-based Automatic Discharge Measurement Technology (CADMT), and the results show that the FEWF is effective in forecasting discharge and depth during flood events. The use of CADMT technology for real-time data can develop an accurate and reliable FEWF, which can help mitigate the impacts of extreme rainfall events and reduce the number of flood-related casualties in small stream basins.

The Schwarzschild solution of Einstein’s field equation comes in two variants, one for a single spherical mass (black hole), and one for the universe as a whole (in which dark energy prevails over matter). The cosmic variant represents a special form of expanding De-Sitter space (and is a good match with cosmic reality). In the cosmic variant, the Schwarzschild horizon of a black hole is replaced by the cosmic event horizon. The world-lines of escaping galaxies and also of photons is given by a function r(t) in which no square root of a negative number appears, so that the functionvalue is a real number even when it comes to r larger than the distance to the horizon. It turns out that no singularity exists beyond the cosmic event horizon. A surprising symmetry is thereby revealed (with the cosmic event-horizon functioning as a symmetry line). This symmetry comprises timereversals along world-lines, and the possibility of crossing the cosmic event horizon in both directions. As a consequence thereof, loop-shaped world lines of objects are within reach (similar to those in Gödel’s universe), even in the vicinity of planet Earth. As Gödel had correctly pointed out, loop-shaped world lines are proof of the static model of time, according to which present, past and future events occurring at the same spatial location are equally part of physical reality, not different from events occurring at the same time at different places. Kruskal-Szekeres charts do not obstruct any of these results. These charts have so far been used in an incorrect manner. When using them correctly, no singularity exists beyond event horizons, neither in the back-hole case, nor in the cosmic case. Doubts with regard to the existence of singularities, recently expressed by R. P. Kerr (2023), are thus proved to be justified.

The time-dependent behavior and long-term stability of deep-buried tunnels in soft rocks have received lots of considerations in tunnel engineering and allied sciences. To better explore and deepen the engineering application of rock creep, extensive research studies are still needed, although fruitful outcomes have already obtained in many related investigations. In this article, the Weilai Tunnel in China’s Guangxi province is studied taking its host rocks as the main research object. In fact, aiming at forecasting the time-varying deformation of this tunnel, a novel elasto-visco-plastic creep constitutive model with two variants is proposed, by exploiting the typical complex load-unload process of rock excavation. The model is well validated and good agreements are found with the relevant experimental data. Moreover, the time-dependent de-formation rules are properly established for the surrounding rocks, by designing two new closed-form solutions based on the proposed creep model and the Hoek-Brown criterion. The convergence deformations calculated from the closed-form solutions conform well to the on-site monitoring data. In only 27 days after excavation, the creep deformation of the Weilai tunnel overtakes 400 mm, which is enormous. To guarantee the long-term stability of this tunnel, a ro-bust support scheme and its long-term monitoring with appropriate remote sensors are strongly suggested.

Earthquakes are one of the most catastrophic natural phenomena. After an earthquake, earthquake reconnaissance enables effective recovery by collecting building damage data and other impacts. This paper aims to identify state-of-the-art data sources for building damage assessment and provide guidance for more efficient data collection. We have reviewed 38 articles that indicate the sources used by different authors to collect data related to damage and post-disaster recovery progress after earthquakes between 2014 and 2021. The current data collection methods have been grouped into seven categories: fieldwork or ground surveys, omnidirectional imagery (OD), terrestrial laser scanning (TLS), remote sensing (RS), crowdsourcing platforms, social media (SM) and closed-circuit television videos (CCTV). The selection of a particular data source or collection technique for earthquake reconnaissance includes different criteria depending on what questions are to be answered by this data. We conclude that modern reconnaissance missions can not rely on a single data source and that different data sources should complement each other, validate collected data, or systematically quantify the damage. The recent increase in the number of crowdsourcing and SM platforms used to source earthquake reconnaissance data demonstrates that this is likely to become an increasingly important source of data.

This study presents an exact solution to the free vibration analysis of a uniform Timoshenko beam, with a harmonic vibration being assumed. The Timoshenko beam theory covers cases associated with small deflections based on shear deformation and rotary inertia considerations. In this paper, a moment-shear force-circular frequency-curvature relationship was presented. The complete study was based on this relationship and closed-form expressions of efforts and deformations were derived. The free vibration response of single-span systems and spring-mass systems was analyzed; closed-form formulations of matrices expressing the boundary conditions were presented and the natural frequencies were determined by solving the eigenvalue problem. Systems with intermediate mass, spring, or spring-mass system were also analyzed. Furthermore, first-order dynamic stiffness matrices in local coordinates were derived. Finally, a second-order analysis of beams resting on an elastic Winkler foundation was conducted. The results obtained in this paper were in good agreement with those of other studies.

The abundant mechanical vibration energy in bridge road environment can be converted into electric energy by using the piezoelectric energy harvest technology, which could be an efficient way to provide energy required by the wireless sensor network in the bridge condition monitoring system. An autonomous energy harvesting system has been designed based on cantilever beams for sensing and acquiring the bridge vibration energy. After the analysis of the dynamic properties of the piezoelectric cantilever beam in the energy conversion, three kinds of interface circuits were compared through simulation and experimental results. It was shown that the VD interface circuit has less power loss. Furthermore, the proposed closed loop control method based on the VD circuit was simple, adaptive, and self-powered, which is suitable for the road energy harvesting application. Finally, the energy harvesting system based on VD circuit was realized with harvested power of around 0.8mW.

A simple line of reasoning, based on the most fundamental concepts of thermodynamics, yields some intriguing results for a better understanding of the processes occurring in the observable Universe. Gravitational mass must be continuously generated within an expanding thermodynamic system for this system to remain closed. The Second Law is a direct consequence of this production of mass. Simple expressions for the entropy and temperature of the Universe were obtained and the results agree well with observable values. Furthermore, it is demonstrated that the conservation laws within the Universe are independent of its energy density. Based on the solution for the quantum state of the Universe, it is conjectured that the Second Law is incomplete and must be complemented to a conservation law, which takes into account the growth of the amount of information within the Universe. Once the Second Law is complemented to a conservation law, the importance of mass generation within the Universe becomes well pronounced – not only gravitational effects play the role of an organising force, but also the amount of mass within the Universe defines both the amount of information within the Universe and the level of the Universe’s complexity.

Most astrophysicists today believe that the present universe was produced in a big bang. This article explores the big cycle of matter and energy in the universe, with the big bang as an important part of the cycle.The authors approve of the idea that the universe is gravitationally closed. That is, its average density is higher than the critical value. All the matter and radiation cannot fly out the closed universe.The 3k background radiation is a vast heat ocean in the closed universe, stable and eternal. It is not the afterglow of the thermal radiation of the decoupled fire ball, 380,000 years after the big bang, as many people believed so far. The big bang and the following big expansion drove the matter of more than 2×10¹² galaxies to the remote space. Their potential energies become higher and higher, while their huge kinetic energies that they derived from the big bang become smaller and smaller until drop down to zero. The galaxies will then return back one after another, passing the central region of the universe with tremendously great kinetic energies. They of course cannot all return back directly to their start point of the big bang and restore to the state of the original cosmic core. They will rush to pass the central region and fly to the other sides of the universe, and shuttle around the central part ceaselessly. From the big bang to the following expansion, to the numerous galaxies, to the more than 2×10²³ stars, and to the stars releasing huge nuclear energy due to their internal nuclear fusion each for about 10¹⁰ years, all these enormous processes are irreversible, resulting in enormous increase in entropy. These processes produce large amount of light and other radiations and pour them into the extremely vast heat ocean. These light and other radiations will also be shuttling ceaselessly in the vast heat ocean until, by their interaction with the rare dusts in the galaxies, they mingle into the 3K thermal radiation of the heat ocean. In all the galaxies, there are various black holes. Every black hole, since its birth, ceaselessly extracts the matter and radiation that approach it, and gets larger. In the above mentioned shuttling of all the galaxies, numerous stars and black holes in these galaxies have many chances to approach even meet each other. A black hole can annex other celestial bodies that it meets, including annex other black holes. All these processes carry on and on ceaselessly, resulting in the matter of these celestial bodies to concentrate again and again. The number of all the celestial bodies including the black holes reduces ceaselessly, and the mass of the survived black holes become larger, and their shuttling amplitudes become shorter. The larger black holes and the shorter amplitudes result in the rate of concentration of mass to be faster. Eventually, all the matter in the universe will be concentrated to form a tremendously large central black hole. The central black hole has an astonishingly large Schwarzschild sphere, absorbing the thermal radiation from the vast heat ocean very rapidly and ceaselessly until some threshold value of its internal energy is exceeded, and a new big bang breaks out. The black holes provide a way in the Universe to re-concentrate matter and energy again. Black holes are Maxwell’s demons in the Nature.

This literature review investigates the morphological and behavioral significance of the horns of Carnotaurus sastrei, a theropod dinosaur from the Late Cretaceous period. Through a comprehensive analysis of fossil specimens, comparative anatomy, and biomechanical modeling, this review explores the evolutionary adaptations and potential functions of these distinctive cranial structures. The horns of Carnotaurus are hypothesized to serve multiple roles, including species recognition, thermoregulation, and intraspecific combat. Our findings suggest that its cranial horns likely served a primary role in species recognition, intimidating rivals and signaling mating readiness. It also could have been used occasionally in head-butting contests, potentially as a display of dominance, but likely did not play a role in thermoregulation. Additionally, we examine the ecological context in which Carnotaurus lived, assessing how environmental factors could have influenced the development of such features. The implications of this study extend to broader discussions on the functional morphology and adaptive strategies of theropod dinosaurs, highlighting the complex relationship between form and function in the evolutionary history of predatory dinosaurs like Carnotaurus sastrei.

In this manuscript, we first introduce some properties of r-fuzzy soft α-open sets in fuzzy soft topological spaces based on the manuscript Aygunoglu et al. (Hacet. J. Math. Stat. 2014, 43, 193-208). In addition, we define the concepts of fuzzy soft α-closure (α-interior) operators, and investigate some properties of them. Furthermore, the concept of r-fuzzy soft α-connected sets is defined and characterized with help of fuzzy soft α-closure operators. Thereafter, we introduce and study the concepts of fuzzy soft almost (weakly) α-continuous mappings, which are weaker forms of fuzzy soft α-continuous mappings, and we discuss some properties of fuzzy soft α-continuity. Moreover, we establish that fuzzy soft α-continuity → fuzzy soft almost α-continuity → fuzzy soft weakly α-continuity, but the converse may not be true. It is also we show that the composition is fuzzy soft almost α-continuous mapping if, is fuzzy soft α-continuous mapping and is fuzzy soft almost continuous mapping. Finally, some new types of compactness via r-fuzzy soft α-open sets are defined, and the relationships between them are examined.

We dive into the axion-dilaton model within the supergravity framework, with a specific focus on the intricacies of domain wall construction and stability. Employing holographic vitrification, we unravel the dynamics of domain wall formation in gauge theories featur- ing periodic vacuum structures. Our model, incorporating a QCD-like axion term and a stabilizing dilaton, undergoes scrutiny for conductivity variations under weak disorder. The investigation reveals the model’s resilience, manifesting near-perfect conductivity under mild disorder conditions. However, the rigorous mathematical motivation for the holographic setup demands further elucidation. The scattered nature of our results prompts the neces- sity for a more systematic interpretation of QCD phenomena and conductivity transitions. This study contributes to the mathematical understanding of the axion-dilaton model’s be- havior, highlighting the imperative for a refined holographic framework and a more coherent interpretation of observed phenomena.

Abstract: This review addresses the complexities of type 1 diabetes (T1D)and its associated complications, with a par-ticular focus on diabetic retinopathy (DR). This review outlines the progression from non-proliferative to proliferative diabetic retinopathy and diabetic macular edema, highlighting the role of dysglycemia in the pathogenesis of these conditions. A significant portion of the review is devoted to technological advances in diabetes management, particu-larly the use of Hybrid Closed Loop systems (HCLS) and to the potential of open-source HCLS systems, which could be easily adapted to different patiens’needs using big data analytics and machine learning. Personalized HCLS algorithms that integrate factors such as patient lifestyle, dietary habits, and hormonal variations are highlighted as critical to reducing the incidence of diabetes-related complications and improving patient outcomes.

In the present study. At first, some properties of r-fuzzy soft β-closed sets are introduced on fuzzy soft topological spaces based on the paper Aygunoglu et al. (Hacet. J. Math. Stat. 2014, 43, 193-208). Also, we define the closure and interior operators with respect to the classes of r-fuzzy soft β-closed and r-fuzzy soft β-open sets, and investigate some of their properties. In addition, the concept of r-fuzzy soft β-connected sets is introduced and characterized with help of fuzzy soft β-closure operators. Thereafter, some properties of a fuzzy soft β-continuity are studied. Furthermore, we introduce and study the concepts of fuzzy soft almost (weakly) β-continuous functions, which are weaker forms of a fuzzy soft β-continuity. Also, the relationships between these classes of functions are specified with the help of some illustrative examples. Finally, we explore new types of fuzzy soft functions called, fuzzy soft β-irresolute (strongly β-irresolute, β-irresolute open, β-irresolute closed and β-irresolute homeomorphism) functions, and discuss some properties of them. Also, we show that fuzzy soft strongly β-irresolute → fuzzy soft β-irresolute → fuzzy soft β-continuity, but the converse may not be true.

We introduce the linear subgroup of volume-preserving diffeomorphism as the underlying symmetry to construct an action within the effective field theory framework and the Schwinger-Keldish formalism. The formulated action is posited to effectively incorporate dissipative effects into the Navier-Stokes equations.