Smallsats are becoming the predominant electro-optical Earth observation (EO) imaging platforms. While atmospheric correction of smallsat data enhances its utility, an established pathway to do so may constrain accuracy and utility. The alternative, Closed-form Method for Atmospheric Correction (CMAC), developed for smallsat application provides surface reflectance derived solely from scene statistics. In a prior paper, CMAC closely agreed with Land Surface Reflectance Code (LaSRC) software for correction of the four VNIR bands of Landsat-8/9 images for conditions of low to moderate atmospheric effect over quasi-invariant warehouse-industrial targets. Those results were accepted as surrogate surface reflectance to support analysis of CMAC and LaSRC reliability for surface reflectance retrieval in two contrasting environments: shortgrass prairie and barren desert. Reliability was defined and tested through a null hypothesis: the same top-of-atmosphere reflectance under the same atmospheric condition will provide the same estimate of surface reflectance. Evaluated against the prior surrogate surface reflectance, the results found decreasing error with increasing wavelength for both methods. From 58 comparisons across the four bands, LaSRC average absolute error ranged from 0.59% (NIR) to 50.30% (blue). CMAC error was well constrained from 0.01% (NIR) to 0.98% (blue) sustaining the null hypothesis for reliability.

The successful 2020 launch and 2021 landing of the National Aeronautics and Space Administration’s (NASA) Perseverance Mars rover initiated the first phase of the NASA and European Space Agency (ESA) Mars Sample Return (MSR) campaign. The goal of the MSR campaign is to collect scientifically interesting samples from the Martian surface and return them to Earth for further study in terrestrial laboratories. The MSR campaign consists of three major spacecraft components to accomplish this objective: the Perseverance Mars rover, the Sample Retrieval Lander (SRL) and the Earth Return Orbiter (ERO). Onboard the ERO spacecraft is the Capture, Containment and Return System (CCRS). CCRS will capture, process and return to Earth the samples that have been collected after they are launched into Mars orbit by the Mars Ascent Vehicle (MAV), which is delivered to Mars onboard the SRL. To facilitate the processing of the orbiting sample (OS) by CCRS we have designed and developed a vision system to determine the OS capture orientation. The vision system is comprised of two cameras sensitive to the visible portion of the electromagnetic spectrum and two illumination modules constructed from broadband light emitting diodes (LED). Vision system laboratory tests and physics-based optical simulations predict CCRS ground processing will be able to correctly identify the OS post-capture orientation using only a single vision system image that is transmitted to Earth from Mars orbit.

This paper investigates the relationship between public spaces and quality of life (QoL) for older adults, aiming to identify knowledge gaps within the context of population ageing and urbanization. Recognizing the growing importance of sustainable urban development, the research explores how cities can foster active ageing and improve QoL through accessible and inclusive public spaces. A scoping literature review identifies five key QoL domains for older adults: autonomy, meaningful activities, positive social relationships, leisure opportunities, and health. The review highlights areas requiring further investigation, including the interplay between environmental design and social connections, intergenerational perspectives on public space liveliness, the influence of context on QoL and the built environment, and the value of qualitative research in this field. By contributing to the understanding of QoL in relation to public spaces through the lens of Person-Environment fit theory, this study aims to inform urban design, landscape architecture, and policymaking in the creation of age-friendly communities with inclusive public spaces.

This paper explores the application of machine learning (ML) algorithms in predicting trends in the fixed bond market, where traditional analytical methods have proven inadequate. Focusing on various ML techniques such as supervised and unsupervised learning, neural networks, and deep learning, the study evaluates their effectiveness in forecasting market movements. It details a series of experiments in which different ML models are rigorously trained and tested against historical bond market data. The findings reveal that models employing time series analysis and advanced deep learning show marked potential in accurately predicting bond market trends. Additionally, the paper delves into the challenges and limitations inherent in these ML approaches, including data requirements and the risk of model overfitting. Finally, it proposes directions for future research, emphasizing the integration of ML into broader financial market analysis.

In order to tackle the issue of severe rocking phenomenon under seismic conditions in structures equipped with steel spring isolation bearings, this paper investigates a novel type of anti-rocking bearing. Firstly, the structural configuration and working principle of the novel anti-rocking bearing are introduced, and a design method for bearing parameters is proposed. Secondly, a finite element analysis model is established using SAP2000 software to conduct nonlinear dynamic time history analysis under seismic loading. The analysis results show that the structural arrangement of the novel anti-rocking bearing reduces both the vertical displacement difference and the rocking angle of the isolation layer. The bearing exhibits a certain level of anti-rocking effect, but it may cause significant tensile forces in some bearings, necessitating the installation of anti-tensile reinforcement. The effectiveness of the anti-rocking effect improves as the stiffness of the steel tension rod in the bearing increases; however, it also leads to higher maximum tension in individual bearings as well as the total tension in all bearings. For structures equipped with the novel anti-rocking bearing, the acceleration amplifies under most cases, with amplification coefficients ranging from 0.82 to 1.55. The performance of the novel anti-rocking bearing varies significantly for different seismic waves. The stiffness of the steel tension rod should be determined considering the reference pressure of the bearing and the maximum designed tension of the bearing. Through the finite element simulation of the bearing, the mechanical properties of the bearing are basically the same as the theoretical analysis results. For the cylinder and the joint bearing, certain structural measures need to be taken to ensure its strength and stiffness.

Previous research has proven that one of the fundamental requirements for ensuring increased profitability and economic competitiveness of offshore-based projects is co-locating different technologies within the same marine space. This paper presents a number of techno-feasibility analyses for floating offshore technologies for the Maltese Islands, located in the Central Mediterranean Sea. The first part compares the feasibility of offshore-based solar photovoltaic prices with those onshore, taking into consideration Malta’s land prices. The second part considers the use of a novel floating breakwater design that integrates energy storage. The breakwater is used to create a sheltered water area in deep waters for a multi-use marine park. Different revenue streams for the floating break water are considered, including renting the sheltered marine space out to operators of floating solar farms, aquaculture cages and vessel berthing facilities, and the provision of energy storage services. It is found that the combined income from the multiple revenue streams is still insufficient to justify the investment and that financially support from Government is essential to render the floating breakwaters viable.

Background. Escherichia coli commonly causes catheter-related bloodstream infection (C-RBSI) in specific populations. The differential time to positivity (DTTP) technique is the recommended conservative procedure for diagnosing C-RBSIs. Methods. We conducted a retrospective study of episodes in which E. coli was isolated from catheter lumens obtained using the DTTP technique. We analysed microbiological and clinical data based on the DTTP technique as either catheter colonization, C-RBSI, or non-C-RBSI. Results. We included 89 catheter blood cultures classified as follows: catheter colonization, 33.7%; C-RSBI, 9.0%; and non-C-RBSI, 57,3%. Catheter withdrawal was 15.7% without positive catheter-tip cultures. We found no statistically significant differences in catheter type, antibiotic treatment, or clinical outcome among groups, except for the frequency of catheter lock therapy or in the frequency of successful treatment. Mortality was associated with C-RBSI in only 1 patient. Conclusion. E. coli bacteremia diagnosed by the DTTP technique was non-catheter related in most patients. As the majority of the catheters were retained, E. coli bacteremia could not be microbiologically confirmed or ruled out as catheter related by catheter-tip culture. Future studies are needed to assess the profitability of the DTTP technique for diagnosing E. coli C-RBSIs..

Turbidity stands as a crucial indicator for assessing water quality, and while turbidity sensors exist their high cost prohibit their extensive use. In this paper, we introduce an innovative turbidity sensor, and it is the first low-cost turbidity sensor which is designed specifically for long-term stormwater in-field monitoring. Its low cost ($23.50 USD), enables the implementation of high spatial resolution monitoring schemes. The sensor design is available under open hardware and open-source licences, and the 3D-printed sensor housing is free to modify based on different monitoring purposes and ambient conditions. The sensor was tested both in the laboratory and in the field. The laboratory results show a strong linear relationship (R2 > 0.99) between the sensor readings and the commercial hand-held turbidimeter (Thermo Scientific AQ4500) results of the solution. In the field, the low-cost sensor measurements were statistically significantly correlated (p < 0.01) to a standard high-cost commercial turbidity sensor (GreenSpan TS-1000). Biofouling and drifting issues were also analysed after the sensors were deployed in the field for more than 6 months, showing both biofouling and drift occur during monitoring. Nonetheless, in terms of maintenance requirements, the low-cost sensor exhibited similar needs compared to the Green-Span sensor.

Time, traditionally viewed as a linear, non-dynamic parameter, is re-envisioned in this study as a Hyperdimensional concept. This paper conducts a cross-disciplinary examination, critically analysing the conceptualization of time in classical mechanics, quantum mechanics, and cosmology to propose a ground breaking reconceptualisation that extends beyond conventional frameworks. In classical mechanics, time is perceived as an absolute, continuously progressing backdrop, largely independent of events. Quantum mechanics treats time as a static parameter that does not influence quantum states but provides a framework for their evolution. In cosmology, time is considered a dimension that emerges from the Big Bang and serves as a measure for the universe's expansion, yet it does not interact with the structural dynamics of the cosmos. Challenging the transformative insights of Einstein’s relativity, which merges time with spatial dimensions under extreme conditions, we advocate for a perspective that views time as a Hyperdimensional and universal constant. This perspective posits that time, despite its unique and intrinsic properties, does not dynamically interact with or alter physical phenomena. Instead, it underpins our understanding of phenomena across different scales—from the minutiae of quantum states to the macroscopic dynamics of cosmology—without direct causation or change. A critical examination of time dilation and relativistic assumptions reveals significant discrepancies in traditional interpretations, particularly in how they are applied across different physical contexts. Our findings challenge the uniform applicability of time dilation, suggesting that observed phenomena often attributed to relativistic effects might better be explained through non-relativistic mechanisms such as phase shifts or changes in wavelength rather than temporal dilation. By synthesizing insights from various scientific domains, we advocate for a unified theory that recognizes time as a fundamental, universal dimension that is conceptual and non-interactive. Our goal is to bridge existing gaps between diverse scientific interpretations and promote a more integrated, profound understanding of time's autonomous and intrinsic nature.

Speech emotion recognition (SER) is a technology that can be applied in distance education to analyze speech patterns and evaluate speakers’ emotional states in real-time. It provides valuable insights and can be used to enhance the learning experience by enabling the assessment of instructors’ emotional stability, a factor that significantly impacts information delivery effectiveness. Students demonstrate different engagement levels during learning activities, and assessing this engagement is an important aspect of controlling the learning process and improving e-learning systems. An important aspect that may influence student engagement is the emotional states of their instructors. Accordingly, this research uses deep learning techniques to create an automated system for recognizing instructors’ emotions in their speech when delivering distance learning. This methodology entails integrating Transformer, convolutional neural network, and long short-term memory architectures into an ensemble to enhance SER. Feature extraction from audio data used Mel-frequency cepstral coefficients, chroma, Mel spectrogram, zero crossing rate, spectral contrast, centroid, bandwidth, roll-off, and root-mean square, with subsequent optimization processes adding noise to, conducting time stretching, and shifting the audio data. Notably, several Transformer blocks were incorporated, and a multi-head self-attention mechanism was employed to identify the relationships between the input sequence segments. The pre-processing and data augmentation methodologies significantly enhanced the precision of the results in that the model achieved accuracy rates of 96.3%, 99.86%, 96.5%, and 85.3% on the Ryerson Audio-Visual Database of Emotional Speech and Song, Berlin Database of Emotional Speech, Surrey Audio-Visual Expressed Emotion, and Interactive Emotional Dyadic Motion Capture datasets. Furthermore, it achieved 83% accuracy on another dataset created for this research—the Saudi Higher Education Instructor Emotions dataset. The results demonstrate this model’s considerable accuracy in detecting emotions in speech data across different languages and datasets.

A spatial turn is increasingly being recognised across education, the humanities and social sciences to critique Western Cartesian assumptions treating space as either empty or a diametric opposition bringing dualistic splits between reason/emotion, and mind/body. Bacon’s vision of human subjugation of nature as a tool for human progress is examined as a diametric spatial projection, where humans are above and apart from nature, in a mirror image inverted symmetry of above/below hierarchy and side-by-side assumed separation as diametric space. Building on an interdisciplinary synthesis between an aspect of the structural anthropology of Lévi-Strauss, De Beauvoir’s othering and Bronfenbrenner’s social-ecological systems in psychology, allied with a Heideggerian critique of being as needing a mode of ‘being alongside the world’, a shift in experiential and conceptual space is proposed in this conceptual review article for education. This shift is towards a framework of concentric spatial systems of sustainability. Concentric relational spaces of assumed connection and relative openness and away from diametric spaces of splitting and closure have been developed recently for sustainability concerns regarding inclusion in education. This article goes further to interrogate systems of concentric relational space for belonging with and encountering the natural world for environmental sustainability.

This paper introduces a novel architecture—bidirectional optical neural network (BONN)—for providing backward connections alongside forward connections in artificial neural networks (ANNs). BONN incorporates laser diodes and photodiodes and exploits the properties of Köhler illumination to establish optical channels for backward directions. Thus, it has bidirectional functionality that is crucial for algorithms such as the backpropagation algorithm. BONN has a scaling limit of 96 × 96 for input and output arrays, and a throughput of 8.5 × 1015 MAC/s. While BONN's throughput may rise with additional layers for continuous input, limitations emerge in the backpropagation algorithm as its throughput doesn't scale with layer count. Successful BONN-based implementation of the backpropagation algorithm requires the development of fast spatial light modulator to accommodate frequent data flow changes. A two-mirror-like BONN and its cascaded extension are alternatives for multilayer emulation, and they help save hardware space and increase the parallel throughput for inference. An investigation into the application of the clustering technique to BONN revealed its potential to help overcome scaling limits and to provide full interconnections for backward directions between doubled input and output ports. BONN's bidirectional nature holds promise for enhancing supervised learning in ANNs and increasing hardware compactness.

Sepsis is a life-threatening syndrome triggered by infection and accompanied by high mortality, with antimicrobial resistances (AMRs) further escalating clinical challenges. Rapid and reliable detection of causative pathogens and AMRs are key factors for fast and appropriate treatment, in order to improve outcome in septic patients. However, current sepsis diagnostics based on blood culture is limited by low sensitivity and specificity while current molecular approaches fail to enter clinical routine. Therefore, we developed a Suppression PCR-based selective enrichment sequencing approach (SUPSETS), providing a molecular method combining multiplex suppression PCR with Nanopore sequencing to identify most common sepsis-causative pathogens and AMRs using plasma cell-free DNA. Applying only 1 mL of plasma, we target eight pathogens across three kingdoms and ten AMRs in a proof-of-concept study. SUPSETS was successfully tested on first ten clinical samples and revealed comparable results to clinical metagenomics while clearly outperforming blood culture. Several clinically relevant AMRs could be detected additionally. Furthermore, SUPSETS provided first pathogen and AMR-specific sequencing reads within minutes of starting sequencing, thereby potentially decreasing time to results to 11 - 13 hours and suggesting diagnostic potential in sepsis.

The Polyurethane (PU) mixture is a high−performance engineering material with different dynamic properties compared to a hot−mixed asphalt mixture (HMA). This paper analyzed whether the Kramers−Kronig (K−K) relation and thermo−rheological simple properties were applicable to the PU mixture. Based on the result discussion, the PU mixture exhibited thermo−rheological simple properties within the test conditions. The time−temperature superposition principle (TTSP) was applicable for the PU mixture to construct the dynamic modulus master curve using the standard logistic Sigmoidal (SLS) model, the generalized logistic sigmoidal (GLS) model, and the Havriliak−Negami (HN) model. The Hilbert integral transformed SLS and GLS models for the phase angle can accurately fit the measured phase angle data with newly fitted shift factors and predict the phase angle within the viscoelastic range. The Core−Core and black space diagrams both displayed single continuous smooth curves, which can be utilized to characterize the viscoelastic property of the PU mixture. The K−K relation is applicable for the PU mixture to obtain the phase angle master curve model, storage modulus, and loss modulus from the complex modulus test results. The phase angle of the PU mixture cannot be derived from the dynamic modulus data and currently needs to be derived from the laboratory measurement.

Special and general relativity (SR/GR) describe nature “subjectively”, that is, from the perspective of just one observer at a time (one class of observers, to be exact). Mathematically, SR/GR are correct. I show: (1) Physically, SR/GR have an issue. There is always just one active perspective—despite the Lorentz covariance of SR, the general covariance of GR, and coordinate-free formulations. This is a fact because SR/GR do not consider a unique 4D vector “flow of proper time” τ for each object. The vector is only disclosed by Euclidean relativity (ER). Because of this constraint, SR/GR lack a holistic view of nature. The issue shows itself in mysteries. Some mysteries (time’s arrow, Hubble tension) are solved by ER. Other mysteries (accelerating expansion of space, entanglement) require concepts (dark energy, non-locality) that are obsolete in ER. Still, SR/GR work well for observers because the Lorentz factor and gravitational time dilation are correct. (2) ER describes nature “objectively”, that is, from the perspectives of all objects at once. An object’s (!) proper space d₁, d₂, d₃ and proper time τ span 4D Euclidean spacetime (ES), where d₁, d₂, d₃ and d₄ = cτ are treated the same. ER provides a holistic view because ES is absolute. An observer’s reality is created by projecting ES orthogonally to his proper space and to his proper time. The SO(4) symmetry of ES is incompatible with waves. This is fine because waves and particles are subjective concepts construed by observers. I conclude: The master reality ES (described by ER) is beyond each observer’s reality (described by SR/GR).

China is experiencing rapid urbanization. The focus on health issues has shifted from the treatment of diseases to passive or active prevention. Diseases caused by the deterioration of the urban environment, such as cardiovascular disease, diabetes, obesity and other chronic diseases and mental illness, have gradually become the main threat to public health. Studies have confirmed that urban green spaces (UGS) can help residents relieve mental stress, improve mood, reduce mental fatigue and restore attention, which has a positive effect on people's physical and mental health. In this study, the relationship between the quantity and quality factors of UGS and the physical and mental health of urban residents in Xihu District of Hangzhou is examined, and on this basis, UGS design strategies are proposed to promote the physical and mental health of residents. This study is of great significance for the future construction of UGS that are beneficial to the health of residents and the promotion of a healthy China and healthy city construction.

The theories of Evolution and Big Bang have brought a major impact upon the scientific and societal perception upon the origins, abilities and roles of mankind on Earth. It is conclusively evident that Mother Nature and the physical realm is autonomous and all phenomena in the world occur without an imposition against the “free will” of such events and patterns. Nevertheless, this extent of freedom does not imply that life on Earth represents an accident and has no purpose. By careful analysis of ancient religious texts, it can be suggested even otherwise, that it is especially free will that is offered as a gift from outside of the physical dimensions of existence, with the purpose of a continuous edification and improvement of the overall life conditions and of the human perception. It may be that the multi-generational focus on improvement and progress have been misattributed as a long-term evolution of species, that humans came from animal ancestors and that there is a blurred line associating humans with animals. Furthermore, it may be that scientists based their suggestions that no outside Creator would have brought the Earth into existence on physical perspectives, when the extra-dimensional process of Creation implies that all elements of the physical existence undergo a process of Creation from the outside, where time, space and physical matter do not exist, in spite of such elements possibly reflecting unseen elements of the meta-physical world. Finally, there is the following example that deserves attention within the scientific community; just because all living cells - human, animal and plant - contain DNA chromosomes, ribosomes, mitochondria and a plasma membrane, it does not indicate that humans are animals, just as this does not indicate that plants are animals. In Science, there is a golden statement, that correlation does not imply causation. This example is in complete agreement with the verses of the Book of Genesis in the Holy Scriptures regarding the origins of life; namely, that animals could have been created by an Author of all life on Earth so that man would experience companionship. An improved scientific perception of the timeline of life on Earth may be reached via an approach that combines molecular biology with quantum physics, given that the three layers of Science - Biology, Chemistry and Physics - together with their foundational layer of Mathematics, are in fact situated in a relationship of complete harmony.

The present study analyzed the effect of temperature, pH, retention time, pretreatment and mixing ratio on the anerobic digestion process. The parameters during the anaerobic co digestion of cow manure and food waste were then optimized using the Taguchi experimental design method. ANOVA is carried out to find the significant parameters which influence the biogas production. Experimental tests were carried out at laboratory scale reactors kept at different temperatures (28 °C, 35 °C, and 50 °C). The specific methanogenic Performance (SMP) during anerobic digestion at higher temperatures was characterized with the analysis of acetate, propionate, butyrate, hydrogen, glucose, and formate. The improvement of biogas production with different pre-treatment i.e., ultrasonic, autoclave, and microwave techniques also analysed. The results showed that reactor that maintained at 35 °C showed the highest biogas production. While the reactor that maintained at lower temperature (28 °C) produced the lower volume of biogas. As the retention time increases, the amount of biogas produced increases. Methanogenic activities of microorganisms reduced at higher temperature conditions (65 °C). Biogas production increased by 28.1%, 20.23%, and 13.27 % when the of substrates treated with ultrasonic, autoclave, and microwave, respectively, compared to the untreated substrate. The optimized condition for the highest biogas production during anaerobic co digestion of food waste and cow manure is temperature of 35 °C, pH of 7 and mixing ratio (CM: FW=1.5:0.5). ANOVA showed that temperature is the most important input parameter affecting biogas production, followed by mixing ratio.

Time series forecasting has been a challenging area in the field of Artificial Intel-ligence. Various approaches such as linear Neural Networks, Recurrent Linear Neural Networks, Convolutional Neural Networks and recently Transformers have been attempted for the time series forecasting domain. Although, Trans-former-based architectures have been outstanding in the Natural Language Pro-cessing domain, especially in autoregressive language modeling, the initial at-tempts to use transformers in the time series arena have met with mixed success. One of the recent papers demonstrated that modeling the multi-variate time se-ries problem as independent channels on a transformer architecture produced lower mean square and mean absolute errors on benchmarks, however, another recent paper claimed that a simple linear neural network out-performs previous approaches including transformer-based designs. We investigate this paradox in detail comparing the linear Neural Network and Transformer based designs, provide insights to why a certain approach may be better for a particular type of problem. We also improve upon the recently proposed simple linear Neural Network based architecture by using dual pipelines with batch normalization and reversible instance normalization. Our enhanced architecture outperforms all existing architectures for time series forecasting on majority of the popular benchmarks.

In the field of railroad safety, effective detection of surface cracks is critical, necessitating reliable, high-speed non-destructive testing (NDT) methods. This study introduces a hybrid Eddy Current Testing (ECT) probe, specifically engineered for railroad inspection, to address the common issue of ’lift-off noise’ due to varying distances between the probe and test material. Unlike traditional ECT methods, this probe integrates transmit and differential receiver coils, aiming to enhance detection sensitivity and minimize lift-off impact. The study optimizes ECT probes employing different driver coils, emphasizing three main objectives: a) quantitatively evaluating each probe using signal- to-noise ratio (SNR) and outlining a real-time data processing algorithm based on SNR methodology; b) exploring the frequency range proximal to the electrical resonance of the receiver coil; c) examining sensitivity variations across varying lift-off distances. The experimental outcomes indicate that the newly designed probe with figure 8-shape driver coil significantly improves sensitivity in detecting surface cracks on railroads. It achieves an impressive SNR exceeding 100 for defects with minimal dimensions of 1 mm in width and depth. Simulation results closely align with experimental findings, validating the investigation of optimal operational frequency and lift-off distance for selected probe performance, determined to be 0.3 MHz and 0.5 mm, respectively. The realization of this project would lead to notable advancements in enhancing railroad safety by improving crack detection efficiency.

Research has shown that emotional states may influence the subjective experience of time. The present study involved 111 healthy adult participants and examined the impact of emotional stimuli on time perception, using a time estimation task with four conditions: in one of the conditions, participants estimated the exposure time of a black screen, wherein the duration could vary be-tween 2 to 7 s (condition without emotional interference); in the other conditions, participants es-timated the exposure time (also ranging from 2 to 7 s) of images that would induce pleasant, un-pleasant, or neutral emotions, to which participants were instructed to focus their attention (pleasant, unpleasant, or neutral emotions). The results showed that participants estimated “shorter” time intervals (underestimation) for pleasant and unpleasant images compared to the condition without interference, but no significant differences were found between the neutral condition and the condition without interference. It is suggested that increased attention to an ex-ternal stimuli, regardless of its emotional valence, produces an underestimated perception of time.

In the last decade Electromagnetic Induction (EMI) measurements have been increasingly used for investigating the soil salinization caused by the use of brackish or saline water as irrigation source. EMI measurements proved to be a powerful tool for providing spatial information of the investigated soil because of the strict correlation between the output geophysical parameter, i.e. the electrical conductivity, to soil moisture and salinity. In addition, their non-invasive nature and their capability to collect a high number of data over broad areas and in relatively short time, makes these measurements attractive for monitoring flow and transport dynamics, otherwise undetectable with conventional measurements. In an experimental field, EMI measurements were collected during the growth season of the tomato, irrigated with three different irrigation strategies. The data were collected over three months in a time-lapse mode in order to visualize changes in electrical conductivity to be associated with soil salinity. A rigorous time-lapse inversion procedure has been set for modeling the soil salinization induced by brackish irrigation water.

P versus NP is considered as one of the most fundamental open problems in computer science. This consists in knowing the answer of the following question: Is P equal to NP? It was essentially mentioned in 1955 from a letter written by John Nash to the United States National Security Agency. However, a precise statement of the P versus NP problem was introduced independently by Stephen Cook and Leonid Levin. Since that date, all efforts to find a proof for this problem have failed. Another major complexity class is NP-complete. It is well-known that P is equal to NP under the assumption of the existence of a polynomial time algorithm for some NP-complete. We show that the Monotone Weighted Xor 2-satisfiability problem (MWX2SAT) is NP-complete and P at the same time. Certainly, we make a polynomial time reduction from every directed graph and positive integer k in the K-CLOSURE problem to an instance of MWX2SAT. In this way, we show that MWX2SAT is also an NP-complete problem. Moreover, we create and implement a polynomial time algorithm which decides the instances of MWX2SAT. Consequently, we prove that P = NP.

The paper primarily demonstrates that the three internal triangles formed by connecting any point on a midsegment with the vertices of a generic triangle satisfy the geometric Proof of the Pythagorean theorem in Euclidean geometry. Moreover, this study elucidates the Pythagorean relationships inherent within three-dimensional geometric constructs resulting from the arrangement of three-dimensional spatial triangles. This geometric relationship, akin to a generalized extension of the Pythagorean theorem, unveils a unique spatial region characterized by this harmonious area interrelation among triangles.

This article begins with exploring fundamental limits in the universe. It examines key principles, such as the uniformity of physical laws and Energy conservation, that lead to maximum speed, locality, and maximum density. These universal limits govern physical phenomena, leading to very interesting results.I demonstrate that quarks and leptons comprise smaller entities named "Quantum Black Holes." These Quantum black holes are relativistically rotating miniature charged black holes consisting of a single core at the highest possible density. Quantum black holes are the only structures small enough in space-time capable of keeping all charges quantized (including gravitational charges.)By the end of the article, I prove that Quantum black holes explain the deficiencies of SM. They facilitate explanations of quantized gravity, the nature of Luminous and dark Matter, establishing the Mass, size, and (quantized) charges quantities of elementary particles, the nature of neutrino oscillations, and more. Elementary particles release their Energy outward, altering the curvature of nearby space-time and providing new insights into the nature of space-time curvature change. With this understanding, we can characterize movements and processes in local space-time using five sets of equations simultaneously: four representing the four charge types and one representing Dark Matter.

The aim of the study was to assess the impact of two lengths of Nordic walking (NW) training interventions combined with time restricted eating (TRE) on improving body composition parameters, lipid profile, and levels of selected adipokines in women with disrupted body mass. Overweight and obese women (n=55, age: 21-85) were recruited. Four groups were selected: 6 weeks (SG6, n=13) and 12 weeks intervention (SG12, n=13); and two control groups: CON6 (n=13); and CON12 (n=13). The training sessions took place 3 times a week (60 minutes each) and were conducted outdoor under the supervision of professional coach. The training intensity was determined individually. The extended NW program combined with TRE induced a significant weight reduction in SG12 by 1.96 kg (p=0.010) and fat tissue by 1.64 kg (p=0.05). The proposed interventions did not affect LBM, TBW [kg], VFA and lipid profile. The LDL/HDL ratio changed with small size effect. Leptin concentration differed between groups (p=0.006), but not over time. For resistin, the differentiating factor was time (p=0.019, with lower results observed after the intervention). The change in leptin concentration was negatively correlated with its baseline concentration. Extended to 12 weeks, this intervention allows for an improvement in body composition. Neither 6 nor 12 weeks of training and fasting affected the lipoprotein profile.

This paper is devoted to the study of multi-dimensional integral transform with Fox H-function in the kernel in weighted spaces integrable functions in the domain R+n with positive coordinates. Mapping properties such as the boundedness, the range, the representations of the considered transformation are established.

Differences between the quantum mechanical and relativistic concepts of time observed in GPS satellites are accounted for by applying the equivalence principle to the transitioning electron of an atomic clock. It allows a differential equation of motion to be derived for the electron in the Minkowski space between electron shells. Using Hamilton’s principle we transform the differential equation relativistically into an integral equation of motion, the time integral of a Lagrangian. This newly derived equation accounts for the abstract mathematics of the more familiar non-relativistic model by means of a physical interpretation. Abstract rotations in Hilbert space are replaced by the rotations of real particle field geometries in Minkowski space. Because the properties of energy are universal the same equations are then used to describe the field geometry of galaxies despite vast differences in lifetime. They reveal a symmetry between the electromagnetic fields of atoms and the gravitational fields of galaxies due to similarities in the exchange of energy by radial and transverse fields. Our analysis reveals that the conjugate variables energy and time permit differences between atomic and galactic structure to be compared in a more intuitive way than by means of the differential equations of motion which use the conjugate variables position and momentum.

Space-based gravitational wave detection is extremely sensitive to disturbances. The Keplerian configuration cannot accurately reflect the variations in spacecraft configuration. Planetary gravitational disturbances are one of the main sources. Numerical simulation is an effective method to investigate the impact of perturbation on spacecraft orbits. This study shows that, in the context of the Taiji project, Earth’s gravity is an essential factor in the change in heliocentric formation configuration, contributing to the relative acceleration between spacecrafts in the order of O(10−6)m·s−2. Considering 00:00:00 on October 27, 2032 as the initial orbiting moment, under the influence of Earth’s gravitational perturbation, the maximum relative change in armlengths and variation rates of armlengths for Taiji is 1.6×105km, 32m·s−1 respectively, compared with the unperturbed Keplerian orbit. Additionally, by considering the gravitational perturbations of Venus and Jupiter, the armlength and relative velocity for Taiji are reduced by 16.01% and 17.45%, respectively, compared with when only considering that of Earth. The maximum amplitude of the formation motion indicator changes with the orbit entry time. Results show that the relative velocity increase between the spacecrafts is minimal when the initial orbital moment occurs in July. Moreover, the numerical simulation results are inconsistent when using different ephemerises. The differences between ephemeris DE440 and DE430 are smaller than those between DE440 and DE421.

The social- and self-directed behaviours of two golden lion tamarins (Leontopithecus rosalia) was investigated while having residence in the tropical house of Aalborg Zoo, Denmark. The behaviour of the female had been distinct from the male since 2018. Despite several diagnostic examinations and medicinal treatments, the cause of the aberrant and apparently stereotypical behavioural patterns remained undetermined, which initiated this study. The pair were recorded throughout a predetermined observation period and these recordings were analysed to illuminate the behaviours of the individuals. The results showed that there were differences in the type, frequency, and durations of both social- and self-directed behaviours between the sick female and the healthy male. The female expressed both social- and self-directed behaviours more frequently and for longer durations, while the male were more socially reserved and did not engage in social behaviours as frequently. Furthermore, subsequent necropsy of the female revealed uro-genital disease.

Amid escalating urbanization, devising rational commercial space layouts is a critical challenge. Leveraging machine learning, this study uses a Back-propagation (BP) neural network to optimize commercial spaces in Weinan City's central urban area. The results indicate an increased number of commercial facilities with a trend of multi-centered agglomeration and outward expansion. Based on these findings, we propose a strategic framework for rational commercial space development emphasizing aggregation centers, development axes, and spatial guidelines. This strategy provides valuable insights for urban planners in small and medium-sized cities in the Yellow River Basin and metropolitan areas, ultimately showcasing the power of machine learning in enhancing urban planning.

The physical roots, interpretation, controversies and precise meaning of the Landauer Principle are surveyed. Landauer's principle is a physical principle pertaining to the lower theoretical limit of energy consumption of computation. It states that an irreversible change in information stored in a computer, such as merging two computational paths, dissipates a minimum amount of heat kBTln2 per a bit of information to its surrounding. The Landauer Principle is discussed in the context of fundamental physical limiting principles, such as the Abbe diffraction limit, the Margolus-Levitin limit and the Bekenstein limit. Synthesis of the Landauer bound with the Abbe, Margolus-Levitin limit and Bekenstein limits yields the minimal time of computation, which scales as τmin~hkBT. Decrease in a temperature of a thermal bath will decrease the energy consumption of a single computation, but, in parallel, it will slow the computation. The Landauer principle bridges between John Archibald Wheeler “it from bit” paradigm and thermodynamics. Experimental verifications of the Landauer Principle are surveyed. Interrelation between thermodynamic and logical irreversibility is addressed. Generalization of the Landauer principle to the quantum and non-equilibrium systems is addressed. Landauer Principle represents the powerful heuristic principle bridging the physics, information theory and computer engineering.

The application of space robotic manipulators and heightened autonomy for ios represents a paramount pursuit for leading space agencies, given the substantial threat posed by space debris to operational satellites and forthcoming space endeavors. This work presents a guidance algorithm based on drl to solve for the space manipulator path-planning during the motion synchronization phase with the mission target. The goal is the trajectory generation and control of a spacecraft equipped with a 7-dof robotic manipulator, such that its end effector remains stationary with respect to the target point of capture. The ppo drl algorithm is used to optimize the manipulator’s guidance law, and the autonomous agent generates the desired joints rates of the robotic arm, which are then integrated and passed to a model-based feedback linearization controller. The agent is first trained to optimize its guidance policy and then tested extensively to validate the results against a simulated environment representing the motion synchronization scenario of an ios mission.

Multivariate Time Series Classification (MTSC) is one of most important tasks in time series analysis, aiding in activities such as human motion recognition and medical diagnostics. Existing methods for MTSC do not explicitly model temporal differences and generalize the idea of temporal difference into a efficient temporal module. Additionally, existing methods are not yet able to capture cross-variable relationships well during network training. As a result, they are unable to achieve convincing feature representation, leading to suboptimal classification accuracy. In this paper, we propose a novel MTSC model called Temporal Difference and Cross-variate Fusion Network (TDCFN), which integrates a two-stream differential LSTM network and a cross-variate feature extraction network to enhance feature representation. TDCFN achieves superior classification accuracy by capturing dynamic temporal evolution and inter-variable relationships. The experimental results show that TDCFN can achieve competitive performance with state-of-the-art multivariate time series classification approaches.

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

A difficult open problem that has never been fully resolved in the literature to date is the behaviour of the (TDCDP) third approximation. As a giant step towards modern control theory, this cutting-edge paper will advance control theory and other relevant inter-disciplinary subjects. Because control theory is important in industry and engineering, this study will be especially beneficial to anyone working in these disciplines who wish to understand more about recent advances in control theory settings. In contrast, the wealth of applications of Fokker Planck Kolmogorov (FPK) equations numerous disciplines As a result, the study instantly gains more taste and credibility. At the end of the paper, there are several challenging open problems, some concluding remarks, and recommendations for further investigation.

Droplet-based microfluidics has revolutionized numerous fields such as biomedical research, pharmaceuticals, drug discovery, food engineering, flow chemistry, and cosmetics. This paper presents a comprehensive study focusing on the detection and characterization of droplets with volumes in the nanoliter range. Leveraging the precise control of minute liquid volumes, we introduced a novel spectroscopic On-Chip microsensor equipped with integrated microfluidic channels for droplet generation, characterization, and sensing, simultaneously. The microsensor, designed with Interdigitated-Ring-Shaped Electrodes (IRSE) and seamlessly integrated with microfluidic channels, offers enhanced capacitance and impedance signal amplitudes, reproducibility, and reliability in droplet analysis. We were able to make analyses of droplets length in the range 1.0-6.0 mm, velocity 0.66-2.51 mm/s, droplet volume 1.07nL-113.46nL. Experimental results demonstrated that the microsensor's has a great performance in terms of droplet size, velocity, and length, with a significant signal amplitude of capacitance and impedance, and real-time detection capabilities, thereby highlighting its potential for facilitating microcapsule reactions and enabling on-site real-time detection for chemical and biosensor analyses on-chip.

In this work, a novel approach is presented for the multivariate prediction of hydrological variables, employing a specialized type of recurrent neural network (RNN) known as the long-term memory network (LSTM).The central objective is to develop a flood prediction model using data collected from two hydrological stations situated along the Atrato River in the Choc´o Department, Colombia. The interconnected variables of water level, water flow, and water precipitation are analyzed in this model to enhance flood prediction accuracy. The LSTM model, integrated into an RNN structure, is designed to capture the complex dynamics and cross-correlations inherent in these hydrological variables. Validation involves a comparison with linear and nonlinear Nonlinear AutoRegressive with eXogenous input (NARX) models, considering factors such as estimation error and computational time. Additionally, the study conducts further analysis for water level prediction under two scenarios: utilizing only outflow and inflow measurements or predicting outflow alongside measuring inflow, with the objective of utilizing the proposed approach as a flood early warning system. † This article is a revised and expanded version of a paper entitled Multivariable NARX based Neural Networks Models for Short-term Water Level Forecasting, which was presented at International Conference on Time Series and Forecasting (ITISE-2023), Gran Canaria, Spain, 12th-14th July, 2023.

This study investigates the mean annual water temperature trends at the confluence of the Sava and Danube Rivers, along with air temperature trends at the Belgrade meteorological station, spanning from 1956 to 2020. Results reveal a consistent increase in temperature across all three measuring stations, with the Danube experiencing a rise of 0.34°C/10 years, the Sava at 0.44°C/10 years, and Belgrade's air temperature increasing by 0.39°C/10 years. Employing the RAPS method, sharp rises in water temperature were pinpointed in 1989 for the Sava and 1990 for the Danube, while Belgrade's air temperature surge began in 1998. The highest intensity of air temperature increase within the recent period (1998-2020) was observed at the Belgrade observatory, reaching 0.76°C/10 years. Notably, the Sava exhibited a faster increase in water temperature over the last thirty years compared to the Danube. August marked the peak average water temperature for both rivers, while July recorded the highest average air temperature in Belgrade. Despite differing flow rates, both rivers exhibit similar hydrological regimes, with maximum flows occurring in April and minimum flows in August for the Sava, and October for the Danube. Seasonal temperature increases were most pronounced in summer, notably in August, with the smallest rises occurring during cold periods. Additionally, an inverse proportional relationship between mean annual water temperatures and discharges was observed at both river stations.

As new vaccines reduce P. falciparum (Pf) cases, clinicians can focus on rescuing more children with cerebral malaria (CM). Adjunctive “therapeutically-rational exchange transfusion” (T-REX) refers to using special “Pf-resistant” donor red blood cells (RBCs) that secrete nano-sized RBC extracellular vesicles (EVs). Can some RBC EVs rapidly dislodge Pf-infected RBCs (iRBCs) sequestered in blood vessels and reduce inflammation? Does post-exchange “rebound parasitemia” reflect sequestration-reversal? We reviewed case-reports, EV and liposome studies, expert perspectives, and time-sequence data. In the AQUAMAT study, median coma-recovery time was 20 hours for artesunate. In contrast, a CM patient treated with type-O T-REX quickly began speaking (during the procedure). For other rapid-recovery CM patients, donor RBC variables had not been specified. Despite rapid Pf-killing, drugs need 20 hours to substantially reduce iRBC cytoadhesion while EVs can selectively bind distant inflamed tissues within 15 minutes. RBCs stressed by blood-bank storage and Pf infection secrete EVs. Post-exchange “rebound parasitemia” can occur within 60 minutes and may reflect release of sequestered iRBCs. Sequestration-reversal can be assessed by monitoring Pf parasitemia and total Pf biomass. New data suggest clinicians, working with transfusion- and laboratory-medicine physicians, can, and should, assess T-REX options and publish their findings to help clarify how RBC EVs may serve as therapeutic “decoy ligands.”

Based on our recent thermodynamic formulation of the Friedmann equation, we demon- strate how the age of the universe must be approximately 14.6 billion years. This is about 800 million years older than predicted by the Λ-CDM model and therefore greatly alleviates the early galaxy formation problem.

Electrospun ultrathin fibers based on binary compositions of polylactide (PLA) and poly(ε-caprolactone) (PCL) with different ratios of polymer components from 0/100 to 100/0 wt. % were studied. Using a combination of thermal (DSC) and relaxation (EPR) measurements, the effect of biopolymers content on the characteristics of the crystal structure of PLA and PCL and the diffusive rotational mobility of the stable TEMPO radical in the amorphous regions of PLA/PCL compositions was shown. It was revealed that after PLA and PCL blending, significant changes in the degree of crystallinity of PLA, PCL segmental mobility, sorption capacity of the radical as well as activation energy of rotational diffusion in the amorphous regions of PLA/PCL composition are observed. The characteristic region of biopolymers’ composition from 50/50 to 30/70 % PLA/PCL blends ratio was found, where the inversion transition of PLA from dispersive medium to dispersive phase where an inversion transition is assumed when the continuous medium of the PLA transforms into a discrete phase. The performed studies made it possible for the first time to carry out a comprehensive analysis of the effect of the system component ratio on the structural and dynamic characteristics of the PLA/PCL film material at the molecular level.

The Imbalance Cost Pass-Through (ICPT) is a flexible component of the Incentive Regulation (IBR) that empowers power producers to adjust tariffs in response to variable fuel prices, thereby enhancing the economic resilience of electricity generation. However, the cost of electricity generation is significantly influenced by the volatility of commodity prices, including coal, gas and LNG. In Malaysia, the Energy Commission has conducted biannual reviews of fuel and other generation costs. Any cost savings or increases identified during these reviews will be passed on to customers in the form of rebates or surcharges. Due to that reason, this study proposes ICPT price forecasting for the electricity market in Peninsular Malaysia. The study aims to construct an ICPT-related baseline model for the peninsular generation data by employing three forecasting methods. The forecasting performance is analysed by a Mean Absolute Percentage Error (MAPE). In findings, the ARIMA method is one of the most accurate forecasting methods for fuel prices compared to the Moving Average (MA) and LSSVM methods. The observed price differences between the ARIMA and LSSVM models for ICPT are minimal. The ICPT price for July-December 2022 and January-June 2023 is MYR 0.21/ kWh for ARIMA and MYR 0.18/kWh for LSSVM, which are close to the actual TNB’s ICPT tariff. As for the forecasting, the ICPT price is expected to drop for the next announcement. The findings of this study may contribute to a positive impact on the sustainability of the energy sector in Malaysia.

Dynamic time history analysis is a powerful and effective method to study the seismic response of tunnels, the dynamic time history to analyze the seismic response of the tunnel in the typical subway in this paper. The analysis results show that the overall levelling of the tunnel will not affect the tunnel too much, and the seismic response of the tunnel is mainly related to the relative displacement of the ground around the tunnel. The analysis results show that the internal force of the tunnel and the tunnel inclination have a good linear relationship, and the tunnel inclination can be used to measure the magnitude of the seismic response of the tunnel.

The paper examines the various uncertainties encountered in high-frequency trading (HFT) environments and delves into the multiple challenges faced by HFT firms in navigating the Dodd-Frank Wall Street Reform and Consumer Protection Act (referred to as the "Dodd-Frank Act"), particularly during the initial stages of its enactment. These challenges include the ambiguity surrounding the definition of HFT, the lack of clarity regarding regulatory requirements and boundaries, inconsistencies in enforcement resulting from deviations in understanding the content, and the absence of detailed descriptions of the Act’s provisions. These hurdles significantly impact not only the daily operations of HFT firms but also pose higher demands on their long-term strategic planning and risk management. Drawing upon the Data, Information, Knowledge, Wisdom, and Purpose (DIKWP) model, this study employs an innovative analytical framework. Through the comprehensive application of conceptual space, cognitive space, and semantic space, it provides a systematic methodology for identifying and analyzing the aforementioned issues. This approach not only aids firms in better comprehending and adhering to complex regulatory requirements but also enables them to explore new business opportunities and competitive advantages while ensuring compliance.

This study investigates the impact of rotor spacing on the aerodynamic performance of a coaxialcopter. It has been observed that a small distance between two rotors can result in significant interaction between the propellers, consequently affecting the rotor's aerodynamic efficiency. Exploiting this characteristic, the present research introduces a coaxialcopter with variable rotor spacing. Employing finite element numerical simulations, we assess the aerodynamic behavior of this novel configuration. Through comprehensive measurements and analysis of its aerodynamic performance across varying rotor spacings from 0.1R to 1R, we validate the effectiveness of a rotor spacing control strategy for enhancing takeoff maneuvers. Our numerical simulation results reveal that the performance characteristics of both upper and lower rotor converges toward that of a single rotor as pitch ratio increases, along with the reduce of their thrust fluctuations and aerodynamic performance periodicity. Considering stable power consumption patterns and endurance performance, we analysis the interrelations binding of pitch distance of the rotors, rotational speed, and pitch angle, vis-à-vis the thrust coefficient and power coefficient. Through parameter optimization method, we demonstrate that adjusting rotor spacing offers a practical means to enhance payload capacity without increasing power input, thereby improving the efficiency, which validates the practicality and efficacy of the parameter optimization approach. Furthermore, optimizing rotor spacing for specific operational scenarios enhances overall aerodynamic performance, suggesting a viable flight control strategy for takeoff and landing conditions.

With the increasingly online exposure of urban public spaces, the new concept of "Internet-celebrity cities" has emerged in China. The online internet-famous sites are the main characteristics of "Internet-celebrity cities". To fully understand online users' preferences in such kind of public spaces, this article took 27 typical riverfront internet-famous sites (RIFS) in Changsha city (China), as an example. Through the online images and review comments on social media platform "Xiaohongshu", the study analyzed users’ perception of RIFS specially on visual and emotional preferences. It revealed the following findings:(1) The popularity of RIFS had a significant head effect and there were far more positive emotions than neutral and negative emotions in review comments. (2) According to 5 different categories of RIFS: modern buildings with river views, restaurants with strong visual impact became the main attractions on commercial RIFS. The art exhibition RIFS attracted visitors to experience traditional culture and highlight their aesthetic pursuits. In the historical and cultural RIFS, people preferred to see the historical buildings with surrounding natural environment, as well as river and mountains views. Ecological Recreational RIFS showed the similar results with the uncultivated RIFS, for the main focus was on the ecological environment, a broader vision and the specific atmosphere. Moreover, the uncultivated RIFS showed more diversified attraction points. This study can provide a new perspective on the waterfront vitality and can offer a targeted and attractive manner for waterfront regeneration that are different from traditional methods.

The attitude dynamics and orbit dynamics of large rigid space structures are coupled with each other under gravity gradient, which may affect the stability of the large rigid space structures. In this paper, the gravity gradient stability of a large rigid space structure is studied under both small and large disturbances. Based on the rigid body dynamics and orbit dynamics, an accurate dynamic model without any linearization of the large rigid space structure is established via the natural coordinate formulation (NCF), which is able to describe the large overall motions of the structures. By using the generalized-α algorithm, the gravity gradient stability of the large rigid space structure is simulated and analyzed via various examples, including the influence of large disturbance angles, the positions at the stabilization and unstabilization regions. Finally, the relationship between spinning stability and gravity gradient stability is also investigated via a large spinning space structure.

In the light of almost a century of struggle to make (common) sense of Quantum Mechanics and to reconcile it with General Relativity, it is proposed to (for some time) forget about quantizing gravity or striving for one Theory of Everything or “Weltformel”, which would describe the whole of reality without any joints or suture marks. Instead of one single monolithic formalism, a three-legged compound approach is argued for. Quantum Mechanics, Relativity and Thermodynamics are proposed as the main pillars of reality, each with its well-defined realm, specific features, and clearly marked interfaces between the three of them. Not only classical reality, which is rather directly accessible to us, is then comprehensively modelled by their encompassing combination. Quantum phenomena are understood as undoubtedly lying at the bottom of classical physics and at the same time, they become “fully real” only when embedded in classical frames between preparation and measurement in time. It is then where thermodynamics steps in and provides the mediating glue. The aim of this short contribution is not to deliver novel quantitative results but rather to propose a comprehensive research program and to coarsely lay out a very roughly coherent self-referential sketch starting from the beginning of the one universe, which we inhabit.

Today's city needs more than ever methodological devices that ensure a specific urbanism, in keeping with the complexity of relationships that occur in the urban space. Networks or systems of diverse nature must be activated to achieve a certain success of the city, even more so in its fragile central fabrics. The study is focused on the historic neighborhoods of the city of Jaén (Spain), which have a high vulnerability index. The aim is to establish a strategy to revitalize their urban and social capital and improve their articulation with the rest of the urban and territorial structure. A methodological proposal for the analysis of vulnerability factors and an urban and cartographic analysis of the public space is addressed through an interweaving of a triple network: environmental, social, and urban. For this purpose, the configuration of this overlapping network of analysis and formulation of criteria is presented, which considers the urban multiplicity and promotes new dynamics for the integrated urban regeneration of the area and for the activation of public and collective urban spaces.

Abstract: Experiments conducted to date to verify the relativistic gravitational time dilation have limited scientific significance because the basic postulate of Einstein’s relativistic GR that the same time (t0) is measured in all non-inertial frames of reference, because all non-inertial frames of reference must be equal, has not yet been verified by time measurements. According to Einstein's relativistic GR, a correlation between time and different gravitational potentials must be the result of a relative relation between non-inertial frames of reference and must not the result of any other physical influence. An experiment that can differentiate between a causal correlation (relative relation) and an apparent correlation (relativistic relation) between time and gravitational potentials is still outstanding. The expressions "relative" and "relativistic" are often used as synonyms. However, Einstein's GR is a relativistic theory. In the case of general relativity, relativistic means that time depends only on the relative relation between non-inertial frames of reference and not on other physical factors. The author proposes an easy-to-realize experiment that is able to distinguish between a causal correlation (relative relation) and an apparent correlation (relativistic relation) between time and gravitational potentials, which can confirm or falsify Einstein's relativistic GR. .

Suppose for n∈ ℕ, set A⊆ℝⁿ and function f∶A→ℝⁿ. If set A, using the Hausdorff outer measure, is measurable in the sense of Carathèodory; we want to find an extension of the expected value, w.r.t the Hausdorff measure, that's unique, finite and "natural" (defined on §2.3 & §2.4) for all f in a prevalent subset of ℝᴬ. The issue is current extensions of the expected value are finite for all functions in only a shy subset of ℝᴬ. The reason this issue wasn't resolved is mathematicians have not thought of the problem, focusing on application rather than generalization. Despite the lack of potential use, we'll attempt to solve the problem by defining a choice function---this shall choose a unique set of equivalent sequences of sets (Fₖ***) , where the set-theoretic limit of Fₖ*** is the graph of f; the measure Hʰ is the ℎ-Hausdorff measure, such for each k∈ℕ, 0 < Hʰ(Fₖ***) < +∞; and (fₖ*) is a sequence of functions where {(x,fₖ*(x))∶x∈ dom(Fₖ***)}=Fₖ***. Thus, the extended expected value of or E**[f,Fₖ***] is: ∀(ε>0)∃(N∈ℕ)∀(k∈N)(k≥N⇒1/Hʰ(dom(Fₖ***))∫dom(Fₖ*** )fₖ* dHʰ - E**[f,Fₖ***]<ε ) which should be unique, finite, and "natural" (defined on §2.3 & §2.4) for all f in a prevalent subset of ℝᴬ. Note we guessed the choice function using computer programming but we don’t use mathematical proofs due to the lack of expertise in the subject matter. Despite this, the biggest use of this research is the extension of the expected value is finite for "almost all" functions: this is easier to use in application when finding the "average" of functions covering an infinite expanse of space.

In this paper, a proof similar to the Pusey-Barrett-Rudolph (PBR) theorem is given to prove that time in quantum theory is not epistemic but has ontological reality. For this, we first discuss how time can be encoded as an intrinsic property of a quantum system. We prepare a quantum state containing time as an intrinsic property and show by a PBR-type proof that time cannot be an epistemic notion. In fact, the PBR theorem implies an ontic notion of time. Indeed, if the quantum state is a physical property, then quantum state reduction is a physical process involving information destruction. In this case, quantum probabilities are intrinsic probabilities without epistemic origin, and they generate a genuinely new sequence of events. This novelty introduced by quantum probabilities can be interpreted as time.

Green open spaces (GOS) are well known to be vital to enhancing the standard of living conditions in urban environments. The World Health Organization (WHO) says it is important to have at least nine square meters per citizen. The European Environment Agency (EEA) stipulates that 5000 square meters of green space will be reachable within 300 meters to residents. GOS pattern in Kyrenia Region is not adequate or successful in that regard. The process of urban planning has been neglected in the Kyrenia region and these areas have lost their significance and value. This research evaluates the level of accessibility of green spaces in Kyrenia Region. Three urban areas, Kyrenia, Karavas and Agios Epiktitos have been analyzed within this framework. In order to do that, GOS areas and their pattern are researched by deploying geographical information analysis. Accessibility to these areas is measured by using Euclidean and network distance analysis based on 300, 800 and 5000 meters. Mainly, Euclidean distance and network distance methods are measured from building units and results showing accessibility values are constructed. According to the results, network accessibility is very low within the study region. Additionally, Kyrenia, Karavas and Agios Epiktitos have shortage in GOS per capita. To offer effective strategies for urban planning, the factors influencing the accessibility and also the usage of GOS are addressed.

Quantum physics is intrinsically probabilistic. The entropy of a quantum state quantifies the amount of randomness (or information loss) of such state. The degrees of freedom of a quantum state are position and spin, and upon their specification Born's rule in phase space defines randomness. We focus on the spin degree of freedom and elucidate the spin entropy. Then, we present some of its properties and show how entanglement increases spin entropy. Some speculative predictions on the decay of the $Z^0,W^{+,-}$ gauge bosons conclude the paper.

This retrospective study examines 248 test-bolus examinations preceding contrast-enhanced magnetic resonance angiography (CE-MRA) to extract clinically relevant data for critical limb ischemia (CLI) management. Methods involved a retrospective review of test-bolus exams, analysing 60 graphs for time-to-peak (TTP), full-width half-maximum (FWHM) time, and time to continual rise in signal intensity. These values were correlated with heart function parameters (ejection fraction, ASA-Classification, Lee-Index, and MET-Score). Results indicate a mean TTP of 31.2 ± 7.3s, showing a correlation between ejection fraction and ASA classification. Patients with atrial fibrillation exhibited prolonged TTP compared to those without. Despite population heterogeneity, findings facilitate risk stratification for limb-saving interventions in CLI. TTP emerges as a potential clinical cardiovascular parameter and a risk factor for vascular interventions. Given the variation in injection protocols across centres, this study underscores the importance of precise bolus arrival time documentation for future multicentre studies.

The author introduces a novel theoretical framework that suggests matter and energy are both converted from curved space. In Space Theory, gravitation is generated by the flow of space, instead of being transmitted by the graviton as in String Theory. This theory also suggests that Newton's gravitational constant, denoted as G, may not be truly constant but could vary over time. The equivalent equation of space is S=Ec²=mc⁴, and the gravitation of hollow sphere space is S_μν=4πGm=(4/3)π((r+a)³-r³). The Space Theory also predicts that the surface gravitational acceleration of the neutron star Crab Pulsar (PSR B0531+21) is approximately 8.21924883×10⁶ m/s².

Based on recent progress in cosmological thermodynamics, we present a new thermody- namic formulation of the Friedmann equations in the new Haug-Tatum cosmology model, as well as for other similar models put forward in the literature from different solutions to Einstein’s field equation. Since the CMB temperature has been measured much more accu- rately than the Hubble constant, we demonstrate that our thermodynamic formulation of the Friedmann equation dramatically narrows the acceptable range for the critical density of the universe. Furthermore, we show how our thermodynamic formulation leads to a more precise cosmological constant estimate.

In the context of improving aircraft safety, this study focuses on the development and evaluation of a graphene-based ice detection system using an environmental chamber. The research is driven by the need for more accurate and efficient ice detection methods, crucial in mitigating in-flight icing hazards. The methodology employed involves testing flat graphene-based sensors in a controlled environment, simulating a variety of climatic conditions that could be experienced in an aircraft during its entire flight. The environmental chamber enabled precise manipulation of temperature and humidity levels, thereby providing a realistic and comprehensive test bed for sensor performance evaluation. The results were significant, revealing the graphene sensors’ heightened sensitivity and rapid response to the subtle changes in environmental conditions, especially the critical phase transition from water to ice. This sensitivity is the key to detecting ice formation at its onset, a critical requirement for aviation safety. The study concludes that graphene-based sensors, tested under varied and controlled atmospheric conditions, exhibit a remarkable potential in enhancing ice detection systems for aircraft. Their lightweight, efficient and highly responsive nature makes them a superior alternative to traditional ice detection technologies, paving the way for more advanced and reliable aircraft safety solutions.

Hybrid forecasting methods have emerged as a solution surpassing the limitations of both statistical and deep learning approaches. While the first emphasize the significance of variables, they often produce worse forecasting results when compared to newer techniques. In contrast, deep learning models remain enigmatic "black boxes" in terms of interpretability, although achieving better results in forecasting. This article introduces the Comprehensive Cross-Correlation and Lagged Linear Regression Deep Learning (CCLR-DL) framework, designed to harness the best of both approaches, enhancing forecasting accuracy while retaining model interpretability through a feature selection process. CCLR-DL blens cross-correlation analysis, lagged multiple linear regression and granger's causality procedures with deep learning architectures based on LSTM. In a practical demonstration, CCLR-DL was applied to a real database of clinical visits associated to diagnoses in Catalonia, Spain (tracking a population of 6.3 million patients during 10 years). Predicting visits enables the healthcare managers to be ready for future demand shifts. Results demonstrate a consistent and substantial improvement over standalone statistical and deep learning methods when predicting healthcare demand. This hybrid approach not only showcases its efficacy but also offers a promising solution to the challenge of balancing predictive accuracy with model explicability. In this context, this work aims to design and validate a method for feature selection and forecasting of multivariate high dimensional time series datasets not only to improve prediction accuracy but also to model transparency by identifying a subset of variables that improve predictions and G-cause the target variable.

To reduce the redundant counting of TDC in high-speed applications and thus reduce power consumption, a TDC architecture is proposed to quantify the difference between two adjacent rows of pixel signals. This structure can remove the identical part between two rows of pixel signals by adjusting the start and stop signal of the TDC, which will reduce the number of flipping of D flip-flops in the TDC. In the 110nm CMOS process, simulation results show that this design achieves an effective number of bits (ENOB) of 4.72 bits and a Figure of Merit (FoM) of 104.7 fJ/step - 162.3 fJ/step with a power consumption ranging from 60 µW to 93 µW. Compared with traditional counting methods, the proposed TDC can reduce counting power consumption by 30%.

This paper presents a new implementation of a 2-box absolute flow model, enabling the calculation of CO₂ transfer between the atmosphere and a mixing reservoir representing the combined effect of the terrestrial and ocean regions. The model uses published values of anthropogenic CO₂ fossil fuel emissions (CO2ff), atmospheric CO₂ mixing ratio and nuclear weapons bomb yields, to compute atmospheric d¹³C and Δ¹⁴C time-series. The level of agreement between the calculated values and the accepted values for d¹³C is within ± 0.05 ‰, and for Δ¹⁴C is within ± 3‰, spanning 200 years. The model contains only seven internal parameters; these are varied to optimize the fit, leading to reasonable parameter values, indicating the validity of the method. In addition, the model shows how a rising CO₂ exchange influx fluctuating with surface temperature is compatible with a nett atmospheric CO₂ sink. The study demonstrates that a single CO₂ residence time applies to both the ¹⁴C bomb pulse and the anthropogenic flux, contrary to the conventional view that "bomb radiocarbon and anthropogenic CO₂ do not behave identically." [Joos 1994 Nature 370, 181–182]. It is shown that the difference in behaviour, claimed to be due to seawater chemistry, is not significant in practice since fluctuating bulk carbon dominates fluctuating isotopic ratio. A new analysis of the airborne fraction indicates that the assumption of a time-dependent exchange influx results in a similar residence time for bulk CO₂ as for ¹⁴C in the nuclear bomb pulse, reinforcing the view that the ¹²C, ¹³C and ¹⁴C carbon isotopic forms of CO₂ behave similarly in the carbon cycle.

The process of establishing secure communication between devices in the Internet of Things (IoT) can be approached by using a One-time-Pad (OTP) protocol. We propose using a known secure multiparty sum protocol for generating a One-time-Pad key using true (physical) random numbers in each device (party). We implemented the proposal using ZeroC-Ice, a middleware for distributed computing. The protocol security properties were analyzed under the assumptions of the Dolev-Yao threat model.

Sharding shows great potential for extending the blockchain. The current challenge facing sharded blockchain technology lies in addressing the extended transaction confirmation times caused by isolated states between shards and unbalanced transaction allocation strategies. These factors contribute to an increase in cross-shard transactions and disproportionate shard workload, ultimately resulting in indefinite confirmation delays for cross-shard transactions. A critical priority for sharded blockchain systems is to conduct a comprehensive qualitative analysis to better understand and mitigate the prolonged transaction confirmation times. We introduce a Product-Form Queue Network (PFQN) model to address the transaction confirmation time problem in sharded blockchains and incorporate a new confirmation queue to more accurately simulate the actual transaction confirmation process in the blockchain. In addition, we provide a detailed quantitative analysis of the relationship between network load, consensus efficiency, and security in sharded blockchains, laying a theoretical foundation for achieving robustness and efficiency in sharded blockchains. This research not only contributes to addressing the scalability issues in sharded blockchains but also offers a new perspective for future research directions.

A time interval only description necessarily needs its own independent definitions, without one moment time coordinates to it. In this paper derived are time interval only set properties, including commutation relations, addition, multiplication and derivatives. Time interval only set commutation relations, consistent with one moment time set properties, are introduced by defining correspondence relations for these sets. Time development and equilibrium within the time interval description depend on the well-known ‘mean velocity theorem’ and the time interval version of the Legendre transform. In contrast, usually applied is only the traditional vector and one moment time coordinate kinematic approach from Newton’s laws. The main results of this paper are correspondences and time interval only set commutation relations. All other properties are derived from these results, while for the time interval only set, different from the one moment time set the canonical property is not valid. The time interval only description can be applied assuming spherical symmetric star-source radiation propagation, with finite time intervals for realistic measurement events. From time development with (a-)symmetry of time intervals, and from Curie’s principle, change can be described with a set theoretic approach. Time interval only set properties include the time interval only version of Noether charges and structure constants. A time interval only description for wave propagation, including group-velocity, for zero and non-zero mass wave particles, relates to the properties of the time interval only set. A second result in terms of the time interval only description is propagation wave energy equivalence with gravitation energy, derived from time interval only set commutation relations. A time interval approach, however including one moment time description dependence, was introduced in earlier publications of this author. In part 1 investigated are the time interval only set and its properties, a forthcoming part 2 to application of the time interval only description to specific groups of stars as emission sources.

This study explores the significance of active suspension systems for vehicles with lower chassis compared to conventional ones, aiming at the development of future automobiles. Conventional linear MR (Magneto-Rheological) dampers were found inadequate in ensuring sufficient vibration control because the vehicle's chassis becomes lowered in the unmanned vehicles or purposed based vehicles. As an alternative, a rotary type of MR damper is proposed in this work. The proposed damper is designed based on pre-specified design parameters through mathematical modeling and magnetic field analyses. Subsequently, a prototype of the rotary MR damper identical to the design is fabricated, and effectiveness is shown through experimental investigations. In configuring the experiments, a proportional-integral (PI) controller is employed for current control to reduce the response time of the damper. The results presented in this work provides useful guidelines to develop a new type of MR damper applicable to various types of future vehicles’ suspension systems with low distance from the tire to the body floor.

Spatial planners are nowadays strongly interested in the benefits of greenspace for the health of urban residents. However, concrete and context-specific guidance on effective greening strategies is still lacking. We present a novel, model-based approach to support the development of such strategies. The approach is quantitative and spatially-explicit, and accounts for multiple health benefits as well as burdens. In this study, we applied the approach to the city of Maastricht (The Netherlands), and conducted an integrated, city-scale assessment of the health benefits and burdens of four urban greenspace designs. These included: ‘No greenspace’, ‘Current greenspace’, ‘Green parking lots and squares’, and ‘Optimized greenspace locations’. For each greenspace design, indicator values were calculated for five health determinants: heat stress, air pollution, perceived unsafety, unattractive views, and tick-bite risk. To assess the health contribution of urban greenspace in a given design, these indicator values were compared with the values in the ‘No greenspace’ design. The study produced clear, quantitative conclusions about the health benefits and burdens of the urban greenspace designs for the case of Maastricht, but also generated novel, more general insights relevant to planning of urban greenspace for health. These insights concern the importance of translating health policy objectives into specific target values or thresholds, and the importance of ‘smart’ choices in greenspace type and location that can effectively reduce trade-offs between health benefits and burdens. Priorities for future research, addressing limitations of the presented approach, concern a further expansion of the range of health benefits and burdens covered by the model, and the development of a common metric for the entire range of health benefits and burdens allowing optimization of greenspace design to maximize its overall net health benefit.

This study aimed to evaluate the effects of Blazepod technology when incorporated with various training regimens on the essential elements of physical fitness in volleyball, such as agility, speed, visual response time, and vertical leap. Thirty-six participants (age :17.33±0.48 y, height: 183.78±6.34 cm, weight: 77.14±5.16 kg) were in-volved in this study. In randomized design, three equal groups with two experimental groups and one control group were involved in the study over a period of six weeks: (GE1) used Blazepod technology to workout at a low level; (GE2) used Blazepod technology to workout at a higher intensity; (CG) did not employ Blazepod technology, but it adhered to the same fundamental training curriculum. We conducted agility, speed, reaction time, and vertical jump tests before, midway and after the study to determine optimal training volume, intensity, and frequency. A significant main effect of time (P0.01), and time×group interaction (P>0.001) were found for all tests. Post hoc test showed that the two experimental groups gadget significantly improved in all performance variables (P

Transformation formula under the action of a general linear fractional transformation for generalized Dedekind eta-function has been a subject of intensive study, Rademacher, Dieter, Meyer et al. However, the (Hecke) modular relation structure has not been recognized until the work of Goldstein-de la Torre, and streamlining the classical proofs in the modular relation will reveal the meaning hidden in those works. Our main aim is to elucidate the works of these researchers in the context of modular relations.

In an effort to enhance the efficiency and safety of open-pit mines, this study explores the optimization of end slope road parameters and slope structures, specifically focusing on unmanned driving lanes.A significant aspect of the study is the development of a truck trajectory offset model, which considers the different reaction times between automated sensors and human drivers in adapting to environmental changes. To test these concepts, the study uses numerical simulations to confirm the stability of the proposed end slope designs. Using Victory West Mine No. 1 as a case study, the research determines the optimized width for unmanned driving lanes and the maximum angle for safe steepening of end slopes. The findings indicate that the optimized unmanned lane width for NTE240 mining dump trucks is 1743 mm, allowing for a 2-degree increase in the slope angle at the south end slope. This optimization leads to a steep mining stripping volume of 3.2735 million m³ and a coal output of 2.49628 million tons, maintaining a stripping ratio of 1.31m³/t. These results demonstrate that the unmanned driving road width optimization not only ensures slope safety but also significantly boosts the economic benefits of steep mining in open-pit mines.

This paper presents a groundbreaking approach to real-time image processing in electronic component assembly, enhancing quality control in manufacturing. By capturing images from pick and place machines between component pickup and mounting, defects are identified and addressed in-line, significantly reducing the likelihood of defective products. Leveraging fast network protocols like gRPC and orchestration with Kubernetes, along with C++ programming and TensorFlow, this method achieves an average turnaround time of less than 5 milliseconds. Tested on 20 live production machines, it ensures compliance with IPC-A-610, and IPC-STD-J-001 standards while optimizing production efficiency and reliability.

A cyclic antipodal points of a circle is a pair of points that are the intersection of the circle with a diameter of the circle. A recent proof of Ptolemy’s Theorem, simultaneously in both (i) Euclidean geometry; and (ii) the relativistic model of hyperbolic geometry (which is identified with the Klein model of hyperbolic geometry), motivates in this article the study of four cyclic antipodal points of a circle, ordered arbitrarily counterclockwise. The translation of results from Euclidean geometry into hyperbolic geometry is obtained by means of hyperbolic trigonometry, called gyrotrigonometry, to which Einstein addition gives rise. Formulas that extend the Pythagorean formula in both Euclidean and hyperbolic geometry are obtained as byproducts

High seismic activity in the Himalayas and the increasing urbanization of its surrounding areas in the northern Indian region pose significant threats to both lives and properties. To mitigate the risk of seismic events, an earthquake early warning system can be used in the region. This system would be particularly beneficial to cities and towns in the mountainous and foothill regions that are located near earthquake sources. The government and the science and engineering community have re-sponded to this call by establishing the Uttarakhand State Earthquake Early Warning System (UEEWS). The system became fully operational on August 4, 2021, after being launched by the government of Uttarakhand. The UEEWS includes 170 accelerometers in the seismogenic part of the Uttarakhand region of the Himalayas. Ground motion data is transmitted to a central server through a dedicated private telecommunication network 24 hours a day, seven days a week.The system is designed to issue warnings for moderate to high-magnitude earthquakes via a mobile application installed on users' devices and sirens installed in government-owned public buildings. The UEEWS has successfully issued alerts for light earthquakes that occurred in the instrumented region and warnings for moderate earthquakes that occurred in the vicinity of the instrumented area. This paper provides an overview of the design of the UEEWS, details of the instrumentation, adaptation of attributes and their relation to earthquake parameters, the operational flow of the system, and information about the dissemination of warnings

The inter-tip times (ITTs) of tipping-bucket rain gauges potentially provide the highest-resolution intensity data that can be acquired from this type of gauge. At an intensity of 100 mm h-1, a typical gauge with a sensitivity of 0.2 mm of rainfall would be expected to tip every 7.2 seconds. However, TBRGs are often equipped with syphons, to reduce the dynamic calibration error that results from continued (and unmeasured) inflow to a bucket as it tips. This increases the accuracy of rainfall depth recording, but the time to fill and empty the syphon can reduce the ability of a TBRG to respond to (and for the ITTs to reflect) short-term intensity fluctuations. This ability is already limited by the discretisation arising from the filling and emptying of the buckets themselves. Laboratory tests with controlled water inflow rates were performed using two high-quality TBRGs, one a 'straight-through' design and the other syphon-equipped. These confirmed that at all intensities at which the syphon operates, a regular sequence of fixed-duration ITTs (such as the 7.2 s mentioned above) does not occur. Rather, the ITTs are perturbed by the syphon cycling. The gauges were also co-located in the field, and linked to carefully synchronised event data loggers. Data collected during several rainfall events revealed differences in the ITTs, and again confirm that the ITT sequence of a syphon-equipped TBRG exhibits artefacts related to syphon operation, that are not present in the 'straight-through' data. These artefacts can result in ITT differences of many minutes, depending on the rainfall intensity, and are problematic for the use of ITTs to estimate intensity. Peaks and troughs in the intensity profile also differed between the two gauges. It is recommended that in the application of TBRGs for studies where short-term intensity data are required, 'straight-through' gauges should be used, and syphon-equipped gauges avoided.

The Simulation analogy presented in this work enhances the accessibility of abstract quantum theories, specifically the stochastic hydrodyanimc model (SQHM), by relating them to our daily experiences. The SQHM incorporates the influence of fluctuating gravitational background, resembling dark energy, into quantum equations. This model successfully addresses key aspects of Objective-Collapse Theories, including resolving the 'tails' problem through the definition of quantum potential length in addition to the De Broglie length, beyond which coherent Schrödinger quantum behavior and wavefunction tails cannot be maintained. The SQHM emphasizes that an external environment is unnecessary, asserting that the quantum stochastic behavior leading to wave-function collapse can be an inherent property of a system in a spacetime with fluctuating metrics. Embedded in relativistic quantum mechanics, the theory establishes a coherent link between the uncertainty principle and the constancy of light speed, aligning seamlessly with finite information transmission speed. Within a fluctuating quantum system, the SQHM derives the indeterminacy relation between energy and time, offering insights into measurement processes impossible within a finite time interval in a truly quantum global system. Experimental validation is found in confirming the Lindemann constant for solid lattice melting points and the transition from fluid to superfluid states. The SQHM's self-consistency lies in its ability to describe wavefunction collapse and the measure process. Additionally, the theory resolves the Pre-existing Reality problem by showing that large-scale systems naturally decay into decoherent states stable in time. Continuing, the paper demonstrates that the physical dynamics of SQHM can be analogized to a computer simulation employing optimization procedures for realization. This perspective elucidates the concept of time in contemporary reality and enriches our comprehension of free will. The overall framework introduces an irreversible process impacting the manifestation of macroscopic reality at the present time, asserting that the multiverse exists solely in future states, with the past comprising the formed universe after the current moment. Decoherence at the present time functions as a reduction of the multiverse to a single universe. The macroscopic reality, characterized by fractal consistency where microscopic domains with quantum properties coexist, provides insights into how our consciousness apprehends dynamic reality, the spontaneous emergence of gravity in discrete spacetime evolution, and the attainment of the classical General Relativity limit in Quantum Loop Gravity and Causal Dynamical Triangulation. The Simulation Analogy highlights a strategy focused on minimizing information processing, facilitating the universal simulation in solving its predetermined problem. From within, reality becomes the manifestation of specific physical laws emerging from the inherent structure of the simulation devised to address its particular issue. In this context, the reality simulation appears to employ an entropic optimization strategy, minimizing information loss while efficiently compressing data in line with the simulation's intended purpose.

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.

Significant changes to the new National College Entrance Examination (NCEE) and the implementation of the “Double First-Class” (DFC) initiative in China are coincidentally in the national spotlight and fall within the same policy window. However, few studies have investigated the effects of the new NCEE on the quality of students in DFC universities. By leveraging the 2018-2022 college admission data from Shandong Province, these effects are examined via the interrupted time-series technique. Weighted rankings for liberal arts and science disciplines and the admission ranking coefficient are adopted to ensure comparability before and after the reform. The findings reveal that after the reform, the quality of students in both world-class universities and first-class discipline universities improved, with greater improvements seen in world-class universities. Focusing on urban differences, the quality of students in DFC universities located in second-tier cities is found to have experienced a higher increase as compared with students in the first-tier and new first-tier cities. In addition, the reform has had different impacts on the quality of students in different majors. Furthermore, when selecting postsecondary institutions, high-scoring students prioritize the quality of universities and majors over urban factors. Finally, the implications of the new NCEE in relation to a sustainable development of DFC universities for research, policy, and practice are further discussed.

Let $(\{f_n\}_{n=1}^\infty, \{\tau_n\}_{n=1}^\infty)$ and $(\{g_n\}_{n=1}^\infty, \{\omega_n\}_{n=1}^\infty)$ be unbounded continuous p-Schauder frames ($0<p<1$) for a disc Banach space $\mathcal{X}$. Then for every $x \in ( \mathcal{D}(\theta_f) \cap\mathcal{D}(\theta_g))\setminus\{0\}$, we show that \begin{align}\label{UB} \|\theta_f x\|_0\|\theta_g x\|_0 \geq \frac{1}{\left(\displaystyle\sup_{n,m \in \mathbb{N} }|f_n(\omega_m)|\right)^p\left(\displaystyle\sup_{n, m \in \mathbb{N}}|g_m(\tau_n)|\right)^p}, \end{align} where \begin{align*} & \theta_f: \mathcal{D}(\theta_f) \ni x \mapsto \theta_fx \coloneqq \{f_n(x)\}_{n=1}^\infty\in \ell^p(\mathbb{N}), \quad \theta_g: \mathcal{D}(\theta_g) \ni x \mapsto \theta_gx \coloneqq \{g_n(x)\}_{n=1}^\infty\in \ell^p(\mathbb{N}). \end{align*} Inequality (1) is unexpectedly different from both bounded uncertainty principle \textit{[arXiv:2308.00312v1]} and unbounded uncertainty principle \textit{[arXiv:2312.00366v1]} for Banach spaces.

Traversal time in tunneling effect for ultrasonic waves in tapered waveguides is derived considering its analogy with quantum and electromagnetic waves tunneling. If, as traversal time, the so called phase time is considered, the ultrasonic wavepacket shows the equivalent in acoustics of superluminality i.e. the derived velocity , crosses the limit of bulk transverse ultrasonic waves in the medium of the waveguide that is the equivalent of c in the quantum and electromagnetic cases. Graphs clearly illustrating this so called Hartman effect are obtained confirming the experimental results in the three different fields.

As the adoption of renewable energy sources grows, ensuring a stable power balance across various time frames has become a central challenge for modern power systems. In line with the "dual carbon" objectives and the seamless integration of renewable energy sources, harnessing the advantages of various energy storage resources and coordinating the operation of long-term and short-term storage have become pivotal directions for future energy storage deployment. To address the complexities arising from the coupling of different time scales in optimizing energy storage capacity, this paper proposes a method for energy storage planning that accounts for power imbalance risks across multiple time scales. Initially, the Seasonal and Trend decomposition using the Loess (STL) decomposition method is utilized to temporally decouple actual operational data. Subsequently, power balance computations are performed based on the obtained data at various time scales to optimize the allocation of different types of energy storage capacities and assess the associated imbalance risks. Finally, the effectiveness of the proposed approach is validated through hourly applications using real-world data from a province in China over recent years.

Quantum cryptography revolutionizes secure information transfer, providing defense against both quantum and classical computational attacks. The primary challenge in extending the reach of quantum communication comes from the exponential decay of signals over long distances. Addressing this challenge, we have developed Quantum-protected Control-based Key Distribution (QCKD), overcoming transmission range limitations by monitoring signal leakages and rendering leaked quantum states significantly non-orthogonal. This paper reports on the experiments with the QCKD, conducted over a 1,707 km fiber line. We demonstrate advancements in critical components of the protocol, showing its remarkable scalability and adaptability for extended distances and multi-user configurations.

SARS-CoV-2 Omicron variant spike RBD epitopes in complex with spike (S) -protein D614G mutations now predominate globally and increase infectivity by assembling more functional S proteins into the virion. On average, homeopathic medicine contains less than one molecule per dose on average. Single variable SphericalHarmonicY, LaguerreL, WhittakerM, SphericalBesselJ, LegendreP, LegendreQ, LaguerreL, ChebyshevT, and Hypergeometric1F1 Functions pFqarise in connection with the power series solution of the Schrodinger equation or in the summation of perturbation expansions in quantum mechanics. A quantum interpretation of the homeopathic method is presented here through a novel algebraic topology approach to supersymmetry and symmetry breaking in quantum fields and quantum gravity theory with the aim of developing a wide range of physical-based drug design applications in a Small Molecule Quantized Water Memory Network suggesting that the Hidden Black Hole Paradox of Information Loss might be solved under suitable conditions.

Urban rivers and waterfronts play a vital role in the ecological, social, and economic fabric of cities, providing not only aesthetic value but also serving as important ecosystems that contribute to the overall well-being of urban environments. However, many urban rivers, including the Beirut River in Lebanon, face challenges such as pollution, neglect, and the loss of recreational and ecological value due to urbanization and industrialization. According to the Lebanese MOE (Ministry of Environment), almost 70% of Lebanese rivers are polluted due to untreated waste management systems and which leads to undrinkable water and possible flooding disasters if not treated. This study addresses the problem of abandoned and degraded spaces along the Beirut River riverside through the application of urban acupuncture, a strategic approach that targets specific points in the urban environment to stimulate positive change and regeneration. The aim of the study is to assess the effectiveness of implementing small-scale ‘sensitive urban points’ known as urban acupuncture as the method for regenerating the Beirut River riverside, with the hypothesis that targeted interventions through Blue Urban Acupuncture or Aqua-puncture- can lead to significant improvements in the ecological, social, and economic aspects of the area that re-connect the people of Beirut with its river. The methodology involves a multidisciplinary approach that integrates urban design, and community engagement, and analysing similar examples of different approaches through creating a comparative table. Data collection includes environmental assessments of water quality, biodiversity, and ecosystem health, as well as social surveys to understand community needs and perceptions. By applying urban acupuncture principles to the Beirut River riverside, this study seeks to demonstrate how strategic interventions can lead to the regeneration of abandoned spaces, improve the overall quality of the urban environment, and create sustainable and inclusive riverside landscapes that benefit both the environment and the community.

If "quantization is an art" then it can be greatly rened by adopting cyclic time formalism. In past papers we have proven the effectiveness of a formulation of physics based on cyclic relativistic time. Now we can demonstrate in a general way, by using theorems of Geometric Quantization, that the Poisson brackets of intrinsically cyclic time dynamics directly imply the ordinary canonical commutation relations and the other Dirac's rules of canonical Quantum Mechanics. In other words, according to our result, canonical quantization is an implicit way of imposing intrinsically cyclic time dynamics without explicitly saying that time is a cyclic dimension.

Noninvasive brain stimulation technique can be used for modulation of motor behaviors such as reaction time (RT). The main aim of this study was to investigate whether RT during a sequential visual isometric pinch task (SVIPT) can be affected by anodal transcranial direct current stimulation (a-tDCS) over three different stimulation sites such as dorsolateral prefrontal cortex (DLPFC), primary motor cortex (M1) or posterior parietal cortex (PPC). We also aimed to assess if stimulation of these cortical sites affect the transfer of learning during SVIPT. A total of 48 right-handed healthy participants were randomly assigned to one of the four a-tDCS groups: 1) left M1, 2) left DLPFC, 3) left PPC and 4) sham. A-tDCS was applied concurrent with SVIPT in which the participants were precisely controlled their forces to reach seven different target forces from 10 to 40% of maximum voluntary contraction (MVC) presenting on a computer screen with right dominant hand. Four test blocks were randomly performed at baseline and 15 min after the intervention including sequence and random blocks with either hand. Our results showed significant differences between a-tDCS groups on ratio RT in the sequence blocks of both the right trained (P = .041) and left untrained hands (P = .023) for target forces of 15% and 30 % of MVC, respectively. In sequence blocks, M1 showed significant elongation in ratio RT for the target force of 15% and 30 % MVC compared to PPC and Sham groups in the right hand. In sequence blocks with left hand, this negative effect were found between M1-DLPFC and M1-Sham groups. In random blocks, no significant differences were found among four groups at each target forces for the left hand while there were significant differences for 15% (P =. 04) and 40% MVC (P =. 035) in the right hand. Our findings suggest that three different stimulation sites (DLPFC, M1 or PPC) were differentially affected by a single session of a-tDCS at some target forces during SVIPT. The effects of a-tDCS on ratio RT were transferred in the left untrained hand for sequence blocks but not random blocks. Further research is needed to understand fundamental aspects of these main areas of the brain on temporal processing in a precision control task such as SVIPT.

The application of smartphone-based color evaluation of passive sampling devices for gases has only been sparsely reported. The present review aims to compile available publications with respect to the configuration of the passive samplers, conditions of smartphone photographing, analytical procedure for color detection and quantification (including calibration processes), and their application to different target gases. The performance of the methods - whenever available - is presented regarding the analytical specifications selectivity, sensitivity, and limit of detection in comparison with other color evaluation methods of passive samplers. Practical aspects like requirements of instrumentation and ease of use will be outlined in view of the potential employment in education and citizen science projects. In one section of the review the inconsistent terminology of passive and diffusive sampling is discussed in order to clarify the distinction of information obtained from the uptake of the passive samplers between gas-phase concentration and the accumulated deposition flux of gaseous analytes. Colorimetric gas sensors are included in the review when applied in passive sampling configurations and evaluation is performed with smartphone-based color evaluation. Differences in the analytical procedures employed after the passive sampling step and prior to the detection of the colored compounds are also presented.

In the modern power grid, characterized by the increased penetration of power electronics and extensive utilization of renewable energy, inverters-based power plants play a pivotal role as the principal interface of renewable energy sources (RESs) and the grid. Considering the stability characteristics of grid-following (GFL) inverters when the grid is relatively weak, the application of grid-forming (GFM) controls becomes imperative to enhance the stability of the entire power plant. Thus, there is an urgent need for suitable and effective models to study the interaction and stability of the paralleled inverters employing GFL and GFM controls. Thus, the small-signal modeling with full-order state space model and eigenvalues analysis is presented in this paper. First, the small-signal state-space model of the individual GFL and GFM inverters is obtained considering the control loop, interaction, reference frame, transmissions, and time delays. Then, the models of the individual inverter are extended to the hybrid inverters to study the effects of the GFM inverters on the small- signal stability of the entire system. And, the impacts of the inertia and damping are analyzed by the eigenvalues of the state-transition matrix. Case comprising three parallel GFL inverters and two GFL inverters with one GFM inverter, respectively, are studied to examine the effectiveness and accuracy of the model. Finally, the stability margin obtained from the eigenvalue analysis of the entire system is verified by time-domain simulations.

This paper draws upon the theory of turbulence in physics to explore the similarities and differences between volatility in financial markets and turbulent phenomena at a statistical physics level. By analogizing the dynamics of financial markets with fluid turbulence, we have developed an innovative analytical framework aimed at deepening the understanding of the complexity inherent in financial markets. Our research methodology includes a comparative analysis of simulated time series data for the Standard & Poor's 500 Index and fully developed turbulent velocity time series. We focus on the similarities in key statistical physical properties, including probability distributions, correlation structures, and power spectral densities. Furthermore, we have established a model of capital flow in financial markets and proposed corresponding solutions. Through computational simulations and data analysis, we find that while financial market volatility shares some statistical characteristics with turbulent phenomena, significant differences exist in the shapes of probability distributions and the temporal scales of correlations. This suggests that although financial markets exhibit patterns akin to turbulence, the behavior of this complex, multi-variable driven system does not completely correspond to natural turbulence, highlighting the limitations of directly applying turbulence theory to financial market analysis. Our study offers a new perspective for the theories of financial markets and the field of econophysics, providing fresh insights into the complexity of financial markets and contributing to the prevention and management of financial risk.

Solar flares are characterized by sudden bursts of electromagnetic radiation from the Sun’s surface, and caused by the changes in magnetic field states in solar active regions. Earth and its surrounding space environment can suffer from various negative impacts caused by solar flares ranging from electronic communication disruption to radiation exposure-based health risks to the astronauts. In this paper, we address the solar flare prediction problem from magnetic field parameter-based multivariate time series (MVTS) data using multiple state-of-the-art machine learning classifiers that include MINImally RandOm Convolutional KErnel Transform (MINIROCKET), Support Vector Machine (SVM), Canonical Interval Forest (CIF), Multiple Representations SEQuence Learner (Mr-SEQL), and Long Short-Term Memory (LSTM)-based deep learning model. Our experiment is conducted on the on the Space Weather ANalytics for Solar Flares (SWAN-SF) benchmark data set, which is a partitioned collection of MVTS data of active region magnetic field parameters spanning over 9 years of operation of the Solar Dynamics Observatory (SDO). The MVTS instances of the SWAN-SF dataset are labeled by GOES X-ray flux-based flare class labels, and attributed to extreme class imbalance because of the rarity of the major flaring events (e.g., X and M). As a performance validation metric in this class-imbalanced dataset, we used the true skill statistic (TSS) score. Finally, we demonstrate the advantages of the MVTS learning algorithm MINIROCKET, which outperformed the aforementioned classifiers without the need for essential data preprocessing steps such as normalization, statistical summarization, and class imbalance handling heuristics.

The recent availability of commercial platforms for behavioral analysis in zebrafish larvae based on video-tracking technologies has exponentially increased the number of studies analyzing different behaviors in this model organism to assess neurotoxicity. Among the most commonly used assays in zebrafish larvae are basal locomotor activity (BLA) and visual motor response (VMR). However, the effect of different intrinsic and extrinsic factors that can significantly alter the outcome of these assays is still not well understood. In this work we have analyzed in 143 larvae the influence of age (5-8 days post-fertilization), time of day (8:00, 10:00, 12:00, 14:00; 16:00, 18:00, and 20:00 h), and experiment (three experiments performed at different days) on BLA and VMR results (4,004 analyses for each behavior). Results from both behaviors were adjusted to a Random-Effects linear regression model using generalized least squares (GLS), including in the model the effect of the three variables, the second-way interactions between them and the three-way interaction. The results presented in this manuscript show a specific effect of all three intrinsic factors and their interactions on both behaviors, supporting the view that the most stable time period for performing these behavioral assays is from 10:00 am to 04:00 pm, with some differences depending on age of the larva and the behavioral test.

The aim of the research was to determine the most productive tree cutting methods and the factors influencing them in flat and sloping terrain in tree plantations in Brazil. The study utilized drone-captured video material from eucalyptus and pine plantations harvesting operations. In both terrains, two cutting methods were compared, differing in the felling to the side method used: either at the edge of the harvesting front or inside. In addition, on flat terrain, the efficiency of forward felling was studied in relation to the aforementioned methods. In slope terrain, the machines were also equipped with a winch assistance system. Statistical tests were used to determine the most productive cutting methods by analyzing differences in productivity. With an average tree size of 0.3 m3, cutting productivity was 45 m3/E0h in pine cuttings and 55 m3/E0h in eucalyptus cuttings. The average cutting productivity on flat terrain was about 11 m3/E0h higher than on sloping terrain, mainly due to the time spent attaching the winch assistance system, which was a necessary phase of the work in sloping terrain. The research results suggest that it would be the most productive to use sideways felling inside the harvesting front method. However, the need for further research is evident if we want to precisely identify the harvesting conditions and work phases in the tree cutting cycle affecting the differences in the productivity of the harvesting chain in tree plantations.

Addressing non-unions involves stabilizing the affected area through osteosynthesis and improving bone biology using bone grafts. However, there is no consensus on the optimal treatment method. This study aims to compare outcomes of non-union revision using conventional treatment methods (metal hardware ± graft) versus osteosynthesis with the human, allogeneic cortical bone screw (Shark Screw®). Thirty-four patients underwent conventional treatment, while 28 cases received Shark Screws®. Patient demographics, bone healing, time to bone healing, and complications were assessed. Results revealed a healing rate of 96.4% for the Shark Screw® group, compared to 82.3% for the conventionally treated group. The Shark Screw® group exhibited a tendency for faster bone healing (9.4±3.2 vs. 12.9±8.5 weeks, p=0.05061). Hardware irritations led to six metal removals in the conventional group versus two in the Shark Screw® group. The Shark Screw® emerges as a promising option for personalized non-union treatment in the foot, ankle, and select lower leg cases, facilitating effective osteosynthesis and grafting within a single construct, promoting high union rates, low complications, and a rapid healing process.

The aim of the present work is to explore a different non-traditional approach to higher dimensional spacetime which differs from the usual approaches such as large extra space dimensions, warped extra space dimensions and multiple extra time dimensions. This approach will be referred to as "Dynamic" higher dimensional spacetime. By this term will be introduced a new kind of higher dimensional spacetime (more than the usual 3+1 dimensions), which behaves dynamically in the sense that time is not a fixed dimension but is the extra plus one dimension to the spatial dimensions of the phenomenon we are studying. For a higher dimensional phenomenon, the lower dimensional time will behave as space and the new time will be a plus one dimension, meaning if we study a 3-dimensional phenomenon then time is the usual 4th dimension but if we are studying a 4-dimensional phenomenon then its time will be an extra 5th dimension and for this phenomenon the 4th dimension will behave as space. All spatial dimensions are indistinguishable from each other and behave in the exact same way, which means that the important parameter is not the dimension we are studying (for example the 4th or the 5th) but the number of dimensions in which a phenomenon can interact and how higher dimensional phenomena interact with lower ones. This non-traditional approach to higher dimensional spacetime may appear confusing at first but will become clearer in the rest of the paper. For this reason, we will first associate the time dimension with propagation relative to space dimensions and change orthogonal to them in order to give the reader a better intuition. Following that, we will describe how higher - dimensional phenomena would appear to us, the 3 - dimensional observer and try to set some guidelines on how we should mathematically model higher - dimensional phenomena in order for us to make accurate predictions of their behaviour. Then we will express the general framework of a "Dynamic" higher - dimensional spacetime and turn our gaze to 4+1 – dimensional phenomena. We will explore how a mass term arises for 4 – dimensional waves by generalizing the frequency – speed – wavelength relation of 3D waves and give a basic description on a possible way to describe a 4+1 – dimensional disturbance in a scalar Energy Field in order to make accurate predictions on our 3+1 dimensional plane. In this framework we will derive the Klein – Gordon equation by generalizing the wave equation and ignoring all lower than 4+1 - dimensional disturbances and compere our mass term findings with the Klein – Gordon equation mass term and with results from gravity – induced quantum interference experiments. Lastly, we will describe how a "Dynamic" 5 - dimensional spacetime would appear in a 3D observer and examine whether our findings are compatible with quantum mechanics and the special theory of relativity.

We develop a renormalizable model of Quantum General Relativity (QGR). We do this by building on earlier work with quantum electrodynamics (QED). Working with the Feynman path integral (FPI) approach to QED, we generalize the paths from varying in space to varying in space and time. This gives the standard results plus dispersion in time of order attoseconds or left. Over longer times, the dispersion in time averages out, but at attosecond times it should be detectable with current technology. As an unexpected but welcome side-effect, the approach caused the usual loop integrals to be finite. Since the usual UV divergences are significantly harder to renormalize in QGR than in QED, and since using paths in time plus space is definitely more in keeping with the general spirit of GR, we here apply the same approach to QGR. We show that with an appropriate choice of gauge (trace-reversed de Donder gauge) we can extend the earlier results to include QGR. Sub-attosecond measurements of individual gravitons are not within our reach, but at least the ultraviolet divergences in QGR are contained in the same way. We have therefore a renormalizable model of QGR

This study derives space travel pricing by Walrasian Equilibrium, which is logical reasoning from the general relativity theory (GRT), the accounting equation, and economic supply and demand functions. The Cobb-Douglas functions embed the endogenous space factor as new capital to form the space travel firm's production function, which is also transformed into the consumer's utility function. Thus, the market equilibrium occurs at the equivalence of supply and demand functions, like the GRT presents the equivalence between the spatial geometric tensor and the energy-momentum tensor, which explains the principles of gravity and the motion of space matter in the spacetime framework. The mathematical axiomatic set theory of the accounting equation explains the equity premium effect that causes a short-term accounting equation inequality, then reaches the equivalence by suppliers' incremental equity through the closing accounts process of the accounting cycle. On the demand side, the consumption of space travel can be assumed as a value at risk (VaR) investment to attain the specific spacetime curvature in an expected orbit. Spacetime market equilibrium is then achieved to construct the space travel pricing model. The methodology of econophysics and analogy method was applied to infer the space travel pricing by the model of profit maximization, single-minded, and envy-free pricing in unit-demand markets. A case study with simulation was conducted for empirical verification of the math models and algorithm. Results show that space travel pricing remains the principle of market equilibrium but needs to be extended to the spacetime tensor of GRT.

A model of space-time is presented, whose origin is set before the appearance of any universe. It uses concepts of previous work, a central one being that the information about the laws of nature is stored locally everywhere in space such that all physical processes obey them. Since information storage is bound to matter or energy, space is assumed to consist of dark energy (DE), which thus assumes an importance far beyond its function as a stopgap for an energy deficit in our universe (U). The primordial state (PS) is a timeless and relatively large space of 3 dimensions described by a Wheeler DeWitt (WDW) equation, whose solution is interpreted as an arrangement of very many space quanta and possesses all the characteristics of the time-honored concept of the unmoved mover. The comparison of WDW solutions belonging to different mass densities of the DE favors one in which the space quanta are mini black holes, and allows the space quanta to be imagined as mass points that are kept at a distance compatible with the quantum volume by the Pauli principle or something equivalent. Triggered by an increase in probability, the PS is followed by a time-dependent state of space expansion (ES). The concomitant emergence of time occurs in a lightning huge crash, consuming almost all DE of the PS. The subsequent expansion proceeds in quantum leaps, whose huge size emerges from a WDW equation novelly derived from the time-dependent classical expansion solution, and is also used as size of the PS. Information is assumed to be geometrically stored in arrangements of space quanta similar to how genetic information is stored in DNA molecules. During space expansion information must be transferred from already existing "information quanta" to new ones. This requires time, slows down the expansion and is taken into account by a friction term in the cosmological momentum equation. Sinc e the Friedmann-Lemaître (FL) equation remains fully valid, the model can exclusively be based on recognized equations, so that the assumptions used to build it can be understood as interpretations.

Using multi-color flow cytometry analysis, we studied the immunophenotypical differences between leukemic blasts/LSCs from patients with AML/MDS and hematopoietic stem and progenitor cells (HSPCs) from patients in complete remission (CR) following their successful treatment. The panel of markers included CD34, CD38, CD45RA, CD123 as representatives for a hierarchical hematopoietic stem and progenitor cell (HSPC) classification as well as programmed death ligand 1 (PD-L1). Rather than restricting the evaluation on a 2- or 3-dimensional analysis, we applied a t-distributed stochastic neighbor embedding (t-SNE) approach to get a deeper insight and segregation between leukemic and normal HPSCs. For that purpose, we created a t-SNE map, which resulted in the visualization of 27 cell clusters based on their similarity concerning the composition and intensity of antigen expression. Two of these clusters were “leukemia-related” containing a great proportion of CD34⁺/CD38^- hematopoietic stem cells (HSCs) or CD34⁺ cells with a strong coexpression of CD45RA/CD123, respectively. CD34⁺ cells within the latter cluster were also highly positive for PD-L1 reflecting their immunosuppressive capacity. Beyond this proof of principle study, the inclusion of additional markers will be helpful to refine the differentiation between normal HSPCs and leukemic cells, particularly in the context of minimal disease detection and antigen-targeted therapeutic interventions. Furthermore, we suggest a protocol for the assignment of new cell ensembles in quantitative terms, via a numerical value, the Pearson coefficient, based on a similarity comparison of the t-SNE pattern with a reference.

Space exploration is an arduous journey, with future explorations extending in duration, increasing the risk for common space-related health issues such as bone density loss due to microgravity, impaired gut microbiota, cardiovascular ailments, and exposure to cosmic radiation. These ailments can be addressed using medicinal plants. Enhancing their efficacy entails employing gene editing to target specific secondary metabolite pathways associated with therapeutic properties. Moreover, gene editing can combine multiple medicinal properties from various plants, culminating in a singular 'superplant' with enhanced therapeutic benefits. This review discusses the current usage of medicinal plants in promoting human health during space travel, the application of gene editing technology in modifying medicinal plants and presents a vision for the utilization of gene-edited medicinal plants in space to mitigate the risk of various space-related health issues.

Background: One challenge in implant dentistry is to reduce marginal bone resorption to avoid long-term esthetic and biological complications. Sub-gingival implant placement has been suggested as a suitable strategy. Methods: 38 healthy patients were enrolled to receive bone level (BL – Control group) or 2 mm sub-crestal (SC - Test group) conical connection, platform-switched implants. An immediate tissue level abutment was used in the Test group by following a One Time Abutment (OTA) restorative procedure. Marginal Bone Modification (MBM) was calcu-latied on standardized radiographs at surgery (T0), loading (T1), and 6 months (T2) and 12 months after loading (T3), and cathegorised in Bone Loss (BL) if the resorption occurred below the implant neck and Bone Remodeling (BR) if above. Pocket probing depth (PPD), Bleeding on probing (BoP) and Plaque Index (PI) were also collected. Results: The mean MBM in the test group after 12 months was 0.61mm, compared to 0.52mm in the control group. However, no BL was observed in the test group, as the MBM completely occurred above the implant neck as BR, whilst in the control group MBM corresponded in total to BL. The average PPD was 2.38mm in the test group and 3.04mm in the control group after 12 months, BoP 50% and 43%, PI 33% and 19.44% respectively. Conclusions: Sub-crestal conical connection, platform-switched implants could be a suitable clinical choice to avoid BL with exposure of the treated implants surfaces.

When dealing with limited sample sizes or missing values in time series data, achieving high accuracy in forecasting becomes challenging. This challenge is particularly common in wind energy forecasting, where many wind farms lack complete data. In this paper, we employ the widely-used ARIMA (Autoregressive Integrated Moving Average) model for time series forecasting. To address the difficulties posed by limited sample sizes and missing values, we adopt a unique approach by utilizing multiple ARIMA models for different datasets. A key distinction from other multiple models methods for time series forecasting lies in each model within our approach using its own dataset, making the fusion process more intricate. To overcome this, we incorporate neural networks and two techniques for model fusion: direct fusion with a learning mechanism and compensation for missing data through training. For each ARIMA model, we introduce a noise estimation method to circumvent the white noise assumptions inherent in ARIMA models. Finally, we apply these methods to wind energy prediction, and our experimental results showcase a significant enhancement in forecasting accuracy.