A very high-resolution DSM covering an area of 400km² over the Athens Metropolitan Area has been produced using Pleiades 1B 0,5m panchromatic tri-stereo images. Applied Remote Sensing and Photogrammetry tools have been used resulted in a 1x1m DSM over the study area. DSM accuracy has been evaluated by comparison with measured elevations with D-GPS and a reference DSM provided by the National Cadaster & Mapping Agency S.A. In addition, different combinations of stereo images have been prepared for further exploitation of the quality of the produced DSM by stereo vs. tri-stereo images. Results show that the produced by the tri-stereo images DSM has an RMSE of 1.17m in elevation (z), which is among the best reported in the relevant literature. Stereo based DSMs from the same sensor have worst performance to this end. Satellite Remote Sensing (SRS) based DSMs over urban areas provide the best cost-effective approach in comparison to airborne-based datasets due to high spatial coverage, lower cost and high temporal coverage. Pleiades-based high-quality DSM products can serve the domains of urban planning/climate, hydrological modelling and natural hazards, as major input for simulation models and morphological analysis at local scale.

The paper presents an analysis of the latest developments in the field of stereo vision in the low-cost segment, both for prototypes and for industrial designs. We described the theory of stereo vision and presented information about cameras and data transfer protocols and their compatibility with various devices. The theory in the field of image processing for stereo vision processes is considered and the calibration process is described in detail. Ultimately, we presented the developed stereo vision system and provided the main points that need to be considered when developing such systems. The final, we presented software for adjusting stereo vision parameters in real-time in the python language in the Windows operating system.

This study presents an instant preview and analysis system implementation of intelligent stereo cameras (ISCs). A parameter optimization prototype adopted the instant preview and analysis system of the ISCs has been achieved the automatic alignment function, and obtained optimal stereo films with the automatic alignment function by adjusting gap and angle between dual cameras. The instant preview and analysis system of the ISCs with parameter optimization can enhance the quality of stereo films effectively and reduce filmed errors and save retouched cost and time in harsh filmed environment.

With the development of remote sensing satellite technology for Earth observation, remote sensing stereo images have been used for three-dimensional reconstruction in various fields, such as urban planning and construction. However, remote sensing images often include noise, occluded regions, weakly textured areas and repeated textures, which can lead to reduced accuracy in stereo matching and affect the quality of the 3D reconstruction results. To reduce the impact of complex scenes in remote sensing images on stereo matching and to ensure both speed and accuracy, we propose a new end-to-end stereo matching network based on convolutional neural networks (CNNs). The proposed stereo matching network can learn features at different scales from the original images and construct cost volumes with varying scales to obtain richer scale information. Additionally, when constructing the cost volume, we introduce negative disparity to adapt to the common occurrence of both negative and nonnegative disparities in remote sensing stereo image pairs. For cost aggregation, we employ a 3D convolution-based encoder-decoder structure that allows the network to adaptively aggregate information. Before feature aggregation, we also introduce an attention module to retain more valuable feature information, enhance feature representation, and obtain a higher-quality disparity map. By training on the publicly available US3D dataset, we obtain the accuracy that 1.115 pixel in end-point error (EPE) and 5.32% in the error pixel ratio (D1) on the test dataset, and the inference speed is 92 ms. Comparing our model with existing state-of-the-art models, we achieve higher accuracy, and the network is beneficial for the three-dimensional reconstruction of remote sensing images.

This study investigated the factors affecting consumers’ acceptance to use cashless payment services in Malaysia through the construction of the Cashless Society Acceptance (CSA) model. The Technology Readiness Index 2.0 and Unified Theory of Acceptance and Use of Technology 2 were employed to create the CSA model. A total of 434 questionnaires were collected from Malaysian consumers, aged 18 years and above. The results show that Perceived Usefulness, Perceived Ease of Use, and Discomfort have the most significant influence on the consumers’ acceptance of cashless payment services with R-square of 71.4%.

As we all know, many more dynamic objects appear almost continuously in real world, which are immensely able to impair the performance of the majority of vision-based SLAM systems that are based on the static-world assumption. In order to improve the robustness and accuracy of visual SLAM in the high dynamic environment, a real-time and robust stereo SLAM system for dynamic scenes was proposed. To weaken influences of dynamic content, the moving object detection method was put forward in our visual odometry, then the semantic segmentation network was combined into our stereo SLAM to extract pixel-level contours of dynamic objects. Then influences of dynamic objects were extremely weaken and the performance of our system was increased markedly in dynamic, complex and crowed city spaces. Experiment with both on KITTI Odometry dataset and in a real-life scene, the results show that our method can dramatically decrease the tracking error or drift, improve the robustness and stability of our stereo SLAM in high dynamic outdoor scenarios.

The Compact Midwave Imaging System (CMIS) is a wide field of view, multi-angle, multi-spectral pushframe imager that relies on the forward motion of the satellite to create a two-dimensional (2D) image swath. An airborne demonstration of CMIS was successfully completed in January-February 2021 on the NASA Langley Research Center Gulfstream III. The primary objective of the four-flight campaign was to demonstrate the capability of this unique instrument to perform stereo observations of clouds and other particulates (e.g. smoke) in the atmosphere. It is shown that the midwave infrared (MWIR) spectral bands of CMIS provide a unique 24/7 capability with high resolution for accurate stereo sensing. The instrument relies on new focal plane array (FPA) technology, which provides excellent sensitivity at much warmer detector temperatures than traditional technologies. This capability enabled a compact, low-cost design that can provide atmospheric motion vectors and cloud heights to support requirements for atmospheric winds in the 2017-2027 Earth Science Decadal Survey. Applications include day/night observations of the planetary boundary layer, severe weather, and wildfires. A comparison with current space-based earth science instruments demonstrates that the SWIR/MWIR multi-spectral capability of CMIS is competitive with larger, more expensive instrumentation. Imagery obtained over a controlled burn and operating nuclear power plant demonstrated the sensitivity of the instrument to temperature variations. The system relies on a mature stereoscopic imaging technique applied to the same scene from two independent platforms to unambiguously retrieve atmospheric motion vectors (AMVs) with accurate height assignment. This capability has been successfully applied to geostationary and low-earth orbit satellites to achieve excellent accuracy. When applied to a ground-point validation case, the accuracy for the CMIS aircraft observations was 20 m and 0.3 m/s for cloud heights and motion vectors, respectively. This result was confirmed by a detailed error analysis with analytical and covariance models. The results for CMIS cases with underflights of Aeolus, CALIPSO and Aqua provided a good validation of expected accuracies. The paper also showed the feasibility of accommodating CMIS on CubeSats to enable multiple instruments to be flown in a leader-follower mode.

Newly build offshore wind farms (OWFs) render a collision risk between ships and installations. The paper proposed a real-time traffic monitoring method based on machine vision and deep learning technology to improve the efficiency and accuracy of the traffic monitoring system in the vicinity of offshore wind farms. Specifically, the method employs real automatic identification system (AIS) data to train a machine vision model, which is then used to identify passing ships in OWF waters. Furthermore, the system utilizes stereo vision techniques to track and locate the positions of passing ships. The method is tested in offshore water in China to validate its reliability. The results prove that the system sensitively detects the dynamic information of the passing ships, such as the distance between ships and OWFs, ship speed and course. Overall, this study provides a novel approach to enhancing the safety of OWFs, which is increasingly important as the number of such installations continues to grow. By employing advanced machine vision and deep learning techniques, the proposed monitoring system offers an effective means of improving the accuracy and efficiency of ship monitoring in challenging offshore environments.

Accurately estimating the current state of local traffic scenes is one of the key problems in the development of software components for automated vehicles. In addition to details on free space and drivability, static and dynamic traffic participants, information on the semantics may also be included in the desired representation. Multi-layer grid maps allow to include all this information in a common representation. However, most existing grid mapping approaches only process range sensor measurements such as LIDAR and Radar and solely model occupancy without semantic states. In order to add sensor redundancy and diversity it is desired to add vision based sensor setups in a common grid map representation. In this work, we present a semantic evidential grid mapping pipeline including estimates for eight semantic classes that is designed for straightforward fusion with range sensor data. Unlike in other publication our representation explicitly models uncertainties in the evdiential model. We present results of our grid mapping pipeline based on a monocular vision setup and a stereo vision setup. Our mapping resulsts are accurate and dense mapping due to the incorporation of a disparity- or depth-based ground surface estimation in the inverse perspective mapping. We conclude this paper by providing a detailed quantitative evaluation based on real traffic scenarios in the Kitti odometry benchmark and demonstrating the advantages compared to other semantic grid mapping approaches.

We propose an approach for estimating the error in depth data provided by generic 3D sensors, which are modern devices capable of generating an image (RGB data) and a depth map (distance) or other similar 2.5D structure (e.g. stereo disparity) of the scene. Our approach starts capturing images of a checkerboard pattern devised for the method. Then proceed with the construction of a dense depth map using functions that generally comes with the device SDK (based on disparity or depth). The 2D processing of RGB data is performed next to find the checkerboard corners. Clouds of corner points are finally created (in 3D), over which an RMS error estimation is computed. We come up with a multi-platform system and its verification and evaluation has been done, using the development kit of the board nVIDIA Jetson TK1 with the MS Kinects v1/v2 and the Stereolabs ZED camera. So the main contribution is the error determination procedure that does not need any data set or benchmark, thus relying only on data acquired on-the-fly. With a simple checkerboard, our approach is able to determine the error for any device. Envisioned application is on 3D reconstruction for robotic vision, with a series of 3D vision sensors embarked in robots (UAV of type quadcopter and terrestrial robots) for high-precision map construction, which can be used for sensing and monitoring.

Dynamic optical structural color is always desired in various display applications and usually involves active materials. Full-color generation, especially bi-directional full-color generation in both reflective and transmissive modes, without any active materials included has been rarely investigated. Herein, we demonstrate a scheme of bi-directional full-color generation based on a plasmonic metasurface modulated by rotation of the polarization angle of the incident light without varying the geometry and the optical properties of the materials and the environment where the metasurface resides. The metasurface unit cell consists of plasmonic modules aligning in three directions and is patterned in a square array. The metasurface structural color device generates full colors in both reflection and transmission. Based on the proposed polarization-dependent structural color, information encoding of three multiplexed animal images and quick-responsive (QR) codes is demonstrated to verify the efficient information encoding and decoding of the proposed scheme. The animals can be seen under different polarization incidence and the QR codes can be successfully decoded by the polarization rotation in transmission. The proposed bi-directional full-color generation metasurface has great potential in applications such as kaleidoscope generation, anti-counterfeiting, dynamic color display, and optical information encoding.

The study investigates the influence of road intersections on pedestrian accessibility in urban-rural fringe areas. An evaluation method to support planners and decision makers in the classification of crossing areas according to their effect on walking and in the prioritization of improvement interventions is proposed. In these peripheral parts of towns, pedestrians are almost ignored and people depend on car use for any necessity. Initiatives to improve livability can include the design of walkable friendly environments aiming at offering potential users good levels of security, comfort and convenience when walking to destinations. These spatial requirements have to be provided along road segments and even more on crossing areas which represent sensitive points of the entire connection system with a hindering influence on people’s propensity to walk. Starting with spatial basic interventions aiming at enhancing the continuity, safety and quality of pedestrian paths it is possible to reduce the physical and perceptual distance which separates fringe contexts from the rest of the city leading to a progressive integration of urban functions.

Smart City has emerged as the mainstream paradigm for urban governance innovation, sustainable development, and strategy upgrades, which is drawing attention from scholars worldwide. However, current frameworks for Smart City assessment remain incomplete and simplistic. In is paper, 30 national or provincial capitals in China were selected and we designed a tri-dimensional SPI model—Social, Physical, and Information Space—for smart city spatial development assessment. Utilizing methods such as entropy weighting, coupled coordination degree models, and the Dagum Gini coefficient, this study assesses the spatial development and coupled coordination of 30 cities from 2011 to 2019. Finally, by means of BP neural networks, the study examines the contribution of each indicator to the spatial coupled coordination. The results indicated that with a narrowing disparity in development speeds among different regions, the spatial coupled coordination development level of smart capitals in China has steadily increased, presenting a pattern of staggered distribution. Moreover, the IS subsystem plays the most significant role in coupled coordination. The significance of this research lies in its tri-dimensional spatial perspective of the spatial development and coupled coordination differences of the Smart City, providing evidence-based support for the regional layout and optimization in China.

This experimental study probes the dynamic behaviour of a 3mm ABS sheet during positive mould vacuum-assisted thermoforming. In this process, the sheet undergoes large and fast deformations, caused by the applied vacuum and mechanical stretching by the mould. The objective is to elucidate the complexities of these large, rapid and non-isothermal deformations. The non-isothermal conditions are caused by the radiative heating of the sheet, convective heat loss to the surrounding air and conductive heat transfer from the sheet to the mould. Utilizing stereo Digital Image Correlation (DIC) in tandem with thermal imaging, the present study accurately maps the occurring displacement, strain and strain rate field in relation to real-time temperature variation of the material. The study progresses to observe the ABS material from the moment it contacts the mould until it conforms to a positive 250mm diameter semi-sphere cast aluminium mould. The DIC methods are validated by comparing thickness values derived from DIC’s principal strain directions to ultrasonic thickness gauge readings. This knowledge not only broadens the understanding of the thermo-mechanical behaviour of the material but also aids in optimizing process parameters for improved thickness uniformity in thermoformed products.

Self-driving vehicles demand efficient and reliable depth sensing technologies. Lidar, with its capacity for long-distance, high-precision measurement, is a crucial component in this pursuit. However, conventional mechanical scanning implementations suffer from reliability, cost, and frame rate limitations. Solid-state lidar solutions have emerged as a promising alternative, but the vast amount of photon data processed and stored using conventional direct time-of-flight (dToF) prevents long-distance sensing unless power-intensive partial histogram approaches are used. In this paper, we introduce a groundbreaking ‘guided’ dToF approach, harnessing external guidance from other onboard sensors to narrow down the depth search space for a power and data-efficient solution. This approach centers around a dToF sensor in-which the exposed time widow of independent pixels can be dynamically adjusted. We utilize a 64-by-32 macropixel dToF sensor and a pair of vision cameras to provide the guiding depth estimates. Our demonstrator captures a dynamic outdoor scene at 3 fps with distances up 75 m. Compared to a conventional full histogram approach, on-chip data is reduced by over 25 times, while the total laser cycles in each frame are reduced by at least 6 times compared to any partial histogram approach. The capability of guided dToF to mitigate multipath reflections is also demonstrated. For self-driving vehicles where a wealth of sensor data is already available, guided dToF opens new possibilities for efficient solid-state lidar.

A waterbody detection technique is an essential part of digital elevation model (DEM) generation to delineate land-water boundaries and set flattened elevations. This paper describes the technical methodology for improving the initial tile-based waterbody data that are created during production of the ASTER GDEM, because without improvement such tile-based waterbody data are not suitable for incorporating into the new ASTER GDEM Version 3. Waterbodies are classified into three categories: sea, lake, and river. For sea-waterbodies, the effect of sea ice is removed to better delineate sea shorelines in high latitude areas, because sea ice prevents accurate delineation of sea shorelines. For lake-waterbodies, the major part of the processing is to set the unique elevation value for each lake using a mosaic image that covers the entire lake area. Rivers present a unique challenge, because their elevations gradually step down from upstream to downstream. Initially, visual inspection is required to separate rivers from lakes. A stepwise elevation assignment, with a step of one meter, is carried out by manual or automated methods, depending on the situation. The ASTER GWBD product consists of a global set of 1º latitude-by-1º longitude tiles containing water body attribute and elevation data files in geographic latitude and longitude coordinates and with one arc second posting. Each tile contains 3601-by-3601 data points. All improved waterbody elevation data are incorporated into the ASTER GDEM to reflect the improved results.

The topological index is a numerical quantity based on the characteristics of various invariants or molecular graph. For ease of discussion, these indices are classified according to their logical derivation from topological invariants rather than their temporal development. Degree based topological indices depends upon the degree of vertices. This paper computes Zagreb polynomials and redefined first, second and third Zagrebindices of Bismuth Tri-Iodide chains and sheets.

The topological index is a numerical quantity based on the characteristics of various invariants or molecular graph. For ease of discussion, these indices are classified according to their logical derivation from topological invariants rather than their temporal development. Degree based topological indices depends upon the degree of vertices. This paper computes degree based topological indices of Bismuth Tri-Iodide chains and sheets with the help of M-polynomial.

Over a century ago, low-dose-rate (LDR) brachytherapy was introduced to treat prostate cancer (PCa). Since then, it has been widely applied worldwide, including in East Asia. LDR brachythera-py has been performed in 88 institutes in Japan. Beneficial clinical outcomes of LDR brachytherapy for intermediate-to-high-risk PCa have been demonstrated in large clinical trials. These clinical outcomes were achieved through advances in methods, such as urological precise needle puncture and seed placement, and the quantitative decision-making regarding radiological parameters by radiation oncologists. Combined use of LDR brachytherapy with other therapeutical modalities, such as external beam radiation and androgen deprivation therapy, for clinical risk classification of PCa has led to better anticancer treatment efficacy. In this study, we summarized basic LDR brachytherapy findings that should remain unchanged and be passed down in urology depart-ments. We also discussed the applications of LDR brachytherapy for PCa in various clinical settings, including focal and salvage therapies. In addition, we highlighted technologies associated with brachytherapy that are under development.

ORB (Oriented FAST and Rotated Brief) features are the most commonly used features in visual SLAM and visual odometry that have high computational speed, and rotation scale invariance. However, due to the homogenization of ORB features, the corner properties of specific features are poor in some artificial environments, and it can lead to poor matching performance when the environmental texture is not rich. The underlying reason is that the pixel grayscale changes in the less-richly textured regions on the image are not obvious, leading to a certain degree of mis-matching in the matching process. At the same time, when the camera motion speed is low, there is much overlap between adjacent frames. This results in minimal or almost no changes in the projection of feature points, and the system is highly sensitive to errors, In this case, even small errors can cause significant fluctuations in the calculation results. In response to the above issues, an improved feature point method for stereo vision mileage calculation is proposed to solve the problem of system stability deterioration when cameras move at low speeds in artificial envi-ronments. Firstly, weight calculation based on different texture regions is used to solve the problem of low corner properties of feature points caused by environmental texture differences. Then, keyframes are used for motion model estimation to improve the system's stability under low-speed motion. The experimental results of the dataset showed that the key frame rate was optimal between 10% and 12%, and the positioning accuracy was higher than these open-source systems compared with three common open-source VO systems.

We investigated experimentally, analytically and numerically the formation process of double emulsion formations under dripping regime in a tri-axial co-flow capillary device. The results show that mismatches of core and shell droplets under a given flow condition can be captured both experimentally and numerically. We propose a semi-analytical model using the match ratio between the pinch-off length of the shell droplet and the product of the core growth rate and its pinch-off time. The mismatch issue can be avoided if the match ratio is lower than unity. We considered a model with the wall effect to predict the size of the matched double emulsion. The model shows slight deviations with experimental data if the Reynolds number of continuous phase is lower than 0.06, but asymptotically approaches to good agreement if the Reynolds number increases from 0.06 to 0.14. The numerical simulation generally agrees with the experiments under various flow conditions.

The thermal stabilizers, lubricant, and plasticizers are three crucial additives for processing poly (vinyl chloride) (PVC). In this study, a new mannitol stearate ester-based aluminum alkoxides (MSE-Al) was designed and synthesized as a novel additive for PVC. The thermal stability and processing performance of PVC stabilized by MSE-Al were evaluated by Congo red test, conductivity measurement, thermal aging test, ultravioletevisible (UV-vis) spectroscopy test, and torque rheometer test. Results showed that the addition of MSE-Al can not only markedly improve the long-term thermal stability of PVC, but also greatly accelerate the plasticizing and decrease the balance torque which demonstrated that MSE-Al possesses the lubricating property. Thus, MSE-Al was demonstrated to be able to provide tri-functional additive roles, e.g., thermal stabilizer, plasticizer, and lubricant. The test results for the thermal stability of PVC indicated that the initial whiteness of PVC stabilized with MSE-Al was not good enough, thus the synergistic effect of MSE-Al with zinc stearates (ZnSt₂) on the thermal stability of PVC was also investigated. The results showed that there exhibited an appreciable synergistic effect between MSE-Al and ZnSt₂. The thermal stabilization mechanism and synergism effect of MSE-Al with ZnSt₂ were then discussed.

The National Research Centre’s experimental research station (NRCERS) locates in Wadi El Natrun, Egypt 30°29'54.22"N 30°19'10.94"E. The NRCERS has various crop yields (vegetables, fruits, ornamental, and field crops) for different experimental treatments. It followed conventional agricultural procedures in vegetation, fertilisation, irrigation, and plant protection. Such policies have not been evaluated for their impacts on arthropod diversity and distribution. Thus, this study conclusion aims to sufficiently map the arthropod species (pest/predators) distribution, measure the biodiversity indices, to the NRCERS agricultural policies to be modified to support arthropod diversity.

Communication, compression of information, transmission of information through noisy channels, interconnecting different information systems, cryptography, gate construction –– these areas all depend on classical information theory. We show that, in classical terms, semantic aspects of communication are not at all irrelevant to the engineering problem, contrary to Shannon, and affect the message intended to be transmitted. This is revisited and captured by an analogy to trust, in that they are essential to the channel (for proper use), but cannot be transferred (under risk of flaws) through that same channel. Information is also described by, at least, a tri-state system — not by binary logic. The trust analogy semantics can be coded as the Curry-Howard relationship, connecting computer code with structural logic, by way of different categories. Two-state and Boolean logic (aka Shannon semantics) was used classically before, with Shannon theory, but without trust analogy semantics – found to be a sine qua non condition. This is now familiar in classical gate construction with physical systems with, e.g., Verilog and SystemVerilog. The applications to computation and quantum theory are further explored. The most fundamental entity in today`s theory of information is proposed to use at least three logical states, not bits, in all applications, including: cyber-physical systems, devices, in computation, and in quantum theory.

Low-cost RGB-D cameras are increasingly used in several research fields including human-machine interaction, safety, robotics, biomedical engineering and even Reverse Engineering applications. Among the plethora of commercial devices, the Intel RealSense cameras proved to be among the best suitable devices, providing a good compromise between cost, ease of use, compactness and precision. Released on the market in January 2018, the new Intel model RealSense D415 has a wide acquisition range (i.e. ~160-10000 mm) and a narrow field of view to capture objects in rapid motion. Given the unexplored potential of this new device, especially when used as a 3D scanner, the present work aims to characterize and to provide metrological considerations on the RealSense D415. In particular, tests are carried out to assess the device performances in the near range (i.e. 100-1000 mm). Characterization is performed by integrating the guidelines of the existing standard (i.e. the German VDI/VDE 2634 part 2 normative) with a number of literature-based strategies. Performance analysis is finally compared against latest close-range sensors, thus providing a useful guidance for researchers and practitioners aiming to use RGB-D cameras in Reverse Engineering applications.

The study’s objective is to analyse the mechanical properties of steel pipe piles as a part of a trestle bridge subjected to five years of natural marine corrosion degradation. Sixteen tensile specimens were extracted from the steel pipe piles in the splash, tidal, and immersion zones. The experimental tensile test results are used to establish regression equations defining elastic modulus, yield strength, strain hardening index, and strength coefficient for the true stress-strain curves of the three regions. A non-linear time-dependent mathematical model is exploited to identify the corrosion degradation using the data from one single corrosion degradation measurement campaign. The analysis indicated that the splash zone experiences the most severe corrosion degradation, and there are progressive losses in the mechanical properties of each zone as the corrosion degradation progresses. The established relationships of the mechanical properties, as a function of the ratio of corroded plate thickness to the as-built one, can be used as a fast-engineering approach to identify the mechanical properties of severely corroded piles. The corrosion degradation allowance is also defined using the First Order Reliability Method, accounting for existing uncertainties covered by the partial safety factors. By examining the impact of marine corrosion on the mechanical properties of marine structures and developing predictive models to assess the corrosion’s effect on material strength and corrosion allowance, the study aims to improve offshore structures’ safety, design, and maintenance.

Energy demand and consumption in recent times have witnessed a rapid proliferation influenced by technological developments, increased population and economic growth. This has fuelled research trends in the domain of energy management employing tri-generation systems such as the combined cooling, heating and power (CCHP) systems. Furthermore, the incorporation of renewable energy, especially solar energy, to complement the thermal input by fossil fuels has facilitated the effectiveness and sustainability of CCHP systems. This study proposes a new approach to improve the overall efficiency of CCHP systems and compute the optimal design parameters in order to assist decision makers to identify the best geometrical configuration. A multi-objective optimization formulation of a solar-assisted CCHP system was adopted to maximize the net power, the exergy efficiency and minimize the CO2 emission using the greywolf optimization technique. In addition, the effects of the decision variables on the objective functions were analysed. The proposed optimization approach yielded 100 set of Pareto optimal solutions which would serve as options to the decision maker to make a selection in order to improve the performance of a solar-assisted CCHP system. This study demonstrates that the proposed approach is potentially suitable for the optimization of a solar-assisted CCHP system.

Pre-mRNA splicing is an essential process orchestrated by the spliceosome, a dynamic complex assembled stepwise on pre-mRNA. We have previously identified that USH1G protein SANS regulates pre-mRNA splicing by mediating the intra-nuclear transfer of the spliceosomal U4/U6.U5 tri-snRNP complex. During this process, SANS interacts with the U4/U6 and U5 snRNP-specific proteins PRPF31 and PRPF6 and regulates splicing, which is disturbed by variants of USH1G/SANS causative for human Usher syndrome (USH) the most common form of hereditary deaf-blindness.Here, we aimed to gain further insight into the molecular interaction of the splicing molecules PRPF31 and PRPF6 to the CENTn domain of SANS using fluorescence resonance energy transfer assays in cells and in silico deep learning-based protein structure predictions. This demonstrates that SANS directly binds via two distinct conserved regions of its CENTn to the two PRPFs. In addition, we provide evidence that these interactions occur sequentially and a conformational change of an intrinsically disordered region to a short α-helix of SANS CENTn2 is triggered by binding of PRPF6. Furthermore, we found that pathogenic variants of USH1G/SANS perturb the binding of SANS to both PRPFs implying a significance for the USH1G pathophysiology.

Global wind observations are fundamental for studying weather and climate dynamics. Most wind measurements come from atmospheric motion vectors (AMVs) by tracking the displacement of cloud or water vapor features. These AMVs generally rely on thermal infrared (IR) techniques for their height assignments, which are subject to large uncertainties in the presence of weak or reversed vertical temperature gradients around the planetary boundary layer (PBL) and with tropopause folding. Stereo imaging can overcome the height assignment problem using geometric parallax for feature height determination. In this study we develop a stereo 3D-Wind algorithm to simultaneously retrieve AMV and height from geostationary (GEO) and low Earth orbit (LEO) satellite imagery and apply it to collocated Geostationary Operational Environmental Satellite (GOES) and Multi-angle Imaging SpectroRadiometer (MISR) imagery. The new algorithm improves AMV and height relative to products from GOES or MISR alone, with an estimated accuracy of <0.5 m/s in AMV and <200 m in height with 2.2 km sampling. The algorithm can be generalized to other LEO-GEO or GEO-GEO combinations for greater spatiotemporal coverage. The technique demonstrated with MISR and GOES has important implications for future high-quality AMV observations, for which a low-cost constellation of CubeSats can play a vital role.

Quantum computing arrives. Preceded by Mādhava of Sangamagrāma and other Hindu mathematicians, around 1,500 CE, and our previous work, we show at least 4 quantum properties that are indeed universal in some number systems; here we use them to enable quantum computing. Using the sets B={0,1}, B^n, N, Z, Q, and Q*, one has +4 quantum properties that one can trust, as archetypes of easy communication to friends and foes, to ignoranti or cognoscenti, and for quantum consciousness. Therefore, this work applies to computer calculations, apps in cell phones, algebra, atoms, mathematics, physics, and the human mind.

AbstractPolyamines (PAs) including putrescine (PUT), spermidine (SPD) and spermine (SPM) are small, versatile molecules with two or more positively charged amino groups. Despite their importance for almost all forms of life, their specific roles in molecular and cellular biology remain partly unknown. The molecular structures of PAs suggest two presumable biological functions: (i) as potential buffer systems and (ii) as interactants with poly-negatively charged molecules like nucleic acids.The present report focuses on the question, whether the molecular structures of PAs are essential for such functions, or whether other simple molecules like small peptides with closely spaced positively charged side chains might be suitable as well. Consequently, we created titration curves for PUT, SPD, and SPM, as well as for oligolysines like tri-, tetra-, and penta-lysine. None of the molecules provided substantial buffering capacity at physiological intracellular pH values. Apparently, the most important mechanism for intracellular pH homeostasis in neurons is not a buffer system but is provided by the actions of the sodium-hydrogen and the bicarbonate-chloride antiporters.In a similar approach we investigated the interaction with DNA by following the extinction at 260 nm when titrating DNA with the above molecules. Again, PUT and tri-lysine were not able to interact with herring sperm DNA, while SPD and SPM were. Obviously, the presence of several positively charged groups on its own is not sufficient for the interaction with nucleic acids. Instead, the precise spacing of these groups is necessary for biological activity.

We present a new vision on the double-slit experiment (DSE), that does not use any waves or the so-called wave-particle duality. It is based on particles, viewed as localized vibrations. Rather than being illogical, or mysterious, the approach reproduces logically the interference patterns observed externally, using the well-known ``amplification of stimulated emission'' (ASE). The conservation of particle number is not observed. Different particles can present ASE with in-phase or counter-phase behavior, making the patterns observed for electrons, other particles, even atoms. The Law of the Excluded Middle (LEM) is not broken illogically in two-states macroscopically, but broken naturally in three or more states, microscopically, using ASE. Any particle supporting ASE, in-phase or counter-phase, can enter a DSE, and provide an external interference pattern. Frequency plays a role, while amplitude is not considered. This work is important in quantum computing, possibly saving cost, time, and welcoming more participants.

The emergence of new methodologies and tools for digitizing objects belonging to the Cultural Heritage (CH) changed the paradigms adopted so far. Traditionally, the process to acquire artifacts required specialized and often costly equipment tailored to specific purposes. However, the development of more generalized, adaptable, and affordable tools led to novel approaches. This manuscript provides a glimpse into the evolving landscape of custom-made tools for digital documentation, both hardware and software, and their transformative impact on the digitization techniques, built to meet requirements of specific case studies, including ancient drawings, manuscripts, paintings, and museum objects. The advent of self-built instruments has revolutionized the way professionals work today, by leveraging a new generation of low-cost, adaptable gears, leading to unprecedented flexibility and efficiency, while facilitating the capture of high-quality digital representations of objects with minimal damage and preserving their integrity. The outcomes of instruments and tools specifically produced for the contexts described in this paper highlight their potential for promoting interdisciplinary collaboration, facilitating scholarly research, enhancing conservation efforts, and fostering cultural exchange. Ultimately, this research contributes to illustrate how custom software, in combination with recent devices such as smartphones and 3D printers, underscores the importance of adopting these innovative approaches to generate an ecosystem of tools and methods able to preserve, document, and promote the richness of our collective past for future generations.

Structure from Motion with Multi-View Stereo photogrammetry (SfM) is increasingly utilised in geoscience investigations as a cost-effective method of acquiring high resolution (sub-meter) topographic data, but has not been thoroughly tested in gullied savanna systems. The aim of this study was to test the accuracy of topographic models derived from aerial (via an Unmanned Aerial Vehicle, ‘UAV’) and ground-based (via a handheld digital camera, ‘Ground’) SfM in modelling a hillslope gully system in dry-tropical savanna, and to assess the strengths and limitations of the approach at different scales. A UAV survey covered an entire hillslope gully system (0.715 km²), whereas a Ground survey covered a single gully within the broader system (650 m²). SfM topographic models, including Digital Surface Models (DSM) and dense point clouds, were compared against RTK-GPS point data and a pre-existing airborne LiDAR Digital Elevation Model (DEM). Results indicate UAV SfM can deliver topographic models with a resolution and accuracy suitable to define gully systems at a hillslope scale (e.g., 0.1 m resolution with ~ 0.5 – 1.3 m elevation error), while ground-based SfM is more capable of quantifying gully morphology (e.g., 0.01 m resolution with ~ 0.1 m elevation error). Key strengths of SfM for these applications include: the production of high resolution 3D topographic models and ortho-photo mosaics, low survey instrument costs (< $AUD 3,000); and rapid survey time (4 and 2 hours for UAV and Ground survey respectively). Current limitations of SfM include: difficulties in reconstructing vegetated surfaces; uncertainty as to optimal survey and processing designs; and high computational demands. Overall, this study has demonstrated great potential for SfM to be used as a cost-effective tool to aid in the mapping, modelling and management of hillslope gully systems at different scales, in tropical savanna landscapes and elsewhere.

Height assignment is an important problem for satellite measurements of Atmospheric Motion Vectors (AMVs) that are interpreted as winds by forecast and assimilation systems. Stereo methods assign heights to AMVs from the parallax observed between observations from different vantage points in orbit while tracking cloud or moisture features. In this paper, we fully develop the stereo method to jointly retrieve wind vectors with their geometric heights from geostationary satellite pairs. Synchronization of observations between observing systems is not required. NASA and NOAA stereo-winds codes have implemented this method and we have processed large datasets from GOES-16, -17, and Himawari-8. Our retrievals are validated against rawinsonde observations and demonstrate the potential to improve forecast skill. Stereo winds also offer an important mitigation for the loop heat pipe anomaly on GOES-17 during times when warm focal plane temperatures cause infra-red channels that are needed for operational height assignments to fail. We also examine several application areas, including deep convection in tropical cyclones, planetary boundary layer dynamics, and fire smoke plumes, where stereo methods provide insights into atmospheric processes. The stereo method is broadly applicable across the geostationary ring where systems offering similar Image Navigation and Registration (INR) performance as GOES-R are deployed.