Marine renewable energy technologies have a great potential in supplying clean electricity to millions of people across the globe, if technical and economic conditions are in right. So far, ocean energy projects are commonly started by SMEs or educational institutions with limited budgets. Therefore, any effort to reduce expenses is of great value. One of the areas involving substantial expenses are the inevitable seabed inspection prior to deployment of marine renewable energy device. Detailed seabed inspections can also reduce the risk of associated with deployment of structures on uneven seabed, especially marine renewable energy devices with gravity foundations. By reducing the costs and risks of such surveys prior and during the installation phases, the feasibility of marine renewable energy projects can be more favoured and competitive. In this perspective, this study proposes a cost and time effective technique for seabed surveys. The proposed technique involves the use of high precision and inexpensive sonar systems and underwater optical cameras integrated into a versatile and compact subsea monitoring platform. It also involves simple and practical data acquisition and processing protocols that do not requires hi expertise for operation. The results obtained showed that high resolution bathymetric maps and detailed seabed inspections imagery can be acquired. This study concludes that a simple and inexpensive subsea monitoring platform comprising a multibeam, dual beam and video cameras can be effective for high resolution seabed inspection and bathymetric measurements for marine energy applications.

Pore Forming Toxins (PFTs), formed mainly by virulence factors of bacteria, belongs to Pore Forming Protein (PFP) family. Secreted as soluble monomers, they bind specific targets in membranes where their oligomerization and insertion place. Lysenin, a member of the PFTs, forms and oligomer after sphingomyelin binding, the so-called prepore, which become inserted forming a pore after a conformational change triggered by a pH decrease. In crowded conditions, oligomers tends to stay in prepore form because the prepore-to-pore transition is sterically blocked. In this study, we investigate the effect of calcium ions in those crowded conditions, finding that calcium act as a trigger for lysenin insertion. We localize the residues responsible for calcium sensitivity in a small α-helix. Our results are not only one of the few complete structural descriptions of prepore-to-pore transitions but the very first that involves a calcium triggering mechanism. The presence of glutamic or aspartic acids in the insertion domains could be an indication that calcium may be a general trigger for PFTs and more generally PFP.

High fat-diet (HFD) feeding is known to induce metabolic dysregulation, however less is known on its impact in promoting the hypercoagulable state. The current study aimed to evaluate platelet-monocyte aggregate (PMA) formation following short-term HFD feeding. This is particularly important for understanding the link between inflammation and the hypercoagulable state during the early onset of metabolic dysregulation. To explore such a hypothesis, mice were fed a HFD for 8 weeks, with body weights as well as insulin and blood glucose levels monitored on weekly basis during this period. Basal hematological measurements were determined and the levels of spontaneous peripheral blood PMAs were assessed using whole blood flow cytometry. The results showed that although there were no significant differences in body weights, mice on HFD displayed impaired glucose tolerance and markedly raised insulin levels. These metabolic abnormalities were accompanied by elevated baseline PMA levels as an indication of hypercoagulation. Importantly, it was evident that baseline levels of monocytes, measured using the CD14 monocyte marker were significantly decreased in HFD-fed mice when compared to controls. In summary, the current evidence shows that in addition to causing glucose intolerance, such as that identified in a prediabetic state, HFD-feeding can promote undesirable hypercoagulation, the major consequence implicated in the development of cardiovascular complications.

Sulfonated carbon was used as an efficient and reusable heterogeneous solid acid catalyst for the synthesis of biodiesel via esterification of oleic acid with methanol under high voltage conditions. Using an inexpensive and reusable catalyst, environmental benignity, excellent yields in short times, synthesis in atmospheric pressure and low temperature conditions are some of the important features of this protocol. In the final results were confirmed by GC.

The open source CFD code OpenFOAM has emerged as one of the most popular alternative to commercial CFD solvers. The recent version of OpenFOAM supports overlapping grids, so called Overset mesh. In this type of mesh, one or more sub-collection of control volumes (or cells) are allowed to overlap with other set of cells. This allows for great flexibility in modelling Fluid Structure Interaction (FSI) problems. Fluid mesh can be standard structured mesh of a rectangular/cuboidal/or cylindrical domain. The structure mesh can be generated separately by creating multiple layers around a given body. The overset mesh functionality allows for overlapping or immersing this structured mesh inside the fluid mesh and a relevant FSI or moving dynamics problems can be solved. The idea of overset mesh has been around since eighties but its support in OpenFOAM is very recent. Most CFD codes which support overset mesh have either been in-house or commercial CFD codes. OpenFOAM's support for overset is the first major open source code resource available for CFD problems. The aim of this research is to solve a classical benchmark airfoil problem using OpenFOAM overset mesh and compare the numerical results with experimental result. We report here flow simulations results around NACA 0018. The result obtained from overset mesh compares convincingly well with experimental results. Computations have been carried out for Reynolds numbers in the range of 10⁵ with angle of attack ranging from α= 5 degree to α= 30 degree with an interval of 5 degree. Turbulence is incorporated using k - ε turbulence model. This study helps developing confidence in using OpenFOAM overset support for more complicated flows and moving dynamics. This report is complemented with a brief description of finite volume discretization using overset mesh.

Currently the rapid growth of global economy has the competition among high-tech industries develop from regional to global, and the competition becomes fierce. In face of such fierce competition in global high-tech industry, it is realized that tangible assets could no longer be the differentiation basis, but intangible assets are regarded as the differentiation capital. An enterprise with sustainable innovation would dominate the world market and enhance the international competitiveness of domestic economy. When internal entrepreneurial culture is prevalent, an enterprise would naturally promote the innovation capability. Such a point of view also explains more popular of the innovative products or services of some enterprises than those with larger scales. Aiming at employees in high-tech industry in Guanxi Province, total 500 copies of questionnaire are randomly distributed, and 337 valid copies are retrieved, with the retrieval rate 67%. The research results reveal significantly positive correlations between 1.entrepreneurial culture and sustainable innovation capability, 2.sustainable innovation capability and patent, and 3.entrepreneurial culture and patent. According to the results, suggestions are proposed, expecting to explain how a high-tech business outperforms in the changeable digital era and acquires the sustainable innovation capability and patent to grasp the opportunity.

The Gleeble-1500D thermal simulation test machine was used to conduct the isothermal compression test on 21-4N at the strain rate ( ) of 0.01-10s-1, the deformation temperature (T) of 1273-1453K and the maximum deformation is 0.916. The data of the stress-strain ( - )were obtained. Based on the - data, the Johnson-Cook (J-C), modified J-C, Arrhenius and Back-Propagation Artificial Neural Network (BP-ANN) models were established. The accuracy of four models were verified, analyzed and compared. The results show that J-C model has a higher accuracy only under reference deformation conditions. When the deformation condition changes greatly, the accuracy of J-C model is significantly reduced. The coupling effect of T and of modified J-C model is considered, and the prediction accuracy is greatly improved The Arrhenius model introduces Zener-Hollomon (Z) to represent the coupling effect of T and , it has a fairly high prediction accuracy. And it can predict flow stress ( ) accurately at different conditions. The accuracy of BP-ANN model is the highest, but its learning rate is low, the learning and memory are unstable. It has no memory for the weights and thresholds of the completed training. So, there are certain limitations of it in use. Finally, a FEM of the isothermal compression experiment for four models were established, and the distribution of the equivalent stress field, equivalent strain field and temperature field with the deformation degree of 60% were obtained.

_{Superconducting foams of YBa$_2$Cu$_3$O$_y$ (YBCO) are proposed as trapped field magnets or supermagnets. The foams with an open-porous structure are light-weight, mechanically strong and can be prepared in large sample sizes. The trapped field distributions were measured using a scanning Hall probe on various sides of an YBCO foam sample after field-cooling in a magnetic field of 0.5 T produced by a square Nd-Fe-B permanent magnet. The maximum trapped field (TF) measured is about 400 G (77 K) at the bottom of the sample. Several details of the TF distribution, the current flow and possible applicatons of such superconducting foam samples in space applications, e.g., as active elements in flux-pinning docking interfaces (FPDI) or as portable strong magnets to collect debris in space, are outlined.}

Geologists employ high-spatial-resolution (HR) remote sensing (RS) data for many diverse applications as they effectively reflect detailed geological information, enabling high-quality and efficient geological surveys. Applications of HR RS data to geological and related fields have grown recently. By analyzing these applications, we can better understand the results of previous studies and more effectively use the latest data and methods to efficiently extract key geological information. HR optical remote sensing data are widely used in geological hazard assessment, seismic monitoring, mineral exploitation, glacier monitoring, and mineral information extraction due to high accuracy and clear object features. Compared with optical satellite images, synthetic-aperture radar (SAR) images are stereoscopic and exhibit clear relief, strong performance, and good detection of terrain, landforms, and other information. SAR images have been applied to seismic mechanism research, volcanic monitoring, topographic deformation, and fault analysis. Furthermore, a multi-standard maturity analysis of the geological applications of HR images using literature from the Science Citation Index reveals that optical remote sensing data are superior to radar data for mining, geological disaster, lithologic, and volcanic applications, but inferior for earthquake, glacial, and fault applications. Therefore, geological remote sensing research needs to be truly multidisciplinary or interdisciplinary, ensuring more detailed and efficient surveys through cross-linking with other disciplines. Moreover, the recent application of deep learning technology to remote sensing data extraction has improved automatic processing and data analysis capabilities.

Intercropping significantly improves land use efficiency and soil fertility. This study examines the impact of three cultivation systems (monoculture sugarcane, peanut-sugarcane and soybean-sugarcane intercropping) on soil properties and diazotrophs. Sugarcane rhizosphere soil was sampled from the farmers’ field. Soil properties and nifH gene abundance were analyzed by high throughput sequencing. Moreover, a total of 436,458 nifH gene sequences were obtained and classified into the 3201 unique operational taxonomic units (OTUs). Maximum unique OTUs resulted with soybean-sugarcane intercropping (<375). The dominant groups across all cultivation were Alpha-proteobacteria and Beta-proteobacteria. On the basis of microbial community structure, intercropping systems were more diverse than monoculture sugarcane. In the genus level, Bradyrhizobium, Burkholderia, Pelomonas, and Sphingomonas were predominant in the intercropping systems. Moreover, diazotrophic bacterial communities of these cultivation systems were positively correlated to the soil pH and soil enzyme protease. Moreover, low available P recovered from intercropping system showed a strong correlation with higher nutrient uptake activity of soil microbes. Based on the results, our investigation concluded that intercropping system caused a positive effect on the growth of diazotrophic bacterial communities and it might boost the soil fertility and this kind of study helps to develop an eco-friendly technology for sustainable sugarcane production.

A critical discussion on the computation of the dispersion diagram in periodic one-dimensional guiding structures is carried out. In particular, an analysis is presented of the pros and cons of combined methods that make use of full-wave simulations done with commercial software packages with further analytical post-processing based on simplifications brought by an equivalent circuit model of the structure. Some of the most common methods reported in the literature are reviewed and their advantanges and limitations highlighted. Our discussion is complemented with several selected numerical examples in order to discuss the most relevant aspects that a potential user of these methods should be aware of. Special attention is paid to the relevant role played by the high-order coupling between the two halves of a symmetric unit cell of the periodic structure.

Novel high energy density materials N14 (1,6-dihydro-1,2,3,3a,4,5,5a,6,7,8,8a,9,10,10a-tetradecazapyrene) and N18 (1,2,2a,3,4,4a,5,6,6a,7,8,8a,9,10,10a,11,12a-octadecazacoronene) were designed, and their structures, detonation performance and stabilities were calculated employing density functional theory (DFT). Calculations reveals that they have a good balance between high energy and stability. Their energy gaps between LUMO and HOMO are all lower than that of TATB, while their impact sensitivity h_50% is estimated close to that of RDX. Concerning energy, detonation performance of the N14 (P = 43.6 GPa, D = 10040 m/s, Q = 2214 cal/g) and the N18 (P = 37.4 GPa, D = 9400 m/s, Q = 2114 cal/g) are comparable to CL-20.

Obesity and metabolic disorders can be risk factors for the onset and development of neurodegenerative diseases. The aim of the present study was to investigate the protective effects on dysmetabolism and neurodegeneration of a natural dietary supplement (NDS), containing Curcuma longa, silymarin, guggul, chlorogenic acid and inulin, on the brains of high fat diet (HFD)-fed mice. A decreased expression of FACL-4, CerS-1 and CerS-4, reduced cholesterol concentration, increased IR expression and insulin signaling activation, were found in brains of NDS-treated HFD mice, suggesting that NDS is able to prevent brain lipid accumulation and central insulin resistance. In the brains of NDS-treated HFD mice, the levels of RNS, ROS and lipid peroxidation, the expression of p-ERK, H-Oxy, i-NOS, HSP60, NF-kB, GFAP, IL-1β, IL-6, and CD4 positive cell infiltration were lower than in untreated HFD mice, suggesting antioxidant and anti-inflammatory effects of NDS. The decreased expression of p-ERK and GFAP in NDS-treated HFD mice was confirmed by immunofluorescence. Lastly, a lower number of apoptotic nuclei was found in cortical sections of NDS-treated HFD. All these data indicate that NDS exerts neuroprotective effects in HFD mice by reducing brain fat accumulation, oxidative stress and inflammation and improving brain insulin resistance.

Rockburst is a hazardous phenomenon in deep tunnels influenced by geological structural planes like faults, joints, and shear planes. Small-scale shear-plane-like structures have damaging impact on the boundaries of the tunnel, which accumulate high stresses. Such a shear plane was exposed in the side wall of the right headrace tunnel in the Neelum-Jehlum Hydropower Project. This project is constructed in the tectonically active Himalayas with high stress conditions. A shear plane combined with high stress conditions is very dangerous in deep excavations. The influence of a shear zone on rockburst occurrence near a tunnel is studied. The FLAC3D explicit code simulated the shear zone in the right tunnel, revealing that the stresses are concentrated near the shear zone, with no stress concentration in the left tunnel, which has neither shear zone nor rockburst. Rock mass was displaced near this shear zone even before excavation. Modeling results confirm that the side wall shear zone of the tunnel has a major influence on rockburst occurrence. A shear slip along this plane released huge amounts of energy, causing human fatalities and property damage. A numerical simulation validates the actual conditions and helps us understand the phenomenon of stress concentration near the shear zone and its impact during deep tunneling.

Fibrillin (FBN) is a plastid lipid-associated protein found in photosynthetic organisms from cyanobacteria to plants. In this study, 10 CsaFBN genes were identified in genomic DNA sequences of cucumber (Chinese long and Gy14) through database searches using the conserved domain of FBN and the 14 FBN genes of Arabidopsis. Phylogenetic analysis of CsaFBN protein sequences showed that there was no counterpart of Arabidopsis and rice FBN5 in the cucumber genome. FBN5 is essential for growth in Arabidopsis and rice; its absence in cucumber may be because of incomplete genome sequences or that another FBN carries out its functions. Among the 10 CsaFBN genes, CsaFBN1 and CsaFBN9 were the most divergent in terms of nucleotide sequences. Most of the CsaFBN genes were expressed in the leaf, stem, and fruit. CsaFBN4 showed the highest mRNA expression levels in various tissues, followed by CsaFBN6, CsaFBN1, and CsaFBN9. High-light stress combined with low temperature decreased photosynthetic efficiency and highly induced transcript levels of CsaFBN1, CsaFBN6, and CsaFBN11, which decreased after 24 h treatment. Transcript levels of the other seven genes were changed only slightly. This result suggests that CsaFBN1, CsaFBN6, and CsaFBN11 may be involved in photoprotection under high-light conditions at low temperature.

The effects of psychological pressure on perceiving the height of a jump bar just before starting a high jump run was investigated. University students (N = 14) training for a high jump event performed 15 trials (3 practice, 6 pressure, and 6 non-pressure) in counterbalanced order in their daily practice environment. The height of the bar was judged as significantly higher on pressure trials compared to non-pressure trials. A regression analysis indicated that participants who reported increased subjective perceived pressure tended to judge the bar to be higher. There was no significant difference between pressure and non-pressure trials for the performance index, defined as the success rate. This study provides the first evidence that environmental perceptions prior to executing a motor task under pressure may make performance of the task appear to be more difficult.

This paper introduces an innovative theoretical framework for quantum-inspired data embeddings, grounded in foundational concepts of quantum mechanics such as superposition and entanglement. This approach aims to advance semi-supervised learning in contexts characterized by limited labeled data by enabling more intricate and expressive embeddings that capture the underlying structure of the data effectively. Grounded in foundational quantum mechanics concepts such as superposition and entanglement, this approach redefines data representation by enabling more intricate and expressive embeddings. Emulating quantum superposition encodes each data point as a probabilistic amalgamation of multiple feature states, facilitating a richer, multidimensional representation of underlying structures and patterns. Additionally, quantum-inspired entanglement mechanisms are harnessed to model intricate dependencies between labeled and unlabeled data, promoting enhanced knowledge transfer and structural inference within the learning paradigm. In contrast to conventional quantum machine learning methodologies that often rely on quantum hardware, this framework is fully realizable within classical computational architectures, thus bypassing the practical limitations of quantum hardware. The versatility of this model is illustrated through its application to critical domains such as medical diagnosis, resource-constrained natural language processing, and financial forecasting—areas where data scarcity impedes the efficacy of traditional models. Experimental evaluations reveal that quantum-inspired embeddings substantially outperform standard approaches, enhancing model resilience and generalization in high-dimensional, low-sample scenarios. This research marks a significant stride in integrating quantum theoretical principles with classical machine learning, broadening the scope of data representation and semi-supervised learning while circumventing the technological barriers of quantum computing infrastructure.

High temperature Ni-superalloys are limited by reliance on critical elements and complex processing steps. High entropy alloys (HEAs) have demonstrated stable single/dual phase microstructures with strong ordering tendencies. A dual phase (FCC+BCC) Al0.5Co0.5CrFeNi1.5Ti0.25 alloy (developed using CALPHAD) was tested for room and high temperature compression behavior. The microstructure mainly comprises of coarse ordered FCC(L12) surrounding decomposed lamellae of ordered FCC(L12) and BCC(L21) phases, which coarsened upon annealing at high temperature (1100 °C) into a bi-continuous structure of disordered FCC+BCC(B2). Additionally, cold rollability of the cast alloy increased from &lt;5% to ~40% after annealing, with a corresponding softening observed in room temperature compression mainly due to disordering of FCC and BCC phases. Peak flow stresses of 793.45MPa, 535.12MPa, and 324.40MPa were achieved at 800oC, 900oC, and 1000oC respectively for the high temperature annealed alloy.

This paper analyses the viability of different solutions to passively augment the axial stiffness of a horizontal axis radial levitation passive magnetic bearing (PMB) with topology previously studied. The zero-field cooling (ZFC) of high-temperature superconductor (HTS) bulks promotes higher magnetic impulsion and levitation forces and lower electromagnetic losses than with the field-cooling (FC), but on the other hand, the guiding stability is much lower than with FC. Because of stability reasons, FC was adopted in most superconducting maglev systems. The trend of this research group has been to develop an HTS ZFC horizontal axis radial levitation PMB presenting notable levitation forces with reduced electromagnetic losses, defined by a topology that creates guiding stability. Previous work has shown that even optimizing the bearing geometry to maximize magnetic guidance forces, could not be enough to guarantee the axial stiffness required for many applications. First, the extent to which guidance forces are augmented by increasing the number of HTS bulks in the stator is evaluated. Then, the axial stiffness augmentation by passively adding two limiting permanent magnet (PM) rings is evaluated. Results show that the axial stiffness is highly augmented by adding limiting PM rings with no significant additional investment. This change enables using the studied ZFC superconducting PMB in high-precision axial stability applications, such as precision gyroscopes, horizontal axis propellers and turbines.

(1) Background: In most cases, passive isolation control methods are commonly used for the seismic isolation design of bridge engineering. However, for passive seismic isolation devices, due to their non-adjustable performance parameters, it is challenging to achieve a good seismic isolation effect for structures under random and variable seismic loads in the wide frequency range of 0 Hz to 20 Hz; (2) Methods: the sensitivity of the design parameters of the seismic isolation bearing was analyzed using the optimization center gradient method, and an improved genetic algorithm was employed to quickly optimize and obtain the optimal design parameters; (3) Results: the effectiveness of the three-dimensional seismic isolation bearing was validated through experiments. (4) Conclusions: The multi-factor sensitivity analysis approach used in this study for designing novel isolation bearings is applicable not only to seismic design in bridges but also serves as a reference for parameter design in isolation bearings requiring medium to high precision in seismic performance.

The whimsical Las Vegas/Monte Carlo cubic dice are generalized to construct the combinatorial problem of enumerating all n-dimensional hypercube dice, and dice of other shapes that exhibit cubic, icosahedral and higher symmetries. By utilizing powerful generating function techniques for various irreducible representations, we derive the combinatorial enumerations of all possible dice in n-dimensional space with hyperoctahedral symmetries. Likewise a number of shapes that exhibit icosahedral symmetries such as a truncated dodecahedron and a truncated icosahedron are considered for the combinatorial problem of dice enumerations with the corresponding shapes. We consider several dice with cubic symmetries such as truncated octahedron, dodecahedron and Rubik’s cube shapes. It is shown that all enumerated dice are chiral and we provide the counts of chiral pairs of dice in the n-dimension space. During the combinatorial enumeration, it was discovered that two different shapes of dice exist with the same chiral pair count culminating into the novel concept of isochiral polyhedra. The combinatorial problem of dice enumeration is generalized to multi-coloring partitions. Applications to chirality in n-dimension, molecular clusters, zeolites, mesoporous materials, cryptography and biology are also pointed out. Applications to nonlinear n-dimensional hypercube and other dicey encryptions are exemplified with romantic, clandestine messages; “I love U” and “V Elope at 2”.

This proposal advocates using energy states as fundamental units for quantum computer programming. Each programming unit is conceptualized as an energy state, manifested as an essence-unit. The essence-unit, defined as the minimal form encapsulating complete uniqueness or specificity, serves as the cornerstone of this paradigm. This approach allows recording various forms of matter on quantum computers in essence-units representing their energy states. Recording energy states is achieved through the creation of four distinct coherent potentials facilitated by quantum dots or crystals. It is crucial to note that these energy states, embodied in essence-units, cannot be subdivided. The study examines the intricate relationship between similarity, fractals, and uniqueness in quantum dot operations, elucidating their profound implications for information transfer efficiency. Normalized entropy quantifies the charge localization in quantum dot impurities in systems exhibiting distortions. Utilizing N-level recording and entropy-fractal dimension equivalence enables this paper to elucidate the potential of quantum dots in reducing transmission time and modeling complex systems. The proposed methodology represents a significant departure from the current state of quantum computing, offering unprecedented potential for overcoming previously intractable challenges.

Background Robotic-assisted thoracic surgery (RATS) has become the standard procedure for treating lung malignancy, offering numerous advantages over traditional methods. However, the minimally invasive nature of RATS presents unique challenges, notably a limited field of view and reduced tactile feedback for the surgeon. These limitations can significantly impact the surgeon's ability to navigate complex anatomical structures during surgery. To address these challenges, we recognized the need for enhanced preoperative familiarization with each patient’s specific anatomy. In response, we developed an innovative virtual reality (VR) surgical navigation system, utilizing head-mounted displays (HMDs), designed to provide surgeons with a more comprehensive and interactive understanding of the patient's anatomy before the actual surgery. This VR system aims to extend the surgeon's capabilities in both preoperative sumilation and intraoperative navigation, potentially mitigating the inherent limitations of RATS. Methods Three-dimensional (3D) volumized data, meticulously extracted from preoperative computed tomography (CT) scans, were seamlessly integrated into the Perspectus VR Education software. These data were then displayed on an HMD, facilitating an interactive 3D reconstruction of pulmonary structures. This reconstruction allowed for each structure to be visualized individually, enabling detailed preoperative resection simulations tailored to each patient's unique anatomy. During RATS, these specific 3D reconstructed images were made accessible within the surgeon's console through the TilePro™ multi-display input, providing real-time, intraoperative guidance. Results During the preoperative simulations, the 3D anatomic structure of the pulmonary vessels, as well as the spatial relationship between the lesion and adjacent tissues, were successfully visualized. This enhanced visualization enabled surgeons to thoroughly evaluate a patient's anatomy, significantly improving the safety and accuracy of the subsequent procedure. The integration of VR software with the HMD provided surgeons with a true 3D interaction with real patient data. This setup not only offered a unique perspective through the surgical console but also allowed for easy manipulation of the data on a mobile laptop, thereby enhancing the overall surgical planning process. Conclusions VR simulation using HMDs offers a viewing experience akin to that of a robotic 3D viewer, potentially providing an innovative avenue for surgeons to develop specific robotic surgical skills without the need for practicing on live patients. This technology, when integrated with routine imaging modalities, can significantly enhance preoperative planning. Such integration not only contributes to the safety but also improves the accuracy of anatomical resections. Our findings suggest that VR simulation with HMDs is particularly effective in assisting surgeons to accurately identify lesion locations in RATS, thereby optimizing surgical outcomes.

Drone imagery has the potential to enrich urban planning and preservation, especially where it converges with the growing creation and use of 3D models. The authors have conducted a systematic literature review of articles published between 2002 and 2022, drawing from reputable academic repositories including Science Direct, Web of Science, and China National Knowledge Infrastructure (CNKI), to identify current gaps in existing research in the application of UAVs to the creation of 3D models in urban planning and preservation. Findings indicate five research shortcomings: limited participation of planning experts, research focus imbalance, lack of usage for special scenarios, lack of integration with smart city planning, and limited interdisciplinary collaboration. The study also acknowledges current limitations with UAV applications and discusses possible countermeasures as well as future prospects.

The particulars of stimulus-response experiments done on dynamic biosystems clearly limit what one can learn and validate about their structural interconnectivity (topology), even when collected kinetic output data are perfect (noise-free). As always, available access ports and other data limitations rule. For linear systems, exponential modes, visible and hidden, play an important role in understanding data limitations, embodied in what we call dynamical signatures in the data. We show here how to circumscribe and analyze modal response data in compartmentalizing model structures – so that modal analysis can be used constructively in systems biology model building – for nonlinear (NL) as well as linear biosystems. We do this by developing and exploiting the modal basis for dynamical signatures in hypothetical (perfect) input-output data associated with a structural model – one that includes inputs and outputs explicitly – and for NL as well as linear biosystems. The methodology establishes model dimensionality (size, complexity) from particular data sets; helps select among multiple candidate models (model distinguishability); helps in designing new experiments to extract “hidden” structure; and helps to simplify (reduce) models to their essentials. For NL biosystems, results are not as comprehensive, similarly informative about their dominant dynamical properties, and unified with linear models on invariant 2-dimensional manifolds in phase space. Some automation of these highly technical aspects of biomodeling is also introduced.

This paper aims the automatic ball balancers (ABBs) used in passive balancing devices for suppressing vibration of the eccentric rotor. The system model describes which equipped with a skew-mounted ABB with angular deviation. The dynamic equilibrium equations of the system are deduced from the perspective of three-dimensional (3D) dynamics. The results obtained are consistent with those derived from the Euler-Lagrange equations. It is exciting that the spatial dynamics method reveals the spatial geometric characteristic of dynamic balance positioning of the balls when the system is balanced with vibration suppression. The spatial property emerges the perpendicular line from each ball to the rotating spindle of the system must pass through the central axis of the orbit perpendicular to the ABB plane. This characteristic is a general rule that can be used to explain the phenomenon of the stable equilibrium positions of the balls in all previously studied cases.

The theory of special relativity has reexamined and reconstructed the concepts of space and time, which are indispensable for describing physical laws, consequently instigating a major revolution in physics in general. Although the correctness of the special theory of relativity has been con-firmed by many observations and experiments, it is unclear why the "principle of relativity" and the "principle of the constant speed of light," which form the basis of the idea, are valid. Moreo-ver, although special relativity has advanced our understanding of time, our understanding of the fundamental question, "What is time?" is still limited. The theory of special relativity regards space as a four-dimensional construct consisting of one-dimensional time and three-dimensional space. This paper proposes an alternative framework, wherein real space is uniform and isotropic four-dimensional space, and elementary particles are waves that propagate through this four-dimensional space at a constant speed. This new perspective provides evidence to support two of Einstein’s key principles—the "principle of relativity" and the "principle of the constant speed of light." Furthermore, this model clarifies what time is and why time flows at a constant rate from the past to the future.

The properties of the dark matter, dark energy, graviton and photon are discussed in terms of the new three-dimensional quantized space model. Three new particles (bastons) with the electric charges (EC) are proposed as the dark matters. It is proposed that the EC, LC and CC charges are aligned along the time axes but not along the space axes. The photon is confined on its corresponding three-dimensional quantized space. However, the graviton can be evaporated into other three-dimensional quantized spaces. The rest mass of the electron neutrino (n_e) of 3.494·10⁻³ eV/c² is obtained from the experimental vacuum energy density in terms of quantum field theory (QFT). The rest mass and force range of the massive g(0,0,0) graviton with the Planck size are m_g = 3.1872·10⁻³¹ eV/c² and x_r = 3.0955·10²³ m = 10.0 Mpc, respectively, based on the experimental rest mass and rms charge radius of the proton. The possible diameter (10 Mpc) of the largest galaxy cluster is remarkably consistent with the gravitational force range (10 Mpc). Then, the diameter of the largest dark matter distribution related to the largest galaxy cluster is 9.2865·10²³ m = 30 Mpc equal to the force range of the massive g(0) graviton with the rest mass of 1.0624·10⁻³¹ eV/c². Because of the huge number (N) of the evaporated gravitons, the very small Coulomb’s constant of about 10⁻⁴⁸k and large gravitation constant of 10⁶G_N are expected for the charged dark matters. Therefore, F_c(mm) > F_g(dd) > F_g(mm) > F_g(dm) > F_c(dd) > F_c(dm) = 0 for the proton-like particle. The proposed weak gravitational force between the dark matters and normal matters explains the observed dark matter distributions of the bullet cluster, Abell 1689 cluster and Abell 520 cluster. The transition from the galaxy without the dark matters to the galaxy with the dark matters are explained. Also, the accelerated space expansion is caused by the new space quanta created by the evaporated gravitons into the x1x2x3 space and repulsive electromagnetic force between dark matters corresponding to the dark energy. The decreasing coupling constant of the strong force, neutron lifetime anomaly and the pressure distribution inside the proton are explained by the unobservable proton and hadronization. And the rest mass of 1.4 TeV/c² is assigned to the Le particle with the EC charge of −2e. The proposed rest mass (26.12 eV/c²) of the B1 dark matter is indirectly confirmed from the supernova 1987A data. Also, the gravitation constant has been changing with the time because of the graviton evaporation.

High-frequency circuit performance is significantly impacted by impedance variations, particularly within the low-resistance regime. Traditional Ohm’s Law based modeling approaches often fail to accurately predict circuit behavior in these conditions, leading to design inaccuracies and potential system failures. The Standard Ohm’s Law based model’s prediction of infinite current as resistance approaches zero is physically unrealistic and hinders its application in practical scenarios. Despite the recognition of these limitations, existing models have not comprehensively addressed the complex impedance behavior observed in high-frequency circuits. To overcome these challenges, this paper introduces a modified version of the Ohm’s Law incorporating an exponential correction term. The Modified Ohm’s Law’s accuracy was evaluated through simulated experiments across a wide frequency range (1kHz to 1GHz) using various electronic components. The findings demonstrate the superior performance of the modified model in predicting currents under low-resistance and high-current conditions compared to the Standard Ohm’s Law model. By providing finite and accurate current values, the proposed model effectively mitigates the unrealistic infinite current predictions of the standard approach. The enhanced predictive capabilities of the Modified Ohm’s Law hold significant implications for high-frequency circuit design and analysis. Its application can lead to improved performance and reliability in power electronics, telecommunications, and other high-frequency systems. By incorporating non-linear impedance behavior, the model offers a more accurate representation of real-world circuit conditions. Future research should focus on refining the exponential term’s parameters to optimize the model's accuracy across a broader range of applications. Additionally, real-time implementation and hardware validation are essential to assess the model's practical utility in complex circuit environments.

Today electricity is distributed to the individual users via physical Copper connections. From the power stations, the energy is transported through transmission lines where the electricity, sinusoidally modulated at a fixed frequency of about 50 Hz, is raised up to a voltage in a range approximately variating between 30, and 110 kV. When electrons, aligned at this voltage, pass through the transmission lines, they cause coherent vibrations, sometimes even audible in the acoustic frequencies. In the spectrum of movements to which electric cables are subjected, there are also unexpected and sporadic movements caused by winds and rain. The problem of carrying out persistent, precise and spatially distributed monitoring of transmission line health is to use a large number of sensors physically distributed everywhere and somehow transmit the results to a control station. The use of synthetic aperture radar (SAR) data could be a viable solution of persistent and wide-area high-voltage vibration monitoring. In this paper we produce a comprehensive survey on how to monitor both movements in terms of vibrational displacement, due to weathering, and those due to electricity transmission, normally fixed at about 50 Hz. The results demonstrate the technical feasibility of an operational use of SAR for these purposes in the very short term. This would allow the possibility of monitoring malfunctions such as black-outs or other frequency anomalies.

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.

When the power converter connected to the high-frequency transformer breaks through the bottleneck and reaches a frequency of 100kHz or even higher, the high-frequency transformer's inter-turn insulation faces more serious high-frequency discharge and high temperature problems. In order to improve the service performance of oil-immersed high-frequency transformer insulation paper, composite K-BNNSs particles are prepared by ultrasonic stripping, heat treatment and thermomagnetic stirring. Then, K-BNNSs particles are mixed with PMIA slurry to produce composite aramid paper. And the effects of K-BNNSs particles with different contents on the thermal conductivity, dielectric properties, partial discharge properties and mechanical properties of aramid paper are explored. It can be found that when the addition of composite particles (K-BNNSs) is 10%, the comprehensive performance of composite aramid paper is the best. Compared with Nomex paper, the in-plane and through-plane thermal conductivity of composite insulating paper F-10 is increased by 668.33% and 760.66% respectively. Besides, the high-frequency breakdown voltage is increased by 48.73% and the tensile strength is increased by 2.49%. The main reason is that the composite particles form a complete thermal conductive network in the aramid paper matrix and a large number of hydrogen bonds with the matrix, which enhances the internal interface bonding force of the material and changes the charge transport mechanism.

The increasing deployment of large-scale wind turbines in place of conventional generators is expected to lead to the dominance of asynchronous power sources in future power systems, further accelerating the trend toward grid electrification. As a result, the ability of power sources to support system voltage and frequency is gradually diminishing. Synchronous condensers (SC), which are synchronous machines operating without prime movers, serve as effective devices for providing both dynamic voltage support and inertia. They can significantly enhance the system’s capacity to maintain voltage and frequency stability. However, most existing studies on the optimization of synchronous condenser configurations tend to focus on only one aspect at a time, rather than addressing both simultaneously, limiting the full potential of these devices. Optimizing either voltage or frequency in isolation often results in suboptimal improvements in the other. Moreover, simultaneous optimization of both voltage and frequency can lead to non-convergent outcomes, complicating the search for an optimal solution. To address this, the paper proposes a hierarchical optimization strategy for synchronous condenser configuration aimed at enhancing both voltage and frequency stability. First, the configuration sites for the synchronous condensers are determined based on short-circuit ratio (SCR) constraints. Next, an outer layer optimization model is developed to minimize the total installed capacity of the condensers, while taking into account SCR and transient overvoltage levels as constraints. Following this, an inner layer optimization model is introduced, incorporating and as constraints. The model is solved using the bacterial foraging optimization algorithm (BFOA). Finally, a case study of a power grid with a high proportion of wind power validates the effectiveness of the proposed synchronous condenser configuration strategy. Compared to traditional methods, the total required capacity of synchronous condensers was significantly reduced.

Amyotrophic lateral sclerosis (ALS) is a devastating disease whose etiology is currently unknown. This paper presents a novel theory in which ALS is caused by an impairment of the alpha2de;ta subunit of voltage-gated calcium channels (VGCCs), most likely due to autoimmune targeting. I show how the impairment mechanistically induces chronic calcium, which in turn explains the major clinical, epidemiological, and pathological evidence known about the disease. The same theory explains the major variant of frontotemporal dementia (FTD) that greatly overlaps with ALS.

To explore cast HEAs reinforcement by MC carbides three equimolar CoNiFeCrC alloys without or with Carbon and either hafnium or tantalum were investigated. Their microstructures were specified and tests at 1100°C in oxidation by air and flexural creep tests were carried out. The HEAbase was single–phased. The HEAhfc and HEAtac contained eutectic script HfC and TaC carbides respectively, in the interdendritic spaces. After oxidation for 50h at 1100°C all alloys were covered by a (Cr,Mn)2O3 scale with various proportions in Cr and Mn. HfO2 or CrTaO4 also formed. The subsurface was depleted in Cr and especially in Mn. The HEAbase alloy deformed quickly. The MC carbides greatly improved the creep resistance, and divided deformation by five to ten times.

High-intensity interval training (HIIT) is widely used in team sports, particularly in soccer. This study aimed to investigate the effects of a short-term, progressive- load HIIT program on the performance of under-15 soccer players. The sample consisted of 30 adolescent soccer players, aged 14, who were randomly divided into two groups: the control group (CG, n=15) and the intervention group (EX, n=15), which performed additional HIIT sessions. The duration of the training program was six weeks, with progressive overload applied every two weeks. Performance indicators, including speed over 10 and 30 meters, change of direction (COD) to the right and left (505 right and left), maximal oxygen uptake (30-15IFT), and repeated sprint ability (RSA) (RSAtotal, RSAmean, RSAdecrement), were measured before and after the training program. Significant improvement were observed in the intervention group in COD (505 right and left), 30-15IFT, and RSAtotal and RSAmean (p=0.027, p=0.005, p=0, p=0.015, p=0.031, p=0.028, respectively). The findings of the present study suggest that a short-term, progressively overloaded HIIT program can enhance direction change ability, aerobic capacity, and repeated sprint performance.

Real-time simulation of toxic gas dispersion is critical for emergency management in high-sulphur gas fields. The CALPUFF (California Puff model) gas dispersion model, a Lagrangian Gaussian Puff model, is often used in mountainous environments due to its ability to handle complex terrain and weather conditions. Verifying the accuracy of toxic gas dispersion simulations under mountainous conditions is vital for emergency response and rescue. In this article, CALPUFF and Computational Fluid Dynamics (CFD) gas dispersion modeling are compared, studying emissions from a hypothetical pipeline breakout accident in a mountainous area, focusing on range of Semi-Lethal Concentration (LC$_{50}$), Immediate Danger to Life and Health Concentration(IDLH). Thirteen groups of simulation conditions are set up for the experiment, including static wind and winds from the east(E), south(S), west(W), and north(N) at speeds of 1, 2, and 3$m/s$. Comparative experiments between CALPUFF and CFD models show consistent results, confirming the feasibility of CALPUFF for near-field moutainous applications. The overall dispersion range deviation between two methods under calm or light wind of N, E and W is about 300$m$. However,the simulation results of the CALPUFF model and the CFD model show significant differences in S wind. In CALPUFF simulation that the toxic gases are channeled by the valleys, while in the CFD model the toxic gases climb over the mountain top and continue to spread and extend towards the northern valley. The evaluation of CALPUFF’s suitability for applications in near-field mountainous environments indicates its potential use for high-sulfur gas fields and gas dispersion simulations in emergency scenarios.

Dielectric Elastomer Actuators (DEAs) are emerging as promising candidates for various applica-tions in robotics and optical devices due to their lightweight, miniaturization potential, high en-ergy density, simple structure, and low power consumption. However, their effective actuation always demands sophisticated high-voltage driving circuits that are compact and responsive. DEAs need to be capable of generating intricate high-voltage waveforms or simultaneously con-trolling multiple channels with distinct high-voltage levels. This paper proposes a high-voltage power supply for DEAs, featuring a four-channel high-voltage driving circuit. The circuit is ca-pable of independently generating high-voltage signals ranging from 100 V to 6000 V and can be programmed to produce arbitrary waveforms with adjustable frequencies. The independent op-eration of channels without crosstalk showcases the system's integration and potential for cross-disciplinary applications.

Fungi play important roles in the process of material cycling and energy transfers in aquatic ecosystems. Yet little is known about the fungal community in lake sediment. In this study, sediment samples from five habitat types in Baiyangdian Lake (BYD Lake) were collected across three seasons. High-throughput sequencing techniques were used to determine the compositions of fungal communities. Fungi are highly diverse in the sediment of BYD Lake, although some important fungi have not been accurately identified. The fungal diversity was highest in winter and lowest in summer, while the variations of species richness among sampling sites were not significant. The compositions of fungal community differed among seasons and habitats. Physicochemical properties of sediments were measured and the influence of the environmental factors on fungal communities were analyzed. Temperature, P, N, and heavy metals explained 48.98% of the variations of fungal communities across three seasons. Human activities have affected the species and biomass of fungi to some extent. Temperature is the most influential factor and is negative to fungal diversity. Nutrient element in different forms have different effects on shaping the fungal community. The effect of heavy metals is not clear.

As waterflooding multi-layer reservoirs get into the high-water-cut stage, inter-layer conflicts become increasingly serious, leading to a worsening development effect over time. Production layers regroup is an effective approach for resolving inter-layer conflicts and improving waterflooding efficiency. At the current stage, there are limitations for most of the methods of production layers regroup. This article proposes a smart method for optimizing the layer regroup plan based on genetic algorithm. Comprehensively considering various factors that affect the regroup of layers, based on the combination principle of "smaller intra-group variance and larger inter-group variance of each influencing factor are expected ", genetic algorithm is used to calculate the fitness value of the initial combination schemes, the advantageous schemes with higher fitness values are selected as the basis of the next generation. Then crossover and mutation operations are performed to those advantageous schemes to generate new schemes. Through continuous selection and evolution, until the global optimal solution with the highest fitness value is found, the optimal combination scheme is determined. Comparative analysis with numerical simulation results demonstrates the reliability of this intelligent method, with an increased oil recovery of 4.34% for the sample reservoir. Unlike selecting a preferable plan from a limited number of predefined combination schemes, this method is an automatic optimization to solve the optimal solution of the problem. It improves both efficiency and accuracy as compared to conventional reservoir engineering methods, numerical simulation methods and most of the mathematical methods, thus could provide effective guidance for EOR strategies of waterflooding reservoirs in high-water-cut stage.

Background: This study investigated the effect of indirect air-cooling on the variation in intrapulpal temperature (ΔT) during different light-curing protocols of bulk-fill resin composites in molars with class V cavities. Methods: A nonretentive class V cavity was prepared in an upper molar. The intrapulpal temperature changes with and without air-cooling were recorded with type K thermocouple. The cavity was restored with bulk-fill resin composites: Tetric PowerFlow and Filtek Bulk-Fill Flow. The tooth was exposed to different light-curing protocols (n=5) using the Valo Grand light-curing unit: (i) high-intensity light-curing of 3200 mW/cm² (3 and 6 s) and (ii) moderate-intensity light-curing of 1000 mW/cm² (10 and 20 s). The ΔT data were subjected to two-way ANOVA, followed by Bonferroni post hoc test. Results: A significant increase in temperature was observed with the use of the high-intensity light-curing resin composite without indirect air-cooling. In addition, the application of air-cooling significantly decreased the temperature in all the groups except for the Tetric PowerFlow bulk-fill resin composite at 3 s of light-curing. Conclusion: Indirect air-cooling resulted in a lower increase in intrapulpal temperature during the light-curing of bulk-fill resin composites, making it an effective alternative for controlling the temperature rise in class V restorations with 1 mm of remaining dentin.

Chronic stress, culminating in burnout, evolves gradually and is notoriously difficult to detect due to vague symptoms and individuals' hesitance to acknowledge their struggles. To expedite the identification and recognition of this condition, enabling timely psychological intervention, the integration of Artificial Intelligence (AI) is increasingly considered. This research does not assert the feasibility of an AI system managing all aspects of chronic stress's impact. However, it highlights the capability of current technology to detect stress indicators based on quantifiable data like Heart Rate (HR) and organizational climate dimensions. Although other physiological markers such as oximetry, skin galvanic response, and EKG have been explored, they have not shown reliable differentiation between stress and joy. Focused on the unique context of school principals in the Bedouin regions of Israel, this study investigates the interplay between HR, organizational climate, and stress levels. It introduces a novel application of a fuzzy logic tool that combines HR and organizational climate metrics to aid in stress diagnosis. This tool incorporates the psychologist's expertise to provide real-time data crucial for developing effective coping strategies. While the AI-supported fuzzy system does not replace professional psychological intervention, it significantly enhances the speed of condition identification and intervention planning, thus shortening the response time to stress-related issues in educational leadership within culturally specific settings. The application of such AI-driven tools is pivotal for sustaining the well-being and effectiveness of educational leaders, thereby supporting the broader goal of educational sustainability.

A high-gain broadband circularly polarized crossed dipole antenna is designed. This antenna utilizes two pairs of cross dipoles and a pair of phase delay lines to form circularly polarized radiation. Open-circuit stubs are loaded on the four arms of these two pairs of cross dipoles to introduce new circularly polarized resonating frequency. A rectangular ring patch is introduced directly below the cross dipoles to form the third circularly polarized resonating frequency, thereby broadening the axial ratio bandwidth of the antenna. In addition, metal posts are loaded at the four right angles of the rectangular ring patch to increase the antenna gain. Measurement results show that the antenna achieves a 3dB axial ratio bandwidth of 29.2% (1.9 GHz-2.55 GHz) and maintains a gain of 7.5 dB within the passband, exhibiting good circularly polarized radiation performance.

Background/Objectives: Encouraging results reported of Platelet-Rich Plasma (PRP) treatment for knee osteoarthritis (KOA). The present retrospective study reports the efficacy and safety of a high dose of neutrophile and red blood cell-depleted PRP to treat 212 patients with KOA. Methods: 212 consecutive patients diagnosed with Kellgren-Lawrence (KL) grading 1-3 KOA chronic knee pain for at least 1 year were treated with 3 injections at 15-day intervals with a high dose of neutrophil-depleted PRP (4 billion platelets). Clinical outcomes were retrospectively recorded as a percentage of responders at 3,6, and 12-month follow-up, following the OMERACT-OARSI criteria. Pain through VAS score and WOMAC score have also been recorded. Results: 4ml of PRP containing 4X109 platelets were obtained by single spin centrifugation and injected intra-articular into each patient with no pre-activation. The overall responder rate of patients responding to OMERACT-OARSI criteria at 3,6,12 months was 68.9%, 72,7% and 70,6%. There was a significant improvement in VAS and WOMAC scores at 3-, 6- and 12-month follow-up compared to the pre-treatment value (p&lt; 0.01). The lowest VAS score was observed at 6 months overall and in all three-grade KL groups. KL2 groups showed the best results regarding pain reduction and WOMAC score at 6 months (p&lt; 0.01). Conclusions: a high dose of neutrophil-depleted PRP is an effective treatment for KL1-3 KOA. It provides symptomatic relief, can potentially reduce disease progression, and has sustained effects for up to 12 months.

Aiming at the problems of inaccurate segmentation of long object and information loss of small object in real-time semantic segmentation algorithm, this paper proposes a lightweight multi-branch real-time semantic segmentation network based on BiseNetV2. The new auxiliary branch makes full use of spatial details and context information to cover the long object in the field of view. Meanwhile, in order to ensure the inference speed of the model, the asymmetric convolution is used in each stage of the auxiliary branch to design a structure with low computational complexity. In the multi-branch fusion stage, the alignment and fusion module is designed to provide guidance information for deep and shallow feature mapping, so as to make up for the problem of feature misalignment in the fusion of information at different scales, and thus reduce the loss of small target information. In order to further improve the model’s awareness of key information, a global context module is designed to capture the most important features in the input data. The proposed network uses NVIDIA GeForce RTX 3080 Laptop GPU experiment, on the road street view data set Cityscapes and CamVid average occurring simultaneously ratio reached 77.1% and 78.4% respectively, with running speed of 127 frames/s respectively and 112 frames/s. The experimental results show that the proposed algorithm can achieve real-time segmentation and improve the accuracy significantly, showing good semantic segmentation performance

Utilizing deep learning for semantic segmentation of cropland from remote sensing imagery has become a crucial technique in land surveys. Cropland illustrates diverse morphologies and degrees of fragmentation on the Earth’s surface, underscoring the importance of accurately perceiving the complex boundaries of cropland which are crucial for effective segmentation. This paper introduces a UNet-like boundary-aware compensation model BAFormer. Cropland boundaries typically exhibit rapid transformations in pixel values and texture features, often appearing as high-frequency features in remote-sensing images. To enhance the recognition of these high-frequency features as represented by cropland boundaries, the proposed BAFormer integrates a Feature Adaptive Mixer (FAM) and develops a Deep Wide Large Kernel Multi-Layer Perceptron (DWLK-MLP) to enrich the global and local cropland boundaries features separately. Specifically, FAM adaptively mixes high-frequency and low-frequency features through the advantages of convolution and self-attention; DWLK-MLP expands the convolutional receptive field by deeply decomposing large kernel convolutions. The efficacy of BAFormer has been evaluated on the Vaihingen, Potsdam, and LoveDA public datasets, as well as the Mapcup dataset. It has demonstrated advanced performance, achieving mIoU scores of 84.5%, 87.3%, 53.5%, and 83.1% on these datasets respectively. Notably, BAFormer-T, the lightweight iteration of the model, surpasses other lightweight models on the Vaihingen dataset with scores of 91.3% F1 and 84.1% mIoU. The source code is available at https://github.com/WangYouM1999/BAFormer.

The extensive metabolic diversity of microalgae, coupled with their rapid growth rates and cost-effective production, position these organisms as highly promising resources for a wide range of biotechnological applications. These characteristics allow microalgae to address crucial needs in both the agricultural, medical, and industrial sectors. Microalgae are proving to be val-uable in various fields, including the remediation of diverse wastewater types, the production of biofuels and biofertilizers, and the extraction of various products from their biomass. For decades, the microalga Chlamydomonas has been widely used as a fundamental research model organism in various areas such as photosynthesis, respiration, sulfur and phosphorus metabolism, nitrogen metabolism, and flagella synthesis, among others. However, in recent years, the potential of Chlamydomonas as a biotechnological tool for bioremediation, biofertilization, biomass, and bio-products production has been increasingly recognized. Bioremediation of wastewater using Chlamydomonas presents significant potential for sustainable reduction of contaminants and fa-cilitates resource recovery and valorization of microalgal biomass, offering important economic benefits. Chlamydomonas has also established itself as a platform for the production of a wide va-riety of biotechnologically interesting products, such as different types of biofuels, and high-value-added products. The aim of this review is to achieve a comprehensive understanding of the potential of Chlamydomonas in these aspects, and to explore their interrelationship, which would offer significant environmental and biotechnological advantages.

Previous studies show that women with a history of high-grade CIN have a greater risk of subsequent high-grade anogenital intraepithelial neoplasia or cancer, and the risk is greater for vaginal cancer than for anal and vulvar cancers. It is hypothesized that the laparoscopic hysterectomy procedure may cause a higher incidence of VaIN in hysterectomized women. There are few studies addressing this issue and they show mixed results. This study aimed to investigate the incidence of high-grade or worse VaIN in the population of women undergoing hysterectomy for CIN3 or benign uterine disease, illustrate treatment options and follow-up. Methods: This retrospective study was conducted on 170 women who underwent laparoscopic hysterectomy for high-grade cervical intraepithelial neoplasia (CIN3) or benign gynecological disease. The follow-up strategy included performing a cotest and colposcopy with biopsy if necessary. The median time between primary treatment and diagnosis of high-grade VaIN was 18 months. Results: High grade or worse VaIN was found in 8 patients after hysterectomy (4.7%). All cases of high-grade VaIN occurred in women with persistent HPV infection. The most frequent genotype was 16. Women hysterectomized for CIN3 showed an 8-fold greater risk than women hysterectomized for benign disease of developing high-grade VaIN. The risk of VaIN is low in women hysterectomized for benign disease. The risk of developing VaIN is greater in women with viral persistence Conclusion. All these elements suggest that it is the history of HPV-related disease of the lower genital tract and viral persistence, rather than hysterectomy itself, that should be considered a risk factor for the development of high-grade VaIN. After hysterectomy, patients with a history of CIN should undergo annual screening with vaginal dome cytology and HPV testing.

Thermal expansion of four alkaline-earth borates, namely Ca3B2O6 (0D), CaB2O4 (1D), Sr3B14O24 (2D) and CaB4O7 (3D), have been studied by in situ high-temperature powder X-ray diffraction (HTXRD). Strong anisotropy of thermal expansion is observed for the structures of Ca3B2O6 (0D) and CaB2O4 (1D) built up from BO3 triangles only: these borates exhibit the maximal expansion perpendicular to the BO3 plane, i.e. along the direction of weaker bonding in the crystal structure. Layered Sr3B14O24 (2D) and framework CaB4O7 (3D) built up from various B-O groups expand less anisotropically. Thermal properties of the studied compounds compared to the other alka-line-earth borates are summarized depending on the selected structural characteristics like anion dimensionality, residual charge per one polyhedron (BO3 BO4), cationic size, and structural com-plexity. For the first time these dependencies were established as an average for both types of polyhedra (triangle and tetrahedron) occurring in the same structure at the same time. The most common trends were identified for : (i) Melting temperature decreases as the dimensionality of the borate polyanion, and more precisely, as the residual charge per one polyhedron (triangle or tetrahedron) decreases; (ii) volumetric expansion decreases while the degree of anisotropy in-creases weakly when the residual charge decreases; (iii)both trends (i) and (ii) are most steady within borates built by the triangles only, while the borates built by both triangles and tetrahedra show a larger scatter in values.

The growing interest in benchtop NMR systems is visible in a vast number of applications in science and industry. Low-field nuclear magnetic resonance (LF-NMR) became an instant in technologies that productions are dependent on the reliable structure identification, grade and purity control, chemical process inspection or reaction monitoring. Beyond the benefits of being cost-, space-, maintenance- and user friendly, insufficient sensitivity and low signal resolution are the main drawbacks, due to which the low-field NMR (LF-NMR) in the fields of organic chemistry and synthesis remains limited to solely academic teaching purposes. Herein, we discuss the possibilities of LF-NMR for the needs of organic chemistry and synthesis on a set of compounds 1-4 achieved as the products of student’s laboratory course and organic derivatives 5-8 that are from our research interests. Chemical structure determination of all compounds 1-8 presented herein was performed using the benchtop-type NMR instrument operating at 60 MHz (Pulsar Oxford Ltd.). Structure of novel compounds 5-7 prepared under the aims of our research was characterized by combined 1H/19LF-NMR and compared with an appropriate high-field NMR data from Bruker Ascend Instrument (400 MHz). Finally, possibilities of the low-field NMR as an analytical tool for the research purposes in the fields of organic chemistry and synthesis are documented on a set of 1H and 2D 1H-1H COSY for azomethine 8.

High pathogenicity avian influenza (HPAI) H5N1 clade 2.3.4.4b continues to have a substantial impact on wildlife, globally. A recent study has described the putative detection of HPAI in clinically healthy penguins, and those which were fitted with satellite tags reportedly engaged in apparently normal foraging behaviour in the months following sample collection. Herein we investigate the diagnostic approach utilised, and reveal that while the authors likely did detect subtype H5 influenza A virus, the most parsimonious conclusion is that they detected low pathogenicity H5 rather than HPAI H5N1. In response, we have provided an overview key considerations when selecting a diagnostic and outline published diagnostic assays that should be considered for future studies.

Nanoporous materials, such as Metal-Organic Frameworks (MOFs), are renowned for their high selectivity as gas adsorbents due to their specific surface area, nanoporosity, and active surface chemistry. A significant challenge for their widespread application is their behavior and reduced gas uptake in wet conditions, attributed to competitive adsorption between gas and water. The current understanding of gas adsorption in wet materials is constrained by studies that utilize only small amounts of powdered porous materials (in the milligram range) within very small reactors (1-5 mL). This leaves a significant gap in knowledge about gas adsorption behaviors in larger reactors and when MOF sample sizes are increased (to the gram scale) for scaling up the process. Additionally, there is a notable dearth of experimental research in situations where MOFs are heavily saturated with water. To address these gaps, this study measures CH4 adsorption in MOFs under conditions of high moisture content, using larger samples of MOFs (in grams) and a large volume reactor. We selected commercially available MOFs, including HKUST-1, ZIF-8, MOF-303, and activated carbon. A high-pressure isotherms (at T = 274.15 K) using volumetric approach were measured to qualitatively compare the moles of gas adsorbed under both dry and wet conditions across different MOFs and weights. Experimental results show that the presence of water led to a decrease in total CH4 mmol adsorption in MOFs, with a more significant decrease observed in hydrophilic MOFs compared to hydrophobic ones. For hydrophilic MOFs, presence of crossover isotherms at crossover pressure provided evidence of water's conversion to hydrate and its positive role in enhancing total gas uptake, which varied among different hydrophilic MOFs. Oversaturated MOFs showed a larger deviation between dry and wet cases at higher pressures. The high-pressure isotherm data confirm the positive role of hydrophilic MOFs in the conversion of water to hydrate in oversaturated MOFs when MOFs sample size is large.

We present a study of the radio variability of bright, $S_{1.4}\geq100$ mJy, high-redshift quasars at $z\geq3$ on timescales up to 30--40 years. The study involved simultaneous RATAN-600 measurements at frequencies of 2.3, 4.7, 8.2, 11.2, and 22.3 GHz in 2017--2020. In addition, data from the literature were used. We have found that the variability index $V_S$ of the quasars ranges from 0.02 to 0.96, with about half of the objects in the sample showing a variability index in the range of 0.25--0.50, which is comparable to that of the blazars at lower redshifts. The distribution of $V_S$ at 22.3 GHz is significantly different from that at 2.3--11.2 GHz, which may be attributed to the fact that a compact AGN core dominates at the source's rest frame frequencies greater than 45 GHz, leading to higher variability indices obtained at 22.3 GHz (the $V_S$ distribution peaks around 0.4) compared to the lower frequencies (the $V_S$ distribution peaks around 0.1--0.2). Several source groups with distinctive variability characteristics were found using cluster analysis of quasars. We propose 7 new candidates for gigahertz peaked-spectrum (GPS) sources and 5 new megahertz peaked-spectrum (MPS) sources based on their spectrum shape and variability features. Only 6 out of 23 sources previously reported as GPS demonstrate a low variability level typical of classical GPS sources ($V_{S} < 0.25$) at 4.7--22.3~GHz. When excluding the highly variable peaked-spectrum blazars, we expect no more than 20\% of the sources in the sample to be GPS candidates and no more than 10\% to be MPS candidates.

Most works related to the identification of mathematical nonlinear systems make one suppose that such approaches can always be directly applied to any nonlinear system. This misconception produces a great deal of discouragement when the obtained results are not the expected ones. Thus, the current work hypothesizes that the most information one has about the mathematical structure of the model, the most precise the identification result should be. Therefore, a variant of the Sparse Identification of Nonlinear Dynamics (SINDY) approach is presented to obtain the full mathematical nonlinear model of a high-order system with coupled dynamics, namely, a commercial quadcopter. Furthermore, due to its high sensitivity to inputs, a control system is devised using the identified model to stabilize the quadcopter. This illustrates the effectiveness of the proposed identification method.

A novel process design for damage-free and highly accurate positional integration of an optical multi-axial force sensor into a hollow tube by means of rotary swaging is introduced. Numerical simulations reveal relevant process phenomena of thin disc joining inside a pre-toothed hollow tube and help to find an optimal process design. Experimental trials show a significant effect of axial material flow and the number of tools in a rotary swaging process. By taking these effects into account, a successful form- and force-fit joining of the sensor carrying discs into the tube can be achieved. A successful joining of an optical sensor for bending forces and torque measurement shows hysteresis-free sensory behavior and thus backlash-free joining of the sensor carrier discs. The paper finishes with presenting an approach for closed-loop position controlling during the joining process and numerically investigation of the process design.

Whole genome alignment (WGA) is a critical process in comparative genomics, facilitating the detection of genetic variants and aiding our understanding of evolution. This paper offers a detailed overview and categorization of WGA techniques, encompassing suffix tree-based, anchors-based, and graph-based methods. It elaborates on the algorithmic properties of these tools, focusing on performance and methodological aspects. The paper underscores the latest progress in WGA, emphasizing the increasing capacity to manage the growing intricacy and volume of genomic data. However, the field still grapples with computational and biological hurdles affecting the precision and speed of WGA. We explored these challenges and potential future solutions. This paper aims to provide a comprehensive resource for researchers, deepening our understanding of WGA tools and their applications, constraints, and prospects.

This study aimed to use biomineralization technology to improve the bond strength of fiber-reinforced lightweight aggregate concrete (LWAC) after exposure to temperatures of 300 °C and 500 °C. The specimens of a control group (Group A) and two experimental groups (Group B and Group C) were prepared. These specimens healed themselves in different ways after exposure to high temperatures and pull-out tests. The self-healing method of Group A involved placing the specimen into an incubator. The self-healing method of Group B was the same as that of Group A. The self-healing method of Group C involved immersing the specimen in a mixed solution of urea and calcium acetate for two days, then taking it out and placing it in an incubator for two days. A cycle of four days was undertaken until the desired age was reached. After the specimens were healed to the planned age, the first and secondary pull-out tests and repair compound identification were carried out. After exposure to a temperature of 300 °C and self-healing for 90 days, compared with the specimens in Group A, the relative bond strength ratios of the secondary pull-out tests of the specimens in Group C increased by 20.3%. This indicates that biomineralization can effectively improve the bond strength of LWAC after high-temperature damage.

In the broader landscape of cryptocurrency risk management, this study delves into the nuanced estimation of Value at Risk (VaR) for a uniformly weighted portfolio of cryptocurrencies, employing the bivariate Normal Inverse Gaussian distribution renowned for its semi-heavy tails. Utilizing high-frequency data spanning from January 1st, 2017, to October 25th, 2022, with a primary focus on Bitcoin and Ethereum, our research seeks to accentuate the resilience of VaR methodology as a paramount risk assessment tool. The essence of our investigation lies in advancing the comprehension of VaR accuracy by quantitatively comparing observed returns of both cryptocurrencies with their corresponding estimated values, with a central theme being the endorsement of the Normal Inverse Gaussian distribution as a potent model for risk measurement, particularly in the domain of high-frequency data. To bolster the statistical reliability of our results, we adopt a forward test methodology, showcasing not only a contribution to the evolution of risk assessment techniques in Finance but also underscoring the practicality of sophisticated distributional models in econometrics. Our findings not only contribute to the refinement of risk assessment methods but also highlight the applicability of such models in precisely modeling and forecasting financial risk within the dynamic realm of cryptocurrencies, epitomized by the case study of Bitcoin and Ethereum.

This study evaluated the effects of high-temperature and high-pressure treatment on the antioxidant and anti-inflammatory activities of carrot extracts. The total polyphenol and flavonoid content of heated carrot extract increased as the heating temperature increased, with 403.93 mg GAE/100 g and 53.14 mg CE/100 g at 150°C. DPPH and ABTs radical scavenging activity (IC50) of heated carrot extract also increased as the heating temperature increased, with 4.65 mg/mL and 7.31 mg/mL, respectively, at 150°C. The reducing power increased with the heating temperature. Heated carrot extract did not exhibit any temperature- or concentration-dependent cytotoxicity. Nitric oxide (NO) generation was suppressed as the heating temperature and NO production increased. The heated carrot extract showed a decrease in the production of dose-dependent TNF-α, IL-1β, and IL-6 compared to the control group. The above results show that heated carrot extract had effective antioxidant and anti-inflammatory activities.

Background: Oscillation and pulmonary expansion (OPE) therapy can decrease postoperative pulmonary complications in a general surgical population, but its effect after cardiac surgery has not been reported, to our knowledge. We hypothesized that using an OPE device after cardiac surgery before extubation would decrease pulmonary complications. Methods: This retrospective cohort study included adults undergoing elective open cardiac surgery at our institution from January 2018 through January 2019, who had an American Society of Anesthesiologists score of 3 or greater. For mechanically ventilated patients after cardiac surgery, a new OPE protocol was adopted July 1, 2019, comprising an initial 10-minute OPE treatment administered in-line with the ventilator circuit, then continued treatments for 48 hours after extubation. Severe postoperative respiratory complications (primary outcome measure) included need for antibiotics, increased supplemental oxygen use, and prolonged hospital length of stay (LOS). Demographic, clinical, and outcomes data were compared for patients before (usual care with postextubation hyperinflation) and after protocol implementation (OPE). Results: Of 104 patients, 54 patients received usual care, and 50 received OPE. Usual-care recipients had more men (74% vs 62%; P=.19) and were older (median, 70 vs 67 years; P=.009) than OPE recipients. The OPE group had a significantly shorter hospital LOS than the usual-care group (mean, 6.2 vs 7.4 days; P=.04). Other measures improved with OPE but did not reach significance: shorter ventilator duration (mean, 0.6 vs 1.1 days with usual care; P=.06) and shorter LOS in the intensive care unit (mean, 2.7 vs 3.4 days; P=.06). On multivariate analysis, intensive care unit LOS was significantly shorter for the OPE group (mean difference, 0.85 days; 95% CI, 1.65 to 0.06; P=.04). The OPE group had a lower percentage of postoperative complications (10% vs 20%). Conclusion: OPE therapy after cardiac surgery is associated with decreased ICU and hospital LOS.

We present a design of electrostatic comb driver to improve and investigate its actuation performance. The proposed electrostatic comb actuator (ECA) is composed of two set of interdigitated comb microstructures, the inner combs are fixed to form the fish-bone microstructures and the outer combs are movable and connected to crab-leg flexure beams microstructures. The ECA is investigated to optimize the actuation performance by changing the comb shape and the intersection angle of crab-leg flexure beams. The comb shapes are compared between the traditional rectangle shape and the trapezoid shape, while the intersection angles of crab-leg flexure beams are compared between 45°, 60°, and 90° on the influences of ECA displacement and stability characteristics. These parameters are investigated for their impacts on the dynamic comb displacement and driving voltage. Under the condition of a driving DC bias voltage of 100 volts, the ECA displacement is firstly increased and then gradually decreased by increasing the comb finger length. The maximum displacement of ECA with trapezoid comb is 47.2 μm while that of ECA with rectangle comb is 22.4 μm. By using trapezoid comb shape to replace the rectangle comb under the same conditions, the ECA displacement is improved 2-fold. To enhance the stability of ECA system, the intersection angle of 90˚ of crab-leg flexure beams shows highest stability that is great better than the intersection angle of 45° and 60° of crab-leg flexure beams by increasing the driving different DC bias voltage to 100 volts on ECA. The stability of the ECA with the intersection angle of 90° of crab-leg flexure beams is enhanced 1.1-fold and 1.4-fold compared to that of 45° and 60° of crab-leg flexure beams, respectively. This design provides an optimized approach to the electrostatic comb actuator that can be used expansively in the gyroscope, motion sensor, position sensor, imaging sensor, optical sensor, and so on.

We discuss how the interaction of electrons with an overdamped optical phonon can give rise to a strange-metal behavior over extended temperature and frequency ranges. Although the mode has a finite frequency, an increasing damping shifts spectral weight to progressively lower energies so that, despite the ultimate Fermi liquid character of the system at the lowest temperatures and frequencies, the transport and optical properties of the electron system mimic a marginal Fermi liquid behavior. Within this shrinking Fermi liquid scenario, we extensively investigate the electron self-energy in all frequency and temperature ranges, emphasizing similarities and differences with respect to the marginal Fermi liquid scenario.

Due to the lack of theoretical research on the amount of spatio-temporal information in the high-speed photography technologies, obtaining an optimized system with a best amount of spatio-temporal information remains a challenge, resulting in insufficient effective information and observation accuracy for ultrafast events. The paper presents an ultrafast raster imaging (URI) system with a large amount of spatio-temporal information based on the all-optical raster principle in single-shot. Specifically, we derive the optimal equation of spatial resolution and the expression for the maximum amount of spatio-temporal information that can achieve excellent performance for an URI system. It serves as a general guideline for getting a large amount of information design in the URI system. Compared to the existing URI systems, the advanced URI system exhibits an improvement of nearly 1 order of magnitude in the amount of spatio-temporal information, and more than twofold in spatial resolution. It shows a great potential for capturing intricate and non-repetitive ultrafast events on the femtosecond time scale.

New ways of generating energy are currently being discussed, with a transition from traditional primary sources to more environmentally friendly options, particularly renewables. Energy storage is also closely related to this transition. Battery storage currently dominates this area. However, flywheel energy storage system (FESS) technology offers an alternative that uses stored kinetic energy to be transformed into mechanical energy and, using a motor-generator, electrical energy. FESS technology is thus flexible and can be applied in different industrial applications. The management of the technology of recycling W-MMC waste material from other products and the subsequent trial production of high-strength W-MMC material with a density of more than 17 500 kg/m3 from recycled powders allowed to test the limits of the so-called "heavy" flywheels used in rotor production. Materials with densities ≥ 7 800 kg/m3, and operating at lower to medium speeds up to 20 000 rpm. The results achieved lead to the conclusion that the developed recycled materials of the W-MMC type with a density ≥ 17 500 kg/m3, with a yield strength of 1 200 - 1 700 MPa depending on the production method, can be used as a substitute for the structural steels used today, without an enforced reduction of the maximum allowed rotor speed due to exceeding the maximum allowed stress.

The processes of hydrogen reduction of silicon and germanium chlorides under the conditions of high-frequency (40.68 MHz) counteracted arc discharge stabilized between two rod electrodes are investigated. The main gas-phase and solid products of plasma-chemical transformations are determined. Thermodynamic analysis of SiCl4 + H2 and GeCl4 + H2 systems for optimal process parameters was carried out. Using the example of hydrogen reduction of SiCl4 by the method of numerical modeling, gas-dynamic and thermal processes for this type of discharge are investigated. The impurity composition of gas-phase and solid reaction products is investigated. The possibility of single-stage production of high-purity Si and Ge mainly in the form of compact ingots, as well as high-purity chlorosilanes and trichlorogermane, is shown.

Implementing High-Performance Computing to solve In-Memory Data Grid (IMDG)-based energy infrastructure resilience research problems in a heterogeneous environment presents a challenge to workflow management systems. Large-scale energy infrastructure needs multi-variant planning and tools to allocate and dispatch resources in IMDG taking into account the subject domain specificity, resource characteristics, and constraints and quotas for resource use. To that end, we propose a workflow management system using our Orlando Tools framework. To scale computing resources, we provide their integration and use corresponding software to determine key application parameters that can significantly impact the processed data size and the required number of allocated resources. We automated the IMDG cluster launch for the workflow executions. To demonstrate the advantage of our solution, we apply it to evaluate the resilience of the existing energy infrastructure model. Compared to similar approaches, our approach explores large infrastructures by modeling many simultaneously failed elements of different types up to the number of network elements. In terms of problem-solving efficiency and resource use, we achieve near-linear speedup with increasing the number of nodes of each resource.

Selecting drought-tolerant and more water-efficient wheat genotypes is a research priority, spe-cifically in regions with irregular rainfall or areas where climate change is expected to result in reduced water availability. The objective of this work was to use high-throughput measurements with morphophysiological traits to characterize wheat genotypes in relation to water stress. Field experiments were conducted from May to September 2018 and 2019, using a sprinkler bar irriga-tion system to control water availability to eighteen wheat genotypes: BRS 254; BRS 264; CPAC 01019; CPAC 01047; CPAC 07258; CPAC 08318; CPAC 9110; BRS 394 (irrigated biotypes) and Aliança; BR 18_Terena; BRS 404; MGS Brilhante; PF 020037; PF 020062; PF 120337; PF 100368; PF 080492; TBIO Sintonia (rainfed biotypes). The water regimes varied from 22 to 100% of the crop evapotranspiration replacement. Water stress negatively affected gas exchange, vegetation indices and grain yield. High throughput variables TCARI, NDVI, OSAVI, SAVI, PRI, NDRE and GNDVI had higher correlation with yield and morphophysiological measurements. The drought re-sistance index indicated that genotypes Aliança BRS 254, BRS 404, CPAC 01019, PF 020062, and PF 080492 were more drought tolerant.

The valley pseudospin properties of electrons in two–dimensional hexagonal materials result in lots of fascinating physical phenomena, which opens up the new field of valleytronics. The valley-contrasting physics aims at distinguishing the valley degree of freedom based on valley–dependent effects. Here, we theoretically demonstrate that both of the valley–selective high harmonic generation and valley–selective electronic excitation can be achieved by using an orthogonal two–color (OTC) laser field in gapped graphene. It is shown that the asymmetry degrees of harmonic yields in the plateaus, cutoff energies of generated harmonics and electron populations from two different valleys can be precisely controlled by the relative phase of the OTC laser field. Thus the selectivity of the dominant valley for the harmonic radiation and electronic polarization can be switched by adjusting the relative phase of the OTC laser field. Our work offers an all–optical route to produce the valley–resolved high harmonic emissions and manipulate the ultrafast valley polarization on a femtosecond timescale in condensed matter.

Mycoviruses are widespread across the major taxa of fungi including yeasts. Mycoviruses in the yeast fungus Geotrichum candidum are not well studied with three G. candidum-associated viral species characterized to date, all of which belong to the Totiviridae genus Totivirus. In this study, we report the molecular characteristics of another two totiviruses co-infecting isolate Gc6 of G. candidum. The two totiviruses were tentatively named Geotrichum candidum totivirus 2 (GcTV2-Gc6) and GcTV4-Gc6). Both viruses have typical genome organization of totiviruses comprising two ORFs encoding capsid protein (CP) and RNA-dependent RNA polymerase (RdRp) at the N and C termini, respectively. Genomes of GcTV2-Gc6 and GcTV4-Gc6 are 4592 and 4530 bp long, respectively. Both viruses contain the -1 frameshifting elements and their proteins could be expressed as a single fusion protein. GcTV2-Gc6 is closely related to a totivirus isolated from the same host whereas GcTV4-Gc6 is related to insect-associated totiviruses. The phylogenetic analysis indicated that GcTV2-Gc6 and GcTV4-Gc6 belong to two different sister clades, I-A and I-B, respectively. It is interesting that all viruses identified from G. candidum belong to the genus Totivirus. It is possible that the RNA interference (RNAi) mechanism is not active to suppress totivirus accumulation in isolate Gc6.

Understanding the thermal cracks of rock caused by high temperature is of great help to the development of underground engineering, such as geothermal mining, underground coal gasification. Although there has been many study on thermal cracking, it is not systematic and in-depth enough. In order to deeply study the thermal crack mechanism of rock, this paper conducted thermal cracking experiments on granite at different temperatures and heating/cooling paths, and qualitative and quantitative analysis was conducted on the crack initiation characteristics, propagation paths, and crack network morphology of rock thermal crack under different test conditions. The thermal crack mechanism was also analyzed from the perspectives of mineral petrology, fracture mechanics, thermodynamics, and other aspects. The research results show that there are two obvious mutation points in the study temperature range for samples with fast cooling paths (SF path: slow heating and fast cooling; FF path: fast heating and fast cooling), around 200-300 ℃ and 600 ℃, respectively, while for samples with slow cooling paths (SS path: slow heating and slow cooling; FS path: fast heating and slow cooling), there is only one mutation point around 600 ℃. The initiation positions of thermal cracking under all temperature paths are relatively similar, with intergranular crack located between particles at the edge of the sample or intercrystalline crack in the middle of feldspar or quartz aggregates. The initiation temperature of SF and FF path specimens is relatively low compared to SS and FS path specimens, and the number and size of cracks is small. The crack network structure formed by the SF path is the most complex, with the largest crack ratio and cumulative crack length; The crack network structure formed by the FF path is relatively complex, with a larger main crack size but relatively fewer secondary cracks; The FS and SS paths do not form a complex network with good connectivity. The process of thermal crack development can be divided into three stages: the development of small cracks, the joint development of main cracks and small cracks, and the connection of cracks into a network structure. The mechanism of thermal crack propagation is that the expansion and thermal conductivity between different crystals are different. The thermal stress caused by temperature gradient and the tension or shear stress caused by the inconsistent deformation of crystals form stress concentration in weak areas such as particles boundary, cleavage, and original cracks. Firstly, it causes some crystals with smaller strength or less rounded shape to crack, and when the combined stress is large, the cracks will gradually expand along the existing fine cracks. This also explains that the most main cracks of the SF and FF path specimens mainly surround some large mineral aggregates or between particles.

The study of velocimetry is important for characterizing and comprehending the effects of fluid flow, and the Particle Image Velocimetry (PIV) technique is one of the primary approaches for understanding the velocity vector field in a test section. Commercial PIV systems are expensive, with one of the main cost factors being high-speed camera equipment capable of capturing images at high frames per second (fps), rendering them impractical for many applications. This study proposes an evaluation of utilizing smartphones as image acquisition systems for PIV technique application. An experimental setup inspired by the known angular displacement of synthetic particles is proposed. A stepper motor rotates a plate containing an image of synthetic particles on its surface. The motion of the plate is captured by the smartphone camera, and the images are processed using PIVlab-MatLab® software. The use of two smartphones is assessed, with acquisition rates of either 240 fps or 960 fps and varying angular velocities. The results were satisfactory for velocities up to 0.7 m/s at an acquisition rate of 240 fps and up to 1.8 m/s at 960 fps, validating the use of smartphones as a cost-effective alternative for the PIV technique.

In this paper, a robust nonlinear dynamic controller is designed for a wind turbine with a permanent magnet synchronous generator. The wind turbine is subject to variations in all the parameters appearing in its mathematical model. Furthermore, the wind velocity is considered unavailable for direct measurement. This situation is of particular interest in practical applications, where only the nominal parameter values are known, and accurate wind velocity measurement is challenging due to perturbations caused by the turbine itself, even with appropriate sensors. The problem addressed in this work involves tracking the reference angular velocity corresponding to the wind velocity. To achieve accurate tracking, appropriate compensation of the perturbation terms resulting from parameter uncertainties and wind estimation errors is required. To address this problem, an estimator of the wind velocity is utilized, along with high–order sliding mode parameter estimators, to ensure high–performance operation of the turbine.

An experimental platform for laser-driven ion (sub-MeV) acceleration and potential applications was recently commissioned at the HiLASE laser facility. The auxiliary beam of the Bivoj laser system operating at GW peak power (~10 J in 5-10 ns) and 1-10 Hz repetition rate enabled a sta-ble production of high-current ion beams of multiple species (Al, Ti, Fe, Si, Cu, Sn). The pro-duced laser-plasma ion sources were fully characterized against the laser intensity on target (1013-1015 W/cm2) by varying the laser energy, focal spot size, and pulse duration. This al-lowed to provide accurate scaling laws of the maximum ion energy for the different target ma-terials investigated. Such experimental scaling laws are presented for the first time in the inves-tigated laser intensity range and for ns-class laser pulses, and allow to provide a qualitative in-terpretation of the laser-plasma interaction underpinning physics, thus to tune the main features of the accelerated ion beams (energy, temperature, and current). Such a detailed study was facil-itated by the large amount of data acquired at high repetition rate (1-10 Hz) provided by the Bivoj laser system. The versatility and tuneability of such high-repetition-rate laser-plasma ion sources are of po-tential interest for multidisciplinary user applications.

Cervical cancer is the most common female reproductive tract tumor and is currently the only cancer that can be prevented by vaccination. Early detection and treatment of cervical cancer can be achieved through regular screening for human papillomavirus (HPV). Therefore, in this paper, an electrochemical sensor was designed to detect HPV 16 using a dual signal amplification technique. APTES modified glassy carbon electrode to improve stability. Combining gold nanoparticles and chain amplification reactions for signal amplification purposes. The limit of detection (LOD) was 1.731×10-16 mol/L, and the detection range of this electrochemical sensor was increased in comparison to previous research, with a linear response range from 1.0×10-13 mol/L to 1.0×10-5 mol/L (R2 = 0.99232) for the target detector.In addition, the sensor showed equally good recovery in sophisticated human serum samples. It shows that it has good interference resistance and the designed biosensor can be a powerful and reliable tool for clinical disease diagnosis.

A conventionally cast CoNiFeMn0.5Cr1.5 alloy and two versions with 0.25C&amp;3.7Ta or 0.25C&amp;3.7Hf were tested in oxidation at 1000°C for 50h with thermogravimetric recording of the oxidation kinetic. In all cases the obtained mass gain curves are parabolic. Their parabolic constants are much lower than the Kp previously determined for the original alloys with an equimolar base (CoNiFeMnCr). However, the post–mortem exploitation of the oxidized samples revealed analogous oxidation features on surface and subsurface, with here too external oxide strata on surface with different Mn and Cr contents, and rather great Mn–depletion in addition to a moderate Cr–depletion, in subsurface. Globally, the oxidation behavior is significantly better than earlier observed for the equimolar version of these alloys.

We consider new insights into the origin and nature of pointer states and their role in wave function collapse in macroscopic quantum coherence. The work includes new theory of quantum coherence underpinned by turbulence, generated by a field of pointer states in the form of recirculating vortices (toroids), interconnected via a vortex cascade. Decoherence occurs when the interconnected field of vortices between pointer states is disrupted by external forces, leading to their localisation. The applicability of this work is considered in addressing unresolved questions in high temperature superconductivity and macroscopic quantum processes in biological systems. We also consider its implications for our understanding of intrinsic spin and pointer states within the standard "point source" representation of a quantum particle, which intuitively requires a more complexed description.

Nowadays, with the development of laser weapons, the primary power supply of laser weapons puts forward more and more high demand for its performance. The pulsed power supply based on conventional homopolar inductor alternator (HIA) cannot meet the requirements any more. In order to improve the power density and efficiency, this paper proposes applying the high-temperature superconducting (HTS) HIA with slotless stator core to this power supply. In this paper, the design considerations of it are presented, and the comparisons between the two power supplies are discussed. The calculation results show that the power supply based on HTS machine has much larger power density than the conventional HIA, and the efficiency is also larger than the conventional HIA. This can improve the performance of laser weapons dramatically.

Kampus Mengajar is a teaching and learning activity in schools as part of the independent campus learning policy (MBKM) initiated by Nadiem Anwar Makarim, B.A., M.B.A. as Minister of Education, Culture, Research, and Technology of the Republic of Indonesia. This article aims to find out the teaching campus, a form of direct student service in the world of education? This article is a qualitative descriptive with a literature study. The result of this article is that all work program designs that have been prepared together can be implemented well at SMP Dhaniswara Surabaya and get quite satisfactory results.

Global warming causes an alarming increase in temperature which negatively affects growth, physiology, and yield of rice. To gain some insights into the impacts of booting HT (at 42°C, 3 h for 7 days), we investigated its effect in three rice genotypes, namely, N22, KDML105 and IR64. Booting HT caused an extended phenology and lower photosynthesis and plant growth rate but an increase in chalkiness. Although, prolonged phenology from dough to physiological maturity led to longer duration of grain filling, the negative effects of its was significantly lower yield components, yield and harvest index in all rice. Among cultivars, N22 presented adapted ability to maintain leaf gas exchange and compensated vegetative part by an increase in tiller numbers resulting in less affected growth rate. It prolonged phenology that caused extended grain filling. Consequence, N22 was the lowest reduction in number of seed panicle^–1, number of filled seeds hill^–1, yield, HI as well as the lowest percentage chalkiness. KDML105 adapted to booting HT by maintaining leaf gas exchange, increasing specific leaf area and prolonging phenology. The longest extended phenology together with the maintenance of high photosynthesis during dough grain were associated with moderate yield reduction and chalkiness. However, IR64 showed dramatic reductions in photosynthesis, growth rate, and yield but highest percentage grain chalkiness. Therefore, in response to booting HT, N22, KDML105 and IR64 could be indicated as being heat tolerant, moderately heat sensitive, and heat sensitive, respectively. This can be applied for crop modelling and rice heat tolerance in breeding program.

This work reports the first nanocrystalline SnON (7.6 % Nitrogen content) n-type nanosheet Field-Effect Transistor (nFET) with transistor’s effective mobility (µeff) as high as 357 and 325 cm2/V-s at electron density (Qe) of 5×1012 cm-2 and ultra-thin body thickness (Tbody) of 7 and 5 nm, respectively. At the same Tbody and Qe, these µeff values are significantly higher than single crystalline Si, InGaAs, thin-body Si-on-Insulator (SOI), two-dimensional (2D) MoS2 and WS2. New discovery of slower µeff decay rate at high Qe than SiO2/bulk-Si universal curve was found, owing to one order of magnitude lower effective field (Eeff) by more than 10 times higher dielectric constant () in channel material, which keeps the electron wave-function away from the gate-oxide/semiconductor interface and lowers the gate-oxide surface scattering. In addition, the high µeff is also due to the overlapped large radius s-orbitals, low 0.29 mo effective mass (me*) and low polar optical phonon scattering. SnON nFETs with record-breaking µeff and quasi-2D thickness enable potential monolithic three-dimensional (3D) integrated circuit (IC) and embedded memory for 3D biological brain-mimicking structures.

Greenery-covered towers are a new generation of tall buildings characterized by substantial integration of vegetation. They aim to improve the quality of urban life by reducing air pollution, enhancing biodiversity, creating microclimates, and providing aesthetic and psychological benefits. This paper examines the innovative design approaches of greenery-covered towers, drawing on examples from different countries and contexts. It analyzes the technical, environmental, social, and economic aspects of these projects, as well as the challenges and opportunities they pose for the future of sustainable architecture. The paper concludes that greenery-covered towers should be further developed and refined to become a potential solution for addressing dense cities’ environmental and health issues.

Background: Children with anorectal malformation (ARM) require long-term follow-up, especially for fecal continence and main predictors of longer-term success are the type of ARM, associated anomalies and sacral integrity. Three-Dimensional High Resolution Anorectal Manometry (3D-HRAM) provides an image of the pressure profile of anal sphincter complex. Aim of study was to evaluate the anal sphincter function in ARM patients with 3D HRAM correlating this analysis to clinical outcome and to associated malformations. Methods: Forty ARM patients, were submitted to 3D HRAM: manometric, anatomical and clinical score were correlated to response to bowel management (BM). Results: A positive correlation between all scores and type of ARM was found: in high ARM and in patients with spinal anomalies (regardless to ARM type) lower scores were reported and even after BM they do not achieve good continence. Conclusions: 3D-HRAM provides information on the functional anatomy of the sphincter complex. Our study shows good correlation between the manometric results and clinical outcome, confirming spinal malformations and ARM type as most important prognostic risk factors for poor outcome. Specific sphincteric defects can be explored with manometry, allowing for tailored bowel management strategies.

This paper presents a novel high-power rotary waveguide phase shifter based on circular polarizers specifically engineered for high-power microwave (HPM) applications. The phase shifter is capable of performing a precise 360° linear phase shift through rotation and consists of three parts: a linear polarized to left-handed circular polarized (LP-LHCP) mode converter, a left-handed to right-handed circular polarized (LH-RHCP) mode converter, and a linear polarized to right-handed circular polarized (LP-RHCP) mode converter. The paper analyzes the phase shifting principle, optimizes the three parts of the X-band rotary waveguide phase shifter, and conducts simulation studies on the entire phase shifter made of aluminum. The results show that the reflection is less than -20dB and the transmission efficiency is over 95% within 9.5GHz to 10.2GHz. The phase shift has a linear relationship with the rotation angle by a factor of two within this frequency range. Specifically, the phase shifter can achieve a linear phase shift of 360° when rotated from 0° to 180°, with a maximum deviation of less than 1.2°. Moreover, the power-handling capacity of the phase shifter in vacuum exceeds 242mW.

Ultra-short laser pulses (1030 nm/230 fs) were used to laser ablate surface of crystalline sapphire. Laser ablated patterns were annealed at high temperature 1500∘C. Surface reconstruction took place removing ablation debris field at the edges of ablated pits in oxygen flow. Partial reconstruction of ripples was also observed.

The gut microbiota plays a crucial role in childhood obesity, and diet is a dominating driver. The effects of fructo-oligosaccharides (FOS), as a dietary fiber, on the composition and metabolism of gut microbiota in healthy children was investigated by vitro fermentation system with a reformative YCFA medium (rich in tryptic hydrolysates of meat). The 16S rRNA sequencing technology was utilized to analyze the varieties of gut microbiota. Measurement of short chain fatty acids (SCFAs) and gases were used by the gas chromatograph. Majorbio Cloud Platform and MetOrigin, as the interactive cloud server, perform the microbiota analysis, the metabolic pathway enrichment analysis, the statistical correlations, and biological relationships using network visualization. We found that the FOS group significantly regulated the composition and metabolism of gut microbiota. The co-metabolism network showed that 3 metabolites were related to 6 differential bacteria and 8 metabolism pathways. These findings suggest that dietary fiber could regulate the composition of gut microbiota and its metabolites in a better direction, but when dietary fiber participates in precision nutrition formula, it may be relevant for precision obesity, may help identify windows of opportunity for the dietary intervention of childhood obesity.

The quality of underground space information has become a major problem that endangers the safety of underground spaces. Currently, the main methods for the high-precision and long-distance transmission of detection information are radar and optical methods. However, in practical applications, we found that the radar method has the shortcomings of large energy loss and poor anti-jamming ability, which limit the accuracy of information data transmission and distance. The optical method has the shortcomings that the weather has a great impact on its accuracy and can only be applied to static objects above ground; therefore, it has the limitation of application objects and use environment. More importantly, the current high-precision information remote detection methods are limited to the detection of overground space objects and are not applicable to the detection of various information data in underground space. In this study, we analyze the spectral properties of the fractional differential operator and find that it is suitable for studying non-linear, non-causal, and non-stationary signals. The theory of fractional calculus is applied to the field of data processing, and a mathematical model of remote transmission and high-precision detection of information based on fractional difference is established, which realizes the functions of high-precision and remote detection of information. By fusing the information data to detect the mathematical model over a long distance and with high accuracy, a mathematical model for stratum data processing used to provide long-distance and high-accuracy data was established. Through application in engineering practice, the effectiveness of this method for underground space information data detection was verified.

This exploratory study examined the impacts of COVID-19 and emerging challenges and opportunities from aviation recovery. Using archival and secondary data analysis, the study found that there are several challenges to aviation recovery chief among them are labour challenges and extreme weather events, which have been responsible for traffic disruptions in major aviation markets such as Europe and the USA. Other emerging challenges include high debt, inflation, interest rates, fuel, cost of labour, and general operational costs. The study recommends several interventions to address the sector’s challenges, including adopting risk disaster preparedness and management to foster sustainability.

This paper proposes an encryption scheme for high pixel density images. Based on the application of the quantum random walk algorithm, the Long short-term memory (LSTM) can effectively solve the problem of low efficiency of the quantum random walk algorithm in generating large-scale pseudorandom matrices, and further improve the statistical properties of the pseudorandom matrices required for encryption. The LSTM is then divided into columns and fed into the LSTM in order for training. Due to the randomness of the input matrix, the LSTM cannot be trained effectively, so the output matrix is predicted to be highly random. The LSTM prediction matrix of the same size as the key matrix is generated based on the pixel density of the image to be encrypted, which can effectively complete the encryption of the image. In the statistical performance test, the proposed encryption scheme achieves an average information entropy of 7.9992, an average number of pixels changed rate (NPCR) of 99.6231%, an average uniform average change intensity (UACI) of 33.6029% and an average correlation of 0.0032. Finally, various noise simulation tests are also conducted to verify its robustness in real-world applications where common noise and attack interference are encountered.

A large number of studies have concluded that since housing pressure will affect the mobility of highly skilled young migrants (HSYM) in Chinese cities and regions, it is necessary to apply corresponding housing policies to adjust housing unaffordability for HYSM. This study uses a survey data conducted in China's Zhejiang Province of China, where specific policies have been implemented to attract talent and found that housing does crowds out the HSYM from a city, but the HSYM who have a master's degree or above or who work in government organizations or state-owned enterprises are more tolerant of housing unaffordability. The unmarried or those staying in the city for a long period are less tolerant of housing unaffordability. Meanwhile, there are the heterogeneous impacts of factors on the HSYM's tolerance for housing unaffordability across cities of different levels. Therefore, housing policies should highlight urban differences and intra-group differences.

In this paper a high-power and propellant-free electromagnetic propulsion is proposed based on the General Relativity and nuclear fusion technology. We find that Riemann curvature vanish and geodesic motion is free from gravitational field locally in a special space-time, which demonstrates the feasibility of propellant-free electromagnetic propulsion. To achieve high-power propulsion in Schwarzschild background, we choose current loop as axisymmetric field source and obtain exact solution of Einstein-Maxwell field equation using Killing symmetry and Ernst generation technique. An implementation with superconductor shield is given according to the Meissner effect, calculation implies that the device can be sufficiently free from gravitational field with the aid of existing nuclear fusion engineering.

(1) Background: High blood pressure is one of the symptoms of stroke, the Self Care Deficit theory by Dorothea Orem focuses on a person's ability to care for himself independently so that the ability to maintain his health and well-being is achieved. There are currently 600 million hypertensive patients worldwide, of which 3 million die every year. Uncontrolled high blood pressure can lead to a 7-fold increase in the chances of stroke. The existence of this condition can be minimized in patients through several innovative interventions, one of which is foot massage. This study aims to determine the effectiveness of stretching and foot massage with lavender oil in stabilizing high blood pressure in stroke patients.(2) Methods: The method used in this research is descriptive. The subjects of this case study were selected according to the inclusion and exclusion criteria of the journal Evidence-Based. Subjects included intervention patients and control patients. Foot massage therapy with lavender oil is done 2 times a day for 10-15 minutes using the effleurage technique after showering in the morning and evening. Stretching is done 2 times a day every 10-15 minutes.(3) Results: The results of the analysis showed that there was a change in blood pressure after the application of stretching and foot massage with lavender oil. From the initial examination, the results showed that the blood pressure of 170/100 mmHg decreased to 140/90 mmHg and the pain scale decreased from 4 to 0.

Many studies in the field of robot navigation have focused on environment representation and localization. The goal of map representation is to summarize spatial information in topological and geometrical abstracts. By providing strong priors, maps improve the performance and reliability of automated robots. Due to the transition to fully automated driving in recent years, there has been a constant effort to design methods and technologies to improve the precision of road participants and the environment's information. Among these efforts is the High Definition (HD) Map concept. Making HD maps requires accuracy, completeness, verifiability, and extensibility. Because of the complexity of HD mapping, it is currently expensive and difficult to implement, particularly in an urban environment. In an urban traffic system, the road model is at least a map with sets of roads, lanes, and lane markers. While more research is being dedicated to mapping and localization, a comprehensive review of the various types of map representation is still required. This paper presents a brief overview of map representation, followed by a detailed literature review of HD Map for automated vehicles. The current state of AV mapping is encouraging, the field has matured to a point where detailed maps of complex environments are built in real-time and have been proved useful. Many existing techniques are robust to noise and can cope with a large range of environments. Nevertheless, there are still open problems for future research. AV mapping will continue to be a highly active research area essential to the goal of achieving full autonomy.

Genomics involving tens of thousands of genes is a complex system determining phenotype. An interesting and vital issue is that how to integrate highly sparse genetic genomics data with a mass of minor effects into prediction model for improving prediction power. We find that deep learning method can work well to extract features by transforming highly sparse dichotomous data to lower dimensional continuous data in a non-linear way. This idea may provide benefits in risk prediction based on genome-wide data associated e.g. integrating most of the information in the genotype data. Hence, we developed a multi-stage strategy to extract information from highly sparse binary genotype data and applied it for risk prediction. Specifically, we first reduced the number of biomarkers via a univariable regression model to a moderate size. Then a trainable auto-encoder was used to extract compact representations from the reduced data. Next, we performed a LASSO problem process over a grid of tuning parameter values to select the optimal combination of extracted features. Finally, we applied such feature combination to two prognostic models, and evaluated predictive effect of the models. The results of simulation studies and real data applying indicated that these highly compressed transformation features could better improve predictive performance and did not easily lead to over-fitting.

We present here a five hours experimentation of a didactical path about the electromagnetic induction addressed to students of the last year of an Italian scientific high school and oriented to better understand the physical origin of the induced electromotive force. The expression of the induced electromotive force as the sum of the term linked to the time variation of the magnetic field and of the motional one has been obtained in a detailed way, still suitable for presentation at high school. Many examples have been proposed to the students in order to clarify the conceptual physical knots. The students’ responses to a 6-questions multiple choice questionnaire have been analyzed. It emerged that our approach is concretely feasible although we find the well-known difficulties in calculating flux and circulation of a vector field. Furthermore, it emerged that an integral approach to the problem masks the understanding of the nature of the forces acting locally on the charges. Hence our proposal of a “redefinition” of the induced electric field in terms of the magnetic vector potential is also presented.

Directed energy deposition (DED) is an efficient method to fabricate functionally graded materials (FGMs) with gradient composition and complex structures, allowing for local tailoring of properties instead of the costly need for extraneous welds and joints. In this study, a FGM from stainless steel to Inconel alloy was successfully fabricated using the powder-based laser DED. A very refined grain structure has been observed in at the composition with 75 wt.% Inconel alloy content, which also exhibits the highest (entropy). For the first time, the post heat treatments, microstructure and aging precipitation behaviors of FGMs were systematically studied via experimental characterization and computation, to elucidate their effects on the gradient smoothing and mechanical properties. The diffusion and segregation of Ni, Nb and Ti elements underly the transformation mechanism between Laves, δ, γ’ and γ’’ phases during precipitation. Homogenization on FGMs not only eliminates the heterogeneity inherited from the AM process, but also provides a practical way to smoothen the gradient on composition and microstructure for the eventual good gradient properties. It has a direct influence on the following precipitation behaviors in the FGM, which highly relies on the diffusion degree of the elements in the matrix and grain boundaries. The high-throughput thermodynamic modeling and kinetic modeling were exploited to evaluate the experimental microstructure and address computational uncertainty using different thermodynamic conditions and databases, which enables an accelerated design through local tailoring of process-structure-property relationships to develop new functional materials.

The ridge line of the western Pacific subtropical high (WPSHRL) plays an important role in determining the shift of the summer rain belt in eastern China. In this study, we developed a forecast system for the June WPSHRL index based on the latest autumn and winter sea surface temperature (SST). Considering the adverse condition of the small observed sample size, a very simple neural network (NN) model was selected to extract the non-linear relationship between input predictors (SST) and target predictands (WPSHRL) in the forecast system. In addition, some techniques are used to deal with the adverse condition, enhance the stabilization of forecast skills, and analyze the interpretability of the forecast system. The forecast experiments show that the linear correlation coefficient between the predictions from the forecast system and their corresponding observations is around 0.6, and about three-fifths of the observed abnormal years (the years with an obviously high or low WPSHRL index) are successfully predicted. Furthermore, sensitivity experiments show that the forecast system is relatively stable in terms of forecast skill. The above evaluations suggest that the forecast system is valuable in a real application sense.

In this study, we propose a solution process for realizing color glass for building integrated pho-tovoltaic (BIPV) systems by spin coating a color solution composed of a pearlescent pigment mixed in a norland optical adhesive (NOA) matrix. Color solutions are made from mixing pearlescent pigments in NOA63. Compared to a physical vapor deposition process, color coatings are achieved by spin coating in a relatively simple and inexpensive process at room temperature. The optical properties can be easily controlled by adjusting the spin coating speed and the concentra-tion of the pearlescent pigments. The produced color glasses achieved a high transmittance of 85% or more in the visible wavelength range, except the wavelength spectrum exhibiting the maxi-mum reflectance. In addition, we propose a one-step lamination process of color glass on a solar cell by leveraging on the adhesive property of the NOA matrix. This eliminates the cost and pro-cess of additional ethylene vinyl acetate (EVA) layer or other materials used in the conventional lamination process. The color glass produced through this study has stability that does not change its properties over time. Therefore, it is expected to be applied to the BIPV solar module market where aesthetics and energy efficiency are required.

Phenotypical screening is a widely used approach in drug discovery for the identification of small molecules with cellular activities. However, functional annotation of identified hits often poses a challenge. The development of small molecules with narrow or exclusive target selectivity such as chemical probes and chemogenomic (CG) libraries, greatly diminishes this challenge, but non-specific effects caused by compound toxicity or interference with basic cellular functions still poses a problem to associate phenotypic readouts with molecular targets. Hence, each compound should ideally be comprehensively characterized regarding its effects on general cell functions. Here, we report an optimized live-cell multiplexed assay that classifies cells based on nuclear morphology, presenting an excellent indicator for cellular responses such as early apoptosis and necrosis. This basic readout in combination with the detection of other general cell damaging activities of small molecules such as changes in cytoskeletal morphology, cell cycle and mitochondrial health provides a comprehensive time-dependent characterization of the effect of small molecules on cellular health in a single experiment. The developed high-content assay offers multi-dimensional comprehensive characterization that can be used to delineate generic effects regarding cell functions and cell viability, allowing an assessment of compound suitability for subsequent detailed phenotypic and mechanistic studies.

Vocational interest inventories are widely used by career counselors to help individuals to make career choices. The most common approach to assess vocational interests is based on verbal or textual stimuli. However, some of them are based on pictorials to overcome reading limits and provide additional information about the working environment and the activities related to a particular job. This article aims to present two studies on the development and first validation of the Multilingual Iconographic Professional Interest Inventory (MIPII) on two samples, one composed of 792 high-school students, and one composed of 366 middle school students. The inventory aimed to assesses the vocational interests of people over 19 areas by illustrations representing 95 jobs, five for each one, combined with their title in six different languages (Arabic, German, English, Spanish, French and Italian in this order). Both illustrations and titles are provided separately in the male and female version on the same page.

Currently available nationwide prediction models for fine particulate matter (PM_2.5) lack prediction confidence intervals and usually do not describe cross validated model performance at different spatiotemporal resolutions and extents. We used 41 different spatiotemporal predictors, including data on land use, meteorology, aerosol optical density, emissions, wildfires, population, traffic, and spatiotemporal indicators to train a machine learning model to predict daily averages of PM_2.5 concentrations at 0.75 sq km resolution across the contiguous United States from 2000 through 2020. We utilized a generalized random forest model that allowed us to generate asymptotically-valid prediction confidence intervals and took advantage of its usefulness as an ensemble learner to quickly and cheaply characterize leave-one-location-out CV model performance for different temporal resolutions and geographic regions. Using a variable importance metric, we selected 8 predictors that were able to accurately predict daily PM_2.5, with an overall leave-one-location-out cross validated median absolute error of 1.20 ug/m³, an R² of 0.84, and confidence interval coverage fraction of 95%. When considering aggregated temporal windows, the model achieved leave-one-location-out cross validated median absolute errors of 0.99, 0.76, 0.63, and 0.60 ug/m³ for weekly, monthly, annual, and all-time exposure assessments, respectively. We further describe the model’s cross validated performance at different geographic regions in the United States, finding that it performs worse in the Western half of the country where there are less monitors. The code and data used to create this model are publicly available and we have developed software packages to be used for exposure assessment. This accurate exposure assessment model will be useful for epidemiologists seeking to study the health effects of PM across the continental United States, while possibly considering exposure estimation accuracy and uncertainty specific to the the spatiotemporal resolution and extent of their study design and population.