Properties Of Objects Research Articles

Tuning the Mechanical Properties of 3D-printed Objects by Mixing Chain Transfer Agents in Radical Promoted Cationic RAFT Polymerization.

The utilization of (cationic) reversible addition-fragmentation chain transfer (RAFT) polymerization in photoinduced three-dimensional (3D) printing has emerged as a robust technique for fabricating a variety of stimuli-responsive materials. However, methods for precisely adjusting the mechanical properties of these materials remain limited, thereby constraining their broader applicability. In this study, a facile way is introduced to modulate the mechanical properties of 3D printed objects by mixing two chain transfer agents (CTAs) within a radical-promoted cationic RAFT (RPC-RAFT) polymerization-based 3D printing process. Through systematic investigations employing tensile testing and dynamic mechanical analysis (DMA), the influence of CTA concentration and molar ratio between two CTAs on the mechanical behavior of the printed objects are explored. These findings demonstrate that higher concentrations of CTAs or a greater molar ratio of the more active CTA within the mixed CTAs result in decreased Young's modulus and glass transition temperatures of the printed objects. Moreover, the tensile failure strain increased with the increasing CTA content, i.e., the samples became more ductile. This methodology broadens the toolbox available for tailoring the mechanical properties of 3D printed materials.

Lightweight Water Surface Object Detection Network for Unmanned Surface Vehicles

The detection algorithms for water surface objects considerably assist unmanned surface vehicles in rapidly perceiving their surrounding environment, providing essential environmental information and evaluating object attributes. This study proposes a lightweight water surface target detection algorithm called YOLO-WSD (water surface detection), based on YOLOv8n, to address the need for real-time, high-precision, and lightweight target detection algorithms that can adapt to the rapid changes in the surrounding environment during specific tasks. Initially, we designed the C2F-E module, enriched in gradient flow compared to the conventional C2F module, enabling the backbone network to extract richer multi-level features while maintaining lightness. Additionally, this study redesigns the feature fusion network structure by introducing low-level features and achieving multi-level fusion to enhance the network’s capability of integrating multiple levels. Meanwhile, it investigates the impact of channel number differences in the Concat module fusion on model performance, thereby optimizing the neural network structure. Lastly, it introduces the WIOU localization loss function to bolster model robustness. Experiments demonstrated that YOLO-WSD achieves a 4.6% and 3.4% improvement in mAP0.5 on the water surface object detection dataset and Seaship public dataset, respectively, with recall rates improving by 5.4% and 8.5% relative to the baseline YOLOv8n model. The model’s parameter size is 3.3 M. YOLO-WSD exhibits superior performance compared to other mainstream lightweight algorithms.

Are spatial terms rooted in geometry or force-dynamics? Yes.

Theories of spatial term meanings often focus on geometric properties of objects and locations as the key to understanding meaning. For example, in English, "The cat is on the mat" might engage geometric properties characterizing the figure ('cat', a point) and the ground ('mat', a plane) as well as the geometric relationship between the two objects ('on', + vertical, 0 distance from ground object). However, substantial literature suggests that geometric properties are far from sufficient to capture the meanings of many spatial expressions, and that instead, force-dynamic properties of objects that afford containment or support relationships may be crucial to the meanings of those expressions. I will argue that both approaches are needed to understand the variety of spatial terms that appear in language and further, that spatial terms fall into two distinct sets, one represented by geometric properties of figure and ground and their spatial relationships, and the other by the force-dynamic properties of objects and their relationships. This division of labor within spatial terms has many consequences, with the two types differing in the nature of the acquisition problem and likely learning mechanisms, the extent and kind of cross-linguistic variation that has been observed, and the application of pragmatic principles to spatial terms. Speculatively, the two types may also be rooted in different cognitive systems and their neural substrates.

On the Way to Machine Consciousness: Identification of Hidden System Properties of Material Objects

On the Way to Machine Consciousness: Identification of Hidden System Properties of Material Objects

Evaluation of the quality of electrochemical study in the diagnosis of infection of pancreatic cysts

The formation of pancreatic cysts is a serious complication of acute pancreatitis, chronic pancreatitis and pancreatic injuries. Joulemetry is an integral method for evaluating the electrochemical properties of biological objects. To date, this method has not been used in the study of the electrochemical properties of the contents of pancreatic cysts. The purpose of this study was to evaluate the effectiveness of electrochemical analysis in the detection of infection in the contents of necrotic pancreatic cysts. An electrochemical study of contents of necrotic pancreatic cysts carried out on 106 patients. Group 1 included 84 patients without signs of infection of pancreatic cysts; group 2 included 22 patients with signs of infection of pancreatic cysts. The electrochemical study was conducted as follows: 10 ml of the contents of a pancreatic cyst was injected into a liquid ˛ow sensor of a joule meter, where it was exposed to a electrical current for a short period of time. The resulting data was analyzed using a diagnostic research complex. During the study of the electrochemical properties of the contents of postnecrotic pancreatic cysts by using joulemetry, it was revealed that the current work in patients of group 1 ranged from 0.92 to 18.31 mkJ (on average 5.86±5.02 mkJ), in patients of group 2 – from 19.01 to 26.3 mkJ (on average 22.32±1.92 mkJ). When evaluating the quality of the joulemetric study in determining the early signs of in˛ammation of the contents of postnecrotic pancreatic cysts, it was proved that the threshold differential diagnostic value of 19.1 mkJ provides 81.8% sensitivity of the proposed method and 80.7% specificity (AUC = 91.3) with a statistically signi˝cant difference in current work (p < 0.001).

Predicting the effect of binding molecules on the shape and mechanical properties of structured DNA assemblies

Chemo-mechanical deformation of structured DNA assemblies driven by DNA-binding ligands has offered promising avenues for biological and therapeutic applications. However, it remains elusive how to effectively model and predict their effects on the deformation and mechanical properties of DNA structures. Here, we present a computational framework for simulating chemo-mechanical change of structured DNA assemblies. We particularly quantify the effects of ethidium bromide (EtBr) intercalation on the geometry and mechanical properties of DNA base-pairs through molecular dynamics simulations and integrated them into finite-element-based structural analysis to predict the shape and properties of DNA objects. The proposed model captures various structural changes induced by EtBr-binding such as shape variation, flexibility modulation, and supercoiling instability. It enables a rational design of structured DNA assemblies with tunable shapes and mechanical properties by binding molecules.

Quantum communications for image transmission over error‐prone channels

AbstractThe introduction of quantum communications, enabled by advancements in quantum computing, is expected to play a significant role in the field of communications. Inherent properties of quantum objects, such as superposition and entanglement, have the potential to provide novel solutions to overcome the challenges encountered by classical communication systems in bandwidth‐intensive applications such as media transmission. This research explores the performance of a quantum communication system in image transmission using quantum superposition and investigates its performance using a simple quantum channel model. With an increase in channel noise, there are significant gains in the rate distortion performance of images transmitted over the quantum channel compared to an ideal classical channel. This novel attempt at constructing a quantum communication‐based image transmission system indicates the potential of the approach to be applied to satisfy the ever‐increasing demands of high‐quality media transmission applications.

Оценка различных форм груши кавказской (P. caucasica Fed.) для селекции на декоративность

Abstract. The article describes the results of studying the morphological features of 93 forms of P. caucasica Fed. collected in various regions of the Caucasus. The research was carried out in the collection gardens score, and samples with lower scores, but having one or more attractive decorative features. The studied samples of the Caucasian pear had valuable decorative qualities to varying degrees: narrow pyramidal crown (index 2.16) – Kasp-69-59; rounded crown (index 0.88) – 67-Chr-249, 67-B-208, Ard-69-18; large flowers – Ter-69-77, 67-Ku-139, 67-BZ-37, B-69-111, 67-BZ-67, B-69-87, Kasp-69-59; abundant flowering – P. caucasica Fed. № 2, P. caucasica Fed. №3, P. caucasica Fed. №6, B-69-88, L-69-98, L-69-101, Shali-69-36; attractive appearance of leaves, absence of fungal diseases – Arg-69-34, 67-B-190, Ur-69-1, 67-Chr-250, B-69- 78; anthocyanin integumentary coloration of fruits – P. caucasica Fed. №4 and №5, B-69-108, Kasp-69-59. Frost resistance of plants was an important feature for the use in ornamental gardening. This property was noted in the samples of P. caucasica Fed. №4, B-69-78, Ard-69-18. Samples B-69-90, B-69-78 had edible sweet fruits. Selected forms of the Caucasian pear retained their decorative properties during the growing season. The forms B69-88, B-69-78, Kasp-69-59, L-69-96, 67-Ku-127 can have the greatest value for breeding in terms of the sum of points and the presence of valuable features. Keywords: the Caucasus, the Caucasian pear, decorativeness, morphology, diversity of features, selection, breeding Financing source: The research was carried out at the expense of a grant from the Federal State Budgetary Educational Institution «Maikop State Technological University» «Assessment of various forms of Caucasian pear (P. caucasica Fed.) for breeding for decorative purposes», registration number of the scientific project: NP 8-2024 of the Maikop Experimental Station – a branch of All-Union Research Institute of Plant Breeding (VIR) in 2021-2023s in accordance with modern methods of studying and assessing the decorative properties of research objects. Twenty-two samples were identified, including those with the highest total decorative

Digital Light Processing Resins with Programmable Shape Memory for Biomedical Applications.

The creation of biodegradable and biocompatible shape memory polymers amenable to biofabrication techniques remains a challenge. The ability to create shape-changing biodegradable objects that are triggered at body temperature opens up possibilities in tissue engineering, minimally invasive surgery, and actuating bioimplants. Merging Digital Light Processing (DLP) printing with shape memory polymers brings us closer to new smart biomedical outcomes. Previously, we developed a poly(caprolactone-co-trimethylenecarbonate) urethane acrylate resin for the DLP fabrication of biodegradable 3D objects. In further studies, we observed that some of these resins possessed shape memory properties, triggered by body temperature (37 °C). In this subsequent study, we explored the shape memory properties and tunability of this resin family via changes in copolymer composition, molecular weight, and identity of the acrylate end-capping unit. We found that we could create a library of shape memory resins, amenable to DLP printing, which allowed the creation of shape-actuating structures with some tunability over the speed of shape memory and mechanical properties. We observed that increased mole fraction of caprolactone in the copolymer and increased molecular weight of the polymer led to a decrease in speed of the shape memory switch. Furthermore, we observed a trade-off between the composition and the end-capping moiety on the mechanical properties of the polymers. These polymeric resins were able to be processed into shapes that were able to perform work, including the release of cargo and grabbing/lifting of an object. This platform now provides a way to tune the speed and mechanical properties of a shape memory DLP object created from common and scalable polymerization techniques. This work ultimately provides a new platform to develop customizable and biodegradable devices capable of actuating and delivery devices for numerous biomedical applications.

Better-Making Properties and the Objectivity of Value Disagreement

A light form of value realism is defended according to which objective properties of comparison objects make value comparisons true or false. If one object has such a better-making property and another lacks it, this is sufficient for the truth of a corresponding value comparison. However, better-making properties are only necessary and usually not sufficient parts of the justifications of value comparisons. The account is not reductionist; it remains consistent with error-theoretic positions and the view that there are normative facts.

Recent advancements in flow control using plasma actuators and plasma vortex generators

AbstractFlow‐control techniques have attracted significant attention in many scientific areas due to their ability to improve the effectiveness and regulate the flow of aerodynamic devices. This study explores the latest developments in flow‐control techniques, specifically concentrating on the cutting‐edge technologies of plasma vortex generators (PVGs) and actuators. By taking advantage of the ionization of gases or air, plasma actuators have become a viable method for modifying an object's aerodynamic properties without needing physical moving parts. These actuators create localized plasma discharges that interact with the surrounding flow to provide accurate separation control, boundary‐layer dynamics, and aerodynamic forces on aircraft wings, wind turbine blades, and other surfaces. PVG, which produce controlled vortical structures, offer a novel way to manipulate airflow with plasma actuators. These generators create swirling motions through plasma discharges that can be used in various technical applications, such as automotive, marine, and aviation, to modify boundary layers, reduce drag, and improve lift characteristics. This study offers an overview of recent work, focusing on the theoretical underpinnings, experimental validations, and practical applications of plasma‐based flow‐control technologies. Advances in plasma‐generating techniques, computational modeling approaches, and experimental configurations to optimize and comprehend the intricate fluid–structure interactions are covered in the debate. Moreover, the study delves into incorporating plasma‐based flow management into cars, renewable energy systems, and next‐generation aerospace designs, highlighting the possibility of increased agility, decreased emissions, and efficiency. It also discusses the difficulties and potential paths for developing these technologies further for use in business and industry, highlighting the necessity of dependable, scalable, and durable solutions. Finally, this study summarizes the most recent advancements in vortex generators and plasma actuators for flow control. It demonstrates how they have the power to revolutionize fluid dynamics and aerodynamics in a variety of engineering fields.

Modelling and simulating the geoelectrical attributes of near-surface buried objects to optimizing its discovery

Modelling and simulating the geoelectrical attributes of near-surface buried objects to optimizing its discovery

The quantum Gaussian-Schell model: a link between classical and quantum optics.

The quantum theory of the electromagnetic field uncovered that classical forms of light were indeed produced by distinct superpositions of nonclassical multiphoton wave packets. This situation prevails for partially coherent light, the most common kind of classical light. Here, for the first time, to our knowledge, we demonstrate the extraction of the constituent multiphoton quantum systems of a partially coherent light field. We shift from the realm of classical optics to the domain of quantum optics via a quantum representation of partially coherent light using its complex-Gaussian statistical properties. Our formulation of the quantum Gaussian-Schell model (GSM) unveils the possibility of performing photon-number-resolving (PNR) detection to isolate the constituent quantum multiphoton wave packets of a classical light field. We experimentally verified the coherence properties of isolated vacuum systems and wave packets with up to 16 photons. Our findings not only demonstrate the possibility of observing quantum properties of classical macroscopic objects but also establish a fundamental bridge between the classical and quantum worlds.

Francisco J. Ayala: Testing his Ideas on Biological Progress

Francisco J. Ayala was one of the great scholars of progress in biological evolution. For Ayala, progress consists of a net directional change in some characteristic that improves the descendants in a given lineage relative to the ancestors. This is an axiological proposal, but not at all unscientific. The traits are objective properties that can be measured in individuals, populations, or species and, ultimately, the entire evolutionary tree. Here, we develop Ayala’s ideas about progress and propose that the trait where the trend can be contrasted is probably the complexity of genomes. We also consider the need to apply statistical tests to determine whether trends, if they exist, are passive products of evolution from the simplest to the most complex or whether, on the contrary, there is directionality or a process driven, among other things, by natural selection.

Deconstructing SE-Constructions: Number Agreement and Postsyntactic Variation

Most analyses of nonparadigmatic SE sentences derive their agreement patterns structurally, forcing a passive/impersonal distinction against all evidence. Instead, we uniformly analyze them as regular sentences where the T-agreeing subject is se itself, an argumental clitic pronoun, with [person] but no number ϕ-features, and show that the overt argument, which has object properties, does not genuinely agree in syntax. We reveal a new asymmetry between postverbal and preverbal/null arguments, which conceals two postsyntactic processes with very distinctive properties: morphological Clitic Mutation into number agreement, and T’s Number Harmony with a close DP, not ruled by syntax or morphology.

An approximate Kerr–Newman-like metric endowed with a magnetic dipole and mass quadrupole

Approximate all-terrain spacetimes for astrophysical applications are presented. The metrics possess five relativistic multipole moments, namely, mass, rotation, mass quadrupole, charge, and magnetic dipole moment. All these spacetimes approximately satisfy the Einstein–Maxwell field equations. The first metric is generated using the Hoenselaers–Perjés method from given relativistic multipoles. The second metric is a perturbation of the Kerr–Newman metric, which makes it a relevant approximation for astrophysical calculations. The last metric is an extension of the Hartle–Thorne metric that is important for obtaining internal models of compact objects perturbatively. The electromagnetic field is calculated using Cartan forms for locally non-rotating observers. These spacetimes are relevant for inferring properties of compact objects from astrophysical observations. Furthermore, the numerical implementations of these metrics are straightforward, making them versatile for simulating potential astrophysical applications.

Learning feature relationships in CNN model via relational embedding convolution layer

Establishing the relationships among hierarchical visual attributes of objects in the visual world is crucial for human cognition. The classic convolution neural network (CNN) can successfully extract hierarchical features but ignore the relationships among features, resulting in shortcomings compared to humans in areas like interpretability and domain generalization. Recently, algorithms have introduced feature relationships by external prior knowledge and special auxiliary modules, which have been proven to bring multiple improvements in many computer vision tasks. However, prior knowledge is often difficult to obtain, and auxiliary modules bring additional consumption of computing and storage resources, which limits the flexibility and practicality of the algorithm. In this paper, we aim to drive the CNN model to learn the relationships among hierarchical deep features without prior knowledge and consumption increasing, while enhancing the fundamental performance of some aspects. Firstly, the task of learning the relationships among hierarchical features in CNN is defined and three key problems related to this task are pointed out, including the quantitative metric of connection intensity, the threshold of useless connections, and the updating strategy of relation graph. Secondly, Relational Embedding Convolution (RE-Conv) layer is proposed for the representation of feature relationships in convolution layer, followed by a scheme called use & disuse strategy which aims to address the three problems of feature relation learning. Finally, the improvements brought by the proposed feature relation learning scheme have been demonstrated through numerous experiments, including interpretability, domain generalization, noise robustness, and inference efficiency. In particular, the proposed scheme outperforms many state-of-the-art methods in the domain generalization community and can be seamlessly integrated with existing methods for further improvement. Meanwhile, it maintains comparable precision to the original CNN model while reducing floating point operations (FLOPs) by approximately 50%.

White dwarf magnetospheres: Shielding volatile content of icy objects and implications for volatile pollution scarcity

Context. About 25–50% of white dwarfs are found to be contaminated by heavy elements, which are believed to originate from external sources such as planetary materials. Elemental abundances suggest that most of the pollutants are rocky objects and only a small fraction of white dwarfs bear traces of volatile accretion. Aims. In order to account for the scarcity of volatile pollution, we investigate the role of the white dwarfs’ magnetospheres in shielding the volatile content of icy objects. Methods. We estimated the volatile sublimation of inward drifting exocomets. We assume the orbits of the exocomets are circularized by the Alfvén wing drag that is effective for long-period comets. Results. Volatile material can sublimate outside the corotation radius and be shielded by the magnetic field. The two conditions for this volatile-shielded mechanism are that the magnetosphere radius must be larger than the corotation radius and that the volatiles are depleted outside the corotation radius, which requires a sufficiently slow orbital circularization process. We applied our model to nine white dwarfs with known rotational periods, magnetic fields, and atmosphere compositions. Our volatile-shielded model may explain the excess of volatile elements such as C and S in the disk relative to the white dwarf atmosphere in WD2326+049 (G29-38). Nevertheless, given the sensitivity of our model to the circularization process and material properties of icy objects, there remains considerable uncertainty in our results. Conclusions. We emphasize the importance of white dwarfs’ magnetic fields in preventing the accretion of volatile gas onto them. Our work suggests a possible explanation for the scarcity of volatile-accretion signatures among white dwarfs. We also identify a correlation between the magnetic field strength, the spin period, and the composition of pollutants in white dwarf atmospheres. However, given the uncertainties in our model, more observations are necessary to establish more precise constraints on the relevant parameters.

VISUALIZATION OF THREATS IN CIVIL SECURITY USING THREE-DIMENSIONAL SPATIAL MODELING

The article analyzes the main concepts and methods of modeling used in civil security to solve the issues of analyzing the prerequisites for the occurrence of hazards, by forecasting, preventing and managing their components. On-site research, in particular, direct measurements, can only be carried out on an already existing object. Modeling today is one of the important methods, the main methodology of which is to learn the essence of natural and social phenomena of various levels of complexity. It provides an opportunity to demonstrate various systems related to civil security using methods of applied mathematics, mathematical statistics and optimization. The task of analysis and forecasting on any object can be reduced to building a model that reflects the behavior of a natural object. The main tasks of this article are to establish modeling principles and methods for their use in civil security using the example of modeling noise maps from various sources, one of which is construction in a dense residential area. The task of analysis and forecasting on almost any object can be reduced to building a model that adequately reflects the behavior of a natural object. The basic principles on which modeling is based are defined. The principle of information sufficiency – building its model is impossible in the complete absence of information about the object. Feasibility principle – the model should ensure the achievement of the research goal with a non-zero probability value. The principle of multiplicity of models - the model should reflect exactly those properties of a real object or system that are of interest to the researcher. The principle of aggregation - the system is better decomposed as a set of subsystems, for the description of which standard schemes can be used. Principle of parameterization – the model must be built in the form of a known system, the parameters of which are unknown. Crisis simulation training is a common organizational tool for improving civil security preparedness. Although today its general advantages cannot be denied, the conditions under which these simulations offer opportunities for improvement often remain unclear.

TAFSIR ILMI MUKJIZAT AL-QUR’AN TENTANG ASTROFISIKA

This article aims to express the Koran's views on astrophysics, one of the fields of science that studies the properties of physical phenomena and astronomical objects in the Universe. Some of Allah's verses are written and some are implied. The Qur'an is the written verse of Allah while the universe is the written verse of Allah. Because both are verses from Allah, there should be no conflict between the two because they both come from Allah SWT. This effort was carried out using qualitative methods and combining them with thematic interpretation methods. So it was found that the Koran talks a lot about written verses such as the sky, light, sun, moon, stars, black holes, and life outside the earth.