Hasil untuk "Municipal refuse. Solid wastes"

Fabio Turazza, Alessandro Neri, Marcello Pietri et al.

Effective demand forecasting is crucial for reducing food waste. However, data privacy concerns often hinder collaboration among retailers, limiting the potential for improved predictive accuracy. In this study, we explore the application of Federated Learning (FL) in Sustainable Supply Chain Management (SSCM), with a focus on the grocery retail sector dealing with perishable goods. We develop a baseline predictive model for demand forecasting and waste assessment in an isolated retailer scenario. Subsequently, we introduce a Blockchain-based FL model, trained collaboratively across multiple retailers without direct data sharing. Our preliminary results show that FL models have performance almost equivalent to the ideal setting in which parties share data with each other, and are notably superior to models built by individual parties without sharing data, cutting waste and boosting efficiency.

Yuto Yokota, Dai Nakashima, Ryusuke Ikeda

Physical properties of the vortex solid phase formed in the second Landau level (2LL), which may be stabilized by strong paramagnetic pairbreaking (PPB), are examined in type II limit with no magnetic screening. First, it is shown that the spectrum of the low energy mode of this vortex solid has the same form as that of the conventional vortex solid in the first (i.e., the lowest) Landau level. Using this result, the melting line of the 2LL vortex solid is examined according to the Lindemann criterion. In contrast to the properties in equlibrium, the electromagnetic response of this vortex solid is quite unusual: Reflecting the presence of antivortices supporting the stability of the lattice structure, the superfluid stiffness measuring the response for a current perpendicular to the magnetic field is found to be nonvanishing, and its sign depends upon the applied current direction. Consequences of this response property are briefly discussed.

Dalga Merve Özkan, Sergio Lucia, Sebastian Engell

This paper presents a general mathematical programming framework for the design and optimization of supply chain infrastructures for the upcycling of plastic waste. For this purpose, a multi-product, multi-echelon, multi-period mixed-integer linear programming (MILP) model has been formulated. The objective is to minimize the cost of the entire circular supply chain starting from the collection of post-consumer plastic waste to the production of virgin-equivalent high value polymers, satisfying a large number of constraints from collection quota to the quality of the feedstock. The framework aims to support the strategic planning of future circular supply chains by determining the optimal number, locations and sizes of various types of facilities as well as the amounts of materials to be transported between the nodes of the supply chain network over a specified period. The functionality of the framework has been tested with a case study for the upcycling of rigid polyurethane foam waste coming from construction sites in Germany. The economic potential and infrastructure requirements are evaluated, and it has been found that from a solely economic perspective, the current status of the value chain is not competitive with fossil-based feedstock or incineration. However, with the right economic incentives, there is a considerable potential to establish such value chains, once the upcycling technology is ready and the economic framework conditions have stabilized.

Muhammad Ali, Omar Ali AlSuwaidi

In the realm of waste management, automating the sorting process for non-biodegradable materials presents considerable challenges due to the complexity and variability of waste streams. To address these challenges, we introduce an enhanced neural architecture that builds upon an existing Encoder-Decoder structure to improve the accuracy and efficiency of waste sorting systems. Our model integrates several key innovations: a Comprehensive Attention Block within the decoder, which refines feature representations by combining convolutional and upsampling operations. In parallel, we utilize attention through the Mamba architecture, providing an additional performance boost. We also introduce a Data Fusion Block that fuses images with more than three channels. To achieve this, we apply PCA transformation to reduce the dimensionality while retaining the maximum variance and essential information across three dimensions, which are then used for further processing. We evaluated the model on RGB, hyperspectral, multispectral, and a combination of RGB and hyperspectral data. The results demonstrate that our approach outperforms existing methods by a significant margin.

Victor Babiano-Suarez, Javier Balibrea-Correa, Ion Ladarescu et al.

Nuclear energy production is inherently tied to the management and disposal of radioactive waste. Enhancing classification and monitoring tools is therefore crucial, with significant socioeconomic implications. This paper reports on the applicability and performance of a high-efficiency, cost-effective and portable Compton camera for detecting and visualizing low- and medium-level radioactive waste from the decommissioning and regular operation of nuclear power plants. The results demonstrate the good performance of Compton imaging for this type of application, both in terms of image resolution and reduced measuring time. A technical readiness level of TRL7 has been thus achieved with this system prototype, as demonstrated with dedicated field measurements carried out at the radioactive-waste disposal plant of El Cabril (Spain) utilizing a pluarility of radioactive-waste drums from decomissioned nuclear power plants. The performance of the system has been enhanced by means of computer-vision techniques in combination with advanced Compton-image reconstruction algorithms based on Maximum-Likelihood Expectation Maximization. Finally, we also show the feasibility of 3D tomographic reconstruction from a series of relatively short measurements around the objects of interest. The potential of this imaging system to enhance nuclear waste management makes it a promising innovation for the nuclear industry.

Attila Joó

Let $ D=(V,E) $ be a (possibly infinite) digraph and $ A,B\subseteq V $. A hindrance consists of an $ AB $-separator $ S $ together with a set of disjoint $ AS $-paths linking a proper subset of $ A $ onto $ S $. Hindrances and configurations guaranteeing the existence of hindrances play an essential role in the proof of the infinite version of Menger's theorem and are important in the context of certain open problems as well. This motivates the investigation of circumstances under which hindrances appear. In this paper we show that if there is a ``wasteful partial linkage'', i.e. a set $ \mathcal{P} $ of disjoint $ AB $-paths with fewer unused vertices in $ B $ than in $ A $, then there exists a hindrance.

Suman Kunwar, Banji Raphael Owabumoye, Abayomi Simeon Alade

With the increasing use of plastic, the challenges associated with managing plastic waste have become more challenging, emphasizing the need of effective solutions for classification and recycling. This study explores the potential of deep learning, focusing on convolutional neural networks (CNNs) and object detection models like YOLO (You Only Look Once), to tackle this issue using the WaDaBa dataset. The study shows that YOLO- 11m achieved highest accuracy (98.03%) and mAP50 (0.990), with YOLO-11n performing similarly but highest mAP50(0.992). Lightweight models like YOLO-10n trained faster but with lower accuracy, whereas MobileNet V2 showed impressive performance (97.12% accuracy) but fell short in object detection. Our study highlights the potential of deep learning models in transforming how we classify plastic waste, with YOLO models proving to be the most effective. By balancing accuracy and computational efficiency, these models can help to create scalable, impactful solutions in waste management and recycling.

Yoshitaka Ueki, Satoshi Matsuo, Masahiko Shibahara

Degradation in performances of air conditioners and refrigerators is caused by a frost formation and adhesion on the surface. In the present study, by means of the classical molecular dynamics simulation, we investigate how and how much the nanotextured surface characteristics, such as surface wettability and geometry, influenced the interfacial thermal resistance (ITR) between the solid wall and the water/ice. The ITR of the interfacial region was comparable in both the water and the ice states. As the nanostructure gaps became narrower, the ITR of the interfacial region decreased. The local ITR had a weak negative correlation with the local H2O molecule density regardless of the phase of the H2O molecules. The local ITR decreased as the local density increased. The greater amount of the thermal energy was transferred through the material interface by means of the intermolecular interaction when more the H2O molecules were located in the proximity area, which was closer to the Pt solid wall than the first adsorption layer peak. When the H2O molecules were in the crystal form on the solid wall, the proximity molecules decreased, and then the local ITR significantly increased.

Heather Wiebe, Tom L. Underwood, Graeme J. Ackland

The Lennard-Jones potential is perhaps one of the most widely-used models for the interaction of uncharged particles, such as noble gas solids. The phase diagram of the classical LJ solid is known to exhibit transitions between hcp and fcc phases. However, the phase behaviour of the quantum Lennard-Jones solid remains unknown. Thermodynamic integration based on path integral molecular dynamics and lattice dynamics calculations are used to study the phase stability of the hcp and fcc Lennard-Jones solids. The hcp phase is shown to be stabilized by quantum effects in PIMD while fcc is shown to be favoured by lattice dynamics, which suggests a possible re-entrant low pressure hcp phase for highly quantum systems. Implications for the phase stability of noble gas solids are discussed. For parameters equating to Helium, the expansion due to zero-point vibrations is associated with quantum melting: neither crystal structure is stable at zero pressure.

Yasushi Kawashima

It was predicted that solid metallic hydrogen can be obtained if solid molecular hydrogen is pressured to high pressure at low temperature about 80 years ago. Furthermore, the solid metallic hydrogen was theoretically predicted to show superconductivity at room temperature. In addition, surprising prediction was made that the solid metallic hydrogen is a metastable metal with a potential barrier of 1 eV. This prediction implies that the solid metallic hydrogen remains in the metallic solid phase state even after it is released from high pressure. Shock compression synthesized liquid metallic hydrogen so far. However, to obtain metallic hydrogen under ambient pressure at room temperature, it is necessary to synthesize solid metallic hydrogen. It is theoretically predicted that an ultrahigh pressure of ~500 GPa is required to produce solid metallic hydrogen. This pressure is close to the limit of the high pressure that can be generated by the diamond anvil cell (DAC). Therefore, it is difficult to synthesize metallic hydrogen by using DAC. Shock compression methods can generate a sufficiently high pressure to synthesize metallic hydrogen. But it is impossible to synthesize solid metallic hydrogen by these methods because these accompany generation of high temperature. There is currently no definitive way to synthesize solid metallic hydrogen. Here we report a new dynamic high-pressure apparatus which aims for synthesis of solid metallic hydrogen. We show that by using this apparatus, it is possible to generate a high pressure of 1 TPa, the pressure maintaining time is 103 to 106 times longer than the conventional dynamic compression method. Furthermore, we show that this apparatus is not accompanied by the generation of high temperature unlike the conventional dynamic compression method and then it is possible that solid metallic hydrogen might be synthesized by this apparatus.

P. Shukla, R. Srivastava

Moirangthem Shubhakanta Singh, R. K. Brojen Singh

Monte carlo simulation of paths of a large number of impinging electrons in a multi-layered solid allows to define area of spreading electrons (A) to capture overall behavior of the solid. This parameter 'A' follows power law with electron energy. Further, change in critical energies, which are minimum energies lost corresponding to various electrons, as a function of variation in lateral distance also follows power law nature. This power law behavior could be an indicator of how strong self-organization a solid has which may be used in monitoring efficiency of device fabrication.

Cassie Kettwich, David Anderson, Mark Walker et al.

We report laboratory measurements of the absorption coefficient of solid para-H2, within the wavelength range from 1 to 16.7 micron, at high spectral resolution. In addition to the narrow rovibrational lines of H2 which are familiar from gas phase spectroscopy, the data manifest double transitions and broad phonon branches that are characteristic specifically of hydrogen in the solid phase. These transitions are of interest because they provide a spectral signature which is independent of the impurity content of the matrix. We have used our data, in combination with a model of the ultraviolet absorptions of the H2 molecule, to construct the dielectric function of solid para-H2 over a broad range of frequencies. Our results will be useful in determining the electromagnetic response of small particles of solid hydrogen. The dielectric function makes it clear that pure H2 dust would contribute to IR extinction predominantly by scattering starlight, rather than absorbing it, and the characteristic IR absorption spectrum of the hydrogen matrix itself will be difficult to observe.

Nicolas Destainville, Suresh Govindarajan

We study the asymptotic behavior of solid partitions using transition matrix Monte Carlo simulations. If $p_3(n)$ denotes the number of solid partitions of an integer $n$, we show that $\lim_{n\rightarrow\infty} n^{-3/4} \log p_3(n)\sim 1.822\pm 0.001$. This shows clear deviation from the value $1.7898$, attained by MacMahon numbers $m_3(n)$, that was conjectured to hold for solid partitions as well. In addition, we find estimates for other sub-leading terms in $\log p_3(n)$. In a pattern deviating from the asymptotics of line and plane partitions, we need to add an oscillatory term in addition to the obvious sub-leading terms. The period of the oscillatory term is proportional to $n^{1/4}$, the natural scale in the problem. This new oscillatory term might shed some insight into why partitions in dimensions greater than two do not admit a simple generating function.

Naoki Hasegawa, Tatsuro Yuge, Akira Shimizu

We compare rigidity of materials in two phases, liquid and solid phases. As a measure of the rigidity, we employ the one characterizing how firmly the material is fixed by low density of pinning centers, such as impurities and rough surfaces of walls, against a weak force. Although a solid is more rigid than a liquid against a low-frequency force, we find that against a high-frequency force the liquid becomes more rigid than the solid of the same material. Since this result is derived from universal properties of a response function, it is valid for wide classes of materials, including quantum and classical systems and crystalline and amorphous solids. An instructive example is studied using nonequilibrium molecular dynamics simulations. We find that the frequency region in which a solid is more flexible than a liquid is not purely determined by intrinsic properties of the solid. It depends also on extrinsic factors such as the density of pinning centers.

S. Gerassimidou, A. Evangelou, D. Komilis

Nirvana B. Caballero, Mariano Zuriaga, Marcelo A. Carignano et al.

We present a detailed analysis of the molecular kinetics of CHCl$_3$ in a range of temperatures covering the solid and liquid phases. Using nuclear quadrupolar resonance we determine the relaxation times for the molecular rotations in solid at pre-melting conditions. Molecular dynamics simulations are used to characterize the rotational dynamics in the solid and liquid phases and to study the local structure of the liquid in terms of the molecular relative orientations. We find that in the pre-melting regime the molecules rotate about the C-H bond, but the rotations are isotropic in the liquid, even at supercooled conditions.

Rakesh S. Singh, Biman Bagchi

Solid-solid collapse transition in open framework structures is ubiquitous in nature. The real difficulty in understanding detailed microscopic aspects of such transitions in molecular systems arises from the interplay between different energy and length scales involved in molecular systems, often mediated through a solvent. In this work we employ Monte Carlo (MC) simulations to study the collapse transition in a model molecular system interacting via both isotropic as well as anisotropic interactions having different length and energy scales. The model we use is known as Mercedes-Benz (MB) which for a specific set of parameters sustains three solid phases: honeycomb, oblique and triangular. In order to study the temperature induced collapse transition, we start with a metastable honeycomb solid and induce transition by heating. High density oblique solid so formed has two characteristic length scales corresponding to isotropic and anisotropic parts of interaction potential. Contrary to the common believe and classical nucleation theory, interestingly, we find linear strip-like nucleating clusters having significantly different order and average coordination number than the bulk stable phase. In the early stage of growth, the cluster grows as linear strip followed by branched and ring-like strips. The geometry of growing cluster is a consequence of the delicate balance between two types of interactions which enables the dominance of stabilizing energy over the destabilizing surface energy. The nuclei of stable oblique phase are wetted by intermediate order particles which minimizes the surface free energy. We observe different pathways for pressure and temperature induced transitions.

Duk Y. Kim, Moses H. W. Chan

In 2004, Kim and Chan (KC) carried out torsional oscillator (TO) measurements of solid helium confined in porous Vycor glass and found an abrupt drop in the resonant period below 200 mK. The period drop was interpreted as probable experimental evidence of nonclassical rotational inertia (NCRI). This experiment sparked considerable activities in the studies of superfluidity in solid helium. More recent ultrasound and TO studies, however, found evidence that shear modulus stiffening is responsible for at least a fraction of the period drop found in bulk solid helium samples. The experimental configuration of KC makes it unavoidable to have a small amount of bulk solid inside the torsion cell containing the Vycor disc. We report here the results of a new helium in Vycor experiment with a design that is completely free from any bulk solid shear modulus stiffening effect. We found no measureable period drop that can be attributed to NCRI.

Klaus Denecke, Jorg Koppitz, Slavcho Shtrakov

Hypersubstitutions are mappings which map operation symbols to terms. Terms can be visualized by trees. Hypersubstitutions can be extended to mappings defined on sets of trees. The nodes of the trees, describing terms, are labelled by operation symbols and by colors, i.e. certain positive integers. We are interested in mappings which map differently colored operation symbols to different terms. In this paper we extend the theory of hypersubstitutions and solid varieties to multi-hypersubstitutions and colored solid varieties. We develop the interconnections between such colored terms and multi-hypersubstitutions and the equational theory of Universal Algebra. The collection of all varieties of a given type forms a complete lattice which is very complex and difficult to study; multi-hypersubstitutions and colored solid varieties offer a new method to study complete sublattices of this lattice.