Miracle-dz/UniFAR-FTUs huggingface dataset:
3D Monte Carlo simulation: Effects of the scanning strategy on the grain evolution of AISI 304 powder by laser melting deposition

As a typical additive manufacturing, laser melting deposition (LMD) is particularly sensitive to processing parameter. The microstructure dramatically affects the mechanical properties of the parts, but it is highly time-consuming and expensive to reveal the microstructural characteristic by experiments. An optimized Potts-Monte Carlo model was used in this paper to simulate the grain growth of LMD with three different scanning strategies. By analyzing the simulated results, it is revealed that the numerical model can be used to grain evolution patterns. Comparing the trends of grain evolution of three scanning strategies, growth angle of grains is strongly related to the scanning direction of the processing path. It is helpful to restrain the epitaxial growth of grain and homogenize crystallographic texture by adding angular deflection of path at adjacent layers. Simultaneously, the corresponding experiments were carried out to compare with the simulation. These experimental results agree well with the simulation. Graphical abstract
Treatment of Ready-To-Eat Cooked Meat Products with Cold Atmospheric Plasma to Inactivate Listeria and Escherichia coli

Ready-to-eat meat products have been identified as a potential vehicle for Listeria monocytogenes. Postprocessing contamination (i.e., handling during portioning and packaging) can occur, and subsequent cold storage together with a demand for products with long shelf life can create a hazardous scenario. Good hygienic practice is augmented by intervention measures in controlling post-processing contamination. Among these interventions, the application of ‘cold atmospheric plasma’ (CAP) has gained interest. The reactive plasma species exert some antibacterial effect, but can also alter the food matrix. We studied the effect of CAP generated from air in a surface barrier discharge system (power densities 0.48 and 0.67 W/cm2) with an electrode-sample distance of 15 mm on sliced, cured, cooked ham and sausage (two brands each), veal pie, and calf liver pâté. Colour of samples was tested immediately before and after CAP exposure. CAP exposure for 5 min effectuated only minor colour changes (ΔE max. 2.7), due to a decrease in redness (a*), and in some cases, an increase in b*. A second set of samples was contaminated with Listeria (L.) monocytogenes, L. innocua and E. coli and then exposed to CAP for 5 min. In cooked cured meats, CAP was more effective in inactivating E. coli (1 to 3 log cycles) than Listeria (from 0.2 to max. 1.5 log cycles). In (non-cured) veal pie and calf liver pâté that had been stored 24 h after CAP exposure, numbers of E. coli were not significantly reduced. Levels of Listeria were significantly reduced in veal pie that had been stored for 24 h (at a level of ca. 0.5 log cycles), but not in calf liver pâté. Antibacterial activity differed between but also within sample types, which requires further studies.
Structure Formation in Complex Plasma - Quantum Effects in Cryogenic Complex Plasmas

Abstract : This research showed the bow shock formation in a complex plasma, where plasma particles and charged dust particles form a complex entity. The formation was visible by naked eyes through the illumination of laser light on dust particles. The supersonic flow was possible to make in a complex plasma since dust acoustic wave is characterized by a sound speed of a few cm per second. This observation is important as it is a good representation of bow shocks commonly observed in planetary magnetospheres. This experiment showed the vortex formation and mass ejection in a complex plasma. Movement of dust particles is visible through the illumination of dust particles by laser light. The observation clarified the vortex physics commonly observed in nature such as tornados and typhoons, and even in the universe such as solar mass ejection. Molecular dynamic simulation of a complex plasma showed the formation of double helical structures of dust particles. The simulation and theory showed that a complex plasma characterized by its strongly coupled state could play a role in the understanding of structural formation of matters in general. Experiments, computer simulations and theoretical studies have shown that a complex plasma is rich research field to understand basic physics of various phenomena through the observation of dust particles by naked eyes with the help of laser irradiation. This research team has shown that a complex plasma is opening a new field in the well-established plasma physics.
Reshaping the outskirts of planetary systems

We present N -body calculations of the orbital evolution of a test population of primordial Edgeworth-Kuiper Belt objects (EKBOs) in a star cluster submitted to the gravitational perturbations of other cluster members, both single stars and binaries. In order to provide initial conditions for the EKBO test population, three original orbital distributions (eccentricity and semi-major axis) are considered. The (cid:12)rst resembles a conventional model of the evolution of the solar nebula with eccentricity, e = 0.01 and semi-major axis uniformly distributed in the range 35{60 AU. The second distribution considers the stage of planet formation after Neptune’s outward migration with concentration of solid particles at 39 AU and e (cid:24) 0 : 1 − 0 : 3. The third distribution is taken from a non-collisional, two-dimensional simulation of a gaseous protoplanetary disk in which solid particles beyond 60 AU are perturbed by the growing proto-planets, Uranus and Neptune. Metric particles are trapped in an outer resonance with radial distance of about 48.5 AU and eccentricity of 0.16. Stellar encounters lead to signi(cid:12)cant modi(cid:12)cation of the primordial orbital distribution only if the Sun was born in a typical open cluster but not in an association. Our results suggest that the observed orbital distribution of the scattered EKBOs may be the result of these multi-body gravitational interactions in the Sun’s parent star cluster. On the other hand, the circular shape of the Edgeworth-Kuiper Belt-like structure found around (cid:15) Eridani indicates that this star was born in a small cluster or association.
Forecast of surface chloride concentration of concrete utilizing ensemble decision tree boosted

This study proposes the application of Ensemble Decision Tree Boosted (EDT Boosted) model for forecasting the surface chloride concentration of marine concrete A database of 386 experimental results was collected from 17 different sources covering twelve variables was used to build and verify the predictive power of the EDT model. The input factors considered the changes in eleven variables, including the contents of cement, fly ash, blast furnace slag, silica fume, superplasticizer, water, fine aggregate, coarse aggregate, annual mean temperature, chloride concentration in seawater, and exposure time. The results indicate that EDT Boosted is a good predictor of as verified via good performance evaluation criteria, i.e., R2, RMSE, MAE, MAPE values were 0.84, 0.16, 0.17, and 17%, respectively. Partial dependence plot (PDP) was then developed to correlate the eleven input variables with the . PDP implied that the strongest factor affecting Cs was the amount of fine aggregate content, chloride concentration, exposure time, amount of cement, and water, which is useful for material engineers in the design of the grade.
Heightfields for Efficient Scene Reconstruction for AR

3D scene reconstruction from a sequence of posed RGB images is a cornerstone task for computer vision and augmented reality (AR). While depth-based fusion is the foundation of most real-time approaches for 3D reconstruction, recent learning based methods that operate directly on RGB images can achieve higher quality reconstructions, but at the cost of increased runtime and memory requirements, making them unsuitable for AR applications. We propose an efficient learning-based method that refines the 3D reconstruction obtained by a traditional fusion approach. By leveraging a top-down heightfield representation, our method remains real-time while approaching the quality of other learning-based methods. Despite being a simplification, our heightfield is perfectly appropriate for robotic path planning or augmented reality character placement. We outline several innovations that push the performance beyond existing top-down prediction baselines, and we present an evaluation framework on the challenging ScanNetV2 dataset, targeting AR tasks.
4525 - ANISOTROPIC PLANE THAT CONTAINS A CIRCULAR INCLUSION WITH IMPERFECT INTERFACE

The plane problem for an infinite plane that contains a circular inclusion with an imperfect interface is studied. The explicit solutions are derived based on Stroh formalism and the material constants of the matrix and the inclusion are both anisotropic and different from each other. The model for the matrix/inclusion interface is considered as a spring-type layer with vanishing thickness such that the interface effect can be described by continuous tractions but discontinuous displacements across the interface layer. By using analytic continuation in a dual coordinate system, two interfacial conditions lead to the simultaneous equations for two analytical vector functions. The two vector functions which are the main part of the expressions of displacement and stress function are expanded in forms of Laurent’s series. Thereafter, the series coefficients are determined by comparing the coefficients whenever the terms associated with the external load are at hand. The methodology for this research is illustrated by solving an example that the matrix is subjected to a remote uniform stresses field and the three interfacial parameters of homogeneous imperfect interface are identical. The simple and straightforward features of the application of our results reveal the applicability to those problems which is under more complicate external loading.
On the Operational Conditions’ Effect on the Performance of an Anion Exchange Membrane Water Electrolyzer: Electrochemical Impedance Spectroscopy Study

The performance of an anion exchange membrane water electrolyzer under various operational conditions (including voltage, KOH-supporting electrolyte concentration, and flow rate) is studied using conventional time-domain technics and electrochemical impedance spectroscopy (EIS). The water electrolyzer EIS footprint, depending on the variation in operational conditions, is studied and discussed, providing valuable data on the faradaic and non-faradaic processes in MEA, considering their contribution to the total polarization resistance. The distribution of the AEMWE cell voltage contributions is valuable to accessing the key directions in the system performance improvement.
Enhancing work relationships across cultures: The role of energy in cross-cultural work interactions

As culturally different individuals work together, energy may be employed as a resource towards building and sustaining a work relationship. However, current scholarship on energy at work and relational energy fail to take into account cultural considerations. To address this gap, we develop novel theory that distinguishes amongst various forms of energy to explicate how they are differentially interpreted in interactions based on cultural orientation. Integrating theories of interaction rituals and energy at work, our theorizing calls into question common assumptions in prior literature which privilege certain forms of energy expression (such as high intensity) over others (such as calm restraint). We further theorize that energy becomes a resource when culturally-different relationship partners go through a process of discovery as they interact, in which they learn about their partner’s energy contributions and communication preferences. Through adaptation, intercultural partners can then establish an equilibrium, or balanced state, of energy contributions to their interactions. The relational energy gained from reaching this equilibrium replenishes personal resources used in interdependent work with culturally diverse others. We explain how such resource enhancement plays a critical role in sustaining high quality interdependent work in multicultural organizations.
Critical storage capacity of the J = ± 1 neural network

For neural networks in which the coupling Jij are allowed to take on the values Jij = 1 or Jij = -1, the authors determine numerically the critical storage capacity for random unbiased patterns as a function of the stability. They use an exact enumeration scheme based on the Gray code and a continuous distribution for the patterns to control finite-size effects. Results are presented for N ≤ 25; they indicate an optimal storage capacity of αc ≈ 0.82 (N → ∞).
Controllable Patterning of Metallic Photonic Crystals for Waveguide–Plasmon Interaction

Waveguide–plasmon polaritons sustained in metallic photonic crystal slabs show fascinating properties, such as narrow bandwidth and ultrafast dynamics crucial for biosensing, light emitting, and ultrafast switching. However, the patterning of metallic photonic crystals using electron beam lithography is challenging in terms of high efficiency, large area coverage, and cost control. This paper describes a controllable patterning technique for the fabrication of an Ag grating structure on an indium–tin oxide (ITO) slab that enables strong photon–plasmon interaction to obtain waveguide–plasmon polaritons. The Ag grating consisting of self-assembled silver nanoparticles (NPs) exhibits polarization-independent properties for the excitation of the hybrid waveguide–plasmon mode. The Ag NP grating can also be annealed at high temperature to form a continuous nanoline grating that supports the hybrid waveguide–plasmon mode only under transverse magnetic (TM) polarization. We tuned the morphology and the periodicity of the Ag grating through the concentration of silver salt and the photoresist template, respectively, to manipulate the strong coupling between the plasmon and the waveguide modes of different orders.
Cost-minimization analysis to support the HTA of Radiofrequency Echographic Multi Spectrometry (REMS) in the diagnosis of osteoporosis

ABSTRACT Introduction: A timely diagnosis of osteoporosis is key to reducing its growing clinical and economic burden. Radiofrequency Echographic Multi Spectrometry (REMS), a new diagnostic technology using an ultrasound approach, has been recognized by scientific associations as a facilitator of patients’ care pathway. We aimed at evaluating the costs of REMS vs. the conventional ionizing technology (dual-energy X-ray absorptiometry, DXA) for the diagnosis of osteoporosis from the perspective of the Italian National Health Service (NHS) using a cost-minimization analysis (CMA). Methods: We carried out structured qualitative interviews and a structured expert elicitation exercise to estimate healthcare resource consumption with a purposeful sample of clinical experts. For the elicitation exercise, an Excel tool was developed and, for each parameter, experts were asked to provide the lowest, highest and most likely value. Estimates provided by experts were averaged with equal weights. Unit costs were retrieved using different public sources. Results: Considering the base-case scenario (most likely value), the cost of professionals amounts to €31.9 for REMS and €48.8 for DXA, the cost of instrumental examinations and laboratory tests to €45.1 for REMS and €68.2 for DXA. Overall, in terms of current costs, REMS is associated with a mean saving for the NHS of €40.0 (range: €27.6-71.5) for each patient. Conclusions: REMS is associated with lower direct healthcare costs with respect to DXA. These results may inform policy-makers on the value of the REMS technology in the earlier diagnosis for osteoporosis, and support their decision regarding the reimbursement and diffusion of the technology in the Italian NHS.
Effect of Plasma-Activated Water Bubbles on Fusarium graminearum, Deoxynivalenol, and Germination of Naturally Infected Barley during Steeping

Contamination of barley by deoxynivalenol (DON), a mycotoxin produced by Fusarium graminearum, causes considerable financial loss to the grain and malting industries. In this study, two atmospheric cold plasma (ACP) reactors were used to produce plasma-activated water (PAW) bubbles. The potential of PAW bubbles for the steeping of naturally infected barley (NIB) during the malting process was investigated. The PAW bubbles produced by treating water for 30 min using a bubble spark discharge (BSD) at low temperature resulted in the greatest concentration of oxygen-nitrogen reactive species (RONS). This treatment resulted in 57.3% DON degradation compared with 36.9% in the control sample; however, the same treatment reduced germination significantly (p < 0.05). Direct BSD ACP treatment for 20 min at low temperature and indirect treatment for 30 min increased the percentage of germinated rootlets of the seedlings compared with the control. Considering both the DON reduction and germination improvement of barley seeds, continuous jet ACP treatment for 30 min performed better than the other treatments used in this study. At higher temperature of PAW bubbles, the concentration of RONS was significantly (p < 0.05) reduced. Based on quantitative polymerase chain reaction (qPCR) analysis and fungal culture tests, the PAW bubble treatment did not significantly reduce infection of NIB. Nonetheless, this study provides useful information for the malting industry for PAW treatment optimization and its use in barley steeping for DON reduction and germination improvement.
Rodent Models of Dilated Cardiomyopathy and Heart Failure for Translational Investigations and Therapeutic Discovery

Even with modern therapy, patients with heart failure only have a 50% five-year survival rate. To improve the development of new therapeutic strategies, preclinical models of disease are needed to properly emulate the human condition. Determining the most appropriate model represents the first key step for reliable and translatable experimental research. Rodent models of heart failure provide a strategic compromise between human in vivo similarity and the ability to perform a larger number of experiments and explore many therapeutic candidates. We herein review the currently available rodent models of heart failure, summarizing their physiopathological basis, the timeline of the development of ventricular failure, and their specific clinical features. In order to facilitate the future planning of investigations in the field of heart failure, a detailed overview of the advantages and possible drawbacks of each model is provided.
Sustainable Biodegradable Biopolymer-Based Nanoparticles for Healthcare Applications

Biopolymeric nanoparticles are gaining importance as nanocarriers for various biomedical applications, enabling long-term and controlled release at the target site. Since they are promising delivery systems for various therapeutic agents and offer advantageous properties such as biodegradability, biocompatibility, non-toxicity, and stability compared to various toxic metal nanoparticles, we decided to provide an overview on this topic. Therefore, the review focuses on the use of biopolymeric nanoparticles of animal, plant, algal, fungal, and bacterial origin as a sustainable material for potential use as drug delivery systems. A particular focus is on the encapsulation of many different therapeutic agents categorized as bioactive compounds, drugs, antibiotics, and other antimicrobial agents, extracts, and essential oils into protein- and polysaccharide-based nanocarriers. These show promising benefits for human health, especially for successful antimicrobial and anticancer activity. The review article, divided into protein-based and polysaccharide-based biopolymeric nanoparticles and further according to the origin of the biopolymer, enables the reader to select the appropriate biopolymeric nanoparticles more easily for the incorporation of the desired component. The latest research results from the last five years in the field of the successful production of biopolymeric nanoparticles loaded with various therapeutic agents for healthcare applications are included in this review.
Current Therapeutic Strategies for Patients with Hypopharyngeal Carcinoma: Oncologic and Functional Outcomes

Hypopharyngeal cancer is usually diagnosed at an advanced stage and is associated with a high risk of recurrence and poor survival rates. Although they differ greatly in terms of prognosis, hypopharyngeal cancers are usually treated together with laryngeal cancers in clinical trials. Therefore, there are very few studies that focus specifically on patients with hypopharyngeal carcinoma. As a result, the therapeutic management of these patients is highly debated, and their clinical outcomes are poorly reported. The aim of this review is therefore to discuss the current therapeutic options in patients with hypopharyngeal carcinoma and their oncologic and functional outcomes. Patients with early-stage tumors can be treated either by conservative surgery (including transoral robot-assisted surgery) or by RT alone. However, most patients are diagnosed with locally advanced tumors that cannot be treated surgically without total laryngectomy. In this situation, the critical issue is to select the patients eligible for a larynx preservation therapeutic program. However, radical surgery with total laryngectomy still plays an important role in the management of patients with hypopharyngeal carcinoma, either as the primary treatment modality (T4 resectable primary tumor, contraindication to larynx preservation therapies) or, more commonly, as salvage treatment.
Decolorization based on the weighted combination of image entropy and canny edge retention ratio

Abstract. Image decolorization is used to realize the color-to-gray conversion, which is widely used in black-and-white printing, digital-ink display, photo stylization, etc. Image contrast fidelity preservation is the key issue during this conversion process. We present a parametric model combining image entropy and the Canny edge retention ratio (CERR). Maximizing the image entropy keeps the global image contrast content, while maximizing the CERR enhances the local image contrast, mainly along the edges. The weighting parameter λ can be robustly estimated. Experimental results on Cadik’s and the COLOR250 datasets demonstrate that the model can achieve significant performance improvement over state-of-the-art methods both qualitatively and quantitatively.
UniAP: Protecting Speech Privacy With Non-Targeted Universal Adversarial Perturbations

Ubiquitous microphones on smart devices considerably raise users’ concerns about speech privacy. Since the microphones are primarily controlled by hardware/software developers, profit-driven organizations can easily collect and analyze individuals’ daily conversations on a large scale with deep learning models, and users have no means to stop such privacy-violating behavior. In this article, we propose UniAP to empower users with the capability of protecting their speech privacy from the large-scale analysis without affecting their routine voice activities. Based on our observation of the recognition model, we utilize adversarial learning to generate quasi-imperceptible perturbations to disturb speech signals captured by nearby microphones, thus obfuscating the recognition results of recordings into meaningless contents. As validated in experiments, our perturbations can protect user privacy regardless of what users speak and when they speak. The jamming performance stability is further improved by training optimization. Additionally, the perturbations are robust against noise removal techniques. Extensive evaluations show that our perturbations achieve successful jamming rates of more than 87% in the digital domain and at least 90% and 70% for common and challenging settings, respectively, in the real-life chatting scenario. Moreover, our perturbations, solely trained on DeepSpeech, exhibit good transferability over other models based on similar architecture.