bluuebunny/crossref_metadata_2025 huggingface dataset:
Investigation of Programmable Friction with Ionic Liquid Mixtures at the Nano- and Macroscales
Authors: Gatti Felix Joachim , Cai Wanhao , Herzog Richard , Gharavian Amirmasoud , Kailer Andreas , Baltes Norman , Rabenecker Peter , Mörchel Philipp , Balzer Bizan N. , Amann Tobias , Rühe Jürgen
Published: September 2023

Non-mechanical stimuli are used to directly control or program the friction properties of tribosystems. For this purpose, an ionic liquid is used as a lubricant that affects and controls the friction in the presence of external triggers. Here, it is shown that the friction behavior of two surfaces in sliding contact can be controlled and permanently changed by applying an electrical potential to an ionic liquid mixture (ILM). This change in the friction properties was demonstrated both at the nanoscale using an atomic force microscopy (AFM)-based friction force microscopy (FFM) and at the macroscale using a specially designed tribo-setup cell. In tribology, the linking of these two scales of magnitude represents one of the greatest obstacles between basic research and the step towards application-oriented system development and is therefore of fundamental importance. In addition, other parameters affecting the tribological behavior of the system, such as roughness, lubricant film thickness, and wear behavior, were investigated as a function of the electrical potentials. The correlation between the structure of surface-bound ionic liquid layers and the friction behavior can be used to control friction, thus enabling a first step towards tribosystems that automatically adapt to changing conditions.
New Advances in π-Conjugated Materials
Authors: Miao Chuanqi , Yu Xiu , Zhang Haichang
Published: September 2023

Recently, extensive research efforts have been made to develop novel π-conjugated materials for use in various electronic applications, such as solar cells, organic semiconductors (OSCs), organic phototransistors (OPTs), organic light-emitting diodes (OLEDs), coatings, etc [...]
An Inconvenient Truth about Forecast Combinations
Authors: Pincheira-Brown Pablo , Bentancor Andrea , Hardy Nicolás
Published: September 2023

It is well-known that the weighted averages of two competing forecasts may reduce mean squared prediction errors (MSPE) and may also introduce certain inefficiencies. In this paper, we take an in-depth view of one particular type of inefficiency stemming from simple combination schemes: Mincer and Zarnowitz inefficiency or auto-inefficiency for short. Under mild assumptions, we show that linear convex forecast combinations are almost always auto-inefficient, and, therefore, greater reductions in MSPE are almost always possible. In particular, we show that the process of taking averages of forecasts may induce inefficiencies in the combination, even when individual forecasts are efficient. Furthermore, we show that the so-called “optimal weighted average” traditionally presented in the literature may indeed be inefficient as well. Finally, we illustrate our findings with simulations and an empirical application in the context of the combination of headline inflation forecasts for eight European economies. Overall, our results indicate that in situations in which a number of different forecasts are available, the combination of all of them should not be the last step taken in the search of forecast accuracy. Attempts to take advantage of potential inefficiencies stemming from the combination process should also be considered.
Study of a New Software Reliability Growth Model under Uncertain Operating Environments and Dependent Failures
Authors: Lee Dahye , Chang Inhong , Pham Hoang
Published: September 2023

The coronavirus disease (COVID-19) outbreak has prompted various industries to embark on digital transformation efforts, with software playing a critical role. Ensuring the reliability of software is of the utmost importance given its widespread use across multiple industries. For example, software has extensive applications in areas such as transportation, aviation, and military systems, where reliability problems can result in personal injuries and significant financial losses. Numerous studies have focused on software reliability. In particular, the software reliability growth model has served as a prominent tool for measuring software reliability. Previous studies have often assumed that the testing environment is representative of the operating environment and that software failures occur independently. However, the testing and operating environments can differ, and software failures can sometimes occur dependently. In this study, we propose a new model that assumes uncertain operating environments and dependent failures. In other words, the model proposed in this study takes into account a wider range of environments. The numerical examples in this study demonstrate that the goodness of fit of the new model is significantly better than that of the existing SRGM. Additionally, we show the utilization of the sequential probability ratio test (SPRT) based on the new model to assess the reliability of the dataset.
Silver Price Forecasting Using Extreme Gradient Boosting (XGBoost) Method
Authors: Gono Dylan Norbert , Napitupulu Herlina , Firdaniza
Published: September 2023

This article presents a study on forecasting silver prices using the extreme gradient boosting (XGBoost) machine learning method with hyperparameter tuning. Silver, a valuable precious metal used in various industries and medicine, experiences significant price fluctuations. XGBoost, known for its computational efficiency and parallel processing capabilities, proves suitable for predicting silver prices. The research focuses on identifying optimal hyperparameter combinations to improve model performance. The study forecasts silver prices for the next six days, evaluating models based on mean absolute percentage error (MAPE) and root mean square error (RMSE). Model A (the best model based on MAPE value) suggests silver prices decline on the first and second days, rise on the third, decline again on the fourth, and stabilize with an increase on the fifth and sixth days. Model A achieves a MAPE of 5.98% and an RMSE of 1.6998, utilizing specific hyperparameters. Conversely, model B (the best model based on RMSE value) indicates a price decrease until the third day, followed by an upward trend until the sixth day. Model B achieves a MAPE of 6.06% and an RMSE of 1.6967, employing distinct hyperparameters. The study also compared the proposed models with several other ensemble models (CatBoost and random forest). The model comparison was carried out by incorporating 2 additional metrics (MAE and SI), and it was found that the proposed models exhibited the best performance. These findings provide valuable insights for forecasting silver prices using XGBoost.
Deep Models for Low-Resourced Speech Recognition: Livvi-Karelian Case
Authors: Kipyatkova Irina , Kagirov Ildar
Published: September 2023

Recently, there has been a growth in the number of studies addressing the automatic processing of low-resource languages. The lack of speech and text data significantly hinders the development of speech technologies for such languages. This paper introduces an automatic speech recognition system for Livvi-Karelian. Acoustic models based on artificial neural networks with time delays and hidden Markov models were trained using a limited speech dataset of 3.5 h. To augment the data, pitch and speech rate perturbation, SpecAugment, and their combinations were employed. Language models based on 3-grams and neural networks were trained using written texts and transcripts. The achieved word error rate metric of 22.80% is comparable to other low-resource languages. To the best of our knowledge, this is the first speech recognition system for Livvi-Karelian. The results obtained can be of a certain significance for development of automatic speech recognition systems not only for Livvi-Karelian, but also for other low-resource languages, including the fields of speech recognition and machine translation systems. Future work includes experiments with Karelian data using techniques such as transfer learning and DNN language models.
Solving the Problem of Reducing the Audiences’ Favor toward an Educational Institution by Using a Combination of Hard and Soft Operations Research Approaches
Authors: Xu Wenjing , Edalatpanah Seyyed Ahmad , Sorourkhah Ali
Published: September 2023

Because of hyper-complexity, a difficulty to define, multiple stakeholders with conflicting perspectives, and a lack of clear-cut solutions, wicked problems necessitate innovative and adaptive strategies. Operations research (OR) has been a valuable tool for managers to make informed decisions for years. However, as we face increasingly complex and messy problems, it has become apparent that relying solely on either hard or soft OR approaches is no longer sufficient. We need to explore more innovative methodologies to address these wicked problems effectively. This study has bridged the research gap by proposing a structured process encompassing a subdivision-based problem structuring method for defining the wicked problem, a multi-attribute decision-making (MADM) for prioritizing subproblems, and a hard OR technique, data envelopment analysis (DEA) for tackling one of the most critical subdivisions. The proposed methodology, the subdivision-based problem structuring method (SPSM), implemented in a case study, focuses on a higher education institution experiencing a decline in student admissions and involves five steps. First, a diverse group of stakeholders is formed to ensure the comprehensive consideration of perspectives. Second, the wicked problem is defined, considering long-term consequences, multiple stakeholders, and qualitative stakeholder opinions. Third, a hierarchical structure is created to break down the wicked problem into manageable subproblems. Fourth, a multi-criteria decision-making (MCDM) method prioritizes subproblems. Finally, the subproblems are addressed one by one using a combination of soft and hard OR tools. The findings highlight the benefits of integrating hard and soft OR approaches. The study concludes with reflections on the implications of using a combined OR approach to tackle wicked problems in higher education and beyond.
Faculty Performance Evaluation through Multi-Criteria Decision Analysis Using Interval-Valued Fermatean Neutrosophic Sets
Authors: Broumi Said , Sundareswaran Raman , Shanmugapriya Marayanagaraj , Singh Prem Kumar , Voskoglou Michael , Talea Mohamed
Published: September 2023

The Neutrosophic Set (Nset) represents the uncertainty in data with fuzzy attributes beyond true and false values independently. The problem arises when the summation of true (Tr), false (Fa), and indeterminacy In values crosses the membership value of one, that is, Tr+In+Fa<1. It becomes more crucial during decision-making processes like medical diagnoses or any data sets where Tr+In+Fa<1. To achieve this goal, the FNset is recently introduced. This study employs the Interval-Valued Fermatean Neutrosophic Set (IVFNset) as its chosen framework to address instances of partial ignorance within the domains of truth, falsehood, or uncertainty. This selection stands out due to its unique approach to managing such complexities within multi-decision processes when compared to alternative methodologies. Furthermore, the proposed method reduces the propensity for information loss often encountered in other techniques. IVFNS excels at preserving intricate relationships between variables even when dealing with incomplete or vague information. In the present work, we introduce the IVFNset, which deals with partial ignorance in true, false, or uncertain regions independently for multi-decision processes. The IVFNset contains the interval-valued Trmembership value, Inmembership value, and Famembership for knowledge representation. The algebraic properties and set theory between the interval-valued FNset have also been presented with an illustrative example.
Local Solvability and Stability of an Inverse Spectral Problem for Higher-Order Differential Operators
Authors: Bondarenko Natalia P.
Published: September 2023

In this paper, we, for the first time, prove the local solvability and stability of an inverse spectral problem for higher-order (n>3) differential operators with distribution coefficients. The inverse problem consists of the recovery of differential equation coefficients from (n−1) spectra and the corresponding weight numbers. The proof method is constructive. It is based on the reduction of the nonlinear inverse problem to a linear equation in the Banach space of bounded infinite sequences. We prove that, under a small perturbation of the spectral data, the main equation remains uniquely solvable. Furthermore, we estimate the differences of the coefficients in the corresponding functional spaces.
Innovative Imaging Techniques: A Conceptual Exploration of Multi-Modal Raman Light Sheet Microscopy
Authors: Manser Steffen , Keck Shaun , Vitacolonna Mario , Wuehler Felix , Rudolf Ruediger , Raedle Matthias
Published: September 2023

Advances in imaging of microscopic structures are supported and complemented by adaptive visualization tools. These tools enable researchers to precisely capture and analyze complex three-dimensional structures of different kinds such as crystals, microchannels and electronic or biological material. In this contribution, we focus on 3D cell cultures. The new possibilities can play a particularly important role in biomedical research, especially here in the study of 3D cell cultures such as spheroids in the field of histology. By applying advanced imaging techniques, detailed information about the spatial arrangement and interactions between cells can be obtained. These insights help to gain a better understanding of cellular organization and function and have potential implications for the development of new therapies and drugs. In this context, this study presents a multi-modal light sheet microscope designed for the detection of elastic and inelastic light scattering, particularly Rayleigh scattering as well as the Stokes Raman effect and fluorescence for imaging purposes. By combining multiple modalities and stitching their individual results, three-dimensional objects are created combining complementary information for greater insight into spatial and molecular information. The individual components of the microscope are specifically selected to this end. Both Rayleigh and Stokes Raman scattering are inherent molecule properties and accordingly facilitate marker-free imaging. Consequently, altering influences on the sample by external factors are minimized. Furthermore, this article will give an outlook on possible future applications of the prototype microscope.
Genetic Variability of the Internal Transcribed Spacer and Pyruvate:Ferredoxin Oxidoreductase Partial Gene of Trichomonas vaginalis from Female Patients
Authors: Martinez-Hernandez Fernando , Sanchez-Aguillon Fabiola , Martinez-Ocaña Joel , Gonzalez-Arenas Nelly Raquel , Romero-Valdovinos Mirza , Lopez-Escamilla Eduardo , Maravilla Pablo , Villalobos Guiehdani
Published: September 2023

In the present study, we evaluated the genetic variability of the internal transcribed spacer (ITS) region and the pyruvate:ferredoxin oxidoreductase (pfor) A gene of Trichomonas vaginalis from female patients and its possible implications in the host–parasite relationship. Phylogenetic and genetics of populations analyses were performed by analyzing sequences of the ITS region and partial pfor A gene of clinical samples with T. vaginalis, as previously documented. Alignments of protein sequences and prediction of three-dimensional structure were also performed. Although no correlation between the main clinical characteristics of the samples and the results of phylogeny was found, a median-joining analysis of ITS haplotypes showed two main clusters. Also, pfor A, due to its phylogenetic divergence, could be used as a marker to confirm the genus and species of trichomonads. Alignment of protein sequences and prediction of three-dimensional structure showed that PFOR A had a highly conserved structure with two synonymous mutations in the PFOR domain, substituting a V for a G or a S for a P. Our results suggest that the role of genetic variability of PFOR and ITS may not be significant in the symptomatology of this pathogen; however, their utility as genus and species markers in trichomonads is promising.
Piezoelectricity of Bi2Se3 Nanosheet
Authors: Jia Tingting , Yang Liu , Zhang Juncheng , Kimura Hideo , Zhao Hongyang , Guo Quansheng , Cheng Zhenxiang
Published: September 2023

Bi2Se3, one of the most extensively studied topological insulators, has received significant attention, and abundant research has been dedicated to exploring its surface electronic properties. However, little attention has been given to its piezoelectric properties. Herein, we investigate the piezoelectric response in a five-layer Bi2Se3 nanosheet using scanning probe microscopy (SPM) techniques. The piezoelectricity of Bi2Se3 is characterized using both conventional piezoresponse force microscopy (PFM) and a sequential excitation scanning probe microscopy (SE-SPM) technique. To confirm the linear piezoelectricity of Bi2Se3 two-dimensional materials, measurements of point-wise linear and quadratic electromechanical responses are carried out. Furthermore, the presence of polarization and relaxation is confirmed through hysteresis loops. As expected, the Bi2Se3 nanosheet exhibits an electromechanical solid response. Due to the inevitable loss of translational symmetry at the crystal edge, the lattice of the odd-layer Bi2Se3 nanosheet is noncentrosymmetric, indicating its potential for linear piezoelectricity. This research holds promise for nanoelectromechanical systems (NEMS) applications and future nanogenerators.
Recent Advances in the Treatment of Pulmonary Arterial Hypertension Associated with Connective Tissue Diseases
Authors: Smukowska-Gorynia Anna , Gościniak Weronika , Woźniak Patrycja , Iwańczyk Sylwia , Jaxa-Kwiatkowska Karolina , Sławek-Szmyt Sylwia , Janus Magdalena , Paluszkiewicz Jerzy , Mularek-Kubzdela Tatiana
Published: September 2023

Pulmonary hypertension (PH) is a severe vascular complication of connective tissue diseases (CTD). Patients with CTD may develop PH belonging to diverse groups: (1) pulmonary arterial hypertension (PAH), (2) PH due to left heart disease, (3) secondary PH due to lung disease and/or hypoxia and (4) chronic thromboembolic pulmonary hypertension (CTEPH). PAH most often develops in systemic scleroderma (SSc), mostly in its limited variant. PAH-CTD is a progressive disease characterized by poor prognosis. Therefore, early diagnosis should be established. A specific treatment for PAH-CTD is currently available and recommended: prostacyclin derivative (treprostinil, epoprostenol, iloprost, selexipag), nitric oxide and natriuretic pathway: stimulators of soluble guanylate cyclase (sGC: riociguat) and phosphodiesterase-five inhibitors (PDE5i: sildenafil, tadalafil), endothelin receptor antagonists (ERA: bosentan, macitentan, ambrisentan). Moreover, novel drugs, e.g., sotatercept, have been intensively investigated in clinical trials. We aim to review the literature on recent advances in the treatment strategy and prognosis of patients with PAH-CTD. In this manuscript, we discuss the mechanism of action of PAH-specific drugs and new agents and the latest research conducted on PAH-CTD patients.
Non-Anticoagulant Activities of Low Molecular Weight Heparins—A Review
Authors: Feng Ke , Wang Kaixuan , Zhou Yu , Xue Haoyu , Wang Fang , Jin Hongzhen , Zhao Wei
Published: September 2023

Low molecular weight heparins (LMWHs) are derived from heparin through chemical or enzymatic cleavage with an average molecular weight (Mw) of 2000–8000 Da. They exhibit more selective activities and advantages over heparin, causing fewer side effects, such as bleeding and heparin-induced thrombocytopenia. Due to different preparation methods, LMWHs have diverse structures and extensive biological activities. In this review, we describe the basic preparation methods in this field and compare the main principles and advantages of these specific methods in detail. Importantly, we focus on the non-anticoagulant pharmacological effects of LMWHs and their conjugates, such as preventing glycocalyx shedding, anti-inflammatory, antiviral infection, anti-fibrosis, inhibiting angiogenesis, inhibiting cell adhesion and improving endothelial function. LMWHs are effective in various diseases at the animal level, including cancer, some viral diseases, fibrotic diseases, and obstetric diseases. Finally, we briefly summarize their usage and potential applications in the clinic to promote the development and utilization of LMWHs.
Pneumonic Injury and Repair: A Synopsis
Authors: Barabutis Nektarios
Published: September 2023

It has been my great pleasure to have joined forces with Pharmaceutical’s editorial team in order to organize and publish a Special Issue on “Lung Injury and Repair” [...]
Research Status of and Prospects for 3D Printing for Continuous Fiber-Reinforced Thermoplastic Composites
Authors: Yang Yuan , Yang Bo , Chang Zhengping , Duan Jihao , Chen Weihua
Published: September 2023

Continuous fiber-reinforced thermoplastic composites (CFRTPCs) have advantages such as high specific strength, high specific modulus, corrosion resistance, and recyclability and are widely used in the fields of aerospace, rail transit, new energy, and so on. However, traditional methods for preparing CFRTPCs, such as placement and molding, rely more on forming molds, resulting in high manufacturing costs and a slow response speed, which limits the promotion and application of the new generation of CFRTPCs with complex configurations and designable performance. Three-dimensional printing can efficiently create products with multiple materials, complex structures, and integrated functions, introducing new ways and opportunities for the manufacturing of CFRTPCs. However, poor mechanical properties are the bottleneck problem in achieving 3D printing of CFRTPCs. This paper summarizes the research status of the fused deposition modeling (FDM) 3D printing process and the corresponding mechanical properties of CFRTPCs. The focus is on analyzing the influences of the FDM process parameters, such as the material type, printing temperature, speed parameters, layer thickness, scanning space, stacking direction, and fiber volume content, on the mechanical properties of CFRTPCs. Finally, the main problems and future prospects of current CFRTPCs-FDM are analyzed and forecasted, providing new references and ideas for 3D printing of high-performance CFRTPCs.
Preparation and Properties of a Novel High-Toughness Solid Propellant Adhesive System Based on Glycidyl Azide Polymer–Energetic Thermoplastic Elastomer/Nitrocellulose/Butyl Nitrate Ethyl Nitramine
Authors: Zhang Jing , Wang Zhen , Sun Shixiong , Luo Yunjun
Published: September 2023

Glycidyl azide polymer (GAP)–energetic thermoplastic elastomer (GAP-ETPE) propellants have high development prospects as green solid propellants, but the preparation of GAP-ETPEs with excellent performance is still a challenge. Improving the performance of the adhesive system in a propellant by introducing a plasticizer is an effective approach to increasing the energy and toughness of the propellant. Herein, a novel high-strength solid propellant adhesive system was proposed with GAP-ETPEs as the adhesive skeleton, butyl nitrate ethyl nitramine (Bu-NENA) as the energetic plasticizer, and nitrocellulose (NC) as the reinforcing agent. The effects of the structural factors on its properties were studied. The results showed that the binder system would give the propellant better mechanical and safety properties. The results can provide a reference for the structure design, forming process, and parameter selection of high-performance GAP-based green solid propellants.
Synthesis and Evaluation of Antifungal and Antibacterial Abilities of Carbon Nanotubes Grafted to Poly(2-hydroxyethyl methacrylate) Nanocomposites
Authors: Sandoval-García Karina , Alvarado-Mendoza Abraham G. , Orozco-Guareño Eulogio , Olea-Rodríguez María A. , Cajero-Zul Leonardo R. , Nuño-Donlucas Sergio M.
Published: September 2023

Developing nanomaterials with the capacity to restrict the growth of bacteria and fungus is of current interest. In this study, nanocomposites of poly(2-hydroxyethyl methacrylate) (PHEMA) and carbon nanotubes (CNTs) functionalized with primary amine, hydroxyl, and carboxyl groups were prepared and characterized. An analysis by Fourier-transform infrared (FT-IR) spectroscopy showed that PHEMA chains were grafted to the functionalized CNTs. X-ray photoelectron spectroscopy suggested that the grafting reaction was viable. The morphology of the prepared nanocomposites studied by field-emission scanning electron microscopy (FE-SEM) and transmission electron microscopy (TEM) showed significant changes with respect to the observed for pure PHEMA. The thermal behavior of the nanocomposites studied by differential scanning calorimetry (DSC) revealed that the functionalized CNTs strongly affect the mobility of the PHEMA chains. Tests carried out by thermogravimetric analysis (TGA) were used to calculate the degree of grafting of the PHEMA chains. The ability of the prepared nanocomposites to inhibit the growth of the fungus Candida albicans and the bacteria Staphylococcus aureus, Pseudomonas aeruginosa, and Escherichia coli was evaluated. A reduced antifungal and antibacterial capacity of the prepared nanocomposites was determined.
Mesoporous Titanium Dioxide Nanoparticles—Poly(N-isopropylacrylamide) Hydrogel Prepared by Electron Beam Irradiation Inhibits the Proliferation and Migration of Oral Squamous Cell Carcinoma Cells
Authors: Chen Huangqin , Hu Yuzhu , Wu Chizhou , Liu Kun , Feng Rui , Yang Mingzhe , Zhao Mengyao , Huang Bin , Li Yuesheng
Published: September 2023

An urgently needed approach for the treatment of oral squamous cell carcinoma (OSCC) is the development of novel drug delivery systems that offer targeted specificity and minimal toxic side effects. In this study, we developed an injectable and temperature-sensitive composite hydrogel by combining mesoporous titanium dioxide nanoparticles (MTNs) with Poly(N-isopropylacrylamide) (PNIPAAM) hydrogel to serve as carriers for the model drug Astragalus polysaccharide (APS) using electron beam irradiation. The characteristics of MTNs, including specific surface area and pore size distribution, were analyzed, and the characteristics of MTNs-APS@Hyaluronic acid (HA), such as microscopic morphology, molecular structure, crystal structure, and loading efficiency, were examined. Additionally, the swelling ratio, gel fraction, and microscopic morphology of the composite hydrogel were observed. The in vitro cumulative release curve was plotted to investigate the sustained release of APS in the composite hydrogels. The effects on the proliferation, migration, and mitochondrial membrane potential of CAL-27 cells were evaluated using MTT assay, scratch test, and JC-1 staining. The results indicated successful preparation of MTNs with a specific surface area of 147.059 m2/g and an average pore diameter of 3.256 nm. The composite hydrogel displayed temperature-sensitive and porous characteristics, allowing for slow release of APS. Furthermore, it effectively suppressed CAL-27 cells proliferation, migration, and induced changes in mitochondrial membrane potential. The addition of autophagy inhibitors chloroquine (CQ) and 3-methyladenine (3-MA) attenuated the migration inhibition (p < 0.05).
Influence of Protic Ionic Liquid-Based Flame Retardant on the Flammability and Water Sorption of Alkalized Hemp Fiber-Reinforced PLA Composites
Authors: Alao Percy Festus , Press Raimond , Ruponen Jussi , Mikli Valdek , Kers Jaan
Published: September 2023

This article investigates the effects of combining a novel protic ionic liquid-based fire retardant (FR) with alkalized hemp fiber. A pivotal importance of this study refers to the hydrophilic properties and limits regarding poor thermal resistance of green composites where standard guidelines for fire risks are crucial. Although it is well-studied that alkalization is essential for green composite’s moisture and mechanical durability, research on the flammability of such a combined treatment for natural fiber-reinforced biopolymer composites is lacking. The alkaline treatment used in the current study follows a process already studied as optimal, particularly for the selected hemp fiber. The fire performance was examined using a bench scale approach based on self and piloted ignition from cone calorimeter tests. The result from the Fourier-transform infrared analysis of the hemp fiber confirms phosphorylation following the fire-retardant treatment, which was visible from the morphological examination with scanning electron microscope. The presence of FR in the composites led to impactful moisture sorption. However, the FR composites demonstrated an enhanced response to fire, indicating potential use as a Class B standard for building construction, and hazard level 3 (HL3) classification as an interior material in vehicles, provided the problem of high emission of smoke is mitigated.
Study on the Migration and Transformation of Nitrogen in Mine Water under the Action of Water–Coal Interactions
Authors: Jiang Binbin , Zhao Ze , Cao Zhiguo , Liu Deqian , Tang Jiawei , Zhang Haiqin , Liu Yuan , Liang Dingcheng
Published: September 2023

The coal pillar dam of underground reservoirs and residual coal in goaves have a direct impact on the quality of mine water. In this paper, the coal pillar dam of an underground reservoir and residual coal in the goaf and mine water in the Daliuta coal mine are used as research objects. The adsorption mechanism of residual coal with respect to NO3− in mine water was analyzed by carrying out adsorption experiments. The composition and variation of organic matter in mine water at different times were simulated using three-dimensional fluorescence spectrum analysis. The influence of residual coal and microorganisms in underground reservoirs on the change in NO3− contents in mine water was explored. Moreover, the mechanism of NO3− changes in the water body was clarified. The results showed that the concentration of NO3− in the water first decreased and then increased, showing a downward trend as a whole. The adsorption of NO3− by residual coal led to a decrease in its concentration, which conformed to a pseudo-second-order kinetic model and Freundlich isothermal adsorption model, indicating that the adsorption process of NO3− by residual coal is mainly carried out via chemical adsorption and multi-layer adsorption. The increase in NO3− concentration was caused by the hydrolysis of tryptophan and other protein-like substances in the water into nitrate under the action of microorganisms.
Photo-Programmable Processes in Bithiophene–Azobenzene Monolayers on Gold Probed via Simulations
Authors: Savchenko Vladyslav , Hadjab Moufdi , Pavlov Alexander S. , Guskova Olga
Published: September 2023

In this study, we investigate the structural changes, electronic properties, and charge redistribution within azo-bithiophene (Azo-BT)-chemisorbed monolayers under different light stimuli using the density functional theory and molecular dynamics simulations. We consider two types of switches, Azo-BT and BT-Azo, with different arrangements of the Azo and BT blocks counting from the anchor thiol group. The chemisorbed monolayers of pure cis- and trans-isomers with a surface concentration of approximately 2.7 molecules per nm2 are modeled on a gold surface using the classical all-atom molecular dynamics. Our results reveal a significant shrinkage of the BT-Azo layer under UV illumination, whereas the thicknesses of the Azo-BT layer remain comparable for both isomers. This difference in behavior is attributed to the ordering of the trans-molecules in the layers, which is more pronounced for Azo-BT, leading to a narrow distribution of the inclination angle to the gold surface. Conversely, both layers consisting of cis-switches exhibit disorder, resulting in similar brush heights. To study charge transfer within the immobilized layers, we analyze each snapshot of the layer and calculate the mean charge transfer integrals using Nelsen’s algorithm for a number of interacting neighboring molecules. Combining these integrals with reorganization energies defined for the isolated molecules, we evaluate the charge transfer rates and mobilities for electron and hole hopping within the layers at room temperature based on Marcus’ theory. This research offers new perspectives for the innovative design of electrode surface modifications and provides insights into controlling charge transfer within immobilized layers using light triggers. Additionally, we identify molecular properties that are enhanced via specific molecular design, which contributes to the development of more efficient molecular switches for various electronic applications.
Numerical Simulation Study on Vibration Reduction Effect of Flexible Cutting-Tooth Unit
Authors: Ren Haitao , Xu Jingwei , Jia Xin , Zhou Sheng , Zhou Chunxiao , Yang Yingxin , Zhan Qi
Published: September 2023

Under the conditions of drilling in gravel-bearing and heterogeneous stratas, the movement and force of the PDC bit during drilling are highly unstable. Irregular impact loads often cause fatigue failures such as tooth fracture, tooth breakage and delamination of the composite sheet. Dynamic impact load is the main cause of fatigue failure of cutting-tooth, which seriously affects the rock-breaking performance of PDC bits. This paper proposes a flexible cutting tooth unit consisting of a central tooth, an elastic element, and a base. The technical concept of flexible-cutting rock breaking is to reduce the impact load amplitude suffered during the cutting process to a certain threshold range by setting elastic elements or reducing the support stiffness of the cutting tooth, so as to inhibit the expansion of micro defects caused by the impact dynamic load of cutting teeth and prolong the service life of drill bits. The finite-element models of flexible cutting teeth for rock cutting were established. The influence of cutting depth, front rake angle and stiffness of elastic elements on the cushioning and vibration-absorption effect of flexible cutting was analysed. The results show that flexible cutting can reduce the peak and average value of von Mises stress at the cutting edge. Under different cutting-depth conditions, the decline rates were 21.45–49.02% and 9.42–17.8%, respectively. Then, under different front-rake-angle conditions, the decline rates were 20.51–24.02% and 9.41–17.8%, respectively. There is a suitable stiffness of the elastic element, which makes the peak and average value of von Mises stress at the cutting edge of the flexible cutting-tooth unit perform better and the effect of improving the uneven stress distribution at the cutting edge better. Flexible cutting technology can effectively improve the adaptability of the PDC bit in heterogeneous formations and reduce the occurrence of abnormal failure of cutting teeth. The research results of this paper can provide theoretical support for the drilling speed of PDC bits in hard formations.
Optimizing the Control of the Hydraulic Driving System for the Power Shift Gearbox of a Cotton Picker Based on Dual Working Conditions
Authors: Lin Yuangang , Feng Jingan , Zhao Pengda , Ni Xiangdong , Chen Huajun , Ye Haoyun , Zhao Yongqiang , Pan Wenlong , Song Bao
Published: September 2023

In response to the issues of slow dynamic response, uneven shifting, and strong jolting during the starting and shifting operations of the cotton picker, we established a model for automatic power shifting control. We proposed optimization strategies using the Statechart logic control method and BP neural network control method. Different control effects were analyzed concerning pressure, flow rate, motor speed, vehicle speed, impact degree, and slip-grinding work. The results showed that the Statechart logic control method increased the response time of the flow rate by 46.67% during the starting process, with a good linear characteristic during the variation. It reduced the impact during starting and shifting by 38.57% and 67%, and the sliding friction power during starting and shifting by 51.95% and 33.33% respectively. The BP neural network control method reduced the pressure overshoot during starting and shifting by 25% and 30.77%, respectively, demonstrating better robustness. The pump, motor speed, and vehicle speed showed smooth growth after starting and shifting, with faster vehicle speed response during the starting process. Additionally, the vehicle speed overshoot during shifting significantly decreased, ensuring overall performance that meets the operational requirements of the cotton picker. This finding holds practical significance for the advancement of control strategy optimization and the development of the control system for the powershift gearbox in cotton pickers.
Performativity of the Memory of Religious Places through Sound and Image
Authors: Dinis Frederico
Published: September 2023

In this essay, we explore and deepen the confluence between sound and image, linking and relating concepts, purposes and coherence of artistic practices mediating and reconfiguring the memory of religious places. We observed that the performativity of memory, as an autobiographical concept, can be enhanced through live audiovisual performances in religious places. We have established that the performativity of memory in religious places can promote a spatial ‘self’, creating dynamic, immersive and physical experiences in the religious places. And we argue that the construction of this spatial ‘self’ involves processes of social and artistic reconfiguration that contribute to transforming not only the social dynamics within the community but also the artistic representations of memory. These main findings were reached following a process of research through artistic practice, thus a systematization of the processes involved in approaching three religious places. It also assumes the (de)construction of the sense of place throughout a personal reading on the mediation through nonverbal means. In this research, we also observed that the aesthetic and performative configurations can have an impact on the most individual manifestations of religion, religiosity and religious belief, influencing the interpretation and creation of meaning, evoking emotional and spiritual responses.
Children as a Reflection of Transcendence in the Filmography of Andrei Tarkovsky
Authors: Sever Globan Irena , Pavelić Marin
Published: September 2023

Andrej Tarkovsky is a Russian film author who has indebted the entire world’s cinematography with his cinematic style. His (auto)biography and filmography give us a hint that he was a deeply religious man who believed that art should serve to deepen man’s spirituality. By watching and analyzing the author’s films, we came to the hypothesis that Tarkovsky uses the characters of children to express something supernatural, and therefore, we wanted to explore which narratives and stylistic devices the director uses to give his interpretation of the spiritual and transcendent. Thus, we analyzed nine characters of children that appear in the director’s six full-length feature films: Ivan Bondarev (Ivan’s Childhood), Boriska (Andrei Rublev), Aleksej, Ignat and Asafjev (Mirror), Marta (Stalker), Domenico’s son and Angela (Nostalghia), and Gossen (The Sacrifice). The methods we have used are qualitative content analysis, description, comparison, and synthesis. The characteristics we have noticed in the characters of the children, which could point to the transcendent, are a deep and penetrating gaze, the supernatural powers children use, the mysterious environments they inhabit, the deep influence they have on other characters, asking religious questions, hermit-like loneliness, modest clothes, and allusions to a Christ-like figure.
LMSD-Net: A Lightweight and High-Performance Ship Detection Network for Optical Remote Sensing Images
Authors: Tian Yang , Wang Xuan , Zhu Shengjie , Xu Fang , Liu Jinghong
Published: September 2023

Ship detection technology has achieved significant progress recently. However, for practical applications, lightweight ship detection still remains a very challenging problem since small ships have small relative scales in wide images and are easily missed in the background. To promote the research and application of small-ship detection, we propose a new remote sensing image dataset (VRS-SD v2) and provide a fog simulation method that reflects the actual background in remote sensing ship detection. The experiment results show that the proposed fog simulation is beneficial in improving the robustness of the model for extreme weather. Further, we propose a lightweight detector (LMSD-Net) for ship detection. Ablation experiments indicate the improved ELA-C3 module can efficiently extract features and improve the detection accuracy, and the proposed WGC-PANet can reduce the model parameters and computation complexity to ensure a lightweight nature. In addition, we add a Contextual Transformer (CoT) block to improve the localization accuracy and propose an improved localization loss specialized for tiny-ship prediction. Finally, the overall performance experiments demonstrate that LMSD-Net is competitive in lightweight ship detection among the SOTA models. The overall performance achieves 81.3% in AP@50 and could meet the lightweight and real-time detection requirements.
Supraglacial Lake Evolution over Northeast Greenland Using Deep Learning Methods
Authors: Lutz Katrina , Bahrami Zahra , Braun Matthias
Published: September 2023

Supraglacial lakes in Greenland are highly dynamic hydrological features in which glacial meltwater cumulates, allowing for the loss and transport of freshwater from a glacial surface to the ocean or a nearby waterbody. Standard supraglacial lake monitoring techniques, specifically image segmentation, rely heavily on a series of region-dependent thresholds, limiting the adaptability of the algorithm to different illumination and surface variations, while being susceptible to the inclusion of false positives such as shadows. In this study, a supraglacial lake segmentation algorithm is developed for Sentinel-2 images based on a deep learning architecture (U-Net) to evaluate the suitability of artificial intelligence techniques in this domain. Additionally, a deep learning-based cloud segmentation tool developed specifically for polar regions is implemented in the processing chain to remove cloudy imagery from the analysis. Using this technique, a time series of supraglacial lake development is created for the 2016 to 2022 melt seasons over Nioghalvfjerdsbræ (79°N Glacier) and Zachariæ Isstrøm in Northeast Greenland, an area that covers 26,302 km2 and represents roughly 10% of the Northeast Greenland Ice Stream. The total lake area was found to have a strong interannual variability, with the largest peak lake area of 380 km2 in 2019 and the smallest peak lake area of 67 km2 in 2018. These results were then compared against an algorithm based on a thresholding technique to evaluate the agreement of the methodologies. The deep learning-based time series shows a similar trend to that produced by a previously published thresholding technique, while being smoother and more encompassing of meltwater in higher-melt periods. Additionally, while not completely eliminating them, the deep learning model significantly reduces the inclusion of shadows as false positives. Overall, the use of deep learning on multispectral images for the purpose of supraglacial lake segmentation proves to be advantageous.
Novel Features of Canopy Height Distribution for Aboveground Biomass Estimation Using Machine Learning: A Case Study in Natural Secondary Forests
Authors: Ma Ye , Zhang Lianjun , Im Jungho , Zhao Yinghui , Zhen Zhen
Published: September 2023

Identifying important factors (e.g., features and prediction models) for forest aboveground biomass (AGB) estimation can provide a vital reference for accurate AGB estimation. This study proposed a novel feature of the canopy height distribution (CHD), a function of canopy height, that is useful for describing canopy structure for AGB estimation of natural secondary forests (NSFs) by fitting a bimodal Gaussian function. Three machine learning models (Support Vector Regression (SVR), Random Forest (RF), and eXtreme Gradient Boosting (Xgboost)) and three deep learning models (One-dimensional Convolutional Neural Network (1D-CNN4), 1D Visual Geometry Group Network (1D-VGG16), and 1D Residual Network (1D-Resnet34)) were applied. A completely randomized design was utilized to investigate the effects of four feature sets (original CHD features, original LiDAR features, the proposed CHD features fitted by the bimodal Gaussian function, and the LiDAR features selected by the recursive feature elimination algorithm) and models on estimating the AGB of NSFs. Results revealed that the models were the most important factor for AGB estimation, followed by the features. The fitted CHD features significantly outperformed the other three feature sets in most cases. When employing the fitted CHD features, the 1D-Renset34 model demonstrates optimal performance (R2 = 0.80, RMSE = 9.58 Mg/ha, rRMSE = 0.09), surpassing not only other deep learning models (e.g.,1D-VGG16: R2 = 0.65, RMSE = 18.55 Mg/ha, rRMSE = 0.17) but also the best machine learning model (RF: R2 = 0.50, RMSE = 19.42 Mg/ha, rRMSE = 0.16). This study highlights the significant role of the new CHD features fitting a bimodal Gaussian function and the effects between the models and the CHD features, which provide the sound foundations for effective estimation of AGB in NSFs.
High Precision Motion Compensation THz-ISAR Imaging Algorithm Based on KT and ME-MN
Authors: Liu Wei , Wang Hongqiang , Yang Qi , Deng Bin , Fan Lei , Yi Jun
Published: September 2023

In recent years, terahertz (THz) radar has been widely researched for its high-resolution imaging. However, the traditional inverse synthetic aperture radar (ISAR) imaging algorithms in the microwave band perform unsatisfactorily in the THz band. Firstly, due to THz radar’s large bandwidth and short wavelength, the rotation of the target will result in serious space-varying(SV) range migration and space-varying phase error. Furthermore, it is challenging to accurately estimate the rotational velocity and compensate for phase errors in the presence of severe range migration effects. Therefore, in this paper, a high-precision THz-ISAR imaging algorithm is proposed. The algorithm includes the following step: First, the SV first-order range migration(FRM) is corrected using keystone transform (KT); then, the minimum entropy based on modified newton (ME-MN) is used to estimate the rotational velocity roughly, and the remaining SV second-order range migration(SRM) is corrected to obtain the range profile with the envelope alignment. Finally, the echo after the envelope alignment is processed for the second time based on ME-MN. The target rotation velocity is accurately estimated, and the phase error is compensated to obtain a well-focused imaging result. The validity of the proposed method is verified by numerical simulation and electromagnetic calculation data.