bluuebunny/crossref_metadata_2025 huggingface dataset:
Characterising Large-Scale Meteorological Patterns Associated with Winter Precipitation and Snow Accumulation in a Mountain Range in the Iberian Peninsula (Sierra de Guadarrama)
Authors: González-Flórez Cristina , González-Cervera Álvaro , Durán Luis
Published: October 2022

Snow precipitation in mountains surrounded by semi-arid regions represents an important reservoir of fresh water during the melting season. The snow cover helps to compensate for the scarce precipitation that occurs during their long summer droughts. Knowing the phenomenology that leads to winter precipitation and snow at these areas becomes even more relevant in a context of climate change. Precipitation in Sierra de Guadarrama, a medium size mountain range in the middle of the Iberian Plateau, is the main source of fresh water for millions of inhabitants living under its area of influence, for an active industry and for agriculture and farming. In addition, scarce but heavy snow events affect logistics, transport and security in an area with abundant ground and air traffic. This work analyses the links between large scale atmospheric patterns and the complex winter precipitation and snow cover dynamics observed at local scale. Applying principal component analysis and K-means clustering on geopotential height field, a set of circulation weather types are obtained. The contribution of each circulation weather type to precipitation, snow and heavy snow events is analysed, and favouring conditions leading to snowfalls are identified. Results from this work can be useful as a framework for future modelling exercises, statistical downscaling of climate change scenarios, or even for the development of early warning systems.
Improving the Thermal Comfort of an Open Space via Landscape Design: A Case Study in Hot and Humid Areas
Authors: Yang Jiahao , Zhao Yang , Zou Yukai , Xia Dawei , Lou Siwei , Guo Tongye , Zhong Zhengnan
Published: October 2022

Hot and humid areas experience constant high temperatures and high humidity during summer, causing widespread concern about outdoor thermal discomfort. This paper investigates the effects of landscape design strategies on outdoor thermal environments during typical summer and winter weather conditions in the hot–humid areas of China. The physiological equivalent temperature (PET) is used for evaluating the thermal performance of the proposed outdoor environments. ENVI-met software was validated via field measurements for this study and was used to evaluate the outdoor thermal environment under typical summer and winter weather conditions. Three kinds of common landscape elements were analyzed: tree species, pavement, and water bodies. The results show that (1) by properly arranging landscape elements, the PET can be reduced by up to 1.6 °C in summer without sacrificing relevant thermal comfort during winter. (2) Arbors with high leaf area density (LAD) values performed better than those with a low LAD value for improved outdoor thermal comfort. (3) The influence of pavement on outdoor thermal comfort differs when under conditions with and without shade. This study provides practical suggestions for landscape design in open spaces within hot–humid areas.
A Novel Tropical Cyclone Track Forecast Model Based on Attention Mechanism
Authors: Fang Wei , Lu Wenhe , Li Jiaxin , Zou Liyao
Published: October 2022

Tropical cyclones are one of the most powerful and destructive weather systems on Earth. Accurately forecasting the landing time, location and moving paths of tropical cyclones are of great significance to mitigate the huge disasters it produces. However, with the continuous accumulation of meteorological monitoring data and the application of multi-source data, traditional tropical cyclone track forecasting methods face many challenges in forecasting accuracy. Recently, deep learning methods have proven capable of learning spatial and temporal features from massive datasets. In this paper, we propose a new spatiotemporal deep learning model for tropical cyclone track forecasting, which adopts spatial location and multiple meteorological factors to forecast the tracks of tropical cyclones. The model proposes a multi-layer ConvGRU to extract the nonlinear spatial features of tropical cyclones, while Spatial and Channel Attention Mechanism (CBAM) is adopted to overcome the large-scale problem of high response isobaric surface affecting the tropical cyclones. Meanwhile, this model utilizes a Deep and Cross framework to combine the traditional CNN model with the multi-ConvGRU model. Experiments were conducted on the China Meteorological Administration Tropical Cyclone Best Track Dataset (CMA) from 2000 to 2020, and the EAR-Interim dataset provided by the European Centre for Medium-Range Weather Forecasts (ECMWF). The experimental results show that the proposed model is superior to the deep learning tropical cyclone forecasting methods.
Monitoring the Dynamic Changes in Vegetation Cover Using Spatio-Temporal Remote Sensing Data from 1984 to 2020
Authors: Hussain Sajjad , Qin Shujing , Nasim Wajid , Bukhari Muhammad Adnan , Mubeen Muhammad , Fahad Shah , Raza Ali , Abdo Hazem Ghassan , Tariq Aqil , Mousa B. G. , Mumtaz Faisal , Aslam Muhammad
Published: October 2022

Anthropogenic activities and natural climate changes are the central driving forces of global ecosystems and agriculture changes. Climate changes, such as rainfall and temperature changes, have had the greatest impact on different types of plant production around the world. In the present study, we investigated the spatiotemporal variation of major crops (cotton, rice, wheat, and sugarcane) in the District Vehari, Pakistan, from 1984 to 2020 using remote sensing (RS) technology. The crop identification was pre-processed in ArcGIS software based on Landsat images. After pre-processing, supervised classification was used, which explains the maximum likelihood classification (MLC) to identify the vegetation changes. Our results showed that in the study area cultivated areas under wheat and cotton decreased by almost 5.4% and 9.1% from 1984 to 2020, respectively. Vegetated areas have maximum values of NDVI (>0.4), and built-up areas showed fewer NDVI values (0 to 0.2) in the District Vehari. During the Rabi season, the temperature was increased from 19.93 °C to 21.17 °C. The average temperature was calculated at 34.28 °C to 35.54 °C during the Kharif season in the District Vehari. Our results showed that temperature negatively affects sugarcane, rice, and cotton crops during the Rabi season, and precipitation positively affects sugarcane, rice, and cotton crops during the Kharif season in the study area. Accurate and timely assessment of crop estimation and relation to climate change can give very useful information for decision-makers, governments, and planners in formulating policies regarding crop management and improving agriculture yields.
Scenario Analysis of Air Quality Improvement in Warsaw, Poland, by the End of the Current Decade
Authors: Holnicki Piotr , Kałuszko Andrzej , Nahorski Zbigniew
Published: October 2022

Very low air quality in the Warsaw conurbation, Poland, similarly to the case in many large European cities, poses a serious threat to the residents’ health, being a significant source of premature mortality. Many results presented in earlier publications indicated local heating installations and car traffic as the main emission categories responsible for this adverse population exposure, where the dominant polluting compounds are NOx, PM10, PM2.5, and BaP. The last two mainly originate from individual household heating installations, both in the city of Warsaw and in its vicinity. To reduce the health risk of air pollution, the city authorities have recently made fundamental decisions, related to the individual housing sector, aimed at the radical decarbonization of all heating installations in Warsaw and its surroundings. On the other hand, the ongoing modernization of the city’s car fleet (including individual and public transport), taking into account the restrictive EU emission standards, as well as the quickly growing share of electric and hybrid cars (BEVs and PHEVs), gives a good prospect of a fundamental improvement in air quality in Warsaw conurbation. The main subject of the paper is a quantitative assessment of the air quality improvement in the current decade (by 2030), resulting from the above modernization activities. The final results are expressed as the attributed reduction in population exposure, which was found to be 28–30% with respect to NOx and PM, and the associated health risk, i.e., 204 fewer avoidable deaths with respect to NOx and 607 fewer with respect to PM2.5.
Deep Learning Based Calibration Time Reduction for MOS Gas Sensors with Transfer Learning
Authors: Robin Yannick , Amann Johannes , Goodarzi Payman , Schneider Tizian , Schütze Andreas , Bur Christian
Published: October 2022

In this study, methods from the field of deep learning are used to calibrate a metal oxide semiconductor (MOS) gas sensor in a complex environment in order to be able to predict a specific gas concentration. Specifically, we want to tackle the problem of long calibration times and the problem of transferring calibrations between sensors, which is a severe challenge for the widespread use of MOS gas sensor systems. Therefore, this contribution aims to significantly diminish those problems by applying transfer learning from the field of deep learning. Within the field of deep learning, transfer learning has become more and more popular. Nowadays, building a model (calibrating a sensor) based on pre-trained models instead of training from scratch is a standard routine. This allows the model to train with inherent information and reach a suitable solution much faster or more accurately. For predicting the gas concentration with a MOS gas sensor operated dynamically using temperature cycling, the calibration time can be significantly reduced for all nine target gases at the ppb level (seven volatile organic compounds plus carbon monoxide and hydrogen). It was possible to reduce the calibration time by up to 93% and still obtain root-mean-squared error (RMSE) values only double the best achieved RMSEs. In order to obtain the best possible transferability, different transfer methods and the influence of different transfer data sets for training were investigated. Finally, transfer learning based on neural networks is compared to a global calibration model based on feature extraction, selection, and regression to place the results in the context of already existing work.
Ionospheric Disturbances after the 2022 Hunga Tonga-Hunga Ha’apai Eruption above Indonesia from GNSS-TEC Observations
Authors: Muafiry Ihsan Naufal , Meilano Irwan , Heki Kosuke , Wijaya Dudy D. , Nugraha Kris Adi
Published: October 2022

On 15 January 2022, a VEI 5 eruption occurred at the submarine Hunga Tonga-Hunga Ha’apai (HTHH) Volcano in the Southwest Pacific, causing an ash plume reaching a height of 50–55 km. The eruption generated strong acoustic-gravity waves in the near-field and stations all over the world recorded Lamb waves (LW) that travelled around the earth multiple times at a speed of ~0.3 km/s. Here we report ionospheric anomalies due to the LW over Indonesian islands, 5000–10,000 km away from the volcano, in terms of changes in total electron contents (TEC) using the nationwide network of GNSS stations. We detected ionospheric anomalies travelling above Indonesia several times both westward and eastward. The first passage of LW over Java caused strong TEC increases of >12 TECU. The wave circled the earth and returned to Java on subsequent days. The second passage was recorded early 1/17, the anomaly decayed to 6 TECU. We also detected the passage of long-path waves propagating from west to east. In addition to such anomalies, we examined the existence of ionospheric disturbances apparently propagating from the geomagnetic conjugate point of the volcano that could possibly emerge in Indonesia. However, their signatures in Indonesia were not clear.
Nutrient Accumulation in Cover Crops under Contrasting Water Regimes in the Brazilian Cerrado
Authors: Silva Alberto do Nascimento , Ribeiro Junior Walter Quadros , Ramos Maria Lucrecia Gerosa , de Lima Cristiane Andrea , Jayme-Oliveira Adilson , Silva Antonio Marcos Miranda , de Carvalho Arminda Moreira
Published: October 2022

Brazilian Cerrado has a dry period, and the inclusion of new species for diversification in the production system needs to be drought-tolerant. This work aimed to evaluate biomass and nutrient accumulation in species with potential as cover crops and grain crops under different water levels. Irrigation treatments were obtained through an irrigation bar with sprinklers with increasing water flows to create a continuous gradient. The experimental design randomized complete blocks in split plots with four replications. The main plots were composed of four water regimes (167 mm, 268 mm, 381 mm and 432 mm), and the subplots were formed by the following cover crops: Amaranthus cruenthus, Chenopodium quinoa and Pennisetum glaucum, the latter already used for this purpose. Amaranthus cruenthus and P. glaucum recorded the highest dry biomass (10.16 and 9.75 Mg ha−1, respectively). Dry biomass production and the cellulose contents decreased with the reduction of water availability for all species. A. cruenthus was the species that most accumulated P (37.42 kg ha−1), K (416.92 kg ha−1), Mg (30.88 kg ha−1), S (43.53 kg ha−1), Fe (2.22 kg ha−1), B (0.124 kg ha−1) and Zn (0.240 kg ha−1). Amaranthus cruenthus produced the highest yield. Under high and low water availability conditions, A. cruenthus presents potential as a cover crop and grain cash crop, in addition to accumulating more nutrients; P. glaucum has potential as a cover crop and C. quinoa only for grain production.
Influence of Particulate Matter on the Albedo of Qiangtang No. 1 Glacier, Tibetan Plateau
Authors: Xu Tianli , Wu Guangjian , Yu Zhengliang , Pan Yifan , Li Sen , Yan Ni
Published: October 2022

The melting behavior of glaciers on and around the Tibetan Plateau is strongly influenced by their albedo. In this paper, we report continuous observations made on the Qiangtang (QT) No. 1 Glacier, located in the central Tibetan Plateau, during its 2013–2015 melting seasons. Surface snow on the QT No. 1 Glacier mainly had a dust content less than 600 ppm and a black carbon (BC) content less than 10 ppb. A strong negative correlation was observed between albedo and dust content up to a threshold concentration of 1000 ppm, although albedo remained constant when dust concentrations increased above this value. The radii of snow particles showed a log-normal distribution that had a mean value of ~500 μm, but maximum and minimum values of 2539 μm and 40 μm, respectively. Snow density showed a normal distribution with a total range of 193–555 kg/m3, although most snow had a density of 400 kg/m3. Snow, ice, and aerosol radiative (SNICAR) simulations showed that dust and BC in the surface snow of the QT No. 1 Glacier reduced the snow and ice albedo by 5.9% and 0.06%, respectively, during the ablation season in 2015; however, the simulated particle impact was greater than the albedo reduction measured from field data. We interpret that dust has played a significantly more important role in melting of the QT No. 1 Glacier than BC over the study period, which is mainly due to the scarcity of human activities in the region and the low concentration of BC being produced.
Sustainability Enhancement of Fossil-Fueled Power Plants by Optimal Design and Operation of Membrane-Based CO2 Capture Process
Authors: Asadi Javad , Kazempoor Pejman
Published: October 2022

Fossil-fueled power plants are a major source of carbon dioxide (CO2) emission and the membrane process is a promising technology for CO2 removal and mitigation. This study aims to develop optimal membrane-based carbon capture systems to enhance the sustainability of fossil-fuel power plants by reducing their energy consumption and operating costs. The multi-stage membrane process is numerically modeled using Aspen Custom Modeler based on the solution-diffusion mechanism and then the effects of important operating and design parameters are investigated. Multi-objective process optimization is then carried out by linking Aspen Plus with MATLAB and using an evolutionary technique to determine optimal operating and design conditions. The results show that, as the CO2 concentration in the feed gas increases, the CO2 capture cost significantly decreases and CO2 removal is enhanced, although the process energy demand slightly increases. The best possible trade-offs between objective functions are reported and analyzed, which confirm the considerable potential for improving the sustainability of the process. The CO2 capture cost and energy penalty of the process is as low as 13.1 $/tCO2 and 10% at optimal design and operating conditions. This study provides valuable insight into membrane separation and can be used by decision-makers for the sustainable improvement of fossil-fueled power plants.
Indoor Air Quality Intervention in Schools: Effectiveness of a Portable HEPA Filter Deployment in Five Schools Impacted by Roadway and Aircraft Pollution Sources
Authors: Carmona Nancy , Seto Edmund , Gould Timothy R. , Rasyid Everetta , Shirai Jeffry H. , Cummings BJ , Hayward Lisa , Larson Timothy V. , Austin Elena
Published: October 2022

The Healthy Air, Healthy Schools Study was established to better understand the impact of ultrafine particles (UFPs) on indoor air quality in communities surrounding Seattle-Tacoma (Sea-Tac) International Airport. The study team took multipollutant measurements of indoor and outdoor air pollution at five participating school locations to estimate infiltration indoors. The schools participating in this project were located within a 7-mile radius of Sea-Tac International Airport and within 0.5 mile of an active flight path. Based on experimental measures in an unoccupied classroom, infiltration rates of (a) UFPs of aircraft origin, (b) UFPs of traffic origin, and (c) wildfire smoke or other outdoor pollutants were characterized before and after the introduction of a portable high-efficiency particulate air (HEPA) filter intervention. The portable HEPA cleaners were an effective short-term intervention to improve the air quality in classroom environments, reducing the UFP count concentration from one-half to approximately one-tenth of that measured outside. This study is unique in focusing on UFPs in schools and demonstrating that UFPs measured in classroom spaces are primarily of outdoor origin. Although existing research suggests that reducing particulate matter in homes can significantly improve asthma outcomes, further investigation is necessary to establish the benefits to student health and academic performance of reducing UFP exposures in schools.
Exploring the Mass Concentration of Particulate Matter and Its Relationship with Meteorological Parameters in the Hindu-Kush Range
Authors: Usman Farooq , Zeb Bahadar , Alam Khan , Valipour Mohammad , Ditta Allah , Sorooshian Armin , Roy Rana , Ahmad Iftikhar , Iqbal Rashid
Published: October 2022

Particulate matter (PM) is among the deadliest air pollutants due to its negative health impacts and environmental harm. This study reports on monthly and seasonal concentrations of PM10, PM2.5, and PM1, along with their ratios. Twelve-day samples were collected once a month in Mingora city (Swat, Pakistan) from January to December 2019 using a low volume sampler. Maximum average mass concentrations of PM10, PM2.5, and PM1 were recorded in December having values of 78, 56, and 32 μg m−3, respectively. Minimum average values for PM10 (44 μg m−3) and PM2.5 (25.1 μg m−3) were recorded in April, while the lowest PM1 (11 μg m−3) was recorded in August. In comparison to other months, the maximum average mass concentrations were 1.77 times (PM10), 2.23 times (PM2.5), and 2.9 times (PM1) higher in December. During the winter season, average mass concentrations remained high. Substantial correlation coefficients of 0.92, 0.79, and 0.75 were recorded between PM10 and PM2.5, PM2.5 and PM1, and PM2.5 and PM1, respectively. The overall average ratios PM2.5: PM10, PM1: PM2.5, and PM1: PM10 were 68.3, 52.6, and 35.4%, respectively. A moderate negative correlation of PM10, PM2.5, and PM1 with wind speed (−0.34, −0.39, and −0.41), a strong negative correlation with temperature (−0.69, −0.71, and −0.74) and rainfall (−0.63, −0.61, and −0.59), and a weak relationship with relative humidity (−0.32, −0.1, and −0.02) were recorded.
2022: An Unprecedentedly Rainy Early Summer in Northeast China
Authors: Lin Yitong , Fang Yihe , Wu Jie , Ke Zongjian , Zhao Chunyu , Tan Kexin
Published: October 2022

In the early summer (June) of 2022, the spatial mean precipitation in northeast China (NEC) was 62% higher than normal and broke the historical record since 1951. Based on the precipitation data of 245 meteorological stations in NEC and the National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) reanalysis, this paper analyzes the role of large-scale circulation and sea-surface temperature (SST) associated with anomalous precipitation over NEC in June using singular value decomposition (SVD), correlation analysis, regression analysis, and composite analysis methods, and further investigates the possible cause of the abnormal precipitation in June 2022. Results show that the northeast China cold vortex (NCCV) accompanying the blocking high in the Okhotsk Sea (BHOS) has been the primary mid-to-high latitude atmospheric circulation pattern affecting NEC precipitation in June since 2001. This circulation pattern is closely related to the tripole SST pattern over the North Atlantic (NAT) in March. In June 2022, the NAT SST anomaly in March stimulates eastward-propagating wave energy, resulting in the downstream anomalous circulation pattern in which the NCCV cooperates with the BHOS in the mid-high latitudes of East Asia. Under this background atmospheric circulation favorable for precipitation, the Kuroshio region SST anomaly in June led to a more northward and stronger anomalous anticyclone in the northwestern Pacific through local air–sea interaction, which provides more sufficient water vapor for NEC, resulting in unprecedented precipitation in June 2022.
Impact of IMO Sulfur Regulations on Air Quality in Busan, Republic of Korea
Authors: Kim Yumi , Moon Nankyoung , Chung Yoonbae , Seo Jihyun
Published: October 2022

In this study, we investigate the air quality improvement effect in Busan, the largest port city in South Korea, caused by the implementation of International Maritime Organization (IMO) sulfur regulations. Currently, the Korean government is struggling with problems related to PM2.5, and ships are one of the major sources of PM2.5 generation in South Korea. Therefore, we tried to estimate how much the PM2.5 levels in South Korea could be improved via low-sulfur regulation. According to the Clean Air Quality Policy Support System (CAPSS; National Emission Inventory) in 2016, ship emissions in Busan accounted for 39%, 71%, and 39% of PM2.5, SO2, and NO2 emissions, respectively. To simulate the effect of the IMO’s 0.5 percent sulfur regulation, SOx and PM2.5 emissions from oil-fueled cargo ships were reduced. Via ship fuel regulation, the PM2.5 concentration was improved by up to 19% at a site near the port in 2020. In addition, in the case of sulfate, the reduction rate was higher on the downwind side of the Busan port and not near the port, which can be considered as the cause of advection and secondary formation. The PM2.5 contributions from ships to each of the sub-regions in Busan also decreased by an average of 47% because of IMO sulfur regulation. Although there were limitations in terms of emission estimations because of the application of low-sulfur regulation, we expect that the results of this paper can be used for additional PM2.5 improvement plans developed by the Korean government and by the local government as well.
Investigation of the Possibility of Application of Metal Fibrous Media in the Process of Filtration of Liquid Aerosols
Authors: Lecoq Marie , Bourrous Soleiman , Thomas Dominique , Appert-Collin Jean-Christophe , Floc’Hlay Fabien , Barrault Mathieu
Published: October 2022

This manuscript presents a study of the possibility of applying metallic fibre filter media made of stainless steel for the filtration process of liquid aerosols. To perform the experiment, three types of filters were used: single layer and symmetric or non-symmetric multi-layered filters. Filters have been loaded with DEHS (Di-Ethyl-Hexyl-Sebacate) aerosol while the pressure drop and the collection efficiency were monitored. The impact of the filtration velocity on the saturation pressure drop has been quantified for monolayer filters. The building of a draining film on the free surface of the multi-layered filters has been studied and the impact of this phenomenon on the filtration performances and saturation ratio of the medium are discussed. For multilayer filters, the clogging dynamic, occurring by a successive loading of the draining layers, is highlighted in this work. Finally, propositions are made to evaluate the behaviour of metallic multi-layered filters for liquid aerosol filtration applications.
Surface and Bulk Plasmon Excitation on Aluminum Surface at Small to High Grazing Angles
Authors: Sulyok Attila , Tőkési Karoly
Published: October 2022

We present a series of spectra measured by reflected electron energy loss spectroscopy on an aluminum sample using a cylindrical mirror analyzer. The measurements were performed in the energy range between 250 eV and 2000 eV and with various incident angles, including the grazing geometry of an 88° incident angle. The observed spectra were evaluated and decomposed for surface and bulk excitation. The determined surface plasmon excitations were compared to the elastic peak and to the bulk excitation. We found a slight surface plasmon energy shift with altering glancing angles. We show that this shift exists independently from the bulk plasmon interference.
GRASP: The Future?
Authors: Grant Ian , Quiney Harry
Published: October 2022

The theoretical foundations of relativistic electronic structure theory within quantum electrodynamics (QED) and the computational basis of the atomic structure code GRASP are briefly surveyed. A class of four-component basis set is introduced, which we denote the CKG-spinor set, that enforces the charge-conjugation symmetry of the Dirac equation. This formalism has been implemented using the Gaussian function technology that is routinely used in computational quantum chemistry, including in our relativistic molecular structure code, BERTHA. We demonstrate that, unlike the kinetically matched two-component basis sets that are widely employed in relativistic quantum chemistry, the CKG-spinor basis is able to reproduce the well-known eigenvalue spectrum of point-nuclear hydrogenic systems to high accuracy for all atomic symmetry types. Calculations are reported of third- and higher-order vacuum polarization effects in hydrogenic systems using the CKG-spinor set. These results reveal that Gaussian basis set expansions are able to calculate accurately these QED effects without recourse to the apparatus of regularization and in agreement with existing methods. An approach to the evaluation of the electron self-energy is outlined that extends our earlier work using partial-wave expansions in QED. Combined with the treatment of vacuum polarization effects described in this article, these basis set methods suggest the development of a comprehensive ab initio approach to the calculation of radiative and QED effects in future versions of the GRASP code.
Congenital Nonprofound Bilateral Sensorineural Hearing Loss in Children: Comprehensive Characterization of Auditory Function and Hearing Aid Benefit
Authors: Berninger Erik , Drott Maria , Romanitan Mircea , Tranebjærg Lisbeth , Hellström Sten
Published: October 2022

A prospective cross-sectional design was used to characterize congenital bilateral sensorineural hearing loss (SNHL). The underlying material of >30,000 consecutively screened newborns comprised 11 subjects with nonprofound, alleged nonsyndromic, SNHL. Comprehensive audiological testing was performed at ≈11 years of age. Results showed symmetrical sigmoid-like median pure-tone thresholds (PTTs) reaching 50–60 dB HL. The congenital SNHL revealed recruitment, increased upward spread of masking, distortion product otoacoustic emission (DPOAE) dependent on PTT (≤60 dB HL), reduced auditory brainstem response (ABR) amplitude, and normal magnetic resonance imaging. Unaided recognition of speech in spatially separate competing speech (SCS) deteriorated with increasing uncomfortable loudness level (UCL), plausibly linked to reduced afferent signals. Most subjects demonstrated hearing aid (HA) benefit in a demanding laboratory listening situation. Questionnaires revealed HA benefit in real-world listening situations. This functional characterization should be important for the outline of clinical guidelines. The distinct relationship between DPOAE and PTT, up to the theoretical limit of cochlear amplification, and the low ABR amplitude remain to be elucidated. The significant relation between UCL and SCS has implications for HA-fitting. The fitting of HAs based on causes, mechanisms, and functional characterization of the SNHL may be an individualized intervention approach and deserves future research.
A Unique Representation of Cyclic Codes over GR(pn,r)
Authors: Alabiad Sami , Alkhamees Yousef
Published: October 2022

Let R be a Galois ring, GR(pn,r), of characteristic pn and of order pnr. In this article, we study cyclic codes of arbitrary length, N, over R. We use discrete Fourier transform (DFT) to determine a unique representation of cyclic codes of length, N, in terms of that of length, ps, where s=vp(N) and vp are the p-adic valuation. As a result, Hamming distance and dual codes are obtained. In addition, we compute the exact number of distinct cyclic codes over R when n=2.
Complex Dynamic Behaviors of a Modified Discrete Leslie–Gower Predator–Prey System with Fear Effect on Prey Species
Authors: Lin Sijia , Chen Fengde , Li Zhong , Chen Lijuan
Published: October 2022

A discrete modified Leslie–Gower prey-predator model considering the effect of fear on prey species is proposed and studied in this paper. First, we discuss the existence of equilibria and the local stability of the model. Second, we use the iterative method and comparison principle to obtain the set of conditions which ensures the global attractivity of positive equilibrium point. The results show that prey and predator can coexist stably when the intrinsic growth rates of both prey and predator are maintained within a certain range. Then, we study the global attractivity of the boundary equilibrium point. Our results suggest that when the intrinsic rate of prey is small enough or the fear factor is large enough, the prey will tend to go extinct, while the predator can survive stably due to the availability of other food sources. Subsequently, we discuss flip bifurcation, transcritical bifurcation at the equilibria of the system, by using the center manifold theorem and bifurcation theory. We find that system changes from chaotic state to four-period orbit, two-period orbit, stable state, and finally prey species will be driven to extinction, while predator species survive in a stable state for enough large birth rate of prey species with the increasing of fear effect. Finally, we verify the feasibility of the main results by numerical simulations, and discuss the influence of the fear effect. The results show that the fear effect within a certain range can enhance the stability of the system.
Some Multifaceted Aspects of Mathematical Physics, Our Common Denominator with Elliott Lieb †
Authors: Sternheimer Daniel
Published: October 2022

Mathematical physics has many facets, of which we shall briefly give a (very partial) description, centered around those of main interest for Elliott and us (Moshe Flato and I), and around the seminal scientific and personal interactions that developed between us since the sixties until Moshe’s untimely death in 1998. These aspects still influence my scientific activity and my life. They also had as a corollary a variety of “parascientific activities”, in particular, the foundation of IAMP (the International Association of Mathematical Physics) and of the journal LMP (Letters in Mathematical Physics), both of which were strongly impacted by Elliott, and Elliott’s long insistence that publishers do not demand “copyright transfer” as a precondition for publication but are satisfied with a “consent to publish”, which is increasingly becoming standard. This article being mainly a testimony to the huge scientific impacts of Elliott and also of Moshe, their intertwined aspects constitute the core of the present contribution. The last part deals briefly with metaphysical and metamathematical considerations related to axioms.
Patron–Prophet Artificial Bee Colony Approach for Solving Numerical Continuous Optimization Problems
Authors: Thirugnanasambandam Kalaipriyan , Ramalingam Rajakumar , Mohan Divya , Rashid Mamoon , Juneja Kapil , Alshamrani Sultan S.
Published: October 2022

The swarm-based Artificial Bee Colony (ABC) algorithm has a significant range of applications and is competent, compared to other algorithms, regarding many optimization problems. However, the ABC’s performance in higher-dimension situations towards global optima is not on par with other models due to its deficiency in balancing intensification and diversification. In this research, two different strategies are applied for the improvement of the search capability of the ABC in a multimodal search space. In the ABC, the first strategy, Patron–Prophet, is assessed in the scout bee phase to incorporate a cooperative nature. This strategy works based on the donor–acceptor concept. In addition, a self-adaptability approach is included to balance intensification and diversification. This balancing helps the ABC to search for optimal solutions without premature convergence. The first strategy explores unexplored regions with better insight, and more profound intensification occurs in the discovered areas. The second strategy controls the trap of being in local optima and diversification without the pulse of intensification. The proposed model, named the PP-ABC, was evaluated with mathematical benchmark functions to prove its efficiency in comparison with other existing models. Additionally, the standard and statistical analyses show a better outcome of the proposed algorithm over the compared techniques. The proposed model was applied to a three-bar truss engineering design problem to validate the model’s efficacy, and the results were recorded.
Chaos in Topological Modules
Authors: García-Pacheco Francisco
Published: October 2022

Chaotic and pathological phenomena in topological modules are studied in this manuscript. In particular, constructions of noncontinuous linear functionals are provided for a wide variety of topological modules. In addition, constructions of balanced and absorbing sets which are not neighborhoods of zero are also given in an extensive class of topological modules. Finally, we construct a linearly open set with empty interior in a large amount of topological modules. All these constructions are related to each other. Prior to developing all these results, we provide an axiomatization of the topological concept of limit by introducing the limit operators in a similar context as hull operators or closure operators are defined.
Improving the Accuracy of Forecasting Models Using the Modified Model of Single-Valued Neutrosophic Hesitant Fuzzy Time Series
Authors: Pantachang Kittikun , Tansuchat Roengchai , Yamaka Woraphon
Published: October 2022

Proposed in this study is a modified model for a single-valued neutrosophic hesitant fuzzy time series forecasting of the time series data. The research aims at improving the previously presented single-valued neutrosophic hesitant fuzzy time series (SVNHFTS) model by including several degrees of hesitancy to increase forecasting accuracy. The Gaussian fuzzy number (GFN) and the bell-shaped fuzzy number (BSFN) were used to incorporate the degree of hesitancy. The cosine measure and the single-valued neutrosophic hesitant fuzzy weighted geometric (SVNHFWG) operator were applied to analyze the possibilities and pick the best one based on the neutrosophic value. Two data sets consist of the short and low-frequency time series data of student enrollment and the long and high-frequency data of ten major cryptocurrencies. The empirical result demonstrated that the proposed model provides higher efficiency and accuracy in forecasting the daily closing prices of ten major cryptocurrencies compared to the S-ANFIS, ARIMA, and LSTM methods and also outperforms other FTS methods in predicting the benchmark student enrollment dataset of the University of Alabama in terms of computation time, the Mean Absolute Percentage Error (MAPE), Mean Absolute Error (MAE), and the Root Mean Square Error (RMSE).
Three-Way Fuzzy Sets and Their Applications (II)
Authors: Wang Jingqian , Zhang Xiaohong , Hu Qingqing
Published: October 2022

Recently, the notion of a three-way fuzzy set is presented, inspired by the basic ideas of three-way decision and various generalized fuzzy sets, including lattice-valued fuzzy sets, partial fuzzy sets, intuitionistic fuzzy sets, etc. As the new theory of uncertainty, it has been used in attribute reduction and as a new control method for the water level. However, as an extension of a three-way decision, this new theory has not been used in multi-criteria decision making (MCDM for short). Based on the previous work, in this paper, we present rough set models based on three-way fuzzy sets, which extend the existing fuzzy rough set models in both complete and incomplete information systems. Furthermore, the new models are used to solve the issue of MCDM. Firstly, three-way fuzzy relation rough set and three-way fuzzy covering rough set models are presented for complete and incomplete information systems. Because almost all existing fuzzy rough set models are proposed under complete information, the new proposed models can be seen as a supplement to these existing models. Then, a relationship between the three-way fuzzy relation rough set and the three-way fuzzy covering rough set is presented. Finally, a novel method for the issue of MCDM is presented under the novel three-way fuzzy rough set models, which is used in paper defect diagnosis.
Physics-Informed Recurrent Neural Networks with Fractional-Order Constraints for the State Estimation of Lithium-Ion Batteries
Authors: Wang Yanan , Han Xuebing , Guo Dongxu , Lu Languang , Chen Yangquan , Ouyang Minggao
Published: October 2022

The state estimation of lithium-ion battery is the basis of an intelligent battery management system; therefore, both model-based and data-driven methods have been designed and developed for state estimation. Rather than using complex partial differential equations and the complicated parameter tuning of a model-based method, a machine learning algorithm provides a new paradigm and has been increasingly applied to cloud big-data platforms. Although promising, it is now recognized that big data for machine learning may not be consistent in terms of data quality with reliable labels. Moreover, many algorithms are still applied as a black box that may not learn battery inner information well. To enhance the algorithm generalization in realistic situations, this paper presents a fractional-order physics-informed recurrent neural network (PIRNN) for state estimation. The fractional-order characteristics from battery mechanism are embedded into the proposed algorithm by introducing fractional-order gradients in backpropagation process and fractional-order constraints into the convergence loss function. With encoded battery knowledge, the proposed fractional-order PIRNN would accelerate the convergence speed in training process and achieve improved prediction accuracies. Experiments of four cells under federal urban driving schedule operation conditions and different temperatures are conducted to illustrate the estimation effects of the proposed fractional-order PIRNN. Compared to the integer-order gradient descent method, the fractional-order gradient descent method proposed in this work can optimize network convergence and obtains regression coefficient larger than 0.995. Moreover, the experimental results indicate that the proposed algorithm can achieve 2.5% estimation accuracy with the encoding fractional-order knowledge of lithium-ion batteries.
Electrochemical Performance of Li2TiO3//LiCoO2 Li-Ion Aqueous Cell with Nanocrystalline Electrodes
Authors: Lakshmi-Narayana Ambadi , Sivajee-Ganesh Kapu , Dhananjaya Merum , Narayan-Banerjee Arghya , Julien Christian M. , Joo San-Woo
Published: October 2022

A challenge in developing high-performance lithium batteries requires a safe technology without flammable liquid electrolytes. Nowadays, two options can satisfy this claim: all-solid-state batteries and aqueous-electrolyte batteries. Commercially available Li-ion batteries utilize non-aqueous electrolytes (NAE) owing to a wide potential window (>3 V) that achieves high energy density but pose serious safety issues due to the high volatility, flammability, and toxicity of NAE. On the contrary, aqueous electrolytes are non-flammable, low-toxic, and have a low installation cost for humidity control in the production line. In this scenario, we develop a new aqueous rechargeable Li-ion full-cell composed of high-voltage cathode material as LiCoO2 (LCO) and a safe nanostructured anode material as Li2TiO3 (LTO). Both pure-phase LTO and LCO nanopowders are prepared by hydrothermal route and their structural and electrochemical properties are studied in detail. Simultaneously, the electrochemical performances of these electrodes are tested in both half- and full-cell configurations in presence of saturated 1 mole L−1 Li2SO4 aqueous electrolyte medium. Pt//LCO and Pt//LTO half-cells deliver high discharge capacities of 142 and 133 mAh g−1 at 0.5 C rate with capacity retention of ~95% and 94% after 50 cycles with a Coulombic efficiency of 98.25% and 99.89%, respectively. The electrochemical performance of a LTO//LCO full cell is investigated for the first time. It reveals a discharge capacity of 135 mAh g−1 at 0.5 C rate (50th cycle) with a capacity retention of 94% and a Coulombic efficiency of 99.7%.
Electrolyte Additive Strategies for Suppression of Zinc Dendrites in Aqueous Zinc-Ion Batteries
Authors: Zhai Chongyuan , Zhao Dandi , He Yapeng , Huang Hui , Chen Buming , Wang Xue , Guo Zhongcheng
Published: October 2022

Aqueous zinc-ion batteries (ZIBs) with metal zinc as the anode possess the features of safety, environmental friendliness, and high specific capacity, which have attracted a great deal of attention in the past few years. The accompanying zinc dendrites are an important problem that endangers the battery performance. Therefore, the extensive research on the suppression strategies of Zn dendrites reflects a positive effect on improving the performance of ZIBs. In particular, the electrolyte additives (EAs) approach is considered a simple, reliable, and low-cost strategy to address the zinc dendritic issues and can inhibit or alleviate the growth of zinc dendrites while facilitating the amelioration of adverse reactions. In this review, the principles and processes of zinc dendrites, corrosion passivation, and hydrogen evolution side reactions on zinc anodes of ZIBs are firstly categorized. Then, the mitigation and inhibition of zinc dendrites and side reactions via different kinds of EAs are elaborated according to the regulation strategies of EAs, which provides an overview of the research on EAs conducted in recent years and proposed strategies to solve zinc dendrites and other problems. Finally, a reasonable outlook on the future improvement and development of EAs for ZIBs is described, which could provide some guidance for the evolution and design of EAs in the future.
On the Specific Capacity and Cycle Stability of Si@void@C Anodes: Effects of Particle Size and Charge/Discharge Protocol
Authors: Liu Bingyu , Luo Mei , Wang Ziyong , Passolano Christopher , Shaw Leon
Published: October 2022

Silicon has the potential to be a high-performance anode material, but its practical application is impeded by huge volume expansion during lithiation. Many studies have revealed that the huge volume expansion problem can be mitigated by introducing engineered voids into Si/C core–shell structures. In this study, a Si/C core/shell structure with engineered voids, termed Si@void@C, is investigated for its specific capacity and cycle stability as a function of particle size and charge/discharge protocol. The study shows that finer Si@void@C particles result in higher specific capacities, but with little impact on the cycle stability. Further, lower and upper cutoff voltages in charge/discharge have a profound impact on the specific capacity and cycle stability. Importantly, cutoff voltages in formation cycles have long-lasting effects on the cycle stability, indicating the critical role of forming a robust solid electrolyte interphase (SEI) layer during formation cycles. Using a constant current charge followed by potentiostatic hold charge can further improve the cycle stability and minimize the sharp capacity decay in the first 20–40 cycles. With proper choices of charge/discharge protocols, the specific capacities of Si@void@C anodes at the electrode level are 66.8%, 38.2% and 22.7% higher than those of graphite anodes at the 1st, 300th and 500th cycles, respectively, proving that Si@void@C has promising potential to replace graphite anodes for practical applications in the future.
Recent Development of Electrolyte Engineering for Sodium Metal Batteries
Authors: Ji Yingying , Li Jiabao , Li Jinliang
Published: October 2022

Intermittent renewable energy requires a powerful energy storage system to smoothen the relationship between power generation and power consumption. Due to the rapidly rising price of Li resources, the development of Li-ion batteries (LIBs) has been severely limited. Therefore, developing high-efficiency and low-cost Na-ion batteries has become an alternative to energy storage systems. The high potential plateau of most anode materials urges the exploration of the ultimate anode, the Na metal anode. However, three big dilemmas regarding Na metal anodes, including the formation of Na dendrites, the formation of dead Na, and the continuous appearance of bare Na lead to the degradation of the performance of Na metal batteries (NMBs). In this review, we mainly summarize the recent progress to address these dilemmas for NMBs by electrolyte optimization. We firstly discuss the liquid electrolyte progresses to improve the Na metal anode’s electrochemical performance by solvent chemistry, salt chemistry, and additive. In addition, considering the ultimate goal of NMBs is solid-state batteries, we also discuss the recent progress of polymer electrolytes and all-solid-state electrolytes for Na metal anodes and summarize the enhancement of Na-ion transport mechanisms and interface engineering mechanisms of different solid-state electrolytes. Furthermore, the critical challenges and new perspectives of NMBs using electrolyte optimization are also emphasized. We believe that our review will provide insight to conduct more comprehensive and effective electrolyte engineering for high-performance NMBs.