bluuebunny/crossref_metadata_2025 huggingface dataset:
Two Centuries of Drought History in the Center of Chihuahua, Mexico
Authors: Martínez-Sifuentes Aldo Rafael , Villanueva-Díaz José , Estrada-Ávalos Juan , Trucíos-Caciano Ramón , Carlón-Allende Teodoro , Castruita-Esparza Luis Ubaldo
Published: June 2022

Droughts are a climatic phenomenon with local, regional, and large-scale repercussions. Historical knowledge of droughts generated by modeled data allows the development of more accurate climate reconstructions to propose better approaches for the management of hydric resources. The objective of this research was to evaluate the association of precipitation and temperature with data from the NLDAS-002 to develop a reconstruction of droughts in the center of Chihuahua, Mexico using the SPEI from tree rings. We also identified the influence of ocean–atmospheric phenomena on the reconstructed drought index. The best association among chronologies was obtained with the earlywood band and accumulated seasonal precipitation from November of the previous year to June of the current year (r = 0.82, p < 0.05) and for temperature from January to July (r = −0.81, p < 0.05). The reconstructed drought index extended from 1775 to 2017 (243 years), where seven extreme drought events were identified. We found significant correlations between the reconstructed Standardized Precipitation Evapotranspiration Index and the Pacific Decadal Oscillation (r = 0.46, p < 0.05), Atlantic Multidecadal Oscillation (r = −0.34, p < 0.05), Multivariate El Niño Southern Oscillation Index (r = 0.29, p < 0.05), and Southern Oscillation Index (r = −0.22, p < 0.05). The historical reconstruction of hydroclimatology in the center of Chihuahua is important for planning a long-term assessment and for the management of water resources shared by Mexico and the United States.
Life on the Edge: A Powerful Tsunami Overwhelmed Indian Ocean Mangroves One Millennium Ago
Authors: Decker Valeska , Gee Carole T. , Schucht Pia J. , Lindauer Susanne , Hoffmann Gösta
Published: June 2022

In this paper, we demonstrate how subfossil mangrove wood can be used to elucidate the timing of past tsunami events. Although tsunamis generated by submarine earthquakes along the Makran subduction zone in the Arabian Sea are not unusual, rigorous age documentation is generally lacking. The best known is the only instrument-recorded tsunami, which affected the coastlines of Iran, Pakistan, India, and Oman in November 1945. Eyewitness accounts of the effect along the Oman coastline assert that this tsunami was not destructive. However, a 25-cm-thick shell layer in the lagoon adjacent to the city of Sur was attributed to the 1945 tsunami, although dating of the shell deposit proved difficult, and the radiocarbon dates of mollusk shells were regarded as unreliable. Here, we reinterpret the age of this tsunamigenic layer based on the new discovery of parallel-oriented woody axes in the sedimentological context of the tsunami shell layer in the Sur lagoon. The woody axes were analyzed anatomically and identified as pertaining to the gray mangrove Avicennia. Radiocarbon dating of the wood (905–722 cal BP), along with sedimentological investigations, suggests that the deposition of the woody axes should be attributed to an older tsunami event that occurred ca. 1000 years ago, which has been documented at other locations along the Arabian Sea coastline. From this, we conclude that mangroves grew in this lagoon at that time. Very little is known about ancient mangrove distribution in this region and, so far, no records have been provided for this time window at this site. We also deduce that the tsunami event that occurred one millennium ago must have been substantially more severe than the one in 1945. More accurate dating of tsunamigenic events will aid in calculating the recurrence intervals and magnitude of tsunamis generated along the Makran subduction zone.
Potential Influence of Age and Diabetes Mellitus Type 1 on MSH2 (MutS homolog 2) Expression in a Rat Kidney Tissue
Authors: Babić Paško , Filipović Natalija , Hamzić Lejla Ferhatović , Puljak Livia , Vukojević Katarina , Benzon Benjamin
Published: June 2022

Background: Homeostasis of proliferating tissues is strongly dependent on intact DNA. Both neoplastic and non-neoplastic diseases have been associated with MSH2 (MutS homolog 2, a mismatch repair protein) deficiency. In this study, we examined how age and diabetes mellitus influence the expression of MSH2 in the kidney. Methods: To study the effect of age, three groups of healthy rats were formed: 2 months, 8 months, and 14 months old. Two groups of diabetic rats were formed: 8 months old and 14 months old. Expression of MSH2 in the kidney was studied by quantifying immunofluorescent staining. Results: Age was identified as the main factor that influences MSH2 expression in kidneys. The effect of age followed parabolic dynamics, with peak expression at 8 months of age and similar levels at 2 and 14 months. Diabetes had an age-dependent effect, which manifested as the increase of MSH2 expression in 14-month-old diabetic rats in comparison to healthy animals. Conclusions: Age influences MSH2 expression in the kidney more than diabetes mellitus. Since ageing is a risk factor for kidney neoplasia, downregulation of MSH2 in older rats might represent one of the pro-oncogenic mechanisms of ageing at a molecular level.
Teacher Support Matters: The Effect of Self-Control Demands on Safety Behavior of Vocational High School Students in China
Authors: Yuan Xiao , Li Yongjuan , Xu Yaoshan , Yang Huifang
Published: June 2022

The safety behavior of vocational school students is worth noting. The current study is aimed to examine the effect of self-control demands on safety behavior. Drawing on the Self-Control Resource Model, we predict that self-control demands have a negative effect on safety behavior through ego depletion and perceived teacher support moderates the link among self-control demands, ego depletion, and safety behavior. A two-wave survey was conducted and 285 vocational students participated in our study. Mediation and moderated mediation modeling analyses were carried out. Results showed that ego depletion fully mediated the link between self-control demands and safety behavior. Moreover, perceived teacher support moderated the relationship between self-control demands, ego depletion and safety behavior; for students who perceived high levels of teacher support, the negative effect of self-control demands on safety behavior via ego depletion was insignificant, while for students who perceived low levels of teacher support, their negative effect was significant. The present study clarifies the effects of self-control demands on safety behavior through the resource depletion process and highlights the importance of teacher support in buffering the negative effect of self-control demands on workplace safety. Enhancing safety management, engaging in a resource recovery activity, and providing teacher support training are effective ways to maintain high levels of workplace safety.
Spatiotemporal Differentiation and Balance Pattern of Ecosystem Service Supply and Demand in the Yangtze River Economic Belt
Authors: Zhao Chong , Xiao Pengnan , Qian Peng , Xu Jie , Yang Lin , Wu Yixiao
Published: June 2022

Analyzing the supply and demand of ecosystem services and the regional balance pattern is an important basis for improving the ecological management level. Taking the Yangtze River economic belt as the study area, the spatiotemporal characteristics and balance pattern of ecosystem service supply and demand are quantitatively revealed based on equivalent factors, supply and demand balance modeling and quantile regression. The results show that: (1) the ecosystem services value in the research area experienced a change process of “increase–decrease–increase” from 2000 to 2020. The ecological service value of cultivated land and grassland presented a continuous decline, with decreases of 20.446 billion and 4.53 billion yuan, respectively, in the past 20 years, with reduction rates of −4.82% and −3.98%, respectively. (2) The demand for ecosystem services showed an unbalanced and phased growth trend. The total demand for ecosystem services showed heterogeneity and agglomeration effects in space. High demand and higher demand areas are mainly distributed in the regions with relatively developed population and economy, including Yangtze River Delta urban agglomeration, “Changsha–Zhuzhou–Xiangtan” urban agglomeration, Poyang Lake Plain, Jianghan Plain and Chengdu Plain. (3) The overall pattern of the supply–demand balance of ecosystem services has changed little; however, there have also been significant changes in certain areas in individual years.
Editorial on Special Issue “Geo-Information Technology and Its Applications”
Authors: Wu Weicheng , Liu Yalan , Hu Mingxing
Published: June 2022

Geo-information technology plays a critical role in urban planning and management, land resource quantification, natural disaster risk and damage assessment, smart city development, land cover change modeling and touristic flow management. In particular, the development of big data mining and machine learning techniques (including deep learning) in recent years has expanded the potential applications of geo-information technology and promoted innovation in approaches to mining in different fields. In this context, the International Conference on Geo-Information Technology and its Applications (ICGITA 2019) was held in Nanchang, Jiangxi, China, 11–13 October 2019, co-organized by the Key Laboratory of Digital Land and Resources, East China University of Technology, the Institute of Remote Sensing and Digital Earth (RADI) of the Chinese Academy of Sciences (CAS), which was renamed in 2017 the Aerospace Information Research Institute (AIR), CAS, and the Institute of Space and Earth Information Science of the Chinese University of Hong Kong. The outstanding papers presented at this event and some other original articles were collected and published in this Special Issue “Geo-Information Technology and Its Applications” in the International Journal of Geo-Information. This Special Issue consists of 14 high-quality and innovative articles that explore and discuss the typical applications of geo-information technology in the above-mentioned domains.
Lucilia sericata (Diptera: Calliphoridae) as Agent of Myiasis in a Goose in Italy and a Review of Myiasis by This Species in Birds
Authors: Pezzi Marco , Krčmar Stjepan , Mendicino Federica , Carlomagno Francesco , Bonelli Domenico , Scapoli Chiara , Chicca Milvia , Leis Marilena , Bonacci Teresa
Published: June 2022

Myiasis is a type of parasitosis by larvae of Diptera that may affect vertebrates, including wild and domestic birds. Traumatic myiasis was discovered in a domestic goose, Anser anser domesticus L. (Anseriformes: Anatidae), in June 2020 in a rural area of the region Calabria (Southern Italy). The myiasis was caused by Lucilia sericata (Meigen) (Diptera: Calliphoridae). In Italy, this was the first case of myiasis by L. sericata ever described in a bird. It was also the first case of myiasis detected in a goose in Italy. The description of the case is integrated by a discussion on nonhematophagous dipteran larvae causing myiasis in birds and by an updated and detailed review of literature cases of myiasis by L. sericata in birds reported worldwide, useful for monitoring and management of dipteran species of medical and veterinary interest.
Electrodiagnostic Testing and Nerve Ultrasound of the Carpal Tunnel in Patients with Type 2 Diabetes
Authors: Heiling Bianka , Wiedfeld Leonie I. E. E. , Müller Nicolle , Kobler Niklas J. , Grimm Alexander , Kloos Christof , Axer Hubertus
Published: June 2022

In diabetic patients, controversies still exist about the validity of electrodiagnostic and nerve ultrasound diagnosis for carpal tunnel syndrome (CTS). We analyzed 69 patients with type 2 diabetes. Nerve conduction studies and peripheral nerve ultrasound of the median nerve over the carpal tunnel were performed. CTS symptoms were assessed using the Boston Carpal Tunnel Questionnaire. Polyneuropathy was assessed using the Neuropathy Symptom Score and the Neuropathy Disability Score. Although 19 patients reported predominantly mild CTS symptoms, 37 patients met the electrophysiological diagnosis criteria for CTS, and six patients were classified as severe or extremely severe. The sonographic cross-sectional area (CSA) of the median nerve at the wrist was larger than 12 mm2 in 45 patients (65.2%), and the wrist-to-forearm-ratio was larger than 1.4 in 61 patients (88.4%). Receiver operating characteristic analysis showed that neither the distal motor latency, the median nerve CSA, nor the wrist-to-forearm-ratio could distinguish between patients with and without CTS symptoms. Diagnosis of CTS in diabetic patients should primarily be based upon typical clinical symptoms and signs. Results of electrodiagnostic testing and nerve ultrasound have to be interpreted with caution and additional factors have to be considered especially polyneuropathy, but also body mass index and hyperglycemia.
Calibration and Verification of a Hydrodynamic Model for a Narrow Estuary Receiving Submarine Groundwater Discharges
Authors: Chen XinJian
Published: June 2022

This paper presents calibration and verification of the laterally averaged model for estuaries (LAMFE) for the Chassahowitzka River, a spring-fed estuary located on the Gulf coast of central Florida, USA. The river is a narrow and complex riverine system that receives submarine groundwater discharges (SGDs), which are difficult to measure. This study tried to make a reasonable estimate of some unquantified or missing SGD data with a trial-and-error approach in the model calibration process. The model was successfully calibrated against measured real-time data of water level, salinity, and temperature at three locations within the simulation domain from November 2012 to December 2015, before it was verified for the period from January 2016 to March 2017. Skill assessment of the model performance included visual comparisons and statistical quantifications of the difference between measured real-time data and model results. Both have shown that the LAMFE model performs well in simulating hydrodynamics, salinity transport, and thermal dynamics in the estuary. The good agreement of model results with field data suggests that the estimation of unquantified or missing SGDs in the spring-fed estuary is reasonable.
Analysis of Urban Resilience in Water Network Cities Based on Scale-Density-Morphology-Function (SDMF) Framework: A Case Study of Nanchang City, China
Authors: Feng Xinghua , Tang Yan , Bi Manyu , Xiao Zeping , Zhong Yexi
Published: June 2022

In the face of increasing disturbance factors, resilience has become an important criterion for measuring the sustainable development of cities. Quantitatively describing the development process of urban resilience and identifying key areas and important dimensions of urban resilience are of scientific significance for understanding the evolutionary law of urban resilience, guiding regional risk prevention, and building an environment for urban resilience development. For this study, taking Nanchang City as a case study and dividing the natural water network groups, the resilience index system was constructed from scale, density, morphology, and function by drawing on the theory of landscape ecology on the basis of considering the internal relationship between urban development attributes and disturbance factors. On this basis, the study focuses on the evolution process and development differences of resilience in various dimensions from the water network groups and quantitatively describes the coordinated development status and adaptive phase characteristics of urban resilience. This study not only enriches the research scale and perspective of urban resilience but also provides specific spatial guidance for formulating resilient urban planning and promoting sustainable urban development.
Calculating Column Separation in Liquid Pipelines Using a 1D-CFD Coupled Model
Authors: Khani David , Lim Yeo Howe , Malekpour Ahmad
Published: June 2022

This paper proposes a coupled 1D-CFD model for calculating column separation in liquid pipelines. ANSYS Fluent is utilized to calculate two-phase flow analysis. Method of Characteristics and Discrete Gas Cavity Model (DGCM) are both employed to conduct 1D transient analysis. The results show that the proposed model, with both 2D and 3D CFD analysis, captures the transient responses of the system that have nearly identical accuracy and are both consistent with the results of a physical experiment. The results of a pure CFD analysis are employed to evaluate the performance of the proposed model in capturing the shape of the vapor cavity. The comparison shows that the results are generally consistent. However, the vapor cavity in the pure CFD model is established and grown on top of a film of liquid, while the cavity in some places fills the whole pipe cross-section in the proposed model. In addition, the results obtained from using Modified Two-Component Pressure Approach (MTPA), an open-channel based model proposed by the authors, also confirm the results obtained from the pure CFD analysis. Some minor discrepancies are found, which may be attributed to the uniform velocity distribution considered at the interface between 1D and CFD zones.
Classification of Alzheimer’s Disease Based on Core-Large Scale Brain Network Using Multilayer Extreme Learning Machine
Authors: Lama Ramesh Kumar , Kim Ji-In , Kwon Goo-Rak
Published: June 2022

Various studies suggest that the network deficit in default network mode (DMN) is prevalent in Alzheimer’s disease (AD) and mild cognitive impairment (MCI). Besides DMN, some studies reveal that network alteration occurs in salience network motor networks and large scale network. In this study we performed classification of AD and MCI from healthy control considering the network alterations in large scale network and DMN. Thus, we constructed the brain network from functional magnetic resonance (fMR) images. Pearson’s correlation-based functional connectivity was used to construct the brain network. Graph features of the brain network were converted to feature vectors using Node2vec graph-embedding technique. Two classifiers, single layered extreme learning and multilayered extreme learning machine, were used for the classification together with feature selection approaches. We performed the classification test on the brain network of different sizes including the large scale brain network, the whole brain network and the combined brain network. Experimental results showed that the least absolute shrinkage and selection operator (LASSO) feature selection method generates better classification accuracy on large network size, and that feature selection with adaptive structure learning (FSAL) feature selection technique generates better classification accuracy on small network size.
Team Control Problem in Virtual Ellipsoid and Its Numerical Simulations
Authors: Dang Zhiqing , Dai Zhaopeng , Yu Yang , Zhang Long , Su Ang , You Zhihang , Gao Hongwei
Published: June 2022

There is tremendous interest in designing feedback strategy control for clusters in modern control theory. We propose a novel numerical solution to target team control problems by using the Hamilton formalism methods. In order to ensure the smooth wireless information exchange, all members of the team are located in a virtual ellipsoidal container during the whole movement process. An ellipsoidal container tube is constructed as the external state constraint of the team. The corresponding value function is then formulated based on collision avoidance conditions and energy constraints in the process of the team motion. Time-dependent partial differential equations are formulated based on Hamilton formalism, which have been solved numerically by using the traditional finite difference method (FDM). The objective of the presented method is to obtain optimal control and motion trajectory of the cluster at each moment. Lastly, we conduct a simulation study of unmanned aerial vehicles (UAVs) to demonstrate the performance of the proposed method.
On the Boundary Value Problem of Nonlinear Fractional Integro-Differential Equations
Authors: Li Chenkuan , Saadati Reza , Srivastava Rekha , Beaudin Joshua
Published: June 2022

Using Banach’s contractive principle and the Laray–Schauder fixed point theorem, we study the uniqueness and existence of solutions to a nonlinear two-term fractional integro-differential equation with the boundary condition based on Babenko’s approach and the Mittag–Leffler function. The current work also corrects major errors in the published paper dealing with a one-term differential equation. Furthermore, we provide examples to illustrate the application of our main theorems.
A New Kantorovich-Type Rational Operator and Inequalities for Its Approximation
Authors: Özkan Esma Yıldız
Published: June 2022

We introduce a new Kantorovich-type rational operator. We investigate inequalities estimating its rates of convergence in view of the modulus of continuity and the Lipschitz-type functions. Moreover, we present graphical comparisons exemplifying concretely its better approximation for a certain function. The results of the paper are crucial by means of possessing at least better approximation results than an existing Kantorovich-type rational function.
Reduced Basis Approximation for a Spatial Lotka-Volterra Model
Authors: Rashkov Peter
Published: June 2022

We construct a reduced basis approximation for the solution to a system of nonlinear partial differential equations describing the temporal evolution of two populations following the Lotka-Volterra law. The first population’s carrying capacity contains a free parameter varying in a compact set. The reduced basis is constructed by two approaches: a proper orthogonal decomposition of a collection of solution snapshots and a greedy algorithm using an a posteriori error estimator.
Balancing Cost and Demand in Electricity Access Projects: Case Studies in Ecuador, Mexico and Peru
Authors: Galleguillos-Pozo Rosa , Domenech Bruno , Ferrer-Martí Laia , Pastor Rafael
Published: June 2022

Rural areas in developing countries have the highest concentrations of unelectrified communities. There is a clear link between electricity consumption and the Human Development Index, as highlighted by the 7th Development Goal of the United Nations. Estimating the energy needs of the previously nonelectrified population is imprecise when designing rural electrification projects. Indeed, daily energy demand and peak power assessments are complex, since these values must be valid over the project’s lifetime, while tight budgets do not allow for the systems to be oversized. In order to assist project promoters, this study proposes a fuzzy mixed integer linear programming model (FMILP) for the design of wind–PV rural electrification systems including uncertainty in the demand requirements. Two different FMILP approaches were developed that maximized the minimum or the average satisfaction of the users. Next, the FMILP approaches were applied to six Latin American communities from three countries. Compared with the deterministic MILP (where the energy and peak power needs are considered as specific values), the FMILP results achieved a better balance between the project cost and the users’ satisfaction regarding the energy and peak power supplied. Regarding the two approaches, maximizing the users’ minimum satisfaction obtained globally better solutions.
Robust Variable Selection for Single-Index Varying-Coefficient Model with Missing Data in Covariates
Authors: Song Yunquan , Liu Yaqi , Su Hang
Published: June 2022

As applied sciences grow by leaps and bounds, semiparametric regression analyses have broad applications in various fields, such as engineering, finance, medicine, and public health. Single-index varying-coefficient model is a common class of semiparametric models due to its flexibility and ease of interpretation. The standard single-index varying-coefficient regression models consist mainly of parametric regression and semiparametric regression, which assume that all covariates can be observed. The assumptions are relaxed by taking the models with missing covariates into consideration. To eliminate the possibility of bias due to missing data, we propose a probability weighted objective function. In this paper, we investigate the robust variable selection for a single-index varying-coefficient model with missing covariates. Using parametric and nonparametric estimates of the likelihood of observations with fully observed covariates, we examine the estimators for estimating the likelihood of observations. For variable selection, we use a weighted objective function penalized by a non-convex SCAD. Theoretical challenges include the treatment of missing data and a single-index varying-coefficient model that uses both the non-smooth loss function and the non-convex penalty function. We provide Monte Carlo simulations to evaluate the performance of our approach.
Adaptive Color Image Encryption Scheme Based on Multiple Distinct Chaotic Maps and DNA Computing
Authors: Mansoor Shaista , Sarosh Parsa , Parah Shabir A. , Ullah Habib , Hijji Mohammad , Muhammad Khan
Published: June 2022

In this paper, we propose an adaptive encryption scheme for color images using Multiple Distinct Chaotic Maps (MDCM) and DNA computing. We have chosen three distinct chaotic maps, including a 2D-Henon map, a Tent map, and a Logistic map, to separately encrypt the red, green, and blue channels of the original image. The proposed scheme adaptively modifies the parameters of the maps, utilizing various statistical characteristics such as mean, variance, and median of the image to be encrypted. Thus, whenever there is a change in the plain image, the secret keys also change. This makes the proposed scheme robust against the chosen and known plaintext attacks. DNA encoding has also been used to add another layer of security. The experimental analysis of the proposed scheme shows that the average value of entropy is approximately eight, the Number of Pixels Change Rate (NPCR) and Unified Average Changing Intensity (UACI) are 99.61% and 33%, respectively, and correlation coefficients close to zero, making the scheme not only reliable but also resilient against many attacks. Moreover, the use of low-dimensional maps reduces the computational costs of the scheme to a large extent.
Supervised Classification of Healthcare Text Data Based on Context-Defined Categories
Authors: Bolívar Sergio , Nieto-Reyes Alicia , Rogers Heather L.
Published: June 2022

Achieving a good success rate in supervised classification analysis of a text dataset, where the relationship between the text and its label can be extracted from the context, but not from isolated words in the text, is still an important challenge facing the fields of statistics and machine learning. For this purpose, we present a novel mathematical framework. We then conduct a comparative study between established classification methods for the case where the relationship between the text and the corresponding label is clearly depicted by specific words in the text. In particular, we use logistic LASSO, artificial neural networks, support vector machines, and decision-tree-like procedures. This methodology is applied to a real case study involving mapping Consolidated Framework for Implementation and Research (CFIR) constructs to health-related text data and achieves a prediction success rate of over 80% when just the first 55% of the text, or more, is used for training and the remaining for testing. The results indicate that the methodology can be useful to accelerate the CFIR coding process.
Translocating Peptides of Biomedical Interest Obtained from the Spike (S) Glycoprotein of the SARS-CoV-2
Authors: Henao Maria C. , Ocasion Camila , Puentes Paola Ruiz , González-Melo Cristina , Quezada Valentina , Cifuentes Javier , Yepes Arnovis , Burgos Juan C. , Cruz Juan C. , Reyes Luis H.
Published: June 2022

At the beginning of 2020, the pandemic caused by the SARS-CoV-2 virus led to the fast sequencing of its genome to facilitate molecular engineering strategies to control the pathogen’s spread. The spike (S) glycoprotein has been identified as the leading therapeutic agent due to its role in localizing the ACE2 receptor in the host’s pulmonary cell membrane, binding, and eventually infecting the cells. Due to the difficulty of delivering bioactive molecules to the intracellular space, we hypothesized that the S protein could serve as a source of membrane translocating peptides. AHB-1, AHB-2, and AHB-3 peptides were identified and analyzed on a membrane model of DPPC (dipalmitoylphosphatidylcholine) using molecular dynamics (MD) simulations. An umbrella sampling approach was used to quantify the energy barrier necessary to cross the boundary (13.2 to 34.9 kcal/mol), and a flat-bottom pulling helped to gain a deeper understanding of the membrane’s permeation dynamics. Our studies revealed that the novel peptide AHB-1 exhibited comparable penetration potential of already known potent cell-penetrating peptides (CPPs) such as TP2, Buforin II, and Frenatin 2.3s. Results were confirmed by in vitro analysis of the peptides conjugated to chitosan nanoparticles, demonstrating its ability to reach the cytosol and escape endosomes, while maintaining high biocompatibility levels according to standardized assays.
A New Method Based on a Zero Gap Electrolysis Cell for Producing Bleach: Concept Validation
Authors: Belhadj Ammar Rihab , Ounissi Takoua , Baklouti Lassaad , Larchet Christian , Dammak Lasâad , Mofakhami Arthur , Selmane Belhadj Hmida Emna
Published: June 2022

Commercial bleach (3.6 wt% active chlorine) is prepared by diluting highly concentrated industrial solutions of sodium hypochlorite (about 13 wt% active chlorine) obtained mainly by bubbling chlorine gas into dilute caustic soda. The chlorine and soda used are often obtained by electrolyzing a sodium chloride solution in two-compartment cells (chlorine-soda processes). On a smaller scale, small units used for swimming pool water treatment, for example, allow the production of low-concentration bleach (0.3 to 1 wt% active chlorine) by use of a direct electrolysis of sodium chloride brine. The oxidation and degradation reaction of hypochlorite ion (ClO−) at the anode is the major limiting element of this two-compartment process. In this study, we have developed a new process to obtain higher levels of active chlorine up to 3.6%, or 12° chlorometric degree. For this purpose, we tested a device consisting of a zero-gap electrolysis cell, with three compartments separated by a pair of membranes that can be porous or ion-exchange. The idea is to generate in the anode compartment hypochlorous acid (HClO) at high levels by continuously adjusting its pH to a value between 4.5 and 5.5. In the cathodic compartment, caustic soda is obtained, while the central compartment is supplied with brine. The hypochlorous acid solution is then neutralized with a concentrated solution of NaOH to obtain bleach. In this work, we studied several membrane couples that allowed us to optimize the operating conditions and to obtain bleach with contents close to 1.8 wt% of active chlorine. The results obtained according to the properties of the membranes, their durability, and the imposed electrochemical conditions were discussed.
Determination of Compressibility and Relaxation Behavior of Yeast Cell Sediments by Analytical Centrifugation and Comparison with Deposit Formation on Membrane Surfaces
Authors: Weinberger Maria E. , Kulozik Ulrich
Published: June 2022

Separation of cells from produced biomolecules is a challenging task in many biotechnological downstream operations due to deposit formation of the retained cells, affecting permeation of the target product. Compression and relaxation behavior of cell deposits formed during filtration are important factors affecting operational performance. The determination of these factors by flux or pressure stepping experiments is time- and labor-intensive. In this work, we propose a screening method by analytical centrifugation, which is capable of detecting small differences in compression and relaxation behavior induced by milieu changes, using a model system comprised of washed and unwashed yeast cells in the presence or absence of bovine serum albumin as a model target protein. The main effects observed were firstly the impact of pH value, affecting interaction of bovine serum albumin and yeast cells especially close to the isoelectric point, and secondly the effect of washing the yeast cells prior to analysis, where the presence of extracellular polymeric substances led to higher compressibility of the deposited cells. By comparing and validating the obtained results with dead-end filtration trials, the stabilizing role of bovine serum albumin in deposits formed at low pH values due to interactions with the yeast cells was underlined.
Preparation of Alumina-Sphere-Supported Potassium Chabazite Zeolite Membrane with Excellent Potassium Extraction Performance at Room Temperature
Authors: Ouyang Jie , Wei Heng , Hou Jin
Published: June 2022

In this paper, a potassium chabazite (KCHA) zeolite membrane was prepared by coating KCHA zeolite on the surface of a porous alumina sphere. The performance of the KCHA zeolite membrane in extracting potassium from seawater and sea bittern at room temperature was studied in detail. The XRD results show that the prepared KCHA zeolite was a KCHA membrane. The EDS test indicated that the potassium content of the KCHA zeolite membrane reached a value of 18.33 wt.%. The morphology of the KCHA zeolite grown on the surface of the alumina sphere was similar to a sphere, and it had good symmetry. The potassium ion-exchange capacities of the KCHA zeolite membrane reached 32 mg/g in seawater and 77 mg/g in sea bittern at room temperature. Ion exchange between the ammonium ions and potassium ions in the KCHA zeolite membrane could be completed in a short time at room temperature. The KCHA zeolite membrane was proven to have good reusability in seawater and sea bittern. The selective ion-exchange mechanism of the KCHA zeolite membrane was controlled by a specific K+ ion memory.
Thermo-Statistical Effects of Inclusions on Vesicles: Division into Multispheres and Polyhedral Deformation
Authors: Natsume Yuno
Published: June 2022

The construction of simple cellular models has attracted much attention as a way to explore the origin of life or elucidate the mechanisms of cell division. In the absence of complex regulatory systems, some bacteria spontaneously divide through thermostatistically elucidated mechanisms, and incorporating these simple physical principles could help to construct primitive or artificial cells. Because thermodynamic interactions play an essential role in such mechanisms, this review discusses the thermodynamic aspects of spontaneous division models of vesicles that contain a high density of inclusions, with their membrane serving as a boundary. Vesicles with highly dense inclusions are deformed according to the volume-to-area ratio. The phase separation of beads at specific intermediate volume fractions and the associated polyhedral deformation of the membrane are considered in relation to the Alder transition. Current advances in the development of a membrane-growth vesicular model are summarized. The thermostatistical understanding of these mechanisms could become a cornerstone for the construction of vesicular models that display spontaneous cell division.
Pilot-Scale Selective Electrodialysis for the Separation of Chloride and Sulphate from High-Salinity Wastewater
Authors: Li Fuqin , Guo Yanfu , Wang Shaozhou
Published: June 2022

The separation of chloride and sulphate is important for the treatment of high salt wastewater, and monovalent selective electrodialysis (MSED) has advantages in terms of energy consumption and pre-treatment costs compared to nanofiltration salt separation. Most of the research on monovalent anion-selective membranes (MASM) is still on a laboratory scale due to the preparation process, cost, and other reasons. In this study, a low-cost, easy-to-operate modification scheme was used to prepare MASM, which was applied to assemble a pilot-scale electrodialysis device to treat reverse osmosis concentrated water with a salt content of 4% to 5%. The results indicate that the optimum operating conditions for the device are: 250 L/h influent flow rate for the concentration and dilute compartments, 350 L/h influent flow rate for the electrode compartment and a constant voltage of 20 V. The separation effect of the pilot electrodialysis plant at optimal operating conditions was: the Cl− and SO42− transmission rates of 80% and 2.54% respectively, the separation efficiency (S) of 93.85% and the Energy consumption per unit of NaCl (ENaCl) of 0.344 kWh/kg. The analysis of the variation of the three parameters of selective separation performance during electrodialysis indicates that the separation efficiency (S) is a suitable parameter for measuring the selective separation performance of the device compared to the monovalent selectivity coefficient (PSO42−Cl−).
Light Isotope Separation through the Compound Membrane of Graphdiyne
Authors: Poteryaeva Valentina A. , Bubenchikov Michael A. , Bubenchikov Alexey M.
Published: June 2022

The separation of isotopes of one substance is possible within the framework of the quantum mechanical model. The tunneling effect allows atoms and molecules to overcome the potential barrier with a nonzero probability. The membranes of two monoatomic layers enhance the differences in the components’ passage through the membrane, thereby providing a high separation degree of mixtures. The probability of overcoming the potential barrier by particles is found from the solving of the Schrödinger integral equation. Hermite polynomials are used to expand all the terms of the Schrödinger integral equation in a series to get a wave function. A two-layer graphdiyne membrane is used to separate the mixture.
Development and Implementation of Decision Support Systems for Blast Smelting Control in the Conditions of PrJSC “Kamet-Steel”
Authors: Semenov Yurii S. , Shumelchyk Yevhen I. , Horupakha Viktor V. , Semion Igor Y. , Vashchenko Sergii V. , Khudyakov Oleksandr Y. , Chychov Igor V. , Hulina Iryna H. , Zakharov Rostyslav H.
Published: June 2022

This article presents a description of three decision support systems (DSS) in the mode of an adviser to the technological personnel of blast furnaces (BF), which were implemented by the Iron and Steel Institute of Z.I. Nekrasov (Dnipro, Ukraine) or underwent pilot testing as part of the automated control system of the BF shop of PrJSC “Kamet-steel” (Kamianske, Ukraine). The first DSS for managing the thermal state was implemented in 2021; it includes the entire list of information necessary for personnel in a convenient and compact form, generates recommendations in case of technology deviations, and, in the case of incorrect actions by the personnel, signals the need for correct actions. The main recommendations from the DSS are to correct the raceway adiabatic flame temperature, coke consumption when its characteristics are specified in (indicators of strength and abrasion, fractional composition, humidity, ash and sulfur), and ore load change. Using the system allows both reducing the specific coke consumption and preventing unplanned downtime. The second DSS for controlling the distribution of fuel additives over air tuyeres is based on information on thermal loads determined on water-cooled elements of tuyere tools. The main recommendations from the DSS are to adjust the amount of injected pulverized coal fuel on individual tuyeres in order to ensure a uniform distribution of the raceway adiabatic flame temperature around the circumference of the BF and, as a result, the energy efficiency of BF smelting. The third DSS for adjusting the parameters of the charging mode is based on information from the means of controlling the temperatures of the gas flow above the surface of the charge in the BF. The functioning of this DSS is based on determining the reference curves for the distribution of the gas flow along the BF radii, corresponding to the minimum consumption of coke and maximum productivity, and on the search for solutions by direct and iterative optimization methods, which allow one, by adjusting the charging parameters, to ensure a rational distribution of charge materials and gas flow in the BF.
Melting–Dropping Property of Blast Furnace Charge on the Basis of Its Slag Formation Behavior
Authors: Wang Yonghong , Diao Jiang , Xie Bing , Qi Chenglin , Du Ping
Published: June 2022

In order to reveal the melting–dropping property of a charged blast furnace (BF) and the mechanism of its slag formation, such as the temperature interval of slag formation, the pressure drop during the reduction process, and the K value of each sample, the soft melt drop experiment was tested in a large-capacity melting–dropping furnace. The results show that a positive linear relationship exists between the slag melting behavior and the melting–dropping property of the corresponding charge. The results indicate that owing to their poor melting–dropping property, single iron ores are not suitable for BF production and the charging mix can improve slag formation as well as the melting–dropping property when the temperature is increased. Chemical composition is the key factor that will affect slag formation. An excessive amount of lump ore in the charging mix favors the formation of a high-fusion point slag phase such as spinel at low temperatures. The charging mix containing fewer lump ore has high FeO content in the slag, decreasing fluidity at increased temperature. Consequently, the gas path is choked and permeability is reduced.
The Influence of Boron on Microstructural Evolution, Mechanical and Magnetic Behavior of Amorphous Fe91−x(Zr5-Nb4)Bx Melt-Spun Alloys
Authors: Zamora Jonathan , Betancourt Israel , García Hinojosa José Alejandro
Published: June 2022

In this work, we report a systematic study on the microstructure evolution of rapid solidified Fe91−xZr5Nb4Bx alloys (x = 10, 15, 20, 25, 30 at%) under melt-spinning conditions. Mechanical and magnetic properties are also evaluated. X-ray diffraction patterns indicate that the microstructure across the compositional series consists of an amorphous matrix with partial crystallization when boron concentration is increased. These features were identified by transmission electron microscopy (TEM). The radial distribution function (RDF) affords to resolve the nearest-neighbor configuration. The tensile and microhardness properties were measured to correlate the microstructural evolution with boron content. On the other hand, the magnetic properties of these alloy series were determined by vibrating sample magnetometry (VSM); the saturation magnetization and Curie temperature showed an increasing tendency when increasing the boron content, reaching values up to 110 Am2kg−1 and 465 K, respectively. In addition to the aforementioned, the coercive field remained constant. All these magnetic properties were correlated with the microstructure features observed by XRD, RDF and TEM.
Current Status and Outlook of Temporary Implants (Magnesium/Zinc) in Cardiovascular Applications
Authors: Prasadh Somasundaram , Raguraman Sreenivas , Wong Raymond , Gupta Manoj
Published: June 2022

Medical application materials must meet multiple requirements, and the designed material must mimic the structure, shape. and support the formation of the replacing tissue. Magnesium (Mg) and Zinc alloys (Zn), as a “smart” biodegradable material and as “the green engineering material in the 21st century”, have become an outstanding implant material due to their natural degradability, smart biocompatibility, and desirable mechanical properties. Magnesium and Zinc are recognized as the next generation of cardiovascular stents and bioresorbable scaffolds. At the same time, improving the properties and corrosion resistance of these alloys is an urgent challenge. particularly to promote the application of magnesium alloys. A relatively fast deterioration rate of magnesium-based materials generally results in premature mechanical integrity compromise and local hydrogen build-up, resulting in restricted applicability. This review article aims to give a comprehensive comparison between Zn-based alloys and Mg-based alloys, focusing primarily on degradation and biocompatibility for cardiovascular applications. The recent clinical trials using these biodegradable metals have also been addressed.
Simplified Evaluation of Plastic Rotation Demand for Existing EBFs Equipped with Short Links
Authors: Montuori Rosario , Nastri Elide , Piluso Vincenzo , Todisco Paolo
Published: June 2022

The seismic events that occurred in the last decades have highlighted the importance of a correct design of the structures in seismic areas and the seismic inadequacy of a large part of the built heritage. Modern codes are still lacking in terms of prescriptions for the evaluation of the seismic performance of existing buildings. The present work proposes a simplified method for the evaluation of the demand in terms of plastic rotation for short links of steel Eccentrically Braced Frames (EBFs). A relationship for the evaluation of the demand, that exploits elastic analysis and rigid-plastic analysis extended to the second-order effects, is proposed. The calibration of this relationship was carried out on 420 EBFs equipped with short links designed according to three different approaches. The 420 frames have been also used to analyze the behavior in the plastic range of EBF type structures equipped with short links. The study also provides an extensive analysis on the influence of plastic redistribution capacity on the demand in terms of plastic rotations of links, corresponding to the achievement of the maximum bearing capacity. The obtained relation can be exploited as an assessment tool by comparing the demand with the link capacity. Moreover, from a performance-based design point of view, the same can be used for predicting the required ultimate plastic rotation as a function of the plastic redistribution capacity of the structure.
In Vitro Bio-Testing Comparative Analysis of NiTi Porous Alloys Modified by Heat Treatment
Authors: Marchenko Ekaterina , Baigonakova Gulsharat , Dubovikov Kirill , Kokorev Oleg , Yasenchuk Yuri , Vorozhtsov Alexander
Published: June 2022

The present work is aimed at studying the surface cytocompatibility of porous NiTi obtained by self-propagating high temperature synthesis (SHS), and then annealed in air at 500–1000 °C. Using cytotoxicity tests in vitro, it was found that the cells had attached to the oxidized surface in the amount sufficient for their growth and proliferation on the substrate. The surfaces of the annealed samples and the control sample were studied by XRD, SEM and optical microscopy. It was found that there is a correlation between cell hemolysis and nickel-containing phases on the surface. Thus, annealing at 500–700 °C worsens cytocompatibility compared to the control sample, but annealing at 800–1000 °C improves cytocompatibility.
mGWAS-Explorer: Linking SNPs, Genes, Metabolites, and Diseases for Functional Insights
Authors: Chang Le , Zhou Guangyan , Ou Huiting , Xia Jianguo
Published: June 2022

Tens of thousands of single-nucleotide polymorphisms (SNPs) have been identified to be significantly associated with metabolite abundance in over 65 genome-wide association studies with metabolomics (mGWAS) to date. Obtaining mechanistic or functional insights from these associations for translational applications has become a key research area in the mGWAS community. Here, we introduce mGWAS-Explorer, a user-friendly web-based platform to help connect SNPs, metabolites, genes, and their known disease associations via powerful network visual analytics. The application of the mGWAS-Explorer was demonstrated using a COVID-19 and a type 2 diabetes case studies.