bluuebunny/crossref_metadata_2025 huggingface dataset:
30 Years of Vicente Rives’ Contribution to Hydrotalcites, Synthesis, Characterization, Applications, and Innovation
Authors: Trujillano Raquel
Published: August 2022

Hydrotalcite is the name of a mineral discovered in Sweden in 1842 whose formula is Mg6Al2(OH)16CO3·4H2O and presents a layered crystal structure that consists of positively charged hydroxide layers neutralized by interlayer anions as carbonate, also containing water molecules. The ease of their synthesis and the possibility of incorporating other layer cations and interlayer anions have made this type of layered double hydroxides (LDH) a group of very interesting materials for industry. In addition to LDH and due to the name of the most representative mineral, this group of compounds is commonly called hydrotalcite-like materials, or simply hydrotalcites. Another way of referring to them is as anionic clays because of their layered structure but, unlike classical clays, their layers are positive and their interlayers are anionic. The main fields of application of these solids comprise catalysis, catalyst support, anion scavengers, polymer stabilizers, drug carriers, or adsorbents. This paper briefly summarizes some of the work carried out by Professor Rives over more than thirty years, focused, among other topics, on the study of the synthesis, characterization, and applications of hydrotalcites. This research has led him to train many researchers, to collaborate with research groups around the world and to publish reference papers and books in this field. This contribution, written to be included in the Special Issue “A Themed Issue in Honor of Prof. Dr. Vicente Rives”, edited on the occasion of his retirement, only shows a small part of his scientific research and intends to value and recognize his cleverness and his enormous scientific and human quality.
Climate Risk Mitigation and Adaptation Concerns in Urban Areas: A Systematic Review of the Impact of IPCC Assessment Reports
Authors: Monteiro Ana , Ankrah Johnson , Madureira Helena , Pacheco Maria Oliveira
Published: August 2022

Urban areas continue to be the center of action for many countries due to their contribution to economic development. Many urban areas, through the urbanization process, have become vulnerable to climate risk, thereby making risk mitigation and adaptation essential components in urban planning. The study assessed the impacts of IPCC Assessment Reports (ARs) on academic research on risk mitigation and adaptation concerns in urban areas. The study systematically reviewed literature through searches of the Web of Science and Scopus databases; 852 papers were retrieved and 370 were deemed eligible. The results showed that the East Asia and Pacific, and Europe and Central Asia regions were most interested in IPCC ARs, while Sub-Saharan Africa showed little interest. Several urban concerns, including socio-economic, air quality, extreme temperature, sea level rise/flooding, health, and water supply/drought, were identified. Additionally, studies on negative health outcomes due to extreme temperatures and air pollution did not appear in the first four IPCC ARs. However, significant studies appeared after the launch of the AR5. Here, we must state that climate-related problems of urbanization were known and discussed in scientific papers well before the formation of the IPCC. For instance, the works of Clarke on urban structure and heat mortality and Oke on climatic impacts of urbanization. Though the IPCC ARs show impact, their emphasis on combined mitigation and adaptation policies is limited. This study advocates more combined risk mitigation and adaptation policies in urban areas for increased resilience to climate risk.
Genital Folliculosebaceous Cystic Hamartoma: A Case Report and Concise Review of the Literature
Authors: Daruish Maged , Ibrahim Mona Abdel-Halim
Published: August 2022

Folliculosebaceous cystic hamartoma (FSCH) is an uncommon hamartoma that usually presents on the central face area of adults as an asymptomatic, solitary dome-shaped or pedunculated papule. We report a case of a 35-year-old female who presented with six-months history of skin lesions on her labia majora. Histological findings included cystically dilated hair follicles with branching epithelial strands and interconnecting sebaceous gland consistent with the diagnosis of FSCH. The genital variant of FSCH was first described in 1998 and since then only six cases have been reported in the literature. We aim to increase awareness of this rare presentation due to the significant psychological implications and the risk of misdiagnosis.
Apparent Diffusion Coefficient (ADC) Histogram Analysis in Parotid Gland Tumors: Evaluating a Novel Approach for Differentiation between Benign and Malignant Parotid Lesions Based on Full Histogram Distributions
Authors: Hepp Tobias , Wuest Wolfgang , Heiss Rafael , May Matthias Stefan , Kopp Markus , Wetzl Matthias , Treutlein Christoph , Uder Michael , Wiesmueller Marco
Published: August 2022

The aim of this study was to assess the diagnostic value of ADC distribution curves for differentiation between benign and malignant parotid gland tumors and to compare with mean ADC values. 73 patients with parotid gland tumors underwent head-and-neck MRI on a 1.5 Tesla scanner prior to surgery and histograms of ADC values were extracted. Histopathological results served as a reference standard for further analysis. ADC histograms were evaluated by comparing their similarity to a reference distribution using Chi2-test-statistics. The assumed reference distribution for benign and malignant parotid gland lesions was calculated after pooling the entire ADC data. In addition, mean ADC values were determined. For both methods, we calculated and compared the sensitivity and specificity between benign and malignant parotid gland tumors and three subgroups (pleomorphic adenoma, Warthin tumor, and malignant lesions), respectively. Moreover, we performed cross-validation (CV) techniques to estimate the predictive performance between ADC distributions and mean values. Histopathological results revealed 30 pleomorphic adenomas, 22 Warthin tumors, and 21 malignant tumors. ADC histogram distribution yielded a better specificity for detection of benign parotid gland lesions (ADChistogram: 75.0% vs. ADCmean: 71.2%), but mean ADC values provided a higher sensitivity (ADCmean: 71.4% vs. ADChistogram: 61.9%). The discrepancies are most pronounced in the differentiation between malignant and Warthin tumors (sensitivity ADCmean: 76.2% vs. ADChistogram: 61.9%; specificity ADChistogram: 81.8% vs. ADCmean: 68.2%). Using CV techniques, ADC distribution revealed consistently better accuracy to differentiate benign from malignant lesions (“leave-one-out CV” accuracy ADChistogram: 71.2% vs. ADCmean: 67.1%). ADC histogram analysis using full distribution curves is a promising new approach for differentiation between primary benign and malignant parotid gland tumors, especially with respect to the advantage in predictive performance based on CV techniques.
Comparative Dissemination of Aerosol and Splatter Using Suction Device during Ultrasonic Scaling: A Pilot Study
Authors: Engsomboon Nutthawadee , Pachimsawat Praewpat , Thanathornwong Bhornsawan
Published: August 2022

Objective: This study compared the aerosol and splatter diameter and count numbers produced by a dental mouth prop with a suction holder device and a saliva ejector during ultrasonic scaling in a clinical setting. Methodology: Fluorescein dye was placed in the dental equipment irrigation reservoirs with a mannequin, and an ultrasonic scaler was employed. The procedures were performed three times per device. The upper and bottom board papers were placed on the laboratory platform. All processes used an ultrasonic scaler to generate aerosol and splatter. A dental mouth prop with a suction holder and a saliva ejector were also tested. Photographic analysis was used to examine the fluorescein samples, followed by image processing in Python and assessment of the diameter and count number. For device comparison, statistics were used with an independent t-test. Result: When using the dental mouth prop with a suction holder, the scaler produced aerosol particles that were maintained on the upper board paper (mean ± SD: 1080 ± 662 µm) compared to on the bottom board paper (1230 ± 1020 µm). When the saliva ejector was used, it was found that the diameter of the aerosol on the upper board paper was 900 ± 580 µm, and the diameter on the bottom board paper was 1000 ± 756 µm. Conclusion: There was a significant difference in the aerosol and splatter particle diameter and count number between the dental mouth prop with a suction holder and saliva ejector (p < 0.05). Furthermore, the results revealed that there was a statistically significant difference between the two groups on the upper and bottom board papers.
Assigning Degrees of Stochasticity to Blazar Light Curves in the Radio Band Using Complex Networks
Authors: Acosta-Tripailao Belén , Max-Moerbeck Walter , Pastén Denisse , Moya Pablo S.
Published: August 2022

We focus on characterizing the high-energy emission mechanisms of blazars by analyzing the variability in the radio band of the light curves of more than a thousand sources. We are interested in assigning complexity parameters to these sources, modeling the time series of the light curves with the method of the Horizontal Visibility Graph (HVG), which allows us to obtain properties from degree distributions, such as a characteristic exponent to describe its stochasticity and the Kullback–Leibler Divergence (KLD), presenting a new perspective to the methods commonly used to study Active Galactic Nuclei (AGN). We contrast these parameters with the excess variance, which is an astronomical measurement of variability in light curves; at the same time, we use the spectral classification of the sources. While it is not possible to find significant correlations with the excess variance, the degree distributions extracted from the network are detecting differences related to the spectral classification of blazars. These differences suggest a chaotic behavior in the time series for the BL Lac sources and a correlated stochastic behavior in the time series for the FSRQ sources. Our results show that complex networks may be a valuable alternative tool to study AGNs according to the variability of their energy output.
A Novel Distributed Ledger Technology Structure for Wireless Sensor Networks Based on IOTA Tangle
Authors: Zhang Hongwei , Zaman Marzia , Stacey Brian , Sampalli Srinivas
Published: August 2022

Wireless Sensor Networks (WSNs) consist of many wireless sensor nodes for collecting and sensing information. Distributed Ledger Technologies (DLTs) such as Blockchain allow organizations to store and share data in a decentralized, immutable, and secure way through a network of distributed peer-to-peer users or computers. The application of DLT to the Internet of Things (IoT) can improve the efficiency of information transmission and network security. IOTA Tangle is a DLT developed for IoT to process transactions. WSN is a core technology for IoT, and the two have a lot in common in terms of applications. Many solutions for IoT applications can be implemented with WSNs. However, the sensor nodes in WSNs have limited processing speed, storage capacity, communication bandwidth, and energy consumption capabilities. Therefore, a lightweight solution needs to be designed according to the characteristics of WSNs, rather than directly applying Tangle. The similarities between IoT and WSNs determine that the Tangle can be an essential reference for designing new solutions. In this paper, we propose a new DLT structure based on Tangle named Fishing Net Topology (FNT). The aim is to meet the lightweight requirements of sensor nodes in WSNs. We compared FNT with Tangle in terms of the packet network structure and algorithm and also experimentally analyzed the waste rate in the FNT network. It is concluded that FNT can be used at a reasonable Rate based on the requirement of the WSN applications, and it can significantly reduce the computation while enhancing the security of WSNs. Due to its structural stability and algorithmic simplicity, FNT outperforms Tangle in WSNs.
Evolutionary Multi-Objective Optimization Applied to Industrial Refrigeration Systems for Energy Efficiency
Authors: Nedjah Nadia , de Macedo Mourelle Luiza , Lizarazu Marcelo Silveira Dantas
Published: August 2022

Refrigeration systems based on cooling towers and chillers are widely used equipment in industrial buildings, such as shopping centers, gas and oil refineries and power plants, among many others. Cooling towers are used to recover the heat rejected by the refrigeration system. In this work, the refrigeration is composed of cooling towers dotted with ventilators and compression chillers. The growing environmental concerns and the current scenario of scarce water and energy resources have lead to the adoption of actions to obtain the maximum energy efficiency in such refrigeration equipment. This backs up the application of computational intelligence to optimize the operating conditions of the involved equipment and cooling processes. In this context, we utilize multi-objective optimization algorithms to determine the optimal operational setpoints of the cooling system regarding the cooling towers, its fans and the included chillers. We use evolutionary multi-objective optimization to provide the best trade-offs between two conflicting objectives: maximization of the effectiveness of the cooling towers and minimization of the overall power requirement of the refrigeration system. The optimization process respects the constraints to guarantee the correct and safe operation of the equipment when the evolved solution is implemented. In this work, we apply three evolutionary multi-objective algorithms: Non-dominated Sorting Genetic Algorithm (NSGA-II), Micro-Genetic Algorithm (Micro-GA) and Strength Pareto Evolutionary Algorithm (SPEA2). The results obtained are analyzed under different scenarios and models of the cooling system’s equipment, allowing for the selection of the best algorithm and best equipment’s model to achieve energy efficiency of the studied refrigeration system.
Medium-Term Forecasts of Load Profiles in Polish Power System including E-Mobility Development
Authors: Piotrowski Paweł , Baczyński Dariusz , Kopyt Marcin
Published: August 2022

The main objective of this study was to conduct multi-stage and multi-variant prognostic research to assess the impact of e-mobility development on the Polish power system for the period 2022–2027. The research steps were as follows: forecast the number of electric vehicles (using seven methods), forecast annual power demand arising solely out of the operation of the forecast number of electric vehicles, forecast annual power demand with and without the impact of e-mobility growth (using six methods), forecast daily profiles of typical days with and without the impact of e-mobility growth (using three methods). For the purpose of this research, we developed a unique Growth Dynamics Model to forecast the number of electric vehicles in Poland. The application of Multi-Layer Perceptron (MLP) to the extrapolation of non-linear functions (to the forecast number of electric vehicles and forecast annual power demand without the impact of e-mobility growth) is our original, unique proposal to use the Artificial Neural Network (ANN). Another unique, innovative proposal is to include Artificial Neural Networks (Multi-Layer Perceptron and Long short-term memory (LSTM)) in an Ensemble Model for simultaneous extrapolation of 24 non-linear functions to forecast daily profiles of typical days without taking e-mobility into account. This research determined the impact of e-mobility development on the Polish power system, both in terms of annual growth of demand for power and within particular days (hourly distribution) for two typical days (summer and winter). Under the (most likely) balanced growth variant of annual demand for power, due to e-mobility, such demand would grow by more than 4%, and almost 7% under the optimistic variant. Percentage growth of power demand in terms of variation according to time of day was determined. For instance, for the balanced variant, the largest percentage share of e-mobility was in the evening “peak” time (about 6%), and the smallest percentage was in the night “valley” (about 2%).
Robust Output Feedback Control of the Voltage Source Inverter in an AC Microgrid
Authors: Khan Hamid Saeed , Memon Attaullah Y.
Published: August 2022

This paper presents the mathematical model and control of the voltage source inverter (VSI) connected to an alternating current (AC) microgrid. The VSI used in this work was a six-switch three-phase PWM inverter, whose output voltages were controlled in a synchronous (dq) reference frame via a sliding mode control strategy. The control strategy required only output voltages; other states of the system were estimated by using a high-gain observer. The power-sharing among multiple inverters was achieved by solving power flow equations of the electrical network. The stability analysis showed that the error was ultimately bound in the case of the real PWM inverter and/or with a nonlinear load in the electrical network. The microgrid was simulated using the SimPowerSystems Toolbox from MATLAB/Simulink. The simulation results show the effectiveness of the proposed control scheme. The output voltage regulation of the inverter and power-sharing was achieved with the ultimately bounded error for the linear load. Later, the nonlinear load was also included in the electrical network and the error was shown to remain ultimately bounded. The output voltage regulation and power-sharing were achieved with the nonlinear load in the system.
From Genes to Therapy in Autism Spectrum Disorder
Authors: Vorstman Jacob A. S. , Freitag Christine M. , Persico Antonio M.
Published: August 2022

In recent years, findings from genetic and other biological studies are starting to reveal the role of various molecular mechanisms that contribute to the etiology of ASD [...]
Out Like a Light: Feasibility and Acceptability Study of an Audio-Based Sleep Aide for Improving Parent–Child Sleep Health
Authors: Chung Alicia , Jin Peng , Kamboukos Dimitra , Robbins Rebecca , Blanc Judite , Jean-Louis Girardin , Seixas Azizi
Published: August 2022

Our study examines the acceptability and feasibility of Moshi, an audio-based mobile application, among children 3–8 years old using a parent–child dyadic approach. Our 10-day within-subject pre–post study design consisted of five nights of a normal bedtime routine and a subsequent five nights exposed to one story on the Moshi application during the intervention. Each five-night period spanned three weeknights and two weekend nights. The Short-Form Children’s Sleep Habits Questionnaire (SF-CSHQ) was used to measure children’s sleep at baseline and post-intervention. The PROMIS, Epworth Sleepiness Scale and Pittsburgh Sleep Quality Index were used to assess parents’ sleep. Among the 25 child–parent dyads, the mean child age was 4 (SD = 1.23) and 63% were male (n = 15). Mean parent age was 35 (SD = 5.83), 84% were female (n = 21), and 48.0% were Black (n = 12). For child-only comparisons, mean post-SF-CSHQ measures were lower compared to baseline. A trend in parent sleep is reported. This study shows the potential of an audio-based mobile sleep aid to improve sleep health in a racially diverse parent and child dyad sample.
Temporal and Spatial Changes in the Material Exchange Function of Coastal Intertidal Wetland—A Case Study of Yancheng Intertidal Wetland
Authors: Dai Lingjun , Liu Hongyu , Li Yufeng
Published: August 2022

As a transition zone between the terrestrial ecosystem and the marine ecosystem, coastal intertidal wetland provides an important place for material circulation and energy exchange, and it is nature’s most precious resource. The ecological health of intertidal wetlands is an important prerequisite for sustainable green development. The material exchange function objectively and accurately reflects the material balance and ecological health of intertidal wetlands in the coastal zone. This paper uses remote sensing, geographic information technology, and model methods to objectively and accurately assess the temporal and spatial changes in the material exchange function of intertidal wetlands, providing a feasible method for studying the material exchange function of coastal wetlands. The material exchange capacity of wetlands in intertidal zones is affected by many factors, such as vegetation, topography, and base soil. After the invasion of the alien species Spartina alterniflora Lois., the elevation of the Suaeda salsa beach increased by 0.3 m. The elevation of the Phragmites australis beach rose by 0.14 m. The average elevation of S. alterniflora increased by 1.24 m. The material exchange capacity of the intertidal zone decreased by 25%. The functioning of the material exchange between sea and land changed significantly, and the area with a high level of material exchange function capacity was reduced by 71%.
Quadrivalent Vaccines for the Immunization of Adults against Influenza: A Systematic Review of Randomized Controlled Trials
Authors: Mannocci Alice , Pellacchia Andrea , Millevolte Rossella , Chiavarini Manuela , de Waure Chiara
Published: August 2022

Vaccination is the most effective intervention to prevent influenza. Adults at risk of complications are among the targets of the vaccination campaigns and can be vaccinated with different types of quadrivalent influenza vaccines (QIVs). In the light of assessing the relative immunogenicity and efficacy of different QIVs, a systematic review was performed. Randomized controlled trials conducted in adults aged 18–64 years until 30 March 2021 were searched through three databases (Medline, Cochrane Library and Scopus). Twenty-four RCTs were eventually included. After data extraction, a network meta-analysis was not applicable due to the lack of common comparators. However, in the presence of at least two studies, single meta-analyses were performed to evaluate immunogenicity and efficacy; on the contrary, data from single studies were considered. Seroconversion rate for H1N1 was higher for standard QIVs, while for the remaining strains it was higher for low-dose adjuvanted QIVs. For seroprotection rate, the recombinant vaccine recorded the highest values for H3N2, while for the other strains, the cell-based QIVs achieved better results. In general, standard and cell-based QIVs showed an overall good immunogenicity profile. Nevertheless, as a relative comparative analysis was not possible, further research would be deserved.
The “Ensemble”—A Group Music Therapy Treatment for Developing Preschool Children’s Social Skills
Authors: Blanky-Voronov Raya , Gilboa Avi
Published: August 2022

(1) Background: Several music therapy treatments have been developed to assist children with social skill deficiencies. They lack reference to emotions and their connection to social skills and they don’t deal with group dynamics and its impact on the group. We conducted a preliminary examination of the “Ensemble” treatment, which was developed to improve the social skills of children of various client populations, with the social deficiency originating from different sources; (2) Methods: 24 children in four groups went through the year-long “Ensemble” treatment. Observations of the sessions were analyzed quantitatively counting the occurrence of twelve typical socially oriented behaviors. Qualitative interviews were conducted with 24 mothers and 23 kindergarten teachers (KTs) before and after the process; (3) Results: Quantitative results show that children in all four “Ensemble” groups, improved in nine out of twelve social skills. Qualitative results show that the improvement was evident also in the home environment (as reported by mothers) and in the kindergarten environment (as reported by KTs); (4) Conclusions: A comparison between the “Ensemble” and previous music therapy treatments indicates this treatment’s potential to help children with a wide variety of social skill deficiencies. Further investigation based on more rigorous research designs is recommended.
Using Explainable Artificial Intelligence to Discover Interactions in an Ecological Model for Obesity
Authors: Allen Ben , Lane Morgan , Steeves Elizabeth Anderson , Raynor Hollie
Published: August 2022

Ecological theories suggest that environmental, social, and individual factors interact to cause obesity. Yet, many analytic techniques, such as multilevel modeling, require manual specification of interacting factors, making them inept in their ability to search for interactions. This paper shows evidence that an explainable artificial intelligence approach, commonly employed in genomics research, can address this problem. The method entails using random intersection trees to decode interactions learned by random forest models. Here, this approach is used to extract interactions between features of a multi-level environment from random forest models of waist-to-height ratios using 11,112 participants from the Adolescent Brain Cognitive Development study. This study shows that methods used to discover interactions between genes can also discover interacting features of the environment that impact obesity. This new approach to modeling ecosystems may help shine a spotlight on combinations of environmental features that are important to obesity, as well as other health outcomes.
New Aspects on the Treatment of Retinopathy of Prematurity: Currently Available Therapies and Emerging Novel Therapeutics
Authors: Ryu Juhee
Published: August 2022

Retinopathy of prematurity (ROP) is a rare proliferative ocular disorder in preterm infants. Because of the advancements in neonatal care, the incidence of ROP has increased gradually. Now, ROP is one of the leading causes of blindness in children. Preterm infants with immature retinal development are exposed to supplemental oxygen inside an incubator until their cardiopulmonary system is adequately developed. Once they are returned to room air, the relatively low oxygen level stimulates various angiogenesis factors initiating retinal neovascularization. If patients with ROP are not offered adequate and timely treatment, they can experience vision loss that may ultimately lead to permanent blindness. Although laser therapy and anti-vascular endothelial growth factor agents are widely used to treat ROP, they have limitations. Thus, it is important to identify novel therapeutics with minimal adverse effects for the treatment of ROP. To date, various pharmacologic and non-pharmacologic therapies have been assessed as treatments for ROP. In this review, the major molecular factors involved in the pathogenesis of ROP, currently offered therapies, therapies under investigation, and emerging novel therapeutics of ROP are discussed.
Immunometabolism of Immune Cells in Mucosal Environment Drives Effector Responses against Mycobacterium tuberculosis
Authors: Tukiman Mohd Hatimi , Norazmi Mohd Nor
Published: August 2022

Tuberculosis remains a major threat to global public health, with more than 1.5 million deaths recorded in 2020. Improved interventions against tuberculosis are urgently needed, but there are still gaps in our knowledge of the host-pathogen interaction that need to be filled, especially at the site of infection. With a long history of infection in humans, Mycobacterium tuberculosis (Mtb) has evolved to be able to exploit the microenvironment of the infection site to survive and grow. The immune cells are not only reliant on immune signalling to mount an effective response to Mtb invasion but can also be orchestrated by their metabolic state. Cellular metabolism was often overlooked in the past but growing evidence of its importance in the functions of immune cells suggests that it can no longer be ignored. This review aims to gain a better understanding of mucosal immunometabolism of resident effector cells, such as alveolar macrophages and mucosal-associated invariant T cells (MAIT cells), in response to Mtb infection and how Mtb manipulates them for its survival and growth, which could address our knowledge gaps while opening up new questions, and potentially be applied for future vaccination and therapeutic strategies.
Psychological Stress Exacerbates Inflammation of the Ileum via the Corticotropin-Releasing Hormone-Mast Cell Axis in a Mouse Model of Eosinophilic Enteritis
Authors: Kanamori Atsushi , Tanaka Fumio , Ominami Masaki , Nadatani Yuji , Fukunaga Shusei , Otani Koji , Hosomi Shuhei , Kamata Noriko , Nagami Yasuaki , Taira Koichi , Fujiwara Yasuhiro
Published: August 2022

The effects of psychological stress on eosinophilic gastrointestinal disorders have not been elucidated. This study investigated the effects of psychological stress in a mouse model of eosinophilic enteritis (EoN). BALB/c mice were treated with ovalbumin (OVA) to create an EoN model and subjected to either water avoidance stress (WAS) or sham stress (SS). Microscopic inflammation, eosinophil and mast cell counts, mRNA expression, and protein levels of type 2 helper T cell (Th2) cytokines in the ileum were compared between groups. We evaluated ex vivo intestinal permeability using an Ussing chamber. A corticotropin-releasing hormone type 1 receptor (CRH-R1) antagonist was administered before WAS, and its effects were analyzed. WAS significantly increased diarrhea occurrence and, eosinophil and mast cell counts, and decreased the villus/crypt ratio compared to those in the SS group. The mRNA expression of CRH, interleukin IL-4, IL-5, IL-13, eotaxin-1, and mast cell tryptase β2 significantly increased, and the protein levels of IL-5, IL-13, and OVA-specific immunoglobulin E (IgE) also significantly increased in the WAS group. Moreover, WAS significantly increased the intestinal permeability. The CRH-R1 antagonist significantly inhibited all changes induced by WAS. Psychological stress exacerbated ileal inflammation via the CRH-mast cell axis in an EoN mouse model.
Atom Transfer Radical Polymerization of Pyrrole-Bearing Methacrylate for Production of Carbonyl Iron Particles with Conducting Shell for Enhanced Electromagnetic Shielding
Authors: Mrlík Miroslav , Kollár Jozef , Borská Katarína , Ilčíková Markéta , Gorgol Danila , Osicka Josef , Sedlačík Michal , Ronzová Alena , Kasák Peter , Mosnáček Jaroslav
Published: August 2022

The conducting polymer poly(2-(1H-pyrrole-1-yl)ethyl methacrylate (PPEMA) was synthesized by conventional atom transfer radical polymerization for the first time from free as well as surface-bonded alkyl bromide initiator. When grafted from the surface of carbonyl iron (CI) a substantial conducting shell on the magnetic core was obtained. Synthesis of the monomer as well as its polymer was confirmed using proton spectrum nuclear magnetic resonance (1H NMR). Polymers with various molar masses and low dispersity showed the variability of this approach, providing a system with a tailorable structure and brush-like morphology. Successful grafting from the CI surface was elucidate by transmission electron microscopy and Fourier-transform infrared spectroscopy. Very importantly, thanks to the targeted nanometer-scale shell thickness of the PPEMA coating, the magnetization properties of the particles were negligibly affected, as confirmed using vibration sample magnetometry. Smart elastomers (SE) consisting of bare CI or CI grafted with PPEMA chains (CI-PPEMA) and silicone elastomer were prepared and dynamic mechanical properties as well as interference shielding ones were investigated. It was found that short polymer chains grafted to the CI particles exhibited the plasticizing effect, which might be interesting from the magnetorheological point of view, and more interestingly, in comparison to the neat CI-based sample, it provided enhanced electromagnetic shielding of nearly 30 dB in thickness of 500 μm. Thus, SE containing the newly synthesized CI-PPEMA hybrid particles also exhibited considerably enhanced damping factor and proper mechanical performance, which make the material highly promising from various practical application points of view.
Evaluation of the Molecular Landscape in PD-L1 Positive Metastatic NSCLC: Data from Campania, Italy
Authors: Pisapia Pasquale , Iaccarino Antonino , De Luca Caterina , Acanfora Gennaro , Bellevicine Claudio , Bianco Roberto , Daniele Bruno , Ciampi Luisa , De Felice Marco , Fabozzi Teresa , Formisano Luigi , Giordano Pasqualina , Gridelli Cesare , Ianniello Giovanni Pietro , Libroia Annamaria , Maione Paolo , Nacchio Mariantonia , Pagni Fabio , Palmieri Giovanna , Pepe Francesco , Russo Gianluca , Salatiello Maria , Santaniello Antonio , Scamarcio Rachele , Seminati Davide , Troia Michele , Troncone Giancarlo , Vigliar Elena , Malapelle Umberto
Published: August 2022

Background: Immune-checkpoint inhibitors (ICIs) have increased and improved the treatment options for patients with non-oncogene-addicted advanced stage non-small cell lung cancer (NSCLC). However, the role of ICIs in oncogene-addicted advanced stage NSCLC patients is still debated. In this study, in an attempt to fill in the informational gap on the effect of ICIs on other driver mutations, we set out to provide a molecular landscape of clinically relevant oncogenic drivers in programmed death-ligand 1 (PD-L1) positive NSCLC patients. Methods: We retrospectively reviewed data on 167 advanced stage NSCLC PD-L1 positive patients (≥1%) who were referred to our clinic for molecular evaluation of five driver oncogenes, namely, EGFR, KRAS, BRAF, ALK and ROS1. Results: Interestingly, n = 93 (55.7%) patients showed at least one genomic alteration within the tested genes. Furthermore, analyzing a subset of patients with PD-L1 tumor proportion score (TPS) ≥ 50% and concomitant gene alterations (n = 8), we found that n = 3 (37.5%) of these patients feature clinical benefit with ICIs administration, despite the presence of a concomitant KRAS gene alteration. Conclusions: In this study, we provide a molecular landscape of clinically relevant biomarkers in NSCLC PD-L1 positive patients, along with data evidencing the clinical benefit of ICIs in patient NSCLC PD-L1 positive alterations.
The Use of Distinctive Monoclonal Antibodies in FMD VLP- and P1-Based Blocking ELISA for the Seromonitoring of Vaccinated Swine
Authors: Lee Heng-Wei , Yang Cheng-Yao , Lee Ming-Chang , Chen Shih-Ping , Chang Hui-Wen , Cheng Ivan-Chen
Published: August 2022

The serum neutralization (SN) test has been regarded as the “gold standard” for seroconversion following foot-and-mouth disease virus (FMDV) vaccination, although a high-level biosafety laboratory is necessary. ELISA is one alternative, and its format is constantly being improved. For instance, standard polyclonal antisera have been replaced by monoclonal antibodies (MAbs) for catching and detecting antibodies, and inactive viruses have been replaced by virus-like particles (VLPs). To the best of current knowledge, however, no researchers have evaluated the performances of different MAbs as tracers. In previous studies, we successfully identified site 1 and site 2 MAbs Q10E and P11A. In this study, following the established screening platform, the VLPs of putative escape mutants from sites 1 to 5 were expressed and used to demonstrate that S11B is a site 3 MAb. Additionally, the vulnerability of VLPs prompted us to assess another diagnostic antigen: unprocessed polyprotein P1. Therefore, we established and evaluated the performance of blocking ELISA (bELISA) systems based on VLPs and P1, pairing them with Q10E, P11A, S11B, and the non-neutralizing TSG MAb as tracers. The results indicated that the VLP paired with S11B demonstrated the highest correlation with the SN titers (R2 = 0.8071, n = 63). Excluding weakly positive serum samples (SN = 16–32, n = 14), the sensitivity and specificity were 95.65% and 96.15% (kappa = 0.92), respectively. Additionally, the P1 pairing with Q10E also demonstrated a high correlation (R2 = 0.768). We also discovered that these four antibodies had steric effects on one another to varying degrees, despite recognizing distinct antigenic sites. This finding indicated that MAbs as tracers could not accurately detect specific antibodies, possibly because MAbs are bulky compared to a protomeric unit. However, our results still provide convincing support for the application of two pairs of bELISA systems: VLP:S11B-HRP and P1:Q10E-HRP.
Pharmaceutical Cocrystals of Ethenzamide: Molecular Structure Analysis Based on Vibrational Spectra and DFT Calculations
Authors: Wan Mei , Fang Jiyuan , Xue Jiadan , Liu Jianjun , Qin Jianyuan , Hong Zhi , Li Jiusheng , Du Yong
Published: August 2022

Pharmaceutical cocrystals can offer another advanced strategy for drug preparation and development and can facilitate improvements to the physicochemical properties of active pharmaceutical ingredients (APIs) without altering their chemical structures and corresponding pharmacological activities. Therefore, cocrystals show a great deal of potential in the development and research of drugs. In this work, pharmaceutical cocrystals of ethenzamide (ETZ) with 2,6-dihydroxybenzoic acid (26DHBA), 2,4-dihydroxybenzoic acid (24DHBA) and gallic acid (GA) were synthesized by the solvent evaporation method. In order to gain a deeper understanding of the structural changes after ETZ cocrystallization, terahertz time domain spectroscopy (THz-TDS) and Raman spectroscopy were used to characterize the single starting samples, corresponding physical mixtures and the cocrystals. In addition, the possible molecular structures of ETZ-GA, ETZ-26DHBA and ETZ-24DHBA cocrystals were optimized by density functional theory (DFT). The results of THz and Raman spectra with the DFT simulations for the three cocrystals revealed that the ETZ-GA cocrystal formed an O−H∙∙∙O hydrogen bond between the -OH of GA and oxygen of the amide group of the ETZ molecule, and it was also found that ETZ formed a dimer through a supramolecular amide–amide homosynthon; meanwhile, the ETZ-26DHBA cocrystal was formed by a powerful supramolecular acid–amide heterosynthon, and the ETZ-24DHBA cocrystal formed the O−H∙∙∙O hydrogen bond between the 4-hydroxy group of 24DHBA and oxygen of the amide group of the ETZ molecule. It could be seen that in the molecular structure analysis of the three cocrystals, the position and number of hydroxyl groups in the coformers play an essential role in guiding the formation of specific supramolecular synthons.
The Impact of Urbanization Growth Patterns on Carbon Dioxide Emissions: Evidence from Guizhou, West of China
Authors: Zeng Canying , Wu Shaohua , Zhou Hua , Cheng Min
Published: August 2022

Little attention has been paid to the impact of future urban expansion patterns on carbon emissions based on the existing urban pattern of a region. This study used the Central Guizhou Urban Agglomeration as the study area, and the relationships between regional urbanization and CO2 emissions in the study area were analyzed based on historical data. Urban growth patterns were then simulated in four scenarios that focused on the next 15 years, and they were based on the cellular automaton model. In each different scenario, the CO2 emissions were predicted, and some implications regarding the impact of those emissions were provided. The results showed that as urban land-use intensity increases, CO2 emissions first increase then decrease; however, the rate of decline for CO2 emissions is much slower than the rate at which it rises. Moreover, in the next 15 years, urban expansion will lead to a significant increase in CO2 emissions. The CO2 emissions were found to be lowest in the spatial agglomeration scenario and highest in the spatial dispersion scenario. The spatial agglomeration scenario was conducive to understanding how CO2 emissions eventually peak; however, different cities in the study area should adopt different urban expansion patterns. These research results can provide a reference guide for the government with regard to urban planning.
Extraction of Urban Built-Up Area Based on Deep Learning and Multi-Sources Data Fusion—The Application of an Emerging Technology in Urban Planning
Authors: Zhang Jun , Zhang Xue , Tan Xueping , Yuan Xiaodie
Published: August 2022

With the rapid expansion of urban built-up areas in recent years, it has become particularly urgent to develop a fast, accurate and popularized urban built-up area extraction method system. As the direct carrier of urban regional relationship, urban built-up area is an important reference to judge the level of urban development. The accurate extraction of urban built-up area plays an important role in formulating scientific planning thus to promote the healthy development of both urban area and rural area. Although nighttime light (NTL) data are used to extract urban built-up areas in previous studies, there are certain shortcomings in using NTL data to extract urban built-up areas. On the other hand, point of interest (POI) data and population migration data represent different attributes in urban space, which can both assist in modifying the deficiencies of NTL data from both static and dynamic spatial elements, respectively, so as to improve the extraction accuracy of urban built-up areas. Therefore, this study attempts to propose a feasible method to modify NTL data by fusing Baidu migration (BM) data and POI data thus accurately extracting urban built-up areas in Guangzhou. More accurate urban built-up areas are extracted using the method of U-net deep learning network. The maximum built-up area extracted from the study is 1103.45 km2, accounting for 95.21% of the total built-up area, and the recall rate is 0.8905, the precision rate is 0.8121, and the F1 score is 0.8321. The results of using POI data and BM data to modify NTL data to extract built-up areas have not been significantly improved due to the fact that the more data get fused, the more noise there would be, which would ultimately affect the results. This study analyzes the feasibility and insufficiency of using big data to modify NTL data through data fusion and feature extraction system, which has important theoretical and practical significance for future studies on urban built-up areas and urban development.
Spatio-Temporal Evolution and Driving Mechanisms of Rural Residentials from the Perspective of the Human-Land Relationship: A Case Study from Luoyang, China
Authors: Wang Hua , Zhu Yuxin , Huang Wei , Yin Junru , Niu Jiqiang
Published: August 2022

Rural residential area is the core component of rural land, and the process of its transfer exists to guide the change of rural land use. Its evolution is closely related to population migration, so exploring the spatial and temporal evolution of the coupling type of human-land relationship and its driving mechanism is the core scientific basis for the optimal allocation of rural land resources. From the perspective of human-land relationship, this paper introduces spatio-temporal big data on the basis of 3S technology and constructs an elasticity coefficient model. The composite index method is also used to further explore the coupling types of rural human-land relations in the Luoyang region. At the same time, spatial autocorrelation and spatial autoregressive models were used to reveal the driving mechanism of the spatio-temporal evolution of rural human-land relationship types in the Luoyang region. The results showed that: (1) Against the background of the continuous reduction of the rural population in Luoyang, the scale of rural residential area first increases and then decreases, and spatially they continue to gather around the central city (2) At the township scale, the conflict between people and land tends to be moderated. The elasticity coefficient shows a zonal distribution pattern in the southwest of Luoyang region and the townships around the central city. (3) There is a non-negligible spatial correlation between rural human-land relations in Luoyang region. The initial scale of rural residentials, arable land area, rural resident population and industrial output value are positively correlated with the coordination of people-land relationship, and the slope, elevation and distance from the central city have an inverse effect on the harmony of the relationship between people and land.
Optimisation Models for Inventory Management with Limited Number of Stock Items
Authors: Vasilev Julian , Milkova Tanka
Published: August 2022

Background: Stocks of raw materials and finished products are found in all units of logistics systems and require significant financial means of management. For this reason, scientifically justified approaches to stock management and cost minimisation must be explored. Despite the existence of many such approaches in literature and practice, each case has its own specificities and specificities to which stock management models should be adapted. In this article, the aim of the authors is to propose an approach to determine optimal supply sizes from different types of stocks (more than one is known in the literature as multi-nomenclature) that minimises only the cost of inventory management. The cost of inventory is not included. Methods: The article used the methods of mathematical optimisation, the method of least squares, and regression analysis. The scope of the models in the article is inventory management, with a limited number of stock keeping units. Time series data for the delivered quantities and time series data for the costs of stock management are used. Both time series use the same time period. Results: The constructed specific nonlinear mathematical models for optimising the total cost of stock management are approbated based on sample data and the results obtained are analysed. Conclusions: The created mathematical models and methods for optimising the total cost of stock management may be used by logistics managers to minimise the total costs of inventory management.
Novel Green Nanotechnologies Applied in Environmental Protection and Health
Authors: Barbinta-Patrascu Marcela-Elisabeta , Badea Nicoleta , Zgura Irina
Published: August 2022

Today, humanity is facing serious problems due to the environmental pollution [...]
Optimized XGBoost Model with Small Dataset for Predicting Relative Density of Ti-6Al-4V Parts Manufactured by Selective Laser Melting
Authors: Zou Miao , Jiang Wu-Gui , Qin Qing-Hua , Liu Yu-Cheng , Li Mao-Lin
Published: August 2022

Determining the quality of Ti-6Al-4V parts fabricated by selective laser melting (SLM) remains a challenge due to the high cost of SLM and the need for expertise in processes and materials. In order to understand the correspondence of the relative density of SLMed Ti-6Al-4V parts with process parameters, an optimized extreme gradient boosting (XGBoost) decision tree model was developed in the present paper using hyperparameter optimization with the GridsearchCV method. In particular, the effect of the size of the dataset for model training and testing on model prediction accuracy was examined. The results show that with the reduction in dataset size, the prediction accuracy of the proposed model decreases, but the overall accuracy can be maintained within a relatively high accuracy range, showing good agreement with the experimental results. Based on a small dataset, the prediction accuracy of the optimized XGBoost model was also compared with that of artificial neural network (ANN) and support vector regression (SVR) models, and it was found that the optimized XGBoost model has better evaluation indicators such as mean absolute error, root mean square error, and the coefficient of determination. In addition, the optimized XGBoost model can be easily extended to the prediction of mechanical properties of more metal materials manufactured by SLM processes.