bluuebunny/crossref_metadata_2025 huggingface dataset:
Frequency Transition From Weak to Strong Turbulence in the Solar Wind
Authors: Telloni Daniele
Published: June 2022

During a specific time window while approaching the Sun, the longitudinal speed of Parker Solar Probe matches that of the Sun’s rotation. The spacecraft therefore co-rotates with the Sun, and as long as it does so, it is immersed in the solar-wind plasma of the same flow tube. This unique feature of the Parker Solar Probe’s orbital configuration is exploited in this work for the first time, to investigate the spectral properties of the turbulence of the same plasma stream, from large to small scales, very close to the Sun. Standard diagnostics for spectral power, compressibility, and intermittency are applied to the magnetic field data acquired by Parker Solar Probe during its seventh encounter with the Sun. The results clearly show the presence of a frequency transition (at about 5 × 10–3 Hz in the spacecraft frame) within the inertial range, where the spectrum steepens from an Iroshnikov-Kraichnan-like 3/2 to a Kolmogorov-like 5/3 scaling, the Alfvénic content decreases, whereas intermittency grows. This observational evidence is interpreted as the transition from scales dominated by Alfvénic fluctuations (and thus poorly intermittent and turbulent) to scales dominated by nonlinear interactions (and thus more intermittent and turbulent). To the author’s knowledge, this is the first time that such a transition from weak to strong turbulence in the inertial range has been observed, and it certainly deserves further investigation, both from an observational and theoretical perspective.
Is the Solar Wind Electron Strahl a Seed Population for the Earth’s Electron Radiation Belt?
Authors: Borovsky Joseph E. , Runov Andrei
Published: June 2022

1) Since the outer electron radiation belt is lost on occasion, the radiation belt needs seed electrons to rebuild. 2) The clear candidate for that seed population is energetic substorm-injected electrons in the dipolar magnetosphere. 3) The energetic substorm-injected electrons in the dipole come from the suprathermal electron population in the magnetotail plasma sheet, delivered by substorms. Scenario (1)–3) begs the question: Where do these magnetotail suprathermal electrons come from? We are hypothesizing that one source (perhaps the dominant source) is the energetic field-aligned electron strahl in the solar wind, which are electrons fresh from the solar corona.
Optimization and Purification of Terpenyl Flavor Esters Catalyzed by Black Cumin (Nigella sativa) Seedling Lipase in Organic Media
Authors: Haq Naveed Ul , Liaquat Muhammad , Alharby Hesham F. , Alzahrani Yahya M. , Alghamdi Sameera A. , Alharbi Basmah M. , Alabdallah Nadiyah M. , Saud Shah , Ahmed Mukhtar , Sayyed R. Z. , Fahad Shah
Published: June 2022

Geranyl butyrate and citronellyl butyrate esters are industrially important fruity flavors that are being used in food and as a fragrance in cosmetics. Previously terpenyl fruity flavors have been successfully synthesized in organic solvents using crude seedlings enzymes. The purpose of the current study was to standardize reaction parameters for the optimal synthesis of geranyl butyrate using the best chosen black cumin seedling lipase in an organic medium through direct esterification reactions. Geranyl butyrate and citronellyl butyrate esters were identified, quantified through gas chromatography, confirmed through GC-MS, and partiallypurified through the distillation process. Effect of organic solvents (acetonitrile, n-hexane, pentane, heptane, and toluene), alcohol and acid concentrations (0.125–0.3 M), temperature (20–50°C), incubation time (1–72 h), and enzyme concentrations (0.05–0.3 g) were studied on the synthesis of geranyl butyrate using black cumin seedling lipase. The highest conversion yields of ester (96%) were obtained when 0.25 M of geraniol and butyric acid were reacted at 37°C for 48 h in the presence of 0.25 g of crude seedling lipase enzyme in n-hexane. It was concluded that the germinated black cumin seedling lipase proved to be the best among the selected biocatalysts for the synthesis of geranyl butyrate in n-hexane.
Efficacy of the Dynesys Hybrid Surgery for Patients with Multi-Segmental Lumbar Spinal Stenosis
Authors: Xiao Xiao , Chen Gaoyang , Wang Song , Liu Junliang , Lin Erhu , Chen Ke , Xiang Yucheng , Zhan Ke , Liu Congcong , Yuan Zhengbin , Yang Minjie , Zhong Shuyuan , Zhen Wanxin , Yang Dazhi , Peng Songlin
Published: June 2022

Objective

The efficacy of hybrid (Dynesys and fusion) surgery and the traditional transforaminal lumbar interbody fusion surgery was compared in patients with multi-segmental lumbar spinal stenosis.

Methods

A total of 68 patients with multi-segmental lumbar spinal stenosis subjected to surgery were recruited between January 2013 and October 2020 in the First Affiliated Hospital of Southern University of Science and Technology. The patients were divided into a hybrid group (N = 33) and a TLIF group (N = 35) by surgery. After surgery, follow-up was conducted for 12 months. Between the two groups, the following parameters were compared: general conditions, clinical symptom scores, imaging parameters, and early complications.

Results

A statistically significant difference in the duration of surgery was noted between the two groups. After 12 months of follow-up, the range of motion disappeared in the TLIF group, while 63.53% was preserved in the hybrid group with statistically significant differences. A statistically significant difference was identified in the Oswestry Disability Index one week after surgery. Nonetheless, no statistically significant differences were observed at the 12-month post-surgical follow-up. Pfirrmann grade showed a 3.03% upper adjacent segment degeneration rate in the hybrid group (1/33) at 12-month follow-up and 2.86% (1/35) in the TLIF group. Notably, no early complications (screw loosening and wound infection) were identified in the two groups.

Conclusion

The Dynesys hybrid surgery combined the advantages of two systems of dynamic stabilization and rigid fusion. Besides, hybrid surgery is potentially a novel approach for the treatment of multi-segmental lumbar spinal stenosis.
Robot-Assisted Laparoscopic Radical Cystectomy and Modified Y-Shaped Ileal Orthotopic Neobladder Reconstruction
Authors: Mao Weipu , Chen Shuqiu , Zhang Lijie , Li Tao , Sun Si , Xu Bin , Zhu Weidong , Zhang Guangyuan , Zhang Lei , Wu Jianping , Chen Ming
Published: June 2022

Background

Orthotopic neobladder reconstruction has become the preferred method of urinary diversion after radical cystectomy in major medical centers. We performed modified Y-shaped ileal orthotopic neobladder reconstruction and presented the functional results and postoperative complications of the modified surgery.

Methods

We included 21 patients with bladder cancer who underwent radical cystectomy at our center between February 2019 and December 2019. All patients underwent robotic-assisted laparoscopic radical cystectomy and lymph node dissection plus modified Y-shaped ileal orthotopic neobladder reconstruction. We collected the demographic and pathological history of the patients, and perioperative and postoperative functional outcomes and postoperative complications were recorded.

Results

All surgeries were successful and no serious postoperative complications occurred. The mean operative time was 321.43 ± 54.75 min, including 101.67 ± 10.88 min required for neobladder reconstruction. Liquid intake was encouraged about 5 days after surgery, stent and catheter were removed after 13.52 ± 3.28 days, and the patients were discharged 1–2 days after removing the catheter. No ureteral anastomotic and neobladder urethral anastomotic strictures occurred. The volume of the neobladder at 1-year post-surgery was 195.24 ± 16.07 mL and the maximum urinary flow rate was 20.64 ± 2.22 mL/s.

Conclusion

We describe the robotic-assisted modified Y-shaped ileal orthotopic neobladder reconstruction performed at our center, which requires a simple suture and short neobladder construction time, minimizes the occurrence of anastomotic stenosis, facilitates smooth patient emptying, and is clinically scalable and applicable.
Amino Acid Mutations in Hemagglutinin-Neuraminidase Enhance the Virulence and Pathogenicity of the Genotype III Newcastle Disease Vaccine Strain After Intravenous Inoculation
Authors: Lu Xiaolong , Liu Xiaowen , Song Qingqing , Wang Xiaoquan , Hu Shunlin , Liu Xiufan
Published: June 2022

Newcastle disease virus (NDV), the causative agent that generally causes severe disease in poultry, continues to mutate and has thus evolved into 21 genotypes. We previously isolated a velogenic genotype III NDV JS/7/05/Ch that evolved from the vaccine strain Mukteswar, accompanying by amino acid mutations in Hemagglutinin-Neuraminidase (HN). Here, we sought to investigate the role of the mutant HN protein in NDV virulence. The HN genes of Mukteswar and JS/7/05/Ch were replaced reciprocally via reverse genetics, yielding two recombinant viruses rJS/MHN and rMu/JHN, respectively. rMu/JHN, in which the endogenous HN protein was replaced with the HN protein of JS/7/05/Ch, had a higher intravenous pathogenicity index (IVPI) value in chickens. Moreover, dual aa mutations (A494D and E495K from JS/7/05/Ch-type HN) were introduced into the HN protein of Mukteswar to generate the recombinant virus rMukHN494+495JS. This virus showed an equivalent IVPI value to that of rJS/7/05/Ch (generated from parental JS/7/05/Ch via reverse genetics). In vitro and in vivo assays further showed that A494D and E495K in HN induced antigenic changes, a higher replication level and a more intense inflammatory response. Taken together, these findings indicate that aa mutations in HN are crucial for the virulence of the genotype III Newcastle disease (ND) vaccine strain after intravenous inoculation. Our study further highlights that close surveillance is needed to monitor the genetic variation of ND vaccine strains.
Effect of COVID-19 Lockdown on Small Animal Trauma Patterns in Australia: A Multicentre Study
Authors: Hickey Mara C. , Napier Elizabeth , Ong Hui Mei
Published: June 2022

Objective

To determine whether patterns of trauma changed following the start of local lockdowns due to COVID-19.

Design

Multi-institutional retrospective study assessing patients presenting within 2 years prior to local lockdown due to COVID-19 and 1 year following lockdown inclusive.

Setting

Two university teaching hospitals and one private referral center in Australia.

Animals

Dogs and cats with a presenting complaint of known or suspected trauma.

Interventions

Patient signalment, date of presentation, trauma type, treatment interventions and patient outcome (survival to discharge, cardiopulmonary arrest, or euthanasia) were recorded in a web-based data capture system (REDCap).

Measurements and Main Results

Three thousand one hundred eighty-nine patients (682 cats and 2,507 dogs) were included in the study. Overall trauma prevalence was 2.9% with pre-lockdown prevalence of 2.8% and post-lockdown prevalence of 3.1% (p < 0.001). Cats had higher rates of blunt trauma while penetrating trauma was more prevalent in dogs (p < 0.001). Juvenile patients were also more likely to have blunt trauma when compared to adult patients (p < 0.001). Patient age and sex characteristics did not differ when comparing the 2 time periods. Compared to pre-lockdown, blunt and penetrating trauma patterns changed post-lockdown in dogs and cats (p < 0.001 for both). Interventions were performed more frequently (p = 0.039) in the post-lockdown with surgical procedures having a significant increase (p = 0.015). Survival rates increased post-lockdown for both species (p < 0.001) with financially driven euthanasia being less common than in pre-lockdown for dogs (p = 0.02).

Conclusions

Trauma patterns changed for cats and dogs in the post-lockdown period. Compared to pre-lockdown, trauma prevalence was higher with a decrease in mortality rate. No increase in juvenile patients was identified post-lockdown. A decrease in financially driven euthanasia and an increase in interventions suggest no negative financial effect from COVID-19 lockdown on trauma patient care in Australia.
A Missing Data Reconstruction Method Using an Accelerated Least-Squares Approximation with Randomized SVD
Authors: Intawichai Siriwan , Chaturantabut Saifon
Published: June 2022

An accelerated least-squares approach is introduced in this work by incorporating a greedy point selection method with randomized singular value decomposition (rSVD) to reduce the computational complexity of missing data reconstruction. The rSVD is used to speed up the computation of a low-dimensional basis that is required for the least-squares projection by employing randomness to generate a small matrix instead of a large matrix from high-dimensional data. A greedy point selection algorithm, based on the discrete empirical interpolation method, is then used to speed up the reconstruction process in the least-squares approximation. The accuracy and computational time reduction of the proposed method are demonstrated through three numerical experiments. The first two experiments consider standard testing images with missing pixels uniformly distributed on them, and the last numerical experiment considers a sequence of many incomplete two-dimensional miscible flow images. The proposed method is shown to accelerate the reconstruction process while maintaining roughly the same order of accuracy when compared to the standard least-squares approach.
Spatial and Temporal Variations in the Ecological Efficiency and Ecosystem Service Value of Agricultural Land in China
Authors: Guo Shili , Hu Zhiyong , Ma Hanzhe , Xu Dingde , He Renwei
Published: June 2022

In-depth analysis of spatial and temporal variations in the ecological efficiency of agricultural land has important theoretical and practical significance in achieving the efficient utilization of agricultural land, the coordinated development of natural resources and the environment, and the formulation of sustainable agricultural development policies. By including carbon emissions and pollution as undesired output indicators of agricultural land use, and introducing ecological service values as output indicators, an SBM-Undesirable model which can not only avoid the deviation caused by the difference of radial and angular selection, but also reflect the essence of efficiency evaluation, was used to estimate the ecological efficiency of agricultural land in 30 provinces, municipalities and autonomous regions of China from 2004 to 2017. Spatial and temporal differences were then analyzed. The results show that (1) The ecological efficiency of agricultural land in China decreased overall from 2004 to 2017. (2) The eco-efficiency of agricultural land was highest in the eastern provinces, lowest in the central provinces, and moderate in the western provinces. (3) Among the input indicators, the input redundancy rates of agricultural land, chemical fertilizer input and agricultural film input were too high. (4) China’s agricultural land use has not evolved towards harmonious development of the environment and economy. Due to the excessive use of chemical fertilizers, agricultural films and other factors that cause pollution, there has been a one-sided increase in the economic output of agricultural land, and improvements in ecological value have been inhibited. Based on the research results, feasible suggestions are put forward to improve the ecological efficiency of agricultural land in China.
Smart-Map: An Open-Source QGIS Plugin for Digital Mapping Using Machine Learning Techniques and Ordinary Kriging
Authors: Pereira Gustavo Willam , Valente Domingos Sárvio Magalhães , Queiroz Daniel Marçal de , Coelho André Luiz de Freitas , Costa Marcelo Marques , Grift Tony
Published: June 2022

Machine Learning (ML) algorithms have been used as an alternative to conventional and geostatistical methods in digital mapping of soil attributes. An advantage of ML algorithms is their flexibility to use various layers of information as covariates. However, ML algorithms come in many variations that can make their application by end users difficult. To fill this gap, a Smart-Map plugin, which complements Geographic Information System QGIS Version 3, was developed using modern artificial intelligence (AI) tools. To generate interpolated maps, Ordinary Kriging (OK) and the Support Vector Machine (SVM) algorithm were implemented. The SVM model can use vector and raster layers available in QGIS as covariates at the time of interpolation. Covariates in the SVM model were selected based on spatial correlation measured by Moran’s Index (I’Moran). To evaluate the performance of the Smart-Map plugin, a case study was conducted with data of soil attributes collected in an area of 75 ha, located in the central region of the state of Goiás, Brazil. Performance comparisons between OK and SVM were performed for sampling grids with 38, 75, and 112 sampled points. R2 and RMSE were used to evaluate the performance of the methods. SVM was found superior to OK in the prediction of soil chemical attributes at the three sample densities tested and was therefore recommended for prediction of soil attributes. In this case study, soil attributes with R2 values ranging from 0.05 to 0.83 and RMSE ranging from 0.07 to 12.01 were predicted by the methods tested.
Label-Free Mass Spectrometry-Based Proteomic Analysis in Lamb Tissues after Fish Oil, Carnosic Acid, and Inorganic Selenium Supplementation
Authors: Gawor Andrzej , Ruszczyńska Anna , Konopka Anna , Wryk Grzegorz , Czauderna Marian , Bulska Ewa
Published: June 2022

Selenium is an essential nutrient, building twenty five identified selenoproteins in humans known to perform several important biological functions. The small amount of selenium in the earth’s crust in certain regions along with the risk of deficiency in organisms have resulted in increasingly popular dietary supplementation in animals, implemented via, e.g., inorganic selenium compounds. Even though selenium is included in selenoproteins in the form of selenocysteine, the dietary effect of selenium may result in the expression of other proteins or genes. Very little is known about the expression effects modulated by selenium. The present study aimed to examine the significance of protein expression in lamb tissues obtained after dietary supplementation with selenium (sodium selenate) and two other feed additives, fish oil and carnosic acid. Label-free mass spectrometry-based proteomic analysis was successfully applied to examine the animal tissues. Protein-protein interaction network analysis of forty differently-expressed proteins following inorganic selenium supplementation indicated two significant clusters which are involved in cell adhesion, heart development, actin filament-based movement, plasma membrane repair, and establishment of organelle localization.
Resistance to Mecillinam and Nine Other Antibiotics for Oral Use in Escherichia coli Isolated from Urine Specimens of Primary Care Patients in Germany, 2019/20
Authors: Kresken Michael , Pfeifer Yvonne , Wagenlehner Florian , Werner Guido , Wohlfarth Esther ,   Therapy
Published: June 2022

Urinary tract infections (UTIs) are among the most common bacterial infections in humans. Escherichia coli is by far the leading cause of community-acquired UTIs. Pivmecillinam, the oral prodrug of the penicillin derivative mecillinam (amdinocillin), was re-introduced in Germany in March 2016 for first-line treatment of acute uncomplicated cystitis. This study aimed to evaluate the prevalence of resistance to mecillinam in comparison to nine other antibiotics used for oral treatment in E. coli urine isolates after the re-introduction of pivmecillinam. A total of 460 isolates were collected at 23 laboratories of clinical microbiology between October 2019 and March 2020. Forty-six isolates (10.0%) produced an extended-spectrum β-lactamase (ESBL) of the CTX-M family. Resistance to amoxicillin (43.3%) was most widespread, followed by resistance to trimethoprim-sulfamethoxazole (27.0%), amoxicillin-clavulanic acid (18.0%), cefuroxime (11.3%), and ciprofloxacin (11.1%). Twenty-four E. coli isolates (5.2%) were resistant to mecillinam. The concentrations of mecillinam needed to inhibit 50/90% of the ESBL-producing isolates and the remaining isolates were 1/4 mg/L and 0.5/4 mg/L, respectively. The findings support the recommendation to regard pivmecillinam as a first-line option for the treatment of uncomplicated lower UTIs.
Classifying Breast Density from Mammogram with Pretrained CNNs and Weighted Average Ensembles
Authors: Justaniah Eman , Aldabbagh Ghadah , Alhothali Areej , Abourokbah Nesreen
Published: June 2022

We are currently experiencing a revolution in data production and artificial intelligence (AI) applications. Data are produced much faster than they can be consumed. Thus, there is an urgent need to develop AI algorithms for all aspects of modern life. Furthermore, the medical field is a fertile field in which to apply AI techniques. Breast cancer is one of the most common cancers and a leading cause of death around the world. Early detection is critical to treating the disease effectively. Breast density plays a significant role in determining the likelihood and risk of breast cancer. Breast density describes the amount of fibrous and glandular tissue compared with the amount of fatty tissue in the breast. Breast density is categorized using a system called the ACR BI-RADS. The ACR assigns breast density to one of four classes. In class A, breasts are almost entirely fatty. In class B, scattered areas of fibroglandular density appear in the breasts. In class C, the breasts are heterogeneously dense. In class D, the breasts are extremely dense. This paper applies pre-trained Convolutional Neural Network (CNN) on a local mammogram dataset to classify breast density. Several transfer learning models were tested on a dataset consisting of more than 800 mammogram screenings from King Abdulaziz Medical City (KAMC). Inception V3, EfficientNet 2B0, and Xception gave the highest accuracy for both four- and two-class classification. To enhance the accuracy of density classification, we applied weighted average ensembles, and performance was visibly improved. The overall accuracy of ACR classification with weighted average ensembles was 78.11%.
Chemical Quality and Hydrogeological Settings of the El-Farafra Oasis (Western Desert of Egypt) Groundwater Resources in Relation to Human Uses
Authors: Saber Abdullah A. , Ullah Bhat Sami , Hamid Aadil , Gabrieli Jacopo , Garamoon Hassan , Gargini Alessandro , Cantonati Marco
Published: June 2022

In the Egyptian deserts, new land reclamation projects have been recently established to meet the increasing-population growth rate and food demand. These projects mainly depend on the different groundwater aquifers. El-Farafra Oasis is one of the “1.5-million-feddan reclamation project” areas recently established in the Western Desert of Egypt where the only available water source is the world’s largest fossil freshwater reservoir “the Nubian Sandstone Aquifer System (NSAS)”. Groundwater-dependent springs, and their artificial counterpart “drilled wells”, are reliable water systems throughout the world. In the present study, hydrochemical parameters were collected in 2015 from 16 different springs and wells of the El-Farafra Oasis, and analyzed using the different water quality indices. The calculated water quality index (WQI), its correlations with the water quality parameters Gibbs, Piper, US Salinity-Lab Staff and Wilcox diagrams, and Principal Component Analysis (PCA) were used to evaluate the groundwater suitability for human drinking and irrigation purposes. WQI values revealed good-to-excellent groundwater quality for human drinking. In addition, the spring and well water samples investigated showed good indices for irrigation activities. Gibbs and Piper’s diagrams were presented, with most samples falling into the rock-dominance category, and belonging to hydrogeochemical facies determining the following water types: Mg(HCO3)2 type water (37.5% of the samples), no dominant ions (mixed water-type category; Ca/MgCl2) (50% of the samples), and, finally, NaCl water type (the remaining 12.5%). The groundwater chemistry in the study area is mainly controlled by rock-water interactions, particularly the dissolution of carbonate rocks and silicate weathering. The elevated nutrient concentrations, in particular nitrates, are most likely due to agricultural activities, indicating substantial anthropogenic activities in the area studied.
Seismic Performance of Corroded Reinforced Concrete Columns Strengthened with Basalt Fiber Sheets
Authors: Yuan Jiaojiao , Shen Dejian
Published: June 2022

The corrosion of steel bars causes the decline of their mechanical properties, the bond performance between steel bars and concrete and the seismic performance of reinforced concrete columns. Four reinforced concrete columns were designed and fabricated with the corrosion rates set to be 0 and 8%, respectively. By carrying out tests on the seismic performance of four specimens with the axial compression ratio of 0.2, the effect of reinforcement layers on the seismic bearing capacity, stiffness, hysteretic performance, ductility and energy-dissipation capacity of the corroded reinforced concrete columns was analyzed. The results obtained in this research can be directly used for the simulation analysis of the seismic performance of corroded reinforced concrete columns after reinforcement.
Analyzing and Visualizing Text Information in Corporate Sustainability Reports Using Natural Language Processing Methods
Authors: Kang Hyewon , Kim Jinho
Published: June 2022

Sustainability is a major contemporary issue that affects everyone. Many companies now produce an annual sustainability report, mainly intended for their stakeholders and the public, enumerating their goals and degrees of achievement regarding sustainable development. Although sustainability reports are an important resource to understand a company’s sustainability strategies and practices, the difficulty of extracting key information from dozens or hundreds of pages with sustainability and business jargon has highlighted the need for metrics to effectively measure the content of such reports. Accordingly, many researchers have attempted to analyze the concepts and messages from sustainability reports using various natural language processing (NLP) methods. In this study, we propose a novel approach that overcomes the shortcomings of previous studies. Using the sentence similarity method and sentiment analysis, the study clearly shows thematic practices and trends, as well as a significant difference in the balance of positive and negative information in the reports across companies. The results of sentiment analysis prove that the new approach of this study is very useful. It confirms that companies actively use the sustainability report to improve their positive image when they experience a crisis. It confirms that companies actively use the sustainability report to improve their positive image when they experience a crisis. The inferences gained from this method will not only help companies produce better reports that can be utilized effectively, but also provide researchers with ideas for further research. In the concluding section, we summarize the implications of our approach and discuss limitations and future research areas.
A Practical Harmonic Admittance Matrix Derivation Approach for Fluctuating Power Photovoltaic Systems
Authors: Xu Xiao , Dong Anqi , Li Qianting , Gao Hui
Published: June 2022

Due to a range of economic incentives and policy supports, distributed photovoltaic (PV) systems are accelerating their penetration into the distribution network at all voltage levels. However, the PV systems are connected to the grid via power electronic converters, which are nonlinear devices characterized by inherent harmonic emission, and their cumulative harmonic injection into the grid is detrimental to the grid power quality. Although the existing literature proves that harmonic admittance matrix (HAM)-based models can represent well the supply voltage dependence of harmonics, the conventional HAM derivation approach is based on the harmonic sensitivity tests conducted under laboratory conditions, making it infeasible for infield implementation. To address this issue, this paper starts with investigating the harmonic emission and grid interaction mechanisms of PV systems analytically, followed by analyzing the power dependency of HAMs experimentally. Based on the findings, a HAM derivation and self-tuning approach is proposed for fluctuating power PV systems, where only the infield measurements at the point of connection are needed. The model accuracy is compared against the widely used constant current source model and harmonic Norton model, while its integration approach for harmonic power flow analysis is demonstrated via the simulated European low voltage test feeder.
High-Throughput Cross-Technology Communication via Chip-Level Side Channel
Authors: Feng Cheng , Xia Tian
Published: June 2022

Cross-technology Communication (CTC) is a novel technique enabling data transmission among devices equipped with different physical layers in a heterogeneous wireless network. Particularly, by enabling cross-technology communication between ZigBee and WiFi, the energy-saving problem and media access control under cross-technology interference would be resolved easily. However, the current CTC designs are either too slow or destructive to ongoing ZigBee transmissions. In this paper, we propose a new Cross-technology Communication framework based on ZigBee chip-level side channel. The proposed design enables the high-throughput ZigBee-to-WiFi cross-technology communication while maintaining transparency to the existing ZigBee network. Specifically, we modify some ZigBee chips within one ZigBee symbol to create a side channel at the CTC sender (ZigBee) for carrying CTC bits while the CTC receiver (WiFi) can detect those modifications and demodulate the CTC bits at WiFi preamble detection. Both theoretical analysis and experiments show that our design would be transparent to ZigBee and throughput can reach 31.25 Kbps—1000× the state-of-the-art CTC design.
Improving Delivery Performance in High-Mix Low-Volume Manufacturing by Model-Based and Data-Driven Methods
Authors: Gödri István
Published: June 2022

In a high-mix and low-volume (HMLV) manufacturing environment where demand fluctuation is the rule rather than the exception, daily production management in face of conflicting key performance indicators such as high delivery precision, short lead time, and maximal resource utilization is a most challenging task. This situation may even be hampered by unreliable supplier performance. This paper presents a generic decision support workflow, which first identifies the most critical external and internal factors which have a serious impact on delivery performance. Next, it suggests a method which combines traditional manufacturing system simulation with advanced machine learning techniques to support the improved daily routine lot-sizing and production scheduling activities in a HMLV company. Argumentation is motivated and illustrated by a detailed industrial case study.
Orthofaçade-Based Assisted Inspection Method for Buildings
Authors: Draganić Suzana , Popov Srđan , Laban Mirjana , Marković Marko Z. , Lukić Ivan , Malešev Mirjana , Radonjanin Vlastimir
Published: June 2022

Building façade assessment could be performed in a more efficient way using a multidisciplinary approach and modern technologies. This study proposes the orthofaçade-based assisted inspection method (AIM), universal and applicable to different types of façade cladding and suitable for application in the condition assessment of inaccessible building façades or high-rise and large structures of all kinds. The AIM method offers a multidisciplinary approach by combining unmanned aerial vehicle (UAV) technology, electronic tachymetry, and digital image processing techniques (photogrammetry and open-source computer vision methods). The method was verified in a case study performed on a high-rise building façade. On-site data acquisition of high-resolution images of façade and control points was conducted by UAV and tachymetry. The data were further processed in photogrammetric software in order to generate a georeferenced orthofaçade. Crack detection was performed at pixel level via computer code using the OpenCV library methods. The established diagnostic model, defined by control points, enables precise determination of crack location. Crack length, width, or area could be calculated based on the coordinates of its points, by performing simple mathematical operations. The AIM method provides automation of crack detection and precise determination of location and geometrical parameters of detected crack.
The Performance of Empirical Laws for Rebound Hammer Tests on Concrete Structures
Authors: Diaferio Mariella , Varona Francisco B.
Published: June 2022

The assessment of concrete compressive strength plays a key role in the analysis of the seismic vulnerability of existing buildings. However, the adoption of classical destructive tests is usually limited by their invasiveness, cost and time needed for the execution. Thus, in order to overcome these limits and allow investigations to be extended to a large number of points, the use of the rebound hammer test is investigated here with a detailed analysis of the effects on the accuracy of the strength assessment related to the choice of the conversion model relating rebound index to compressive strength. The analysis has been performed by comparing several empirical laws calibrated with data acquired in an experimental investigation of an existing concrete building. The relationships between the coefficients of the examined conversion models are then established, with the aim of reducing the unknowns in the calibration procedure. Furthermore, the influence of the coefficients of variation of concrete strength and rebound index on the results of the calibration procedure has been analyzed, thereby supporting the assessment of the accuracy of the concrete strength.
Novel Approach Using Risk Analysis Component to Continuously Update Collaborative Robotics Applications in the Smart, Connected Factory Model
Authors: Pantano Matteo , Pavlovskyi Yurii , Schulenburg Erik , Traganos Konstantinos , Ahmadi Seyedamir , Regulin Daniel , Lee Dongheui , Saenz José
Published: June 2022

Building on the idea of Industry 4.0, new models of the highly connected factory that leverage factory-generated data to introduce cost-effective automation and involve the human worker for creating higher added value are possible. Within this context, collaborative robots are becoming more common in industry. However, promises regarding flexibility cannot be satisfied due to the challenging process of ensuring human safety. This is because current regulations and standards require updates to the risk assessment for every change to the robotic application, including the parts involved, the robotic components, and the type of interaction within the workspace. This work presents a novel risk analysis software tool that was developed to support change management for adaptive collaborative robotic systems in the connected factory model. The main innovation of this work is the tool’s ability to automatically identify where changes have been made to components or processes within a specific application through its integration with a connected factory architecture. This allows a safety expert to easily see where updates to the risk assessment are required, helping them to maintain conformity with the CE marking process despite frequent changes. To evaluate the benefits of this tool, a user study was performed with an exemplary use-case from the SHOP4CF project. The results show that this newly developed technology for risk assessment has better usability and lower omission errors when compared to existing methods. Therefore, this study underlines the need for tools that can help safety engineers cope with changes in flexible robotics applications and reduce omission errors.
Magnetic Field Effect on the Handedness of Electrodeposited Heusler Alloy
Authors: Giurlani Walter , Vizza Martina , Pizzetti Federico , Bonechi Marco , Savastano Matteo , Sorace Lorenzo , Stefani Andrea , Fontanesi Claudio , Innocenti Massimo
Published: June 2022

Magneto-electrochemistry (MEC) experiments were carried out in the electrodeposition of a ferromagnetic Heusler alloy. The electrodeposition was carried out in the absence (as a reference) and in the presence of a magnetic field that was applied perpendicularly to the electrode–solution interface. The obtained metallic deposit was characterized by SEM-EDS, XRF, and XRD techniques. The ferromagnetic properties are assessed on the basis of SQUID measurements. The experimental results indicate that the influence of the presence of the magnetic field induces differences in the electrochemical measurements and a macroscopic handedness (chirality) in the deposit, which is a function of magnet orientation. Eventually, the coercivity of the Heusler alloy that was obtained in the presence of the magnetic field was larger compared to that of the deposit that was obtained without a magnetic field.
Accumulation and Emission of Water Vapor by Silica Gel Enriched with Carbon Nanotubes CNT-Potential Applications in Adsorption Cooling and Desalination Technology
Authors: Pajdak Anna , Kulakowska Anna , Liu Jinfeng , Berent Katarzyna , Kudasik Mateusz , Krzywanski Jaroslaw , Kalawa Wojciech , Sztekler Karol , Skoczylas Norbert
Published: June 2022

This paper presents a study of the application of the properties of water vapor as a gas with high potential energy, strongly dependent on temperature and pressure. Analyses of water vapor sorption on two types of silica gels (SG) (90 wt.%) enriched with carbon nanotubes (CNTs) (10 wt.%), in the context of their application in the design of adsorption beds in adsorption cooling and desalination systems were conducted. The sorption experiments were performed by gravimetric method at a relative humidity of 0% < RH < 100% and temperatures of 298 K, 313 K, and 333 K. The addition of CNTs to SG caused a decrease in the sorption capacity and depended on the temperature. As the process temperature increased, a lower SG/CNT mixtures sorption capacity to vapor was obtained. The highest influence of CNTs was observed at the highest temperature, and the average decrease of sorption capacity was several percent. The ratio of SG/CNT sorption capacity to pure SG values was below 1 in most measurements.
Sensorineural Hearing Loss Post-COVID-19 Infection: An Update
Authors: Fancello Virginia , Fancello Giuseppe , Hatzopoulos Stavros , Bianchini Chiara , Stomeo Francesco , Pelucchi Stefano , Ciorba Andrea
Published: June 2022

The course of COVID-19 infection may be complicated by a variety of neurological manifestations. Since the inner ear is vulnerable to viruses, sensorineural hearing loss (SNHL) has been reported to occur following the SARS-CoV-2 infection, often resulting in long-term morbidity and worsening the quality of life. The interest in how the virus affects the inner ear has gradually increased since the pandemic’s spread, but little is still known about the SNHL potentially caused by SARS-CoV-2. The aim of this paper is to evaluate the possible association between SNHL and COVID-19 infection, through a systematic literature review. Currently available data suggest that SARS-CoV-2 may hamper cochlear function; however, available reports are still limited. Large cohort and prospective studies are necessary to evaluate the long-term effects of this viral infection in the inner ear.
On Fractional Inequalities Using Generalized Proportional Hadamard Fractional Integral Operator
Authors: Chinchane Vaijanath L. , Nale Asha B. , Panchal Satish K. , Chesneau Christophe , Khandagale Amol D.
Published: June 2022

The main objective of this paper is to use the generalized proportional Hadamard fractional integral operator to establish some new fractional integral inequalities for extended Chebyshev functionals. In addition, we investigate some fractional integral inequalities for positive continuous functions by employing a generalized proportional Hadamard fractional integral operator. The findings of this study are theoretical but have the potential to help solve additional practical problems in mathematical physics, statistics, and approximation theory.
Potential Distribution of Invasive Boxwood Blight Pathogen (Calonectriapseudonaviculata) as Predicted by Process-Based and Correlative Models
Authors: Barker Brittany S. , Coop Leonard , Hong Chuanxue
Published: June 2022

Boxwood blight caused by Cps is an emerging disease that has had devastating impacts on Buxus spp. in the horticultural sector, landscapes, and native ecosystems. In this study, we produced a process-based climatic suitability model in the CLIMEX program and combined outputs of four different correlative modeling algorithms to generate an ensemble correlative model. All models were fit and validated using a presence record dataset comprised of Cps detections across its entire known invaded range. Evaluations of model performance provided validation of good model fit for all models. A consensus map of CLIMEX and ensemble correlative model predictions indicated that not-yet-invaded areas in eastern and southern Europe and in the southeastern, midwestern, and Pacific coast regions of North America are climatically suitable for Cps establishment. Most regions of the world where Buxus and its congeners are native are also at risk of establishment. These findings provide the first insights into Cps global invasion threat, suggesting that this invasive pathogen has the potential to significantly expand its range.
Plasma Exosome-Derived microRNAs as Potential Diagnostic and Prognostic Biomarkers in Brazilian Pancreatic Cancer Patients
Authors: Marin Anelis Maria , Mattar Sibelle Botogosque , Amatuzzi Rafaela Ferreira , Chammas Roger , Uno Miyuki , Zanette Dalila Luciola , Aoki Mateus Nóbrega
Published: June 2022

Pancreatic cancer represents one of the leading causes of oncological death worldwide. A combination of pancreatic cancer aggressiveness and late diagnosis are key factors leading to a low survival rate and treatment inefficiency, and early diagnosis is pursued as a critical factor for pancreatic cancer. In this context, plasma microRNAs are emerging as promising players due to their non-invasive and practical usage in oncological diagnosis and prognosis. Recent studies have showed some miRNAs associated with pancreatic cancer subtypes, or with stages of the disease. Here we demonstrate plasma exosome-derived microRNA expression in pancreatic cancer patients and healthy individuals from Brazilian patients. Using plasma of 65 pancreatic cancer patients and 78 healthy controls, plasma exosomes were isolated and miRNAs miR-27b, miR-125b-3p, miR-122-5p, miR-21-5p, miR-221-3p, miR-19b, and miR-205-5p were quantified by RT-qPCR. We found that miR-125b-3p, miR-122-5p, and miR-205-5p were statistically overexpressed in the plasma exosomes of pancreatic cancer patients compared to healthy controls. Moreover, miR-205-5p was significantly overexpressed in European descendants, in patients with tumor progression and in those who died from the disease, and diagnostic ability by ROC curve was 0.86. Therefore, we demonstrate that these three microRNAs are potential plasma exosome-derived non-invasive biomarkers for the diagnosis and prognosis of Brazilian pancreatic cancer, demonstrating the importance of different populations and epidemiological bias.
Design, Synthesis and Characterization of [G10a]-Temporin SHa Dendrimers as Dual Inhibitors of Cancer and Pathogenic Microbes
Authors: Khan Arif Iftikhar , Nazir Shahzad , Ullah Aaqib , Haque Muhammad Nadeem ul , Maharjan Rukesh , Simjee Shabana U. , Olleik Hamza , Courvoisier-Dezord Elise , Maresca Marc , Shaheen Farzana
Published: June 2022

As the technologies for peptide synthesis and development continue to mature, antimicrobial peptides (AMPs) are being widely studied as significant contributors in medicinal chemistry research. Furthermore, the advancement in the synthesis of dendrimers’ design makes dendrimers wonderful nanostructures with distinguishing properties. This study foregrounds a temporin SHa analog, [G10a]-SHa, and its dendrimers as globular macromolecules possessing anticancer and antibacterial activities. These architectures of temporin SHa, named as [G10a]-SHa, its dendrimeric analogs [G10a]2-SHa and [G10a]3-SHa, and [G10a]2-SHa conjugated with a polymer molecule, i.e., Jeff-[G10a]2-SHa, were synthesized, purified on RP-HPLC and UPLC and fully characterized by mass, NMR spectroscopic techniques, circular dichroism, ultraviolet, infrared, dynamic light scattering, and atomic force microscopic studies. In pH- and temperature-dependent studies, all of the peptide dendrimers were found to be stable in the temperature range up to 40–60 °C and pH values in the range of 6–12. Biological-activity studies showed these peptide dendrimers possessed improved antibacterial activity against different strains of both Gram-positive and Gram-negative strains. Together, these dendrimers also possessed potent selective antiproliferative activity against human cancer cells originating from different organs (breast, lung, prostate, pancreas, and liver). The high hemolytic activity of [G10a]2-SHa and [G10a]3-SHa dendrimers, however, limits their use for topical treatment, such as in the case of skin infection. On the contrary, the antibacterial and anticancer activities of Jeff-[G10a]2-SHa, associated with its low hemolytic action, make it potentially suitable for systemic treatment.
Implications of Hydrogen Sulfide in Development of Pulmonary Hypertension
Authors: Sun Yan , Tang Chaoshu , Jin Hongfang , Du Junbao
Published: June 2022

The pathological mechanisms underlying pulmonary hypertension (PH), as well as its treatment strategy, are crucial issues in this field. This review aimed to summarize the pathological mechanisms by which the hydrogen sulfide (H2S) pathway contributes to PH development and its future implications. The data in this review were obtained from Medline and PubMed sources up to 2022 using the search terms "hydrogen sulfide" and "pulmonary hypertension". In the review, we discussed the significance of endogenous H2S pathway alteration in PH development and showed the advance of the role of H2S as the third gasotransmitter in the mechanisms for hypoxic PH, monocrotaline-induced PH, high blood flow-induced PH, and congenital heart disease-associated PH. Notably, H2S plays a crucial role in the development of PH via certain mechanisms, such as inhibiting the proliferation of pulmonary artery smooth muscle cells, suppressing the inflammation and oxidative stress of pulmonary artery endothelial cells, inducing pulmonary artery smooth muscle cell apoptosis, and interacting with other gaseous signaling pathways. Recently, a variety of H2S donors were developed, including naturally occurring donors and synthetic H2S donors. Therefore, understanding the role of H2S in PH development may help in further exploring novel potential therapeutic targets of PH.