bluuebunny/crossref_metadata_2025_split huggingface dataset:
Purification of carboxymethylated fatty alcohol derivates using ion exchange resins
Authors: Cattelaens Frederike , Jäger Martin , Myrdek Thomas 
Published: November 2022

AbstractDuring synthesis of the surfactants, several byproducts are formed that impact the physico‐chemical properties as well as the quality of the product. Removal of these impurities is hence of vital interest, but the purification has remained chemically challenging. In this work, the ion exchange resin type I strong base anion polymeric catalyst was used to remove impurities such as remaining raw material and byproducts from different ether carboxylic acid surfactants. The efficiency of this preparative purification method was determined through analysis of the product composition using different analytical techniques such as titrimetric acid and saponification value determination, gas chromatography, Infrared (IR) and Nuclear Magnetic Resonance (NMR) spectroscopy. The results showed the high efficiency of the purification of the ether carboxylic acid surfactants using ion exchange resin. For all purified samples, the amount of byproducts such as esters and remaining raw material was found significantly reduced. Pure anionic surfactants (>90%) were obtained. Its ease of use and high efficiency render the method suitable for carboxymethylated surfactants. Additional investigations on industrial scales and further surfactant purification are yet to be analyzed.
On a class of pseudodifferential operators on the product of compact Lie groups
Authors: Federico Serena , Parmeggiani Alberto 
Published: November 2022

AbstractIn this paper, a bisingular pseudodifferential calculus, along the lines of the one introduced by L. Rodino in his paper of 1975, is developed in the global setting of a product of compact Lie groups. The approach follows that introduced by M. Ruzhansky and V. Turunen in their book of 2010 (see also V. Fischer's paper of 2015), in that it exploits the harmonic analysis of the groups involved.
Mild Neurological Phenotype Associated with Hypomorphic Variants in the Ataxia‐Telangiectasia Mutated Gene
Authors: Caputi Caterina , Federici Giulia , Soddu Silvia , Travaglini Lorena , Piane Maria , Bertini Enrico , Zanni Ginevra , Leuzzi Vincenzo 
Published: November 2022

ABSTRACTBackgroundAtaxia‐telangiectasia (A‐T) is a progressive multisystemic neurodegenerative disease. The phenotypic spectrum includes conditions (variant A‐T) with mild, late‐onset, and atypical clinical presentations characterized by the prevalence of dyskinetic rather than ataxic features.CasesWe describe the clinical presentations of 3 siblings with early‐onset truncal ataxia without obvious neurological deterioration or biological markers of classic A‐T phenotype. We performed functional and genetic evaluation of 3 siblings with very mild neurological phenotype. Genetic evaluation with a next‐generation sequencing panel for genes causative of cerebellar ataxia detected 2 known ATM gene variants, missense c.9023G>A p.(Arg3008His), and leaky splicing c.1066‐6T>G variants. Functional studies showed mildly reduced ATM expression and residual kinase activity in the probands compared with healthy controls.ConclusionsThese results suggest the importance of investigating ATM variants even in the presence of clinical and biological atypical cases to ensure specific therapeutic regimens and oncological surveillance in these patients.
Design and characterization of a minimized planar dual‐band MIMO circular ring antenna with high efficiency
Authors: Cai Jing , Dong Guiting , Zhang Chuanba , Li Huiyang , Shi Xiaojing , Liu Gui 
Published: November 2022

AbstractA minimized planar dual‐band multiple‐input multiple‐output antenna with high efficiency for the fifth‐generation applications is proposed in this paper. The designed antenna is composed of two identical radiating elements and a defected ground structure (DGS). Each radiating element is made up of a circular ring, a U‐shaped microstrip, a T‐shaped microstrip, and an L‐shaped microstrip. A rectangular microstrip with a small square stub is connected to the DGS to improve the isolation. The size of the designed antenna element is 24 mm × 15 mm. The measured reflection coefficients are less than ∗10 dB in the 5G New Radio n77/n78/n79 (3.3–4.2 and 4.8–4.96 GHz). The total peak gain and efficiency are greater than 3.5 dBi and 82%, respectively. The values of calculated envelope correlation coefficient are lower than 0.015. The proposed dual‐band MIMO antenna is suitable for 5 G applications.
Investigation and reduction of finite width effect of coupling beam in bandwidth estimation of coupled MEMS resonator
Authors: Brinda Ramasamy , Kanthamani Sundharajan 
Published: November 2022

AbstractBand pass filters are realized by coupled microelectromechanical resonators and their bandwidth is determined by the ratio of coupling beam stiffness to resonator beam stiffness at the coupling location. The coupling beam is connected to the resonator beam in such a way that the resonator beam length and coupling beam width are in the same axis. Practically, it is not possible for the coupling beam to make contact with the resonator beam at a single point. But presently, coupled resonators are designed for specific bandwidth by considering resonator beam stiffness at any point within the contact area between the coupling beam and resonator beam. Due to the finite width of the coupling beam, resonator stiffness at the coupling location is multivalued. It causes additional velocity coupling. So, the bandwidth calculated using single‐point stiffness on the resonator beam will be far from the bandwidth of the actually coupled resonator. For the first time, this finite‐width effect is taken into account. The novelty of this work is the consideration of this finite width effect of coupling beam and cancellation of additional velocity coupling to minimize error in bandwidth estimation. This is achieved by a combination of λ/4 and 3λ/4 coupling beams. In this work, the coupled resonator is modeled using an electrical equivalent circuit.
Design of matched filter for signal‐to‐noise ratio maximization to improve data rate
Authors: Prakash V. , Manimegalai C. T. 
Published: November 2022

AbstractThe matched filter is an optimal linear filter for maximizing signal‐to‐noise ratio (SNR) in the presence of additive random noise. Learning‐based matched filter is the proposed work. The proposed model supports (i) maximizing the SNR and (ii) setting the threshold, it is also called an intelligent matched dual tire filter. This improves the SNR by about 20 dB and the corresponding data rate to over 400 MBit/s. The bit error rate for 20 dB is very lower than FEC (10−3) of up to 10−7. The accuracy of the proposed matched learning filter is proved to be above 95%. Indoor visible light communication is one of the applications, and it can also be used for image processing and outdoor communication such as satellite and radar communication. It is obvious for communication as it avoids signal degradation, lobing, and overfitting to achieve a better data rate. This requires funding support and infrastructure facility that can be used to deploy the proposed algorithm in the real‐time scenario in the future.
Dead detector element detection in flat panels using convolutional neural networks
Authors: Box Jon , Salazar Adam , Johnson Dan , Rutel Isaac 
Published: November 2022

AbstractBackgroundIndependent testing of image quality metrics is important to provide an unbiased determination of medical imaging performance. Due to the underreporting by vendors of dead detector elements, which are elements that do not function but may be corrected using information from surrounding pixels, the health of all imaging detector elements is infrequently reported and extraordinarily difficult to independently determine or verify through traditional means without vendor largesse. In many instances, dead detector data, or dead pixel maps, are only available at the discretion of the vendors, which renders these data inaccessible to many medical physicists.PurposeWe provide a mechanism to predict which detector elements are dead from a single flat field image and describe a convolutional neural network (CNN) to address this task. This technique provides a vendor‐independent and potential correction algorithm‐independent means for obtaining this information, which directly relates to the image quality of the diagnostic imaging system.MethodsA data set of 61 flat field images was obtained from two Varian on‐board imaging (OBI) systems. These images were taken with a range of kVp and mAs settings and with differing levels of copper filtration in the beam path. The dead pixel maps for these detectors were also acquired and used to label the ground truth subimages—or small square images from the original, larger image—from the flat field images. This data set was then used to train, test, and validate five unique CNNs on the task of identifying dead detector elements from subimages derived from the flat field images.ResultsThe CNNs were validated with an average precision of 0.96, an average recall of 0.48, and an average F1 score of 0.55 attributed to the scarcity and imbalanced nature of available data, and the difficulty in training neural networks using flat‐field images. However, performance drastically improved when utilizing a subset of the data with a high dynamic range.ConclusionThis work shows the feasibility of using a CNN to detect dead detector elements from flat field images taken on a detector. Robust training of this type of algorithm could lead to a generalized model that may provide an independent evaluation of dead detectors for a wide range of vendors and models. Ultimately, this method can be a valuable tool for physicists performing quality assurance procedures on all digital diagnostic imaging systems, including X‐ray, mammography, and fluoroscopy.
Artificial intelligence‐based prediction of lycopene content in raw tomatoes using physicochemical attributes
Authors: Sharma Arun , Tiwari Akshat Dutt , Kumari Monika , Kumar Nishant , Saxena Vikas , Kumar Ritesh 
Published: November 2022

AbstractIntroductionLycopene consumption reduces risk and incidence of cancer and cardiovascular diseases. Tomatoes are a rich source of phytochemical compounds including lycopene as a major constituent. Lycopene estimation using high‐performance liquid chromatography is time‐consuming and expensive.ObjectiveTo develop artificial intelligence models for prediction of lycopene in raw tomatoes using 14 different physicochemical parameters including salinity, total dissolved solids (TDS), electrical conductivity (EC), firmness, pH, total soluble solids (TSS), titratable acidity (TA), colour values on Hunter scale (L, a, b), total phenolic content (TPC), total flavonoid content (TFC) and antioxidant activity (AOA).Material and methodsThe post‐harvest data acquisition was collected through investigation for more than 100 raw tomatoes stored for 15 days. Linear multivariate regression (LMVR), principal component regression (PCR) and partial least squares regression (PLSR) models were developed by splitting data set into train and test datasets. The training of models was performed using 10‐fold cross validation (CV).ResultsPrincipal component analysis showed strong positive association between lycopene, colour value ‘a’, TPC, TFC and AOA. The R2 (CV), root mean square error (RMSE) (CV) and RMSE (Test) for best LMVR model was observed to be at 0.70, 8.48 and 9.69 respectively. The PCR model revealed R2 (CV) at 0.59, RMSE (CV) at 8.91 and RMSE (Test) at 10.17 while PLSR model revealed R2 (CV) at 0.60, RMSE (CV) at 9.10 and RMSE (Test) at 10.11.ConclusionResults of the present study show that epidemiological studies suggest fully ripened tomatoes are most beneficial for consumption to ensure recommended daily intake of lycopene content.
Prune‐belly syndrome with severe lordosis
Authors: Konno Hiroko , Murakoshi Takeshi 
Published: November 2022

Key pointsWhat's already known about this topic?

Orthopedic issues in children with prune‐belly syndrome are common because of the lack of the abdominal musculature.

What does this study add?

Even extreme fetal lordosis can be improved substantially after birth.

Our patient with a prenatal diagnosis of prune‐belly syndrome and severe scoliosis could run, jump and maintain a seated position at 4 years of age without orthotic support or surgical treatment.
Longitudinal effects of using and discontinuing central nervous system medications on cognitive functioning
Authors: Koch Elise , Johnell Kristina , Kauppi Karolina 
Published: November 2022

AbstractPurposeTo investigate the longitudinal effect of using and discontinuing central nervous system (CNS) medications on cognitive performance.MethodsUsing longitudinal cognitive data from population representative adults aged 25–100 years (N = 2188) from four test waves 5 years apart, we investigated both the link between use of CNS medications (opioids, anxiolytics, hypnotics and sedatives) on cognitive task performance (episodic memory, semantic memory, visuospatial ability) across 15 years, and the effect of discontinuing these medications in linear mixed effects models.ResultsWe found that opioid use was associated with decline in visuospatial ability whereas using anxiolytics, hypnotics and sedatives was not associated with cognitive decline over 15 years. A link between drug discontinuation and cognitive improvement was seen for opioids as well as for anxiolytics, hypnotics and sedatives.ConclusionsAlthough our results may be confounded by subjacent conditions, they suggest that long‐term use of CNS medications may have domain‐specific negative effects on cognitive performance over time, whereas the discontinuation of these medications may partly reverse these effects. These results open up for future studies that address subjacent conditions on cognition to develop a more complete understanding of the cognitive effects of CNS medications.
A systematic review of the critical success factors for implementing circular economy in construction projects
Authors: Wuni Ibrahim Yahaya 
Published: November 2022

AbstractThe transition to a circular economy in the construction industry provides enormous opportunities to decouple construction activities, processes, and practices from finite consumption of natural resources and environmental externalities. Circular construction leverages the interconnected models of narrowing, slowing, and closing resource loops to minimize extractive and wasteful use of natural resources, eliminate waste and pollution from the outset, and retain construction products and materials in use for a longer duration. However, construction practitioners have struggled to implement circular economy principles into construction projects successfully. This study systematically reviewed the critical success factors for implementing circular construction projects. The results revealed 51 critical success factors for circular construction projects, clustered into six typologies: technological (n = 10, ∑ = 93, μ = 9.30), supply chain (n = 14, ∑ = 84, μ = 6.00), organizational (n = 9, ∑ = 82, μ = 9.11), institutional (n = 7, ∑ = 43, μ = 6.14), stakeholder success (n = 7, ∑ = 73, μ = 10.43), and management success factors (n = 4, ∑ = 27, μ = 6.75). A Pareto analysis revealed 30 vital critical success factors for circular construction projects. Thus, the study established the first comprehensive set of critical success strategies for circular construction projects and enriches the knowledge of construction organizations and project team members on how best to implement circular economy principles in construction projects.
Ultra‐Strong Comprehensive Radiation Effect Tolerance in Carbon Nanotube Electronics
Authors: Zhu Maguang , Lu Peng , Wang Xuan , Chen Qian , Zhu Huiping , Zhang Yajie , Zhou Jianshuo , Xu Haitao , Han Zhengsheng , Han Jianwei , Chen Rui , Li Bo , Peng Lian‐Mao , Zhang Zhiyong 
Published: November 2022

AbstractCarbon nanotube (CNT) field‐effect transistors (FETs) have been considered ideal building blocks for radiation‐hard integrated circuits (ICs), the demand for which is exponentially growing, especially in outer space exploration and the nuclear industry. Many studies on the radiation tolerance of CNT‐based electronics have focused on the total ionizing dose (TID) effect, while few works have considered the single event effects (SEEs) and displacement damage (DD) effect, which are more difficult to measure but may be more important in practical applications. Measurements of the SEEs and DD effect of CNT FETs and ICs are first executed and then presented a comprehensive radiation effect analysis of CNT electronics. The CNT ICs without special irradiation reinforcement technology exhibit a comprehensive radiation tolerance, including a 1 × 104 MeVcm2 mg−1 level of the laser‐equivalent threshold linear energy transfer (LET) for SEEs, 2.8 × 1013 MeV g−1 for DD and 2 Mrad (Si) for TID, which are at least four times higher than those in conventional radiation‐hardened ICs. The ultrahigh intrinsic comprehensive radiation tolerance will promote the applications of CNT ICs in high‐energy solar and cosmic radiation environments.
Constructing Biomass‐Based Ultrahigh‐Rate Performance SnOy@C/SiOx Anode for LIBs via Disproportionation Effect
Authors: Zhang Ning , Liu Kun , Zhang Haibai , Wang Xiaofei , Zhou Yuhao , He Wenxiu , Cui Jinlong , Sun Juncai 
Published: November 2022

AbstractTo break the stereotype that silica can only be reduced via a magnesiothermic and aluminothermic method at low‐temperature condition, the novel strategy for converting silica to SiOx using disproportionation effect of SnO generated via low‐temperature pyrolysis coreduction reaction between SnO2 and rice husk is proposed, without any raw materials waste and environmental hazards. After the low‐temperature pyrolysis reaction, SnOy@C/SiOx composites with unique structure (Sn/SnO2 dispersed on the surface and within pores of biochar as well as SiOx residing in the interior) are obtained due to the exclusive biological properties of rice husk. Such unique structural features render SnOy@C/SiOx composites with an excellent talent for repairing the damaged structure and the highly electrochemical storage ability (530.8 mAh g−1 at 10 A g−1 after 7500 cycles). Furthermore, assembled LiFePO4||SnOy‐50@C/SiOx full cell displays a high discharge capacity of 463.7 mAh g−1 after 100 cycles at 0.2 A g−1. The Li+ transport mechanism is revealed by density functional theory calculations. This work provides references and ideas for green, efficient, and high‐value to reduce SiO2, especially in biomass, which also avoids the waste of raw materials in the production process, and becomes an essential step in sustainable development.
A survey of recent advances in image steganography
Authors: Kumar Akshay , Rani Rajneesh , Singh Samayveer 
Published: November 2022

AbstractOver the course of technological development, data security while transmission and storing has always been a field of continuous advancements and key importance. In the recent times, its importance has increased even further and the main reason behind this is the increase in the amount of data that is being transferred over internet and various networks. Although there are cryptographic approaches to handle these situations, steganography provides a different aspect to the solution. While cryptography encrypts the data such that the cipher text is visible to human eye, but the meaning of that encrypted text is never known. Steganography is the process of hiding data in plain sight inside some images, audio, video and so on, such that it is very difficult for the viewer to directly differentiate if there is some data hidden in the host or not. This paper consists a study of various methodologies to implement Image steganography like spatial domain manipulation, encryption based and deep learning approaches. The paper focuses upon recent advances in all these approaches for image steganography and aims to help other researches in this domain to understand recent developments as well future advancements possible in the same field. Furthermore, this paper illustrates about how different image formats effect various image steganography methods and how the various image color models interact with image steganography. Later this article sheds some light on the domain of steganalysis and reports about the fundamental principles as well as various implementations of steganalysis systems in recent times.
Seroepidemiology of peste des petits ruminants virus in small ruminants in selected districts in Northwest Ethiopia
Authors: Abesha Habtamu , Teshome Yechale , Alemu Yeshwas Ferede , Dejene Haileyesus , Tarekegn Zewdu Seyoum , Assefa Ayalew 
Published: November 2022

AbstractBackgroundPeste des petits ruminants (PPR) is one of the most severe diseases of small ruminants, causing the loss of millions of dollars annually. A cross‐sectional study was conducted to determine the seroepidemiology of peste des petits ruminants virus (PPRV) in unvaccinated sheep and goats in selected districts in Northwest Ethiopia.ObjectivesThe study was designed to investigate the epidemiology of PPRV in unvaccinated sheep and goats and risk factors in the study areas.MethodsA multi‐stage sampling was used to select study districts, villages and households with a random sampling approach. Study animals (403 sheep and goats) older than 5 months were selected with a systematic random sampling approach. From the animals, blood samples were aseptically collected and PPRV antibodies from the serum were analysed with enzyme‐linked immunosorbent assay (ELISA).ResultsThe overall seroprevalence of antibodies to PPRV was 32.5% in both species. It was higher in goats with a prevalence of 34.7% than in sheep (28.3%). District, herd size, sex, animal origin and grazing management were significantly associated with seropositivity of animals to PPRV antibodies. If an animal was from the Dangur district, it had 2.6 times higher chance of being positive than in the Dibati district (OR = 2.6, p = 0.01 and 95% CI = 1.2– 5.6). Herd size was also significantly correlated with the seropositivity with (OR = 4, p = 0.001, and 95% CI = 1.8–9). Also, male animals had 1.7 times higher chance of being positive than females. Further, if an animal comes from the market, it has 2.7 times higher chance of being positive compared to animals born and raised on the farm.ConclusionsThe seropositivity indicates that the disease is circulating in the study areas. Hence, preventive approaches, like vaccination campaigns and strict biosecurity measures, are highly advised to avoid the catastrophic impact of the diseases if an outbreak occurs.