bluuebunny/crossref_metadata_2025 huggingface dataset:
Naked‐eye colorimetric and optical assay of heavy metals based on nano‐architectured prototype of organically functionalized mesoporous titania grafted with 4‐chloro‐2‐(4′‐methyl‐benzothiazol‐2′‐ylazo)‐phenol
Authors: El‐Nahass Marwa N. , Youssif Mahmoud M. , El‐Daly Hosny A. , Fayed Tarek A.
Published: July 2022

Heavy metals are extremely toxic, causing harm to aquatic and human life. Thus, this study focused on developing simple, colorimetric, and low‐cost optical sensors for detection of metal ions with high selectivity and sensitivity. Here, a novel benzothiazole azo‐dye, namely, 4‐chloro‐2‐(4′‐methyl‐benzothiazol‐2′‐ylazo)‐phenol (CMBTAP) was synthesized and characterized by Fourier transform infrared spectroscopy (FT‐IR), 1H‐nuclear magnetic resonance (NMR), 13C‐NMR, and mass spectroscopic techniques. This azo‐dye has been anchored into the amino‐functionalized mesoporous TiO2 which synthesized using pluornic123 and cetyltrimethylammonium bromide as templates to yield CMBTAP‐M‐TiO2 (1) and CMBTAP‐M‐TiO2 (2), respectively. The designed nanosensors were characterized by FT‐IR, transmission electron microscopy, nitrogen adsorption–desorption isotherms, X‐ray diffraction, and thermogravimetric analyses. The colorimetric and optical sensing behavior of CMBTAP and its nanosensor analogs toward different metal ions like Ba2+, Fe3+, Co2+, Ni2+, Cu2+, Cd2+, Hg2+, and Al3+ were explored using naked‐eye observations, steady‐state absorption, and emission techniques. Significant changes in colors, the absorption and emission spectra were observed. The action of these nanosensors is reversible where on adding ethylenediaminetetraacetic acid to the formed complexes, the original absorption and emission spectra of the free sensors are restored, demonstrating that the chelation process is reversible. For CMBTAP and the nanosensors, the binding constants of the complexes formed with the used metal ions, and limit of detection (LOD) were calculated. In comparison with CMBTAP, the results revealed that the nanosensors exhibited a stronger binding affinity, selectivity, sensitivity, and lower LODs for the studied metal ions, implying that the sensing efficiency of CMBTAP is improved after loading onto the nanostructured TiO2. Thus, we have successfully converted the hazardous azo dye into an environmentally safe optical sensor for detection of toxic metal ions in wastewater with high sensitivity.
Prediction for magnetostriction magnetorheological foam using machine learning method
Authors: Rohim Muhamad Amirul Sunni , Nazmi Nurhazimah , Bahiuddin Irfan , Mazlan Saiful Amri , Norhaniza Rizuan , Yamamoto Shin‐Ichiroh , Nordin Nur Azmah , Abdul Aziz Siti Aishah
Published: July 2022

Magnetorheological (MR) foam is a magnetic polymer composite (MPC) that can be used for soft sensors and actuators in soft robotics. Modeling mechanical properties and magnetostriction behavior of MR foam is critical to developing into MR foam devices. This study uses extreme learning machines (ELM) and artificial neural networks (ANN) to predict magnetostriction behavior. These models describe the nonlinear relationship between different carbonyl iron particle compositions, magnetic field, strain, and normal force. The model's hyperparameters (learning algorithms and activation functions) are varied. For ANN, RMSProp, and ADAM learning algorithms were used with sigmoid and ReLU activation functions. The ELM model considered the Hard limit, ReLU, and sigmoid activation function. The model was then evaluated for both training and testing data. Based on the results, ANN RMSProp Sigmoid, ELM with activation function ReLU, and Hard limit are more accurate than other models. However, the correlation analysis and comparison between prediction and experimental data show ELM Hard limit are more generalized in predicting strain and normal force with , 0.999, and RMSE less than 0.002. In conclusion, the ELM Hard limit model accurately predicts the magnetostriction behavior of MR foam, paving the way for future MR foam device development.
Asymptotic analysis of the Heston model and its statistical and financial applications
Authors: Shi Chao
Published: July 2022

Transform inversion algorithm is a popular method in the areas of Statistics and Financial Engineering. However, it is often difficult to guarantee its accuracy due to the lack of error control, which depends heavily on the asymptotic feature of the transform function. This article characterizes the asymptotic behavior of the Heston stochastic volatility model, by which one can derive computable error bounds and achieve any pre‐specified error tolerance in the transform inversion algorithm. Moreover, a universal method is proposed to specify a closed‐form upper bound of the discretization error. Numerical examples indicate that the resulting inversion algorithm with our computable error bounds is reliably accurate and efficient, for parameter estimation and option pricing under the Heston model.
Babylonian records of transient astronomical phenomena
Authors: Steele John , Ganguli Srishti
Published: July 2022

The Late Babylonian Astronomical Diaries and related texts contain a large body of records of astronomical phenomena which were carefully and systematically observed between about 600 BC and 50 BC. Most of these observations are of regular (cyclical) astronomical phenomena such as passages of the planets past certain stars, the first and last appearances, stations, and acronychal risings of the planets, and eclipses of the sun and moon. However, a smaller number of observations of irregular, transient astronomical phenomena were also recorded. In addition to being of historical interest, records of certain transient phenomena have applications in modern science. In this paper, we provide a catalog of three types of transient phenomena observed by the Babylonians – haloes, meteors, and comets – as well as some basic analysis of the records and the necessary contextual information to facilitate their analysis and use by other scholars.
Development and characterization of anti‐HPV16 monoclonal antibodies for assembly of an HPV16 detection kit
Authors: Liu Yuying , Zhang Yao , Zhang Guifeng , Yang Zengmin , Wang Yan , Wu Shuming , Chen Dan , Zhang Haijiang , Liu Yongjiang
Published: July 2022

Quality control is very important during the development of 3‐valent (16/18/58), 9‐valent (6/11/16/18/31/33/45/52/58), and 15‐valent human papillomavirus (HPV) vaccines (6/11/16/18/31/33/35/39/45/52/56/58/59/68). All 3‐valent, 9‐valent, and 15‐valent HPV vaccines contain the HPV16 antigen; therefore, a detection method that can specifically identify HPV16 in vaccines is urgently required. This study aimed to develop and characterize monoclonal antibodies to assemble a highly specific HPV16 detection kit. The HPV16 L1 pentameric protein developed as an immunogen was used to prepare monoclonal antibodies. From the pool of prepared monoclonal antibodies, we selected 4G12 and 5A6 to screen and evaluate their subtypes, specificity, neutralizing activity, serum competition, binding affinity, and gene sequencing. After these characterizations, an enzyme‐linked immunosorbent assay kit for these monoclonal antibodies was developed, and excellent quality was demonstrated in the assessment of linearity, repeatability, and specificity. The developed detection kit has great potential for wide use in clinical testing and quality control in vaccine production processes.
Utilization of Dairy Scum Waste as a Feedstock for Biodiesel Production via Different Heating Sources for Catalytic Transesterification
Authors: Mohd Johari Siti Aminah , Ayoub Muhammad , Inayat Abrar , Ullah Sami , Uroos Maliha , Naqvi Salman Raza , Farukkh Sarah
Published: July 2022

The increasing demand of the world energy consumption has made it necessary to shift energy technologies toward renewable energy sources. The sustainability of feedstock can be maintained when utilizing feedstock from waste sources, such as dairy waste, food waste, and others. Dairy waste is one of the cheapest sources available. The compositions of dairy waste scum, including free fatty acids (8–10 %), triglycerides (more than 80 % in dry bases), and fats around 60 %, which have the potential to be used as the feedstock for biodiesel production in the presence of certain catalysts. To ensure more sustainability, the catalyst should be derived from waste (e.g., eggshells and cow bones) that consists of calcium oxide, which can then be used to catalyze the transesterification of dairy waste. This review emphasizes the current production of dairy waste globally and the potential of the waste and other types of organic waste as feedstock for biodiesel production, as well as determines the optimum reaction conditions for high‐quality biodiesel production.
Predicting single kernel and bulk milled rice alkali spreading value and gelatinization temperature class using NIR spectroscopy
Authors: Armstrong Paul R. , Maghirang Elizabeth B. , Chen Ming‐Hsuan , McClung Anna M. , Yaptenco Kevin F. , Brabec Daniel , Wu Tingting
Published: July 2022

Background and Objectives

The alkali spreading value (ASV) of rice is a widely measured quality parameter and accepted indicator of gelatinization temperature (GT) class. However, the alkali test, developed in 1958, is labor intensive and subjective. Better methods to measure ASV and GT, for single kernel and bulk rice would provide an important tool to determine the effects of individual kernels on end‐use quality and rice with desired cooking qualities. An instrument developed by the USDA‐ARS and a commercially available near infrared (NIR) instrument were evaluated for determining ASV and classification of intermediate and low GT levels for single kernel and bulk milled rice, respectively.

Findings

Quantitative prediction of ASV scores (2–7) demonstrated the potential of NIR spectroscopy for screening with a standard error of prediction for validation samples ranging from 0.91 to 1.39 for the single kernel NIR instrument, and from 0.97 to 1.19 for the commercial instrument. GT categorization into intermediate and low values, using ASV scores, showed 82.4% and 85.0% correct classification using 1 and 30‐single kernel average calibration models, respectively. GT was correctly classified (93.6%–84.4%) using a commercial NIR instrument.

Conclusion

NIR spectroscopy has potential for rough screening of ASV and for two‐category GT rice classification.

Significance and Novelty

Considering that NIR spectroscopy has been proven to be applicable for other quality parameters, such as rice starch content and quality, protein content, and milling degree, the addition of calibrations for ASV as a predictor of GT class will be highly beneficial while not requiring additional resources. The rapid and nondestructive classification of individual kernels may also enable physical segregation of individual kernels for use by rice researchers and/or industry for additional studies on kernels with specific quality parameters and for determining the extent of variant kernels in a milled rice lot that could affect end use quality. Future studies on the use of NIR spectroscopy for brown rice should be evaluated so that quality could be assessed, while maintaining seed viability, and then used in field studies.
Implications of end‐of‐life home care compared with hospital‐based care during the COVID‐19 pandemic: A case report
Authors: Sakamoto Ryo , Bhandari Divya , Yoshida Makoto , Miyatake Hirotomo , Kosaka Makoto , Ozaki Akihiko , Tanimoto Tetsuya , Kami Masahiro
Published: July 2022

Restriction on hospital visits for COVID‐19 infection control continues to have a significant negative impact on patients and their families. For a patient receiving palliative care, this social isolation may deteriorate their mental health. In such situations, home care could be a viable solution to this problem.
A case of post COVID‐19 subacute thyroiditis
Authors: Al‐Shammaa Mohamed Sadoon , Abdlkadir Ahmed Saad
Published: July 2022

Subacute thyroiditis is a type of thyroid disease that occurs after a viral infection. This is usually a temporary condition associated with neck pain and may be accompanied by sore throat and flu‐like symptoms. We present a case of post COVID‐19 subacute thyroiditis and review its presentation and outcome.
COVID‐19‐associated pityriasis rosea in children: Case report and literature review
Authors: Khalili Maryam , Abtahi‐Naeini Bahareh , Rastegarnasab Fereshte , Afshar Kimia
Published: July 2022

Skin lesions are one of the Coronavirus disease 2019 (COVID‐19) symptoms. Pityriasis rosea (PR) is a mucocutaneous manifestation that can occur following virus infections. Most of the PR lesions after COVID‐19 infection were reported in adults. Herein, we report a child with PR lesions, and a literature review on 5 other case reports in children.
Biocatalytic Intramolecular C−H aminations via Engineered Heme Proteins: Full Reaction Pathways and Axial Ligand Effects
Authors: Wei Yang , Conklin Melissa , Zhang Yong
Published: July 2022

Engineered heme protein biocatalysts provide an efficient and sustainable approach to develop amine‐containing compounds through C−H amination. A quantum chemical study to reveal the complete heme catalyzed intramolecular C−H amination pathway and protein axial ligand effect was reported, using reactions of an experimentally used arylsulfonylazide with hemes containing L=none, SH−, MeO−, and MeOH to simulate no axial ligand, negatively charged Cys and Ser ligands, and a neutral ligand for comparison. Nitrene formation was found as the overall rate‐determining step (RDS) and the catalyst with Ser ligand has the best reactivity, consistent with experimental reports. Both RDS and non‐RDS (nitrene transfer) transition states follow the barrier trend of MeO−<SH−<MeOH<None due to the charge donation capability of the axial ligand to influence the key charge transfer process as the electronic driving forces. Results also provide new ideas for future biocatalyst design with enhanced reactivities.
Enantioseparation and antioxidant activity of novel diarylpyrazoline derivatives
Authors: Ameur Messaouda , Sekkoum Khaled , Gonazles Francisco , Comez‐Carpintero Jorge , Menendez Carlos , Belboukhari Nasser , Aboul‐Enein Hassan Y.
Published: July 2022

Three chiral pyrazoline derivatives were synthesized by a flavanone ring‐opening reaction followed by cyclocondensation with hydrazine hydrate to give better yields. Their enantiomeric resolution was achieved using polysaccharide chiral stationary phase columns consisting of cellulose (Chiralcel®OD‐RH, Chiralcel®OZ‐3) and amylose (Chiralpak®IA) by high‐performance liquid chromatography. The separation was affected by the nature and concentration of the alcohol modifiers in the mobile phase. Taking 5‐methoxy‐2‐(3‐phenyl‐4,5‐dihydro‐1H‐pyrazol‐5‐yl)phenol (3a) as an example, the best separation was obtained by using the Chiralpak®IA column, with a separation factor α = 1.24 and Rs = 5.66 within an analysis time of <30 min. The diarylpyrazolines showed good antioxidant activity, studied by the DPPH method.
Ribisins and Certain Analogues Exert Neuroprotective Effects through Activation of the Keap1‐Nrf2‐ARE Pathway
Authors: Tan Shen H. , Karuppasamy Muthukumar , Lan Ping , Zhang Yaochun , Hu Jiayi , Lai Xingchen , Siok‐Cheng Lim Belinda , Liu Weiliang , Chen Jing , Chew Eng‐Hui , Banwell Martin G.
Published: July 2022

Oxidative stress contributes to the pathogenesis of various neurodegenerative diseases and induction of the Kelch‐like ECH‐associated protein 1 (Keap1)‐nuclear factor erythroid 2‐related factor 2 (Nrf2) pathway is a validated neuroprotective strategy. Synthetically‐derived samples of members of the ribisin class of natural product together with a range of analogues were evaluated for their neuroprotective capacities. Four of the twenty‐four compounds tested were found to strongly stimulate antioxidant response element‐dependent transcriptional activity in human‐derived SH‐SY5Y cells. Further, in rat pheochromocytoma PC12 cells and mouse brain cortical cultures these compounds upregulated levels of nuclear factor erythroid 2‐related factor 2 (Nrf2) and its downstream target gene products, namely heme oxygenase (HO‐1) and NAD(P)H quinone reductase 1 (NQO1). Functionally speaking, the compounds conferred protection in these cell models challenged with H2O2. In silico molecular modeling suggests that certain of the ribisins can dock in the Nrf2‐binding Kelch domain in Keap1, while cysteine labeling by biotinylated iodoacetamide suggest that cysteine residues within Keap1 react with the ribisins. It is thus proposed that the most active compounds exert their neuroprotective activities by targeting Keap1, thereby activating Nrf2 and so increasing transactivation of Nrf2‐responsive genes that encode for detoxifying and antioxidant enzymes.
Wetland position in the landscape: Impact on water storage and flood buffering
Authors: Åhlén Imenne , Thorslund Josefin , Hambäck Peter , Destouni Georgia , Jarsjö Jerker
Published: July 2022

On‐going climatic changes and land‐use changes may impact water storage dynamics within wetlandscapes (defined as the entire hydrological catchments of interconnected wetland systems). These dynamics are closely linked to many wetland ecosystem services including flood buffering, nutrient retention and biodiversity support. Here, we investigate if and how current water storage dynamics can differ between wetlands within the same wetlandscape. Based on continuous monitoring of water levels in multiple wetlands throughout a growing season (spring, summer, autumn) in Vattholma, Sweden, we show that there are two distinct storage behaviours depending on the position of the wetland within the landscape. Headwater wetland regions were active in temporary storage of surplus water from regular summer rains while water levels of downstream wetlands dropped to seasonal low values without responding to individual summer precipitation events. Thereby, the downstream wetlands maintained capacity to buffer extreme floods. We also found that headwater wetlands were associated with complex and patchy inundation, which causes habitat conditions to vary over short time scales both within and among these wetlands, in contrast to the prolonged low‐water state of the downstream wetlands. These differences between headwater‐downstream wetlands imply that the functionality of an entire wetlandscape cannot be assessed by simple extrapolation of data from monitoring stations that typically are located downstream of headwater regions. Increased understanding of these differences can support wetland management practices that target location‐specific nature‐based solutions and ecosystem services.
Deep reinforcement learning based cooperative control of traffic signal for multi‐intersection network in intelligent transportation system using edge computing
Authors: Paul Ananya , Mitra Sulata
Published: July 2022

In the current era, the coordination of traffic flow is hindered by the discrepancy between road infrastructure and the number of vehicles which leads to traffic congestion. One of the widely used strategies to mitigate traffic congestion is to control traffic signals with the help of deep reinforcement learning (DRL) in edge computing based intelligent transportation system. This article provides a comprehensive analysis of the most recent DRL algorithms, advantage actor‐critic and proximal policy optimization in multiple deep neural networks (DNNs), including a state‐of‐the‐art transformer model for effective traffic signal management. Here, a single DRL agent is used, which obtains the spatio‐temporal information of the traffic to identify traffic patterns from complex intersection environments. The agent uses this information as the input to the DNNs and then applies the algorithms to retrieve the essential parameters of DNN to seek an optimal action selection policy to mitigate congestion. Different real‐time maps and small city networks are explored here to determine which DNN is best suited for traffic congestion management. The simulation study reveals that both the algorithms significantly outperform the baseline. The transformer model gives the best result when compared to other DNNs. The transformer model decreases average waiting time by 96.16%, implying that it has a higher capability of dealing with congested environments.
Hybrid error correction in fragmented IoT media streams
Authors: Herrero Rolando
Published: July 2022

Wireless personal area networks (WPANs), as most IoT networking technologies, rely on constrained low power devices that support a trade‐off between signal coverage and transmission rates. WPANs are characterized for medium to low transmission rates over low distances. The transmission rates, however, are high enough to support maximum transmission unit (MTU) sizes that are large enough to enable the transmission of IPv6 datagrams. One such WPAN technologies is associated with the IEEE 802.15.4 physical layer. Because IEEE 802.15.4 does not natively support IP encapsulation, an adaptation mechanism known as IPv6 over low‐power wireless personal area networks (6LoWPAN) is used to this end. For large datagrams like those generated when transmitting speech frames, 6LoWPAN fragments them in order to comply with the 127‐byte IEEE 802.15.4 MTU size. Fragmentation, however, aggravates the effects of network packet loss. This article explores this problem and attempts to find a mechanism that overcomes these limitations. Specifically, it introduces a hybrid error correction algorithm that dynamically adjusts the number of fragments that are transmitted in order to balance application layer loss and transmission rate.
Systematic evaluation of machine learning algorithms for neuroanatomically‐based age prediction in youth
Authors: Modabbernia Amirhossein , Whalley Heather C. , Glahn David C. , Thompson Paul M. , Kahn Rene S. , Frangou Sophia
Published: July 2022

Application of machine learning (ML) algorithms to structural magnetic resonance imaging (sMRI) data has yielded behaviorally meaningful estimates of the biological age of the brain (brain‐age). The choice of the ML approach in estimating brain‐age in youth is important because age‐related brain changes in this age‐group are dynamic. However, the comparative performance of the available ML algorithms has not been systematically appraised. To address this gap, the present study evaluated the accuracy (mean absolute error [MAE]) and computational efficiency of 21 machine learning algorithms using sMRI data from 2105 typically developing individuals aged 5–22 years from five cohorts. The trained models were then tested in two independent holdout datasets, one comprising 4078 individuals aged 9–10 years and another comprising 594 individuals aged 5–21 years. The algorithms encompassed parametric and nonparametric, Bayesian, linear and nonlinear, tree‐based, and kernel‐based models. Sensitivity analyses were performed for parcellation scheme, number of neuroimaging input features, number of cross‐validation folds, number of extreme outliers, and sample size. Tree‐based models and algorithms with a nonlinear kernel performed comparably well, with the latter being especially computationally efficient. Extreme Gradient Boosting (MAE of 1.49 years), Random Forest Regression (MAE of 1.58 years), and Support Vector Regression (SVR) with Radial Basis Function (RBF) Kernel (MAE of 1.64 years) emerged as the three most accurate models. Linear algorithms, with the exception of Elastic Net Regression, performed poorly. Findings of the present study could be used as a guide for optimizing methodology when quantifying brain‐age in youth.
Metamaterials: From fundamental physics to intelligent design
Authors: Chen Ji , Hu Shanshan , Zhu Shining , Li Tao
Published: July 2022

Metamaterials are artificial structures with the ability to efficiently control light‐field, attracting intensive attention in the past few decades. People have studied the working principles, design strategies, and fabrication methods of metamaterials, making this field cross and combine with many disciplines, including physics, material science, electronics, and chemistry. In recent years, with the rapid development of high‐efficiency and multifunctional metasurfaces, which are a two‐dimensional version of metamaterials, great efforts have been made to push this material to practical applications. In particular, the introduction of artificial intelligent (AI) algorithms enables metamaterials‐based photonic devices that exhibit excellent performances and intelligent functionalities. In this review, we first introduce the basic concepts, working principles, design methods, and applications of metamaterials, and then focus on the rapidly developing metamaterials research combined with AI algorithms. Finally, we conclude this review with personal perspectives on the current problems and future directions of metamaterials research and developments.
ABO blood group and COVID‐19 in pregnant women: A case–control study
Authors: Torres Alarcón Carmen Gabriela , Cruz Gonzalez Omar David , Sandoval López Chantal , Martinez Alvarez Roberto
Published: July 2022

Synopsis

Study comparing ABO blood group distribution between pregnant women with or without COVID‐19. Blood group ABO did not affect COVID‐19 susceptibility, severity, or death.
The efficacy of remote video‐based training on public speaking
Authors: Laske Matthew M. , DiGennaro Reed Florence D.
Published: July 2022

This study evaluated the efficacy of remote video‐based behavioral skills training (BST) on teaching public speaking behaviors to 4 participants. A multiple‐baseline design across speech behaviors was used to evaluate the effects of the training. Remote video‐based BST was effective at increasing public speaking behaviors for all participants. In addition, performance generalized to an increased audience size. An external expert in communications rated the participants as more effective public speakers following training. All participants reported satisfaction with the training and expressed greater comfort, confidence, overall ability, and less anxiety as a public speaker following training. We also measured potential collateral effects of teaching public speaking behaviors on speech disfluencies. Although remote video‐based BST was effective for all participants, it did not produce a change in the rate of speech disfluencies. Our findings indicate that public speaking behaviors can be taught using a remote video‐based BST package.
Influence of the calcium orthophosphate:glass ratio and calcium orthophosphate functionalization on the degree of conversion and mechanical properties of resin‐based composites
Authors: Campos Amanda Lopes , Fronza Bruna Marin , Rodrigues Marcela Charantola , Souza Chiari Marina Damasceno e , Braga Roberto Ruggiero
Published: July 2022

The study verified the influence of calcium orthophosphate (CaP):glass ratio on the degree of conversion and mechanical properties of resin‐based composites containing either TEGDMA‐functionalized dicalcium phosphate anhydrous (DCPA) or non‐functionalized DCPA particles. The null hypotheses were that the evaluated variables are not affected by (1) CaP:glass ratio or (2) DCPA functionalization. DCPA particles were synthesized and half of them were functionalized with TEGDMA. Particle characterization included x‐ray diffraction, elemental analysis, laser scattering, helium picnometry and scanning electron microscopy. Two series of composites were prepared containing either DCPA‐NF (non‐functionalized) or DCPA‐F (functionalized), with total inorganic content of 50 vol % and DCPA:silanized barium glass (BG) ratios from 10:40 to 50:0. A composite containing 50 vol % BG was tested as control. DC was determined using FTIR spectroscopy. Biaxial flexural strength and modulus were tested after 24 h in water. Data were analyzed using Kruskal–Wallis/Dunn (flexural properties) or analysis of variance/Tukey tests (DC). Materials with similar actual DCPA contents were compared using Student's t test (alpha: 0.05). DC was higher for materials with DCPA‐F, except for the 10:40 ratio. DCPA‐F resulted in higher strength than DCPA‐NF only at 40:10 ratio. Modulus was not affected by functionalization. Materials with similar actual DCPA contents showed differences in DC (F > NF), while no difference in flexural properties was observed between materials with 28%–30% DCPA. Both null hypotheses were rejected.
Synthesis and biological evaluation of baloxavir marboxil analogs for the treatment of influenza A (H1N1) virus
Authors: Liu Yunlong , Wang Xueyuan , Lei Meng , Jiang Le , Miao Hang , Jiang Wanlin , Li Junwei , Zhu Yongqiang
Published: July 2022

The RNA‐dependent RNA polymerase (RdRp) of influenza virus, consisting of subunits of PA, PB1, and PB2 proteins, is responsible for viral mRNA transcription and vRNA replication. Cap‐dependent endonuclease (CEN) exists in PA subunit of RdRp and mediates the critical “cap‐snatching” step of viral RNA transcription, which is considered as a promising anti‐influenza target. In this manuscript, a series of novel compounds were designed, synthesized, and biologically investigated as CEN inhibitors. The cellular activities of the target compounds against influenza A/H1N1 virus were investigated and the structure–activity relationship (SAR) was summarized. The results showed that some compounds were active against influenza A/H1N1 virus with IC50 values of less than 100 μM. The microsomal metabolic stabilities were carried out in human, monkey, and rat species, and the results showed that the active ingredients of compounds 32 and 40 were stable enough to be in vivo investigated. The in vivo pharmacokinetic results showed that compound 32 had acceptable biological parameters for both ig and iv administrations. Then the in vivo toxicity study of compound 32 with the doses of 100 and 50 mg/kg BID was performed in BALB/C mice. No obvious toxicity of compound 32 was observed during the experiment. Finally, the in vivo efficacy study of compound 32 in BALB/C mice showed that it was effective in alleviating influenza symptoms and showed a significant pharmacodynamic dose dependence. These results indicated that compound 32 was a promising candidate for further development.
Green and highly efficient synthesis of pyrimidine derivatives in a novel glycolic acid: urea‐based low transition temperature mixture via C–C and C–O bond formation
Authors: Karande Vishram , Mohire Priyanka , Deshmukh Shubham , Patravale Ajinkya , Desai Vikram , Chandam Dattatray , Sankpal Sandeep , Deshmukh Madhukar
Published: July 2022

The present works describe a highly efficient synthesis of pyrimidine derivatives through a Knoevenagel condensation followed by Michael addition and subsequent cyclization using novel designer Low Transition Temperature Mixture (LTTM) in Glycolic acid: Urea (1:1). The mixture afforded as a green solvent which plays a dual role as a reusable catalyst and solvent, simple to prepare and nontoxic. The thermal stability and working temperature range of low‐temperature mixture were identified by Thermogravimetric analysis and Differential Scanning Calorimetry. The pyrimidine derivatives synthesized via a one‐pot three‐component reaction of two moles of Barbituric/Thiobarbituric acid and one mole of aryl aldehydes reacted through Knoevenagel condensation followed by Michael addition and subsequent cyclization. The Knoevenagel intermediate formed at room temperate while at 80°C Knoevenagel intermediate further reacted with another mole of barbituric acid/Thiobarbituric acid and formed the cyclic compounds. The use of LTTM to yield vital pyrimidine molecules renders this protocol to cope with the current need for an efficient, cost‐effective, and eco‐friendly methodology.
Income, urbanisation and consumption of processed foods: Implications for nutrition and health policies for India
Authors: Mottaleb Khondoker Abdul , Mishra Ashok K.
Published: July 2022

India has witnessed a rapid rise in personal income, increased spending on infrastructure and construction and urbanisation in the past three decades. Households have changed their eating habits by purchasing more processed food. This study examines the factors affecting India's consumption of and expenditures on processed foods. The study uses information from three rounds of data collected by the National Sample Survey Organisation (NSSO) and probit and selection bias‐controlled tobit and ordinary least square (OLS) estimation procedures to estimate the empirical model. Findings reveal that the average expected per capita monthly spending on processed foods increased by about 77% between 1990–1991 and 2011–2012. An increase in total consumption expenditure and rapid urbanisation were the primary drivers of consumption and spending on processed foods by Indian households. Secondly, households with salaried or stable incomes were more likely to consume processed foods than other households. This study suggests public and private initiatives to improve human health and nutritional outcomes in Indian households. The government should strengthen food safety regulations related to processed food preparation, distribution and consumption.
MRI for the Detection of Small Bowel Ischemic Injury in Arterial Acute Mesenteric Ischemia: Preclinical Study in a Porcine Model
Authors: Garzelli Lorenzo , Felli Eric , Al‐Taher Mahdi , Barberio Manuel , Agnus Vincent , Plaforet Vincent , Bonvalet Fanny , Baiocchini Andrea , Nuzzo Alexandre , Paulatto Luisa , Vilgrain Valérie , Gallix Benoit , Diana Michele , Ronot Maxime
Published: July 2022

Background

MRI is the reference for the diagnosis of arterial cerebral ischemia, but its role in acute mesenteric ischemia (AMI) is poorly known.

Purpose

To assess MRI detection of early ischemic bowel lesions in a porcine model of arterial AMI.

Study Type

Prospective/cohort.

Animal Model

Porcine model of arterial AMI obtained by embolization of the superior mesenteric artery (seven pigs).

Field Strength/Sequence

A 5‐T. T1 gradient‐echo‐weighted‐imaging (WI), half‐Fourier‐acquisition‐single‐shot‐turbo‐spin‐echo, T2 turbo‐spin‐echo, true‐fast‐imaging‐with‐steady‐precession (True‐FISP), diffusion‐weighted‐echo‐planar (DWI).

Assessment

T1‐WI, T2‐WI, and DWI were performed before and continuously after embolization for 6 hours. The signal intensity (SI) of the ischemic bowel was assessed visually and quantitatively on all sequences. The apparent diffusion coefficient (ADC) was assessed.

Statistical Tests

Paired Student's t‐test or Mann–Whitney U‐test, significance at P < 0.05.

Results

One pig died from non‐AMI‐related causes. The remaining pigs underwent a median 5 h53 (range 1 h24–6 h01) of ischemia. Visually, the ischemic bowel showed signal hyperintensity on DWI‐b800 after a median 85 (57–276) minutes compared to the nonischemic bowel. DWI‐b800 SI significantly increased after 2 hours (+19%) and the ADC significant decrease within the first hour (−31%). The ischemic bowel was hyperintense on precontrast T1‐WI after a median 87 (70–171) minutes with no significant quantitative changes over time (P = 0.46–0.93). The ischemic bowel was hyperintense on T2‐WI in three pigs with a significant SI increase on True‐FISP after 1 and 2 hours.

Data Conclusion

Changes in SI and ADC can be seen early after the onset of arterial AMI with DWI. The value of T2‐WI appears to be limited.

Evidence Level

1

Technical Efficacy

Stage 2
Cell‐to‐cell transmission of HIV‐1 from provirus‐activated cells to resting naïve and memory human primary CD4 T cells is highly efficient and requires CD4 and F‐actin but not chemokine receptors
Authors: Lan Jie , Li Wei , Yu Richard , Syed Fahim , Yu Qigui
Published: July 2022

Latently infected cells harboring replication‐competent proviruses represent a major barrier to HIV‐1 cure. One major effort to purge these cells has focused on developing the “shock and kill” approach for forcing provirus reactivation to induce cell killing by viral cytopathic effects, host immune responses, or both. We conducted kinetic and mechanistic studies of HIV‐1 protein expression, virion production, and cell‐to‐cell virus transmission during provirus reactivation. Provirus‐activated ACH‐2 cells stimulated with romidepsin (RMD) or PMA produced Nef early, and then Env and Gag in parallel with the appearance of virions. Env on the surface of provirus‐activated cells and cellular F‐actin were critical in the formation of virological synapses to mediate cell‐to‐cell transmission of HIV‐1 from provirus‐activated cells to uninfected cells. This HIV‐1 cell‐to‐cell transmission was substantially more efficient than transmission seen via cell‐free virus spread and required F‐actin remodeling and CD4, but not chemokine receptors. Resting human primary CD4+ T cells including naïve and memory subpopulations and, especially the memory CD4+ T cells, were highly susceptible to HIV‐1 infection via cell‐to‐cell transmission. Cell‐to‐cell transmission of HIV‐1 from provirus‐activated cells was profoundly decreased by protease inhibitors (PIs) and neutralizing antibodies (nAbs) that recognize the CD4‐binding site (CD4bs) such as VRC01, but not by reverse transcriptase (RT) inhibitor Emtricitabine (FTC). Therefore, our results suggest that PIs with potent blocking abilities should be used in clinical application of the “shock and kill” approach, most likely in combination with CD4bs nAbs, to prevent new HIV‐1 infections.
Design of SSG‐1 gate‐based cost‐efficient reversible digital circuits using quantum‐dot cellular automata technology
Authors: Bhat Soha Maqbool , Ahmed Suhaib , Kakkar Vipan
Published: July 2022

In recent times, logic circuit designing with quantum‐dot cellular automata (QCA) technology is being comprehensively researched because of its inherent miniature size, ultra‐high speed, low power dissipation, and better switching frequency in the nanoregime. In this paper, QCA implementation of a 3 × 3 SSG‐1 reversible gate is first proposed. This gate is then used to design a reversible full adder, reversible 1‐bit comparator, and reversible 4:2 compressor. To evaluate the performance of the proposed QCA designs, an in‐depth comparison with existing designs has been performed. It is seen that the proposed SSG‐1 gate is efficient from the existing designs which eventually leads to efficient designs of adders, comparator, and compressor digital circuits. To further validate this, these digital circuits have also been compared with the literature and performance improvement is clearly observed in these circuits. In addition to this, energy dissipation analysis of all proposed logic gates and digital circuits is also performed for different kink energy levels using the QCA Pro tool and their respective energy dissipation maps are also obtained. Based on this, it is seen that the proposed designs are cost‐efficient and dissipate less energy which makes them more appropriate for designing higher‐order lower power circuits.
Sex differences in morphine sensitivity are associated with differential glial expression in the brainstem of rats with neuropathic pain
Authors: Boorman Damien C. , Keay Kevin A.
Published: July 2022

Chronic pain is more prevalent and reported to be more severe in women. Opioid analgesics are less effective in women and result in stronger nauseant effects. The neurobiological mechanisms underlying these sex differences have yet to be clearly defined, though recent research has suggested neuronal–glial interactions are likely involved. We have previously shown that similar to people, morphine is less effective at reducing pain behaviors in female rats. In this study, we used the immunohistochemical detection of glial fibrillary acidic protein (GFAP) expression to investigate sex differences in astrocyte density and morphology in six medullary regions known to be modulated by pain and/or opioids. Morphine administration had small sex‐dependent effects on overall GFAP expression, but not on astrocyte morphology, in the rostral ventromedial medulla, the subnucleus reticularis dorsalis, and the area postrema. Significant sex differences in the density and morphology of GFAP immunopositive astrocytes were detected in all six regions. In general, GFAP‐positive cells in females showed smaller volumes and reduced complexity than those observed in males. Furthermore, females showed lower overall GFAP expression in all regions except for the area postrema, the critical medullary region responsible for opioid‐induced nausea and emesis. These data support the possibility that differences in astrocyte activity might underlie the sex differences seen in the processing of opioids in the context of chronic neuropathic pain.
Observation of the Influence of Generalized Parity on the Alignment Spectra in the Periodically Modulated Warm Atomic Ensemble
Authors: Geng Xu‐xing , Yang Guoqing , Jin Kai , Tang Wangwang , Wu Shao‐ping , Huang Guang‐ming , Li Gao‐xiang
Published: July 2022

Periodically modulated systems with parity symmetry have been extensively investigated in recent years and exhibited various novel phenomena and potential applications in quantum technologies. In this study, a pump‐probe structure is used to observe the influence of generalized parity on the alignment spectra of magnetic resonance in a periodically biharmonic modulated warm atomic cesium ensemble. The alignment spectra are symmetric when the generalized parity of modulated Floquet atomic ensemble is present. The breaking of spectral symmetry is accompanied by the absence of generalized parity. The influence of generalized parity on atomic alignment polarization distribution is analyzed based on the perspective of the angular‐momentum probability surface. A necessary and sufficient condition for generalized parity to maintain spectral symmetry is verified experimentally and theoretically, providing a new perspective to investigative complex periodic modulation system. The results are universally applicable to atomic and solid‐state systems.
The cooling efficiency of s‐CO₂ microchannel heat sink compared with a water‐based design
Authors: Dehdashti Akhavan Navid , Abroug Foued , Arnaud Lionel , Hooman Kamel
Published: July 2022

High‐pressure drops characteristic of microchannel heat sinks (MCHS) is an issue that needs to be addressed to reduce the size of heat‐removing devices in compact electronic devices. Supercritical carbon dioxide (s‐CO₂) is a suitable candidate being proposed as an alternative coolant to enhance the cooling of the microchannel heat sink (MCHS), with high heat flux, due to its favorable thermophysical properties near its critical point. In this study, numerical simulations are conducted to evaluate the thermal and hydraulic performance of a channel for a designed heat sink with s‐CO₂ (at constant
) and compare it with conventional liquid coolant (water). The effect of coolants mass flow rate (
), channel aspect ratio (AR), and inlet temperatures on the thermal and hydraulic performance of one channel is studied by varying
from 0.004 to 0.03 kg/s and AR from 0.33 to 10. The results show that, for the same aspect ratio, same geometry, and constant heat flux, s‐CO₂ offers a higher overall heat transfer coefficient (32%) with a lower friction factor (pumping power) compared with the water at the same inlet temperature (T = 32°C). The results of pumping power comparison between two coolants reveal that for CO₂ in supercritical conditions (
, T = 32°C), the consumed power varies by change of the aspect ratio, which is 1.85 times lower than water for AR = 0.33 and is 3.6 times higher for AR = 10. However, in the subcooled state, the reverse effect of the aspect ratio is seen.
A wideband isolation technique using bezel coupled T‐type isolator for smartwatch MIMO applications
Authors: Baloch Babar A. , Qu Longyue , Zahid Zeeshan , Khan Adnan A.
Published: July 2022

This letter presents a wideband bezel coupled T‐type isolator, decoupling two antenna elements for smartwatch multiple‐input multiple‐out applications. The antenna elements consist of PIFA antennas operating at 2.45 GHz, covering Bluetooth and Wi‐Fi bands. The proposed T‐type isolator has been installed between the antenna elements made by inserting two slits in the bezel separated by 21 mm. The separated segment of the bezel is connected with the circular ground plane by a conducting strip and an inductor. In this way, the slits offer stray capacitance, and the capacitive coupling between the T‐type isolator has been utilized to achieve a wide isolation bandwidth. Meanwhile, the isolation can also be tuned using the gaps of the slits and the inductor. The design performance has been validated in simulations and measurement. The measured impedance bandwidth is higher than 120 MHz whereas the isolation bandwidth is 790 MHz with a maximum isolation higher than 22 dB. The measured envelop correlation coefficient is below 0.01. The proposed design is a good candidate for smartwatch applications.
Obesity contributes to the stealth peritoneal dissemination of ovarian cancer: a multi‐institutional retrospective cohort study
Authors: Iyoshi Shohei , Sumi Asami , Yoshihara Masato , Kitami Kazuhisa , Mogi Kazumasa , Uno Kaname , Fujimoto Hiroki , Miyamoto Emiri , Tano Sho , Yoshikawa Nobuhisa , Emoto Ryo , Matsui Shigeyuki , Kajiyama Hiroaki
Published: July 2022

Objective

The clinical significance of a higher BMI on the prognosis of ovarian cancer remains controversial; therefore, a more detailed analysis is demanded. This study investigated the impact of BMI on peritoneum‐specific recurrence to clarify the involvement of adipose tissue in the proliferation of cancer cells at sites of peritoneal dissemination.

Methods

Among 4,730 patients with malignant ovarian tumors, 280 diagnosed with International Federation of Gynecology and Obstetrics (FIGO) stage IIB to IIIC epithelial ovarian cancer and who underwent complete resection in the primary surgery were included in the present study.

Results

There were 42, 201, and 37 women in the low, normal, and high BMI groups, respectively. Peritoneum‐specific recurrence‐free survival and overall survival were both significantly shorter in patients with a high BMI than in those with a normal BMI (p = 0.028 and 0.018, respectively). No significant differences were observed in the distribution of sites of recurrence between these two groups. A multivariate analysis identified obesity as an independent prognostic factor in addition to pT3 tumor staging and positive ascites cytology.

Conclusions

Patients with a high BMI had a significantly worse prognosis than those with a normal BMI, and peritoneal adipose tissue may have contributed to this difference.
Rao algorithm based optimal Multi‐term FOPID controller for automatic voltage regulator system
Authors: Paliwal Nikhil , Srivastava Laxmi , Pandit Manjaree
Published: July 2022

This article presents a novel application of an optimal Multi‐term Fractional‐Order PID (MFOPID) controller for improving the performance of the automatic voltage regulator (AVR) system. A recently developed Rao algorithm has been used to optimize the proposed Multi‐term FOPID controller. The effectiveness of the Rao algorithm tuned Multi‐term FOPID controller for the AVR system has been proved by performing transient response, robustness, and performance analyses. Statistical analysis of the proposed Multi‐term FOPID controlled AVR system has been carried out to explore the most effective performance index among ITAE, ITSE, ISE, and IAE. The external disturbance rejection capability of the Rao algorithm‐tuned MFOPID controller has been examined by injecting external disturbances into the AVR system of different capacities at different times. The superiority of the proposed Multi‐term FOPID controller is validated by comparing the simulation results with recently employed various PID, PID‐Acceleration (PIDA), and FOPID controllers tuned by different metaheuristic algorithms. In addition, the behavior of the proposed Multi‐term FOPID controller has been examined in a real synchronous generator that is connected to a 10,000 MVA, 230 kV electric power network via a 210 MVA transformer using a MATLAB/Simulink environment. From the various simulation results, it has been concluded that the proposed Rao algorithm tuned optimal and robust Multi‐term FOPID controller has significantly improved the performance, robustness and stability of the AVR system.