bluuebunny/crossref_metadata_2025_split huggingface dataset:
Removal of anionic and cationic dyes using porous copolymer networks made from a Sonogashira cross‐coupling reaction of diethynyl iron (II) clathrochelate with various arylamines
Authors: Shetty Suchetha , Baig Noorullah , Al‐Mousawi Saleh , Alameddine Bassam 
Published: August 2022

AbstractFour copolymers containing alternating units of iron(II) clathrochelate with various arylamine CLA1‐4 were synthesized via a palladium‐catalyzed Sonogashira cross‐coupling reaction using an iron(II) clathrochelate synthon end‐capped with ethynyl groups with various brominated arylamine derivatives. Target copolymers CLA1‐4 were characterized by various instrumental analysis techniques, such as, solid‐state 13C‐nuclear magnetic resonance (SSNMR), Fourier transform infrared (FTIR), and X‐ray photoelectron spectroscopy (XPS). Thermogravimetric analysis (TGA) disclosed the superior thermal stability of the target copolymers with 10% weight loss temperature values up to ~340°C. Nitrogen adsorption measurements of CLA1‐4 using Brunauer–Emmet–Teller (BET) model revealed their porous nature with a surface area and porosity up to ~411 m2 g−1 and 0.411 cm3 g−1, respectively. Interestingly, CLA1‐4 disclose efficient adsorption of both cationic and anionic organic dyes, such as, Methylene Blue (MEB), Rhodamine B (RB), Congo Red (CR), Methyl orange (MO), and Acid orange 7 (AO7) from aqueous solutions. Furthermore, the isothermal adsorption study divulges the CLA4 uptake from aqueous solution of MEB and CR following the Langmuir model with a maximum adsorption capacity (qm) of 146.63 mg g−1 and 787.40 mg g−1, respectively.
Aggregation behavior of triblock terpolymer poly[n‐butyl acrylate‐block‐N‐isopropylacrylamide‐block‐2‐(dimethylamino)ethyl acrylate] at the air/water interface
Authors: Liu Dongxue , Wen Gangyao , Skandalis Athanasios , Pispas Stergios , He Guanying , Zhang Wang 
Published: August 2022

AbstractLangmuir film balance technique was used to study the subphase pH and temperature effects on the aggregation behavior of a dual‐responsive triblock terpolymer poly[n‐butyl acrylate‐block‐N‐isopropylacrylamide‐block‐2‐(dimethylamino)ethyl acrylate] (PnBA‐b‐PNIPAM‐b‐PDMAEA) at the air/water interface. Atomic force microscopy was used to observe the morphologies of its Langmuir–Blodgett (LB) films. At the interface, the terpolymer tends to form isolated circular micelles composed of hydrophobic PnBA cores and hydrophilic PNIPAM‐PDMAEA coronas. The limiting areas in the surface pressure–molecular area isotherms under acidic and alkaline conditions are larger than that under neutral conditions due to the larger interfacial stretching degrees of PNIPAM blocks, which results from the strong electrostatic repulsions of the fully protonated PDMAEA blocks underwater in the acidic case. In our minds, the hysteresis degrees of the compression−expansion cycles under different subphase pH conditions should mainly depend on the initial stretching degrees of the hydrophilic blocks. Under acidic conditions, the isotherms shift toward small areas with the increase of temperature due to the increased solubility of PNIPAM blocks. However, under alkaline conditions, the isotherms significantly exhibit the lower critical solution temperature behavior of PNIPAM blocks, which is a good example to build up the relationship between the interfacial and solution properties of block copolymers.
Iterative learning control for integrated system of robot and machine tool
Authors: Ta Thanh‐Quan , Chen Shyh‐Leh 
Published: August 2022

AbstractThis study is concerned with the integrated system of a robot and a machine tool. The major task of robot is loading the workpiece to the machine tool for contour cutting. An iterative learning control (ILC) algorithm is proposed to improve the accuracy of the finished product. The proposed ILC is to modify the input command of the next machining cycle for both robot and machine tool to iteratively enhance the output accuracy of the robot and machine tool. The modified command is computed based on the current tracking/contour error. For the ILC of the robot, tracking error is considered as the control objective to reduce the tracking error of motion path, in particular, the error at the endpoint. Meanwhile, for the ILC of the machine tool, contour error is considered as the control objective to improve the contouring accuracy, which determines the quality of machining. In view of the complicated contour error model, the equivalent contour error instead of the actual contour error is taken as the control objective in this study. One challenge for the integrated system is that there exists an initial state error for the machine tool dynamics, violating the basic assumption of ILC. It will be shown in this study that the effects of initial state error can be significantly reduced by the ILC of the robot. The proposed ILC algorithm is verified experimentally on an integrated system of commercial robot and machine tool. The experimental results show that the proposed ILC can achieve more than 90% of reduction on both the RMS tracking error of the robot and the RMS contour error of the machine tool within six learning iterations. The results clearly validate the effectiveness of the proposed ILC for the integrated system.
Improvement of steady‐state performance for discrete‐valued input control with an integrator utilizing feedback control of integrated value of input
Authors: Tanemura Masaya , Chida Yuichi , Terada Shohei , Iida Tomoharu 
Published: August 2022

AbstractIn this study, we considered the regulator problem for discrete‐valued input control with an integrator. In some cases, the state does not converge to the origin in the discrete‐valued input control when the plant possesses an integrator. Therefore, a method that adds minor feedback control to the integrated value of the input was proposed. However, the effect of the feedback control of the integrated value of the input was not theoretically interpreted, and the feedback gain for the state of the integrated value of the input was designed with trial and error. Herein, we clarify the effect of feedback control on the integrated value of the input. Furthermore, we reveal that the trade‐off between the steady‐state and transient performances is controlled by one parameter, that is, the feedback gain for the integrated value of the input.
Hybrid Electrolytes Enabling in‐situ Interphase Protection and Suppressed Electrode Dissolution for Aqueous Sodium‐Ion Batteries
Authors: Wang Hao , Liu Tingting , Du Xiaofan , Wang Jinzhi , Yang Yuanyuan , Qiu Huayu , Lu Guoli , Li Hongliang , Chen Zheng , Zhao Jingwen , Cui Guanglei 
Published: August 2022

AbstractAqueous sodium‐ion batteries are promising candidates for grid‐scale energy storage due to their high safety and low cost. However, the constant dissolution of vanadium‐based electrodes and protective solid‐electrolyte interphase (SEI) in aqueous electrolytes severely limits the cycle life. Herein, using adiponitrile as a functional co‐solvent, we designed a super‐concentrated aqueous sodium electrolyte (Na+/H2O=1, molar ratio) to confine almost all water molecules within the primary solvation shell of Na+ with decreased activity. Such a unique solvation structure not only expands the electrochemical stability window of the electrolyte to 2.75 V, but also greatly alleviates the dissolution of vanadium‐based electrodes and NaF‐rich SEI. The assembled Na3V2(PO4)3/NaTi2(PO4)3 battery delivers an average Coulombic efficiency of 99.6 % with 71 % capacity retention after 1000 cycles at 5 C. In addition, the freezing point of the electrolyte could be reduced −79 °C while retaining appreciable low‐temperature conductivity due to the disrupted hydrogen bond among water molecules.
Exploring the potential of machine learning for more efficient development and production of biopharmaceuticals
Authors: Puranik Amita , Dandekar Prajakta , Jain Ratnesh 
Published: August 2022

AbstractPrinciples of Industry 4.0 direct us to predict how pharmaceutical operations and regulations may exist with automation, digitization, artificial intelligence (AI), and real time data acquisition. Machine learning (ML), a sub‐discipline of AI, involves the use of statistical tools to extract the desired information either through understanding the underlying patterns in the information or by development of mathematical relationships among the critical process parameters (CPPs) and critical quality attributes (CQAs) of biopharmaceuticals. ML is still in its infancy for directly supporting the quality‐by‐design based development and manufacturing of biopharmaceuticals. However, adoption of ML‐based models in place of conventional multi‐variate‐data‐analysis (MVDA) is increasing with the accumulation of large‐scale data. This has been majorly contributed by the real‐time monitoring of process variables and quality attributes of products through the implementation of process analytical technology in biopharmaceutical manufacturing. All aspects of healthcare, from drug design to product distribution, are complex and multidimensional. Thus, ML‐based approaches are being applied to achieve sophistication, accuracy, flexibility and agility in all these areas. This review discusses the potential of ML for addressing the complex issues in diverse areas of biopharmaceutical development, such as biopharmaceuticals design and assessment of early stage development, upstream and downstream process development, analysis, characterization and prediction of post‐translational modifications (PTMs), formulation, and stability studies. Moreover, the challenges in acquisition, cleaning and structuring the bioprocess data, which is one of the major hurdles in implementation of ML in biopharma industry, have also been discussed. Regulatory perspectives on implementation of AI/ML in the biopharma sector have also been briefly discussed. This article is a bird's eye view on the recent developments and applications of ML in overcoming the challenges for adopting “Industry – 4.0” in the biopharma industry.
Single access TAVR. How “minimalist” do we need to be?
Authors: Helmy Tarek , Mina George 
Published: August 2022

Highlights

Vascular complications remain one of the main issues with transcatheter aortic valve replacement (TAVR).
The minimalist approach for TAVR is becoming more widely adopted.
There has to be a careful evaluation of the risk/benefit ratio for any procedural strategy.
Valve implantation for successful sealing of a balloon predilatation‐induced annular rupture during transcatheter aortic valve replacement
Authors: Liu Jian‐Di , Zhang Shi‐Yuan , Wu Yan‐Qing , Gong Ren 
Published: August 2022

AbstractAnnular rupture is a rare and dreaded complication of transcatheter aortic valve replacement (TAVR) and even rarer when caused by predilatation balloon aortic valvuloplasty. This complication often presents as sudden cardiac tamponade with hypotension and requires urgent intervention. The traditional rescue strategy for patients with annular rupture is emergency surgical repair. However, the mortality rate is still high, considering that most patients who undergo TAVR are not candidates for conventional cardiac surgery. Therefore, there is a need for additional emergency treatment strategies to decrease mortality. This report describes a case of predilatation‐induced annular rupture during TAVR that was successfully sealed at the rupture site by valve implantation. This case suggests that continuing with valve deployment may be a successful treatment for predilatation‐induced annular rupture during TAVR.
Gingival recessions caused by Herpes Simplex Virus in a patient with COVID‐19 infection
Authors: Franceschi Debora , Di Gianfilippo Riccardo , Rubino Ida , Serni Lapo , Pini Prato Giovan Paolo 
Published: August 2022

AbstractHerpes Simplex Virus type 1 (HSV‐1) is a very common infection often localized in the mucocutaneous junction of the lip. Rarely, it could be detected also in periodontal tissues, associated with an elevated risk of periodontal disease progression and gingival recessions. Recently, HSV‐1 and numerous co‐infections have been reported in literature associated with the Coronavirus and subsequent COVID‐19 disease. This report illustrates a case of HSV‐1 in a patient with Covid‐19 infection, showing the presence of ulcers and vesicles on the gingival margin of maxillary teeth associated with soreness and pain. The histology highlighted the presence of intraepithelial cell ballooning, confirming the diagnosis of HSV‐1 infection.
Interruption of breast cancer care and importance of inter‐hospital cooperation during the COVID‐19 pandemic: A case report of advanced breast cancer in Fukushima, Japan
Authors: Ozaki Akihiko , Kaneda Yudai , Senoo Yuki , Wada Masahiro , Kurokawa Tomohiro , Sawano Toyoaki , Tsubokura Masaharu , Tanimoto Tetsuya , Kanemoto Yoshiaki , Ejiri Tomozo , Shimmura Hiroaki , Kanzaki Norio 
Published: August 2022

AbstractWe experienced the case of a patient with advanced breast cancer who failed to receive comprehensive care despite regular video conferencing with her physician during the COVID‐19 pandemic, resulting in delayed detection of liver metastasis. Inter‐hospital collaboration is required to provide uninterrupted cancer care to those disproportionately affected by crises.
Neurodegenerative disorder and diffuse brain calcifications due to FARSB mutation in two siblings
Authors: Karimzadeh Parvaneh , Rezakhani Sepideh , Miryounesi Mohammad , Alijanpour Sahar 
Published: August 2022

AbstractPathogenic mutations in the FARSB gene are associated with neurodevelopmental disorder involving the brain, liver, and lungs. We report genetic analysis of a family including two affected members with this disorder, which revealed a homozygous pathogenic missense variant, FARSB: NM_005687.4:c.853G > A:p.E285K in both affected patients. The parents were heterozygous for this variant.
Targeted Enzymatic VLP‐Nanoreactors with β‐Glucocerebrosidase Activity as Potential Enzyme Replacement Therapy for Gaucher's Disease
Authors: Chauhan Kanchan , Olivares‐Medina Cindy N. , Villagrana‐Escareño Maria V. , Juárez‐Moreno Karla , Cadena‐Nava Rubén D. , Rodríguez‐Hernández Ana G. , Vazquez‐Duhalt Rafael 
Published: August 2022

AbstractGaucher disease is a genetic disorder and the most common lysosomal disease caused by the deficiency of enzyme β‐glucocerebrosidase (GCase). Although enzyme replacement therapy (ERT) is successfully applied using mannose‐exposed conjugated glucocerebrosidase, the lower stability of the enzyme in blood demands periodic intravenous administration that adds to the high cost of treatment. In this work, the enzyme β‐glucocerebrosidase was encapsulated inside virus‐like nanoparticles (VLPs) from brome mosaic virus (BMV), and their surface was functionalized with mannose groups for targeting to macrophages. The VLP nanoreactors showed significant GCase catalytic activity. Moreover, the Michaelis–Menten constants for the free GCase enzyme (KM=0.29 mM) and the functionalized nanoreactors (KM=0.32 mM) were similar even after chemical modification. Importantly, the stability of enzymes under physiological conditions (pH 7.4, 37 °C) was enhanced by ≈11‐fold after encapsulation; this is beneficial for obtaining a higher blood circulation half‐life, which may decrease the cost of therapy by reducing the requirement of multiple intravenous injections. Finally, the mannose receptor targeted enzymatic nanoreactors showed enhanced internalization into macrophage cells. Thus, the catalytic activity and cell targeting suggest the potential of these nanoreactors in ERT of Gaucher's disease.
A novel deep neural network based marine predator model for effective classification of big data from social Internet of Things
Authors: Shaji B. , Lal Raja Singh R. , Nisha K. L. 
Published: August 2022

SummarySocial Internet of Things (SIoT) is considered as one of the most recently evolved topics that connects people and object, object and object as well as people and people. The SIoT and big data provide an exact representation of IoT and social system for human progression characterization. Numerous machine learning techniques are employed to classify the data gathered from SIoT in a more powerful way. In this article, a deep neural network based marine predator (DRNN‐MP) algorithm is proposed in classifying big data. Here, an adaptive Savitzky–Golay filter is employed for selecting the subset and to eliminate undesirable data, as well as different noises. The big data databases are reduced using a Hadoop map reducing framework thereby enhancing the performances of the proposed approach. In addition to this, a modified relief technique is employed to select optimal features thereby performing better classification. The testing and training process based on the proposed approach for optimal classification of features from the big data considers four different databases namely coronary illness, GPS trajectories, localization data, and water treatment plant obtained from UCI machine learning repository. In addition to this, the proposed approach is evaluated for diverse performance measures namely accuracy, precision, specificity, sensitivity, throughput, and energy consumption. Finally, the proposed approach is compared for various metrics to illustrate the effectiveness of the system and the results demonstrated that the accuracy of our work is 98.25%.
Efficient privacy protection authentication protocol for vehicle network in5G
Authors: Zhang Guixian , Zhao Xiaoyu , Chen Menglu , Ma Shuyi 
Published: August 2022

SummaryThe traditional internet of vehicles (IoV) identity authentication system generally has the security risk that the center is not trusted. In the 5G IoV, a large number of deployed 5G base stations are integrated into it, which has further developed the technologies such as seamless handover, load balancing, and security authentication. The development of the IoV has largely alleviated the traffic pressure and improved the driving efficiency. However, there are many privacy security problems to be solved in 5G IoV. Therefore, with the characteristics of blockchain distribution, traceability, and non‐tampering, an efficient privacy protection authentication protocol based on blockchain is proposed. The method includes two parts: identity registration and authentication. Vehicles and other traffic participants obtain a public identity block through identity registration before accessing the IoV. In the subsequent authentication, the communication parties use this identity block for anonymous authentication. The analysis results based on the formal analysis software Scyther are safe. The security analysis shows that the scheme could meet the security requirements in the IoV. At the same time, the comparison with the existing schemes shows that this scheme has lower computation overhead and communication cost.
A holistic evaluation methodology for configuring production data centers
Authors: Wen Yingying , Zhang Yiming , Cheng Guanjie , Deng Shuiguang , Yin Jianwei 
Published: August 2022

SummaryPerformance evaluation is the basis for choosing appropriate system‐level configurations for large‐scale data centers. While the change of a system‐level configuration would impact lots of jobs in the data centers, traditional load‐testing benchmarks are not sufficient to support the decision‐making because they cannot accurately reproduce the complex behaviors of a large number of jobs. Therefore, we expect to further evaluate the system configuration based on the production environment. However, there are technical challenges, namely, the lack of a holistic evaluation method that can unite the evaluation results of various jobs, and the uninterruptable production environment that should not be affected by the evaluation procedure. To address these challenges, we propose a holistic performance evaluation methodology and design its implementation platform. We introduce a simple but powerful performance metric, ERU (effectiveness of resource usage), and combine the ERU of involved jobs into a summarized value to measure the effect of a configuration change. We validate our ERU metric by comparing it with the CPI (Cycle per Instruction) and QPS (query per second) metrics, deploy the platform to production data centers and demonstrate the effectiveness for measuring system‐level configurations of both software (JVM compiler update) and hardware (NUMA on/off) to save 14.44% and 11% resources respectively in advance.
Work involvement and work satisfaction of psychotherapists—A nationwide online survey among psychotherapeutic practitioners in Germany
Authors: Gossmann Katharina , Rosner Rita , Barke Antonia 
Published: August 2022

AbstractObjectiveThe aim of this study was to explore psychotherapist characteristics associated with work involvement and work satisfaction among psychotherapists in Germany.MethodIn total N = 1358 psychotherapeutic practitioners with different levels of training participated in our nationwide online survey, we assessed work involvement and its sub‐concepts of healing involvement (HI), stressful involvement (SI) and work satisfaction (WS) using the Therapist Work Involvement Scale (TWIS) and combined HI and SI into practice patterns.ResultsIn our study, the levels of HI and WS were high, whereas SI was low. The percentage of effective practice patterns was higher than in previous studies, whereas challenging practice patterns were lower. HI, SI and WS were associated with gender and age, indicating that male and younger participants showed more SI but less HI and WS. Psychodynamic therapists reported more SI and WS. The number of weekly therapy sessions was related to HI, SI and WS. Furthermore, HI was positively related to WS and negatively to SI, while SI and WS were negatively correlated.ConclusionOur results indicated that therapist characteristics influenced their work involvement and work satisfaction. Therefore, therapist training and interventions should consider individualized approaches based on the relevant therapist characteristics to foster HI and WS while reducing SI. One could speculate whether the changes in psychotherapeutic training may have already contributed to improved practice patterns over the last decades.
Upcycling End of Life Solar Panels to Lithium‐Ion Batteries Via a Low Temperature Approach
Authors: Boon Tay Yeow , Sim Ying , Ang Koon Keong Jeremy , Iszaki Bin Patdillah Muhammad , Min Chua Huei , Tang Jun Jie Ernest , Srinivasan Madhavi , Mathews Nripan 
Published: August 2022

AbstractThe massive adoption of renewable energy especially photovoltaic (PVs) panels is expected to create a huge waste stream once they reach end‐of‐life (EoL). Despite having the highest embodied energy, present photovoltaic recycling neglects the high purity silicon found in the PV cell. Herein, a scalable and low energy process is developed to recover pristine silicon from EoL solar panel through a method which avoids energy‐intensive high temperature processes. The extracted silicon was upcycled to form lithium‐ion battery anodes with performances comparable to as‐purchased silicon. The anodes retained 87.5 % capacity after 200 cycles while maintaining high coulombic efficiency (>99 %) at 0.5 A g−1 charging rate. This simple and scalable process to upcycle EoL‐solar panels into high value silicon‐based anodes can narrow the gap towards a net‐zero waste economy.