bluuebunny/crossref_metadata_2025 huggingface dataset:
Comparison of Different Physical Activity Measures in a Cardiac Rehabilitation Program: A Prospective Study
Authors: Alharbi Muaddi , Bauman Adrian , Alabdulaali Mohammed , Neubeck Lis , Smith Sidney , Naismith Sharon , Jeon Yun-Hee , Tofler Geoffrey , Surour Atef , Gallagher Robyn
Published: February 2022

Concordant assessments of physical activity (PA) and related measures in cardiac rehabilitation (CR) is essential for exercise prescription. This study compared exercise measurement from an in-person walk test; wearable activity tracker; and self-report at CR entry, completion (8-weeks) and follow-up (16-weeks). Forty patients beginning CR completed the Six-Minute Walk Test (6MWT), Physical Activity Scale for the Elderly (PASE), and wore Fitbit-Flex for four consecutive days including two weekend days. The sample mean age was 66 years; 67% were male. Increased exercise capacity at CR completion and follow-up was detected by a 6MWT change in mean distance (39 m and 42 m; p = 0.01, respectively). Increased PA participation at CR completion was detected by Fitbit-Flex mean change in step counts (1794; p = 0.01). Relative changes for Fitbit-Flex step counts and a 6MWT were consistent with previous research, demonstrating Fitbit-Flex’s potential as an outcome measure. With four days of data, Fitbit-Flex had acceptable ICC values in measuring step counts and MVPA minutes. Fitbit-Flex steps and 6MWT meters are more responsive to changes in PA patterns following exposure to a cardiac rehabilitation program than Fitbit-Flex or PASE-estimated moderate–vigorous PA (MVPA) minutes. Fitbit-Flex step counts provide a useful additional measure for assessing PA outside of the CR setting and accounts for day-to-day variations. Two weekend days and two weekdays are needed for Fitbit-Flex to estimate PA levels more precisely.
Step Length Estimation Using the RSSI Method in Walking and Jogging Scenarios
Authors: Yang Zanru , Tran Le Chung , Safaei Farzad
Published: February 2022

In this paper, human step length was estimated based on wireless channel properties and the received signal strength indicator (RSSI) method. Path loss between two ankles of the person under test was converted from the RSSI, which was measured using our developed wearable transceivers with embedded micro-controllers in four scenarios, namely indoor walking, outdoor walking, indoor jogging, and outdoor jogging. For brevity, we call it on-ankle path loss. The histogram of the on-ankle path loss showed clearly that there were two humps, where the second hump was closely related to the maximum path loss, which, in turn, corresponded to the step length. This histogram can be well approximated by a two-term Gaussian fitting curve model. Based on the histogram of the experimental data and the two-term Gaussian fitting curve, we propose a novel filtering technique to filter out the path loss outliers, which helps set up the upper and lower thresholds of the path loss values used for the step length estimation. In particular, the upper threshold was found to be on the right side of the second Gaussian hump, and its value was a function of the mean value and the standard deviation of the second Gaussian hump. Meanwhile, the lower threshold lied on the left side of the second hump and was determined at the point where the survival rate of the measured data fell to 0.68, i.e., the cumulative distribution function (CDF) approached 0.32. The experimental data showed that the proposed filtering technique resulted in high accuracy in step length estimation with errors of only 10.15 mm for the indoor walking, 4.40 mm for the indoor jogging, 4.81 mm for the outdoor walking, and 10.84 mm for the outdoor jogging scenarios, respectively.
CFD-Based Flow Channel Optimization and Performance Prediction for a Conical Axial Maglev Blood Pump
Authors: Yang Weibo , Peng Sijie , Xiao Weihu , Hu Yefa , Wu Huachun , Li Ming
Published: February 2022

Ventricular assist devices or total artificial hearts can be used to save patients with heart failure when there are no donors available for heart transplantation. Blood pumps are integral parts of such devices, but traditional axial flow blood pumps have several shortcomings. In particular, they cause hemolysis and thrombosis due to the mechanical contact and wear of the bearings, and they cause blood stagnation due to the separation of the front and rear guide wheel hubs and the impeller hub. By contrast, the implantable axial flow, maglev blood pump has the characteristics of no mechanical contact, no lubrication, low temperature rise, low hemolysis, and less thrombosis. Extensive studies of axial flow, maglev blood pumps have shown that these pumps can function in laminar flow, transitional flow, and turbulent flow, and the working state and performance of such pumps are determined by their support mechanisms and flow channel. Computational fluid dynamics (CFD) is an effective tool for understanding the physical and mechanical characteristics of the blood pump by accurately and effectively revealing the internal flow field, pressure–flow curve, and shear force distribution of the blood pump. In this study, magnetic levitation supports were used to reduce damages to the blood and increase the service life of the blood pump, and a conical impeller hub was used to reduce the speed, volume, and power consumption of the blood pump, thereby facilitating implantation. CFD numerical simulation was then carried out to optimize the structural parameters of the conical axial maglev blood pump, predict the hemolysis performance of the blood pump, and match the flow channel and impeller structure. An extracorporeal circulation simulation platform was designed to test whether the hydraulic characteristics of the blood pump met the physiological requirements. The results showed that the total pressure distribution in the blood pump was reasonable after optimization, with a uniform pressure gradient, and the hemolysis performance was improved.
Design of an Estimator Using the Artificial Neural Network Technique to Characterise the Braking of a Motor Vehicle
Authors: Garrosa María , Olmeda Ester , Díaz Vicente , Mendoza-Petit Mᵃ Fernanda
Published: February 2022

Automatic systems are increasingly being applied in the automotive industry to improve driving safety and passenger comfort, reduce traffic and increase energy efficiency. The objective of this work is focused on improving the automatic brake assistance systems of motor vehicles trying to imitate human behaviour but correcting possible human errors such as distractions, lack of visibility or time reaction. The proposed system can optimise the intensity of the braking according to the available distance to carry out the manoeuvre and the vehicle speed to be as less aggressive as possible, thus giving priority to the comfort of the driver. A series of tests are carried out in this work with a vehicle instrumented with sensors that provide real-time information about the braking system. The data obtained experimentally during the dynamic tests are used to design an estimator using the Artificial Neural Network (ANN) technique. This information makes it possible to characterise all braking situations based on the pressure of the brake circuit, the type of manoeuvre and the test speed. Thanks to this ANN, it is possible to estimate the requirements of the braking system in real driving situations and carry out the manoeuvres automatically. Experiments and simulations verified the proposed method for the estimation of braking pressure in real deceleration scenarios.
A Proof-of-Concept IoT System for Remote Healthcare Based on Interoperability Standards
Authors: Lemus-Zúñiga Lenin-Guillermo , Félix Juan M. , Fides-Valero Alvaro , Benlloch-Dualde José-Vte. , Martinez-Millana Antonio
Published: February 2022

The Internet of Things paradigm in healthcare has boosted the design of new solutions for the promotion of healthy lifestyles and the remote care. Thanks to the effort of academia and industry, there is a wide variety of platforms, systems and commercial products enabling the real-time information exchange of environmental data and people’s health status. However, one of the problems of these type of prototypes and solutions is the lack of interoperability and the compromised scalability in large scenarios, which limits its potential to be deployed in real cases of application. In this paper, we propose a health monitoring system based on the integration of rapid prototyping hardware and interoperable software to build system capable of transmitting biomedical data to healthcare professionals. The proposed system involves Internet of Things technologies and interoperablility standards for health information exchange such as the Fast Healthcare Interoperability Resources and a reference framework architecture for Ambient Assisted Living UniversAAL.
Fast Localization and Characterization of Underground Targets with a Towed Transient Electromagnetic Array System
Authors: Wang Lijie , Zhang Shuang , Chen Shudong , Luo Chaopeng
Published: February 2022

A fast inversion algorithm combined with the transient electromagnetic (TEM) detection system has important significance for improving the detection efficiency of unexploded ordnance. The traditional algorithms, such as differential evolution or Gauss–Newton algorithms, usually require tens to thousands of iterations to locate the underground target. A new algorithm with a magnetic gradient tensor and singular value decomposition (SVD) to estimate the target position and characterization quickly and accurately is proposed in this paper. Two modes of magnetic gradient tensor are constructed to accurately locate shallow and deep targets, respectively. The SVD algorithm is applied to the responses to estimate the electromagnetic characteristics of the target quickly and accurately. To verify the performance of the proposed algorithm, a towed TEM sensor is designed, which is constructed with three transmitting coils and nine three-component receiving coils arranged in a 3 × 3 array. Field experiments in survey and cued modes were taken to verify the performance of the proposed algorithm and the towed system. Results show that the magnetic gradient tensor algorithm proposed in this paper can accurately locate a single target within 2.0 m depth, and the error of depth is no more than 8 cm. Even for overlapping response of multi targets, the error of depth is no more than 12 cm. The underground target can be accurately characterized by the SVD algorithm. For targets with depths over 2.0 m, the signal-to-noise ratio of characteristic response estimated by SVD is higher than that of the traditional method. The proposed method needs approximately 40 ms, only 1% of the traditional one, considerably improving detection efficiency and laying a theoretical and experimental foundation for real-time data processing.
Multi-Agent Reinforcement Learning for Joint Cooperative Spectrum Sensing and Channel Access in Cognitive UAV Networks
Authors: Jiang Weiheng , Yu Wanxin , Wang Wenbo , Huang Tiancong
Published: February 2022

This paper studies the problem of distributed spectrum/channel access for cognitive radio-enabled unmanned aerial vehicles (CUAVs) that overlay upon primary channels. Under the framework of cooperative spectrum sensing and opportunistic transmission, a one-shot optimization problem for channel allocation, aiming to maximize the expected cumulative weighted reward of multiple CUAVs, is formulated. To handle the uncertainty due to the lack of prior knowledge about the primary user activities as well as the lack of the channel-access coordinator, the original problem is cast into a competition and cooperation hybrid multi-agent reinforcement learning (CCH-MARL) problem in the framework of Markov game (MG). Then, a value-iteration-based RL algorithm, which features upper confidence bound-Hoeffding (UCB-H) strategy searching, is proposed by treating each CUAV as an independent learner (IL). To address the curse of dimensionality, the UCB-H strategy is further extended with a double deep Q-network (DDQN). Numerical simulations show that the proposed algorithms are able to efficiently converge to stable strategies, and significantly improve the network performance when compared with the benchmark algorithms such as the vanilla Q-learning and DDQN algorithms.
Information Fusion in Autonomous Vehicle Using Artificial Neural Group Key Synchronization
Authors: Khan Mohammad Zubair , Sarkar Arindam , Ghandorh Hamza , Driss Maha , Boulila Wadii
Published: February 2022

Information fusion in automated vehicle for various datatypes emanating from many resources is the foundation for making choices in intelligent transportation autonomous cars. To facilitate data sharing, a variety of communication methods have been integrated to build a diverse V2X infrastructure. However, information fusion security frameworks are currently intended for specific application instances, that are insufficient to fulfill the overall requirements of Mutual Intelligent Transportation Systems (MITS). In this work, a data fusion security infrastructure has been developed with varying degrees of trust. Furthermore, in the V2X heterogeneous networks, this paper offers an efficient and effective information fusion security mechanism for multiple sources and multiple type data sharing. An area-based PKI architecture with speed provided by a Graphic Processing Unit (GPU) is given in especially for artificial neural synchronization-based quick group key exchange. A parametric test is performed to ensure that the proposed data fusion trust solution meets the stringent delay requirements of V2X systems. The efficiency of the suggested method is tested, and the results show that it surpasses similar strategies already in use.
Near-Infrared Spectral Characteristic Extraction and Qualitative Analysis Method for Complex Multi-Component Mixtures Based on TRPCA-SVM
Authors: Zhang Guiyu , Tuo Xianguo , Zhai Shuang , Zhu Xuemei , Luo Lin , Zeng Xianglin
Published: February 2022

Quality identification of multi-component mixtures is essential for production process control. Artificial sensory evaluation is a conventional quality evaluation method of multi-component mixture, which is easily affected by human subjective factors, and its results are inaccurate and unstable. This study developed a near-infrared (NIR) spectral characteristic extraction method based on a three-dimensional analysis space and establishes a high-accuracy qualitative identification model. First, the Norris derivative filtering algorithm was used in the pre-processing of the NIR spectrum to obtain a smooth main absorption peak. Then, the third-order tensor robust principal component analysis (TRPCA) algorithm was used for characteristic extraction, which effectively reduced the dimensionality of the raw NIR spectral data. Finally, on this basis, a qualitative identification model based on support vector machines (SVM) was constructed, and the classification accuracy reached 98.94%. Therefore, it is possible to develop a non-destructive, rapid qualitative detection system based on NIR spectroscopy to mine the subtle differences between classes and to use low-dimensional characteristic wavebands to detect the quality of complex multi-component mixtures. This method can be a key component of automatic quality control in the production of multi-component products.
An Instrumented Apartment to Monitor Human Behavior: A Pilot Case Study in the NeuroTec Loft
Authors: Gerber Stephan M. , Single Michael , Knobel Samuel E. J. , Schütz Narayan , Bruhin Lena C. , Botros Angela , Naef Aileen C. , Schindler Kaspar A. , Nef Tobias
Published: February 2022

For patients suffering from neurodegenerative disorders, the behavior and activities of daily living are an indicator of a change in health status, and home-monitoring over a prolonged period of time by unobtrusive sensors is a promising technology to foster independent living and maintain quality of life. The aim of this pilot case study was the development of a multi-sensor system in an apartment to unobtrusively monitor patients at home during the day and night. The developed system is based on unobtrusive sensors using basic technologies and gold-standard medical devices measuring physiological (e.g., mobile electrocardiogram), movement (e.g., motion tracking system), and environmental parameters (e.g., temperature). The system was evaluated during one session by a healthy 32-year-old male, and results showed that the sensor system measured accurately during the participant’s stay. Furthermore, the participant did not report any negative experiences. Overall, the multi-sensor system has great potential to bridge the gap between laboratories and older adults’ homes and thus for a deep and novel understanding of human behavioral and neurological disorders. Finally, this new understanding could be utilized to develop new algorithms and sensor systems to address problems and increase the quality of life of our aging society and patients with neurological disorders.
Algorithm of Stability-Analysis-Based Feature Selection for NIR Calibration Transfer
Authors: Zhang Zheyu , Li Yaoxiang , Li Chunxu , Wang Zichun , Chen Ya
Published: February 2022

For conventional near-infrared spectroscopy (NIR) technology, even within the same sample, the NIR spectral signal can vary significantly with variation of spectrometers and the spectral collection environment. In order to improve the applicability and application of NIR prediction models, effective calibration transfer is essential. In this study, a stability-analysis-based feature selection algorithm (SAFS) for NIR calibration transfer is proposed, which is used to extract effective spectral band information with high stability between the master and slave instruments during the calibration transfer process. The stability of the spectrum bands shared between the master and slave instruments is used as the evaluation index, and the genetic algorithm was used to select suitable thresholds to filter out the spectral feature information suitable for calibration transfer. The proposed SAFS algorithm was applied to two near-infrared datasets of corn oil content and larch wood density. Simultaneously, its calibration transfer performances were compared with two classical feature selection methods. The effects of different preprocessing algorithms and calibration transfer algorithms were also assessed. The model with the feature variables selected by the SAFS obtained the best prediction. The SAFS algorithm can simplify the spectral data to be transferred and improve the transfer efficiency, and the universality of the SAFS allows it to be used to optimize calibration transfer in various situations. By combining different preprocessing and classic feature selection methods with this, the sensitivity of the correlation between spectral data and component information are improved significantly, as well as the effect of calibration transfer, which will be deeply developed.
Systematic Review on the Effectiveness of Essential and Carrier Oils as Skin Penetration Enhancers in Pharmaceutical Formulations
Authors: Alhasso Bahjat , Ghori Muhammad Usman , Conway Barbara R.
Published: February 2022

Oils, including essential oils and their constituents, are widely reported to have penetration enhancement activity and have been incorporated into a wide range of pharmaceutical formulations. This study sought to determine if there is an evidence base for the selection of appropriate oils for particular applications and compare their effectiveness across different formulation types. A systematic review of the data sources, consisting of Google Scholar, EMBASE, PubMed, Medline, and Scopus, was carried out and, following screening and quality assessment, 112 articles were included within the analysis. The research was classified according to the active pharmaceutical ingredient, dosage form, in vitro/in vivo study, carrier material(s), penetration enhancers as essential oils, and other chemical enhancers. The review identified four groups of oils used in the formulation of skin preparations; in order of popularity, these are terpene-type essential oils (63%), fatty acid-containing essential oils (29%) and, finally, 8% of essential oils comprising Vitamin E derivatives and miscellaneous essential oils. It was concluded that terpene essential oils may have benefits over the fatty acid-containing oils, and their incorporation into advanced pharmaceutical formulations such as nanoemulsions, microemulsions, vesicular systems, and transdermal patches makes them an attractive proposition to enhance drug permeation through the skin.
Breastfeeding Awareness and Empowerment (BAE): A Black Women-Led Approach to Promoting a Multigenerational Culture of Health
Authors: Duncan Rebecca , Coleman Jabina , Herring Sharon , Kawan Meg , Santoro Christy , Atre Meghana , Mason Aleigha , Moore Shawana , Kumar Aparna
Published: February 2022

(1) Background: Critical gaps in the U.S. healthcare system perpetuate adverse reproductive health outcomes for Black people. Grounded in reproductive justice and trauma-informed care, Breastfeeding Awareness and Empowerment (BAE) has developed a program titled BAE Cafe to directly address these gaps by providing community-based lactation and perinatal mental health support. A literature review identified key programmatic gaps, namely, access to knowledge relevant to troubleshooting breastfeeding, peer support, community support and healthcare system support, and system-level factors that impede families and communities from accessing lactation support. (2) Methods: This paper describes BAE Cafe through a group process observation and participant survey. (3) Results: The observation of groups highlighted the core elements of the BAE Cafe model: knowledge, support and mental health support in a peer driven format. Participant survey feedback was overwhelmingly positive and highlighted the critical importance of lactation support for Black women by Black women and BAE’s role in participants’ decisions to continue breastfeeding. (4) Conclusions: BAE Cafe is a replicable, scalable, peer-driven and low-barrier intervention that has the potential to improve outcomes for Black families. Additional research and investment are now needed to assess large-scale implementation to reduce disparities and address health inequity across different contexts and settings.
An Index of Non-Linear HRV as a Proxy of the Aerobic Threshold Based on Blood Lactate Concentration in Elite Triathletes
Authors: Rogers Bruce , Berk Sander , Gronwald Thomas
Published: February 2022

A non-linear index of heart rate (HR) variability (HRV) known as alpha1 of Detrended Fluctuation Analysis (DFA a1) has been shown to change with increasing exercise intensity, crossing a value of 0.75 at the aerobic threshold (AT) in recreational runners defining a HRV threshold (HRVT). Since large volumes of low-intensity training below the AT is recommended for many elite endurance athletes, confirmation of this relationship in this specific group would be advantageous for the purposes of training intensity distribution monitoring. Nine elite triathletes (7 male, 2 female) attended a training camp for diagnostic purposes. Lactate testing was performed with an incremental cycling ramp test to exhaustion for the determination of the first lactate threshold based on the log–log calculation method (LT1). Concurrent measurements of cardiac beta-to-beat intervals were performed to determine the HRVT. Mean LT1 HR of all 9 participants was 155.8 bpm (±7.0) vs. HRVT HR of 153.7 bpm (±10.1) (p = 0.52). Mean LT1 cycling power was 252.3 W (±48.1) vs. HRVT power of 247.0 W (±53.6) (p = 0.17). Bland–Altman analysis showed mean differences of −1.7 bpm and −5.3 W with limits of agreement (LOA) 13.3 to −16.7 bpm and 15.1 to −25.6 W for HR and cycling power, respectively. The DFA a1-based HRVT closely agreed with the LT1 in a group of elite triathletes. Since large volumes of low-intensity exercise are recommended for successful endurance performance, the fractal correlation properties of HRV show promise as a low-cost, non-invasive option to that of lactate testing for identification of AT-related training boundaries.
Saudi Non-Oil Exports before and after COVID-19: Historical Impacts of Determinants and Scenario Analysis
Authors: Hasanov Fakhri J. , Javid Muhammad , Joutz Frederick L.
Published: February 2022

The diversification of the economy including its exports is at the core of Saudi Vision 2030. The vision targets to raise non-oil export from 16% to 50% of non-oil GDP by 2030. Achieving this, in addition to other goals, necessitates a better understanding of the non-oil export relationship with its determinants. However, we are not aware of a study that estimates the impacts of the determinants on Saudi non-oil exports covering the recent years of reforms and low oil prices and that conducts simulations for future. The purpose of this study is to develop an econometric modeling framework for Saudi non-oil export that can enhance informing the policymaking process through empirical estimations and simulations. For estimations, we applied cointegration and equilibrium correction methodology to the annual data for the period 1983–2018. Results show that Middle Eastern and North African countries’ GDP, as a measure of foreign income, and Saudi Arabia’s non-oil GDP, as a measure of production capacity, have statistically significant positive effects on Saudi non-oil exports in the long run. The real effective exchange rate (REER), as a measure of competitiveness, also exerts a positive effect in the long run if it depreciates and vice versa. Furthermore, our findings support the Export-led growth concept, which articulates that export can be an engine of economic growth and does not support the Dutch disease concept, which highlights the consequences of the resource sector for the non-resource tradable sector for Saudi Arabia. Macroeconometric model-based simulations conducted up to 2030 reveal out that the Saudi non-oil export is more responsive to the changes in REER than any other determinants. The simulation results also show that non-oil manufacturing makes a three times larger contribution to the future expansion of non-oil exports than agriculture. Moreover, the simulations discover that finance, insurance, and other business services, as well as transport and communication play an important role in improving the Saudi non-oil export performance in the coming decade. The key policy recommendation is that measures should be implemented in a coordinated and balanced way to achieve non-oil exports and other targets of the Vision.
A Distributed and Privacy-Preserving Random Forest Evaluation Scheme with Fine Grained Access Control
Authors: Zhou Yang , Shen Hua , Zhang Mingwu
Published: February 2022

Random forest is a simple and effective model for ensemble learning with wide potential applications. Implementation of random forest evaluations while preserving privacy for the source data is demanding but also challenging. In this paper, we propose a practical and fault-tolerant privacy-preserving random forest evaluation scheme based on asymmetric encryption. The user can use asymmetric encryption to encrypt the data outsourced to the cloud platform and specify who can access the final evaluation results. After receiving the encrypted inputs from the user, the cloud platform evaluates via a random forest model and outputs the aggregated results where only the designated recipient can decrypt them. Threat analyses prove that the proposed scheme achieves the desirable security properties, such as correctness, confidentiality and robustness. Moreover, efficiency analyses demonstrate that the scheme is practical for real-world applications.
Fault Diagnosis of Crack on Gearbox Using Vibration-Based Approaches
Authors: Mohammed Sufyan A. , Ghazaly Nouby M. , Abdo Jamil
Published: February 2022

This study experimentally investigates vibration-based approaches for fault diagnosis of automotive gearboxes. The primary objective is to identify methods that can detect gear-tooth cracks, a common fault in gearboxes. Vibrational signals were supervised on a gearbox test rig under different operating conditions of gears with three symmetrical crack depths (1, 2, and 3 mm). The severity of the gear-tooth cracks was predicted from the vibrational signal dataset using an artificial feedforward multilayer neural network with backpropagation (NNBP). The vibration amplitudes were the greatest when the crack size in the high-speed shaft was 3 mm, and the root mean square of its vibration speed was below 3.5 mm/s. The vibration amplitudes of the gearbox increased with increasing depth of the tooth cracks under different operating conditions. The NNBP predicted the states of gear-tooth cracks with an average recognition rate of 80.41% under different conditions. In some cases, the fault degree was difficult to estimate via time-domain analysis as the vibration level increases were small and not easily noticed. Results also showed that when using the same statistical features, the time-domain analysis can better detect crack degree compared to the neural network technique.
Removal of Hexavalent Chromium(VI) from Wastewater Using Chitosan-Coated Iron Oxide Nanocomposite Membranes
Authors: Park Jung , Shin Jun-Ho , Oh Wonzin , Choi Sang-June , Kim Jeongju , Kim Chorong , Jeon Jongho
Published: February 2022

Chromium is a toxic and carcinogenic heavy metal that originates from various human activities. Therefore, the effective removal of chromium from aqueous solutions is an extremely important global challenge. Herein, we report a chitosan-coated iron oxide nanoparticle immobilized hydrophilic poly(vinylidene) fluoride membrane (Chi@Fe2O3–PVDF) which can potentially be used for efficient removal of hexavalent chromium(VI) by a simple filtration process. Membrane filtration is an easy and efficient method for treating large volumes of water in a short duration. The adsorption experiments were conducted by batch and continuous in-flow systems. The experimental data showed rapid capture of hexavalent chromium (Cr(VI)) which can be explained by the pseudo-second-order kinetic and Langmuir isotherm model. The nanocomposite membrane exhibited high adsorption capacity for Cr(VI) (14.451 mg/g in batch system, 14.104 mg/g in continuous in-flow system). Moreover, its removal efficiency was not changed significantly in the presence of several competing ions, i.e., Cl−, NO3−, SO42−, and PO43−. Consequently, the Chi@Fe2O3-PVDF-based filtration process is expected to show a promising direction and be developed as a practical method for wastewater treatment.
Defining the Recipe for an Optimal Rotavirus Vaccine Introduction in a High-Income Country in Europe
Authors: Standaert Baudouin , Benninghoff Bernd
Published: February 2022

Observational data over 15 years of rotavirus vaccine introduction in Belgium have indicated that rotavirus hospitalisations in children aged <5 years plateaued at a higher level than expected, and was followed by biennial disease peaks. The research objective was to identify factors influencing these real-world vaccine impact data. We constructed mathematical models simulating rotavirus-related hospitalisations by age group and year for those children. Two periods were defined using different model constructs. First, the vaccine uptake period encompassed the years required to cover the whole at-risk population. Second, the post-uptake period covered the years in which a new infection/disease equilibrium was reached. The models were fitted to the observational data using optimisation programmes with regression and differential equations. Modifying parameter values identified factors affecting the pattern of hospitalisations. Results indicated that starting vaccination well before the peak disease season in the first year and rapidly achieving high coverage was critical in maximising early herd effect and minimising secondary sources of infection. This, in turn, would maximise the reduction in hospitalisations and minimise the size and frequency of subsequent disease peaks. The analysis and results identified key elements to consider for countries initiating an optimal rotavirus vaccine launch programme.
Humoral Responses and Chronic GVHD Exacerbation after COVID-19 Vaccination Post Allogeneic Stem Cell Transplantation
Authors: Pabst Caroline , Benning Louise , Liebers Nora , Janssen Maike , Caille Leandra , Speer Claudius , He Lixiazi , Schubert Maria-Luisa , Simons Laura , Hegenbart Ute , Schönland Stefan , Radujkovic Aleksandar , Schmitt Michael , Schnitzler Paul , Müller-Tidow Carsten , Dietrich Sascha , Dreger Peter , Luft Thomas
Published: February 2022

The COVID-19 pandemic threatens patients with a compromised immune and endothelial system, including patients who underwent allogeneic stem cell transplantation (alloSCT). Thus, there is an unmet need for optimizing vaccination management in this high-risk cohort. Here, we monitored antibodies against SARS-CoV-2 spike protein (anti-S1) in 167 vaccinated alloSCT patients. Humoral immune responses were detectable in 81% of patients after two vaccinations with either mRNA-, vector-based, or heterologous regimens. Age, B-cell counts, time interval from vaccination, and the type of vaccine determined antibody titres in patients without systemic immunosuppression (sIS). Similar to a healthy control cohort, mRNA vaccine-based regimens induced higher titres than vector-based vaccines. Patients on two or more immunosuppressants rarely developed immunity. In contrast, 62% and 45% of patients without or on only one immunosuppressant, respectively, showed a strong humoral vaccination response (titre > 100). Exacerbation of cGVHD upon vaccination was observed in 6% of all patients and in 22% of patients receiving immunosuppression for cGVHD. cGVHD exacerbation and low antibody titres were both associated with higher angiopoietin-2 (ANG2) serum levels. In conclusion, mRNA-based vaccines elicit strong humoral responses in alloSCT patients in the absence of double sIS. Biomarkers such as ANG2 might help with weighing cGVHD risk versus beneficial responses.
Homologous and Heterologous Anti-COVID-19 Vaccination Does Not Induce New-Onset Formation of Autoantibodies Typically Accompanying Lupus Erythematodes, Rheumatoid Arthritis, Celiac Disease and Antiphospholipid Syndrome
Authors: Thurm Christoph , Reinhold Annegret , Borucki Katrin , Kahlfuss Sascha , Feist Eugen , Schreiber Jens , Reinhold Dirk , Schraven Burkhart
Published: February 2022

The COVID-19 pandemics has caused the death of almost six million people worldwide. In order to establish collective immunity, the first vaccines that were approved in Germany were the vector virus-based vaccine Vaxzevria and the mRNA vaccines Comirnaty and Spikevax, respectively. As it was reported that SARS-CoV-2 can trigger autoimmunity, it is of significant interest to investigate whether COVID-19 vaccines evoke the formation of autoantibodies and subsequent autoimmunity. Here, we analyzed immune responses after different vaccination regimens (mRNA/mRNA, Vector/Vector or Vector/mRNA) with respect to anti-SARS-CoV-2-specific immunity and the development of autoantibodies well known for their appearance in distinct autoimmune diseases. We found that anti-SARS-CoV-2 antibody levels were 90% lower after Vector/Vector vaccination compared to the other vaccinations and that Vector/mRNA vaccination was more effective than mRNA/mRNA vaccination in terms of IgM and IgA responses. However, until 4 months after booster vaccination we only detected increases in autoantibodies in participants with already pre-existing autoantibodies whereas vaccinees showing no autoantibody formation before vaccination did not respond with sustained autoantibody production. Taken together, our study suggests that all used COVID-19 vaccines do not significantly foster the appearance of autoantibodies commonly associated with lupus erythematodes, rheumatoid arthritis, Celiac disease and antiphospholipid-syndrome but provide immunity to SARS-CoV-2.
Intentions Regarding COVID-19 Vaccination in Females Aged 15–49 Years
Authors: Kajiwara Shihoko , Akiyama Naomi , Ohta Michio
Published: February 2022

To control the coronavirus disease 2019 (COVID-19) pandemic, the Japanese government is promoting vaccination, which many people are willing to accept; however, some are reluctant to receive vaccinations. The purpose of this study was to analyze the intentions of women aged 15–49 years regarding the COVID-19 vaccination and to identify methods of promoting vaccination. We used secondary data from a web research company of approximately 1020 participants. The data contained the following variables: vaccination status, reasons for not getting vaccinated, and the intentions and reasons related to the third vaccination. We categorized the reasons using text data and evaluated the age-related differences. The proportion of women aged 15–49 years who refused COVID-19 vaccination in Japan was 17.0%, and the rate was not significantly different by age group. The most common reasons were safety and side effect concerns. Of those who received the second vaccination, 32.7% hesitated or refused the third vaccination, and the rate was not significantly different by age group. The reasons were side-effect concerns, a lack of information, and the influence of their surroundings. Addressing the side effects and providing adequate information may help promote vaccination among women aged 15–49 years.
Anthelmintic Properties of Essential Oils to Control Gastrointestinal Nematodes in Sheep—In Vitro and In Vivo Studies
Authors: Štrbac Filip , Bosco Antonio , Maurelli Maria Paola , Ratajac Radomir , Stojanović Dragica , Simin Nataša , Orčić Dejan , Pušić Ivan , Krnjajić Slobodan , Sotiraki Smaragda , Saralli Giorgio , Cringoli Giuseppe , Rinaldi Laura
Published: February 2022

Herbal products such as essential oils may play a promising role in the treatment of infections caused by gastrointestinal nematodes (GINs). The aim of this study was to evaluate the in vitro potential of 11 essential oils (EOs) and one binary combination of isolated EO compounds, as well as the in vivo anthelmintic efficacy of two EO formulations. Four GIN genera were identified in the coproculture examination: Haemonchus, Trichostrongylus, Teladorsagia and Chabertia. The in vitro egg hatch test (EHT) was performed at six different concentrations (50, 12.5, 3.125, 0.781, 0.195 and 0.049 mg/mL) for each EO, whereas in the in vivo faecal egg count reduction test (FECRT), each EO sample was diluted in sunflower oil and orally administrated at a dose of 100 mg/kg to the different group of animals. In the EHT, the EOs of Origanum vulgare, Foeniculum vulgare, Satureja montana, Satureja hortensis and two types of Thymus vulgaris were the most effective. The dominant compounds of these EOs were carvacrol, thymol, anethol, p-cymene and γ-terpinene, indicating their importance for the anthelmintic activity. In the FECRT, both T. vulgaris EO type 1 and linalool:estragole combination show an anthelmintic potential with a mean effect on FECR of approximately 25%. The results suggest the possible role of tested EOs as anthelmintic agents in sheep farms, although further in vivo tests are needed.
The Impact of Electric Bidet Diffusion on Municipal Water Infrastructure
Authors: Toyosada Kanako , Xu Li
Published: February 2022

Electric bidets have become widespread in Japan and are now rapidly being installed across the rest of Asia, the United States, and the European Union. However, the impact on water infrastructure has not yet been sufficiently evaluated. Using Japan as an example, we assess the impact of the spread of electric bidets on the existing water infrastructure and use the results to predict the impact in countries in which the spread of electric bidets is expected in the future. In this study, we first proposed a model of electric bidet use on the basis of the results of a questionnaire survey. In Japan, the frequency of electric bidet use is considered to be the same as that of toilet use, and this model is used by the Ministry of Economy, Trade and Industry (METI) in its official evaluation of equipment performance. However, in this survey, we found that 30–40% of respondents did not use electric bidets, even though they have become commonplace in Japan. The reason for this was a vague sense of anxiety about sanitation. Based on the results of the survey, the model for electric bidet use was set to once a day for men for flushing following defecation and once a day for women for either flushing following defecation or bidet flushing. This is considerably less frequent than the conventional Japanese electric bidet use model for women, which models for one flush following defecation and three flushes following urination. Japan’s Energy Conservation Law requires improved energy efficiency in 32 items of equipment, of which the electric bidet is one. Because of this regulation, the electricity consumption of electric bidets has decreased by one fourth in the past 10 years. When a new model representing actual usage was applied, the environmental impact of the electric bidets currently sold was shown to be minimal.
Methods and means for agent-based visualization of digitized data
Authors: Ivanova Yoana
Published: February 2022

The research aims to present the possibility to visualize the processes simulated by agent-based modelling method, contributing to a better understanding the methods of digital transformations of physical objects and the means for visualization of digitized data. The theoretical framework is supported by examples related to practical realization of agent-based visualization in the simulation environment NetLogo or a cloud platform. The individual stages in the process of working with a personal online GIS-assistant Land Viewer for performing built-in analysis of satellite images, with data clustering capabilities, are described in detail. The scientific and applied contribution of the research is expressed in the analysis of the possibilities for creating an agent-based visualization to a suitable simulation model, selected by the library of the simulation software.
Application of approaches to artificial intelligence and machine training in cyber security
Authors: Kadrev Vasil , Pasarelski Rosen
Published: February 2022

Of interest is how machine learning is used in cybersecurity for both security and criminal activities, incl. and for cyberattacks targeting machine-learning models. The aim of the development is to show how machine learning, can be applied in the context of security in terms of both protection and attack, as well as the potential threats posed to machine learning models. Results were obtained using analytical descriptive methodology based on literature sources, examining the use of artificial intelligence techniques and machine learning to increase cybersecurity, as well as the most important areas of application that improve cybersecurity. On the other hand, the features and applications of artificial intelligence and machine learning in the service of cybercriminals are considered. Regarding the contribution part, an in-depth and extensive analysis of the features and applications of artificial intelligence and machine learning from two points of view (cybersecurity and cybercrime) has been made.
Концепція виправного покарання Бенджаміна Раша
Authors: Сокальська О. В.
Published: February 2022

Автором проаналізовано есе Дослідження впливу публічних покарань на злочинців і суспільство (1787 р.) одного із піонерів американської пенології, соціального реформатора Бенджаміна Раша. Визначено основні складові концепції виправного покарання, розробленої Б. Рашем, її витоки, зв'язок з європейським пенальним дискурсом, а також вплив ідей просвітника на формування американських пенітенціарних систем.
Пенітенціарні ідеї англійських просвітників: Вільяма Пейлі та Самуеля Роміллі
Authors: Власенко С. І.
Published: February 2022

У статті визначено й проаналізовано ідеї та погляди представників англійського просвітництва Вільяма Пейлі та Самуеля Роміллі на реформу карної політики, мету й систему покарань, визначено місце тюремного ув’язнення та режимних засад його реалізації у концепціях зазначених авторів.
Permanências rurais no espaço urbano:
Authors: De Domenicis Lucchesi Bianca Melzi
Published: February 2022

Analisando instrumentos, sujeitos e processos que construíram a paisagem e o cotidiano de São Paulo no final do século XIX, este trabalho pretende mostrar como a cidade reunia aspectos rurais e urbanos num momento em que o aumento populacional, a importância econômica e a infraestrutura técnica advindos com o café transformaram a dinâmica da capital. A delimitação territorial, a paisagem citadina, o cultivo e comercialização de plantas e animais, entre outros aspectos fazem de São Paulo, mais do que um espaço de embate, um espaço de sincretismo entre as experiências urbanas e rurais. A pesquisa histórica contribui, portanto, para desvendar as imagens e identidades construídas para a capital paulista, considerando seus aspectos rurais e ambientais. Dentro do aporte urbano que configura São Paulo no início do século XX, será destacada a relação dos quintais com as vivências rurais paulistanas, influenciando na dinâmica econômica, social e paisagística da cidade. O sincretismo entre urbano e rural pode ser observado com maior destaque e profundidade nos quintais das casas e chácaras paulistanas, onde pomares, jardins, hortas, criação de animais, ofícios de cozinha e trabalho formam um cotidiano de sustento e abastecimento aos habitantes da cidade. Nesse sentido, os quintais se apresentam como espaço onde se pode pensar a relação entre sociedade e natureza dentro da metrópole através da multiplicidade de cores, alimentos e nacionalidades que ali sociabilizam diariamente.
Intercâmbios educacionais em tempos de guerra
Authors: Mendonça Cunha Adriana
Published: February 2022

este artigo analisa os principais apontamentos do pesquisador estadunidense Robert King Hall acerca das reformas do ensino secundário realizadas durante o Estado Novo. Em 1940, Hall cursava doutorado em educação comparada pela Universidade de Michigan (UM) e visitou o Brasil para realizar um estudo sobre nossa educação secundária. Esta viagem foi possível com o auxílio de uma bolsa de pesquisa obtida através de um convênio, assinado entre o Instituto Brasil-EUA (IBEU) e a UM, para promoção de intercâmbios educacionais entre os dois países. Tal iniciativa era resultado do contexto de aproximação entre Brasil e Estados Unidos promovida pela Política de Boa Vizinhança.  Utilizando dos conceitos de “circulação” e “moving localities”, busco discutir o processo de produção e fluxo de ideias entre educadores das duas nações a partir dos contatos estabelecidos por Hall com instituições e intelectuais brasileiros. Analisando a tese produzida pelo pesquisador, foi possível constatar críticas ao centralismo da educação brasileira e aos programas do curso secundário, recomendando-se uma maior flexibilização desta modalidade de ensino, de acordo com as diferenças regionais.

Palavras-chave: Educação Secundária; Política da Boa Vizinhança; Robert King Hall.
prática musical dos vilancicos no reinado de d. João IV
Authors: Morgado Marcoje Laís
Published: February 2022

João IV foi o principal impulsionador de um gênero poético musical, conhecido como vilancico. Esse gênero fizera parte do cotidiano musical da Casa de Bragança em Vila Viçosa, sendo uma das maiores do reino português. O que torna esse gênero importante não é apenas o interesse que o rei possuía, mas a sua comum prática sobretudo na Espanha, adquirindo um “estatuto” de música de Estado. A temática religiosa presente nas letras era, assim como nos sermões, associada à figura real. Os vilancicos, mesmo tendo uma origem profana, foi sacralizado e incorporado no cotidiano das igrejas ibéricas, estando presente em catedrais e Capela Real. A partir dos trabalhos realizados pela historiadora Beatriz Santos, discutir-se-á a ausência e a presença de referências às tentativas de assassinato a d. João IV.