bluuebunny/crossref_metadata_2025 huggingface dataset:
Development of Binder-Free Three-Dimensional Honeycomb-like Porous Ternary Layered Double Hydroxide-Embedded MXene Sheets for Bi-Functional Overall Water Splitting Reactions
Authors: Hussain Sajjad , Vikraman Dhanasekaran , Nazir Ghazanfar , Mehran Muhammad Taqi , Shahzad Faisal , Batoo Khalid Mujasam , Kim Hyun-Seok , Jung Jongwan
Published: August 2022

In this study, a honeycomb-like porous-structured nickel–iron–cobalt layered double hydroxide/Ti3C2Tx (NiFeCo–LDH@MXene) composite was successfully fabricated on a three-dimensional nickel foam using a simple hydrothermal approach. Owing to their distinguishable characteristics, the fabricated honeycomb porous-structured NiFeCo–LDH@MXene composites exhibited outstanding bifunctional electrocatalytic activity for pair hydrogen and oxygen evolution reactions in alkaline medium. The developed NiFeCo–LDH@MXene electrocatalyst required low overpotentials of 130 and 34 mV to attain a current density of 10 mA cm−2 for OER and HER, respectively. Furthermore, an assembled NiFeCo–LDH@MXene‖NiFeCo–LDH@MXene device exhibited a cell voltage of 1.41 V for overall water splitting with a robust firmness for over 24 h to reach 10 mA cm−2 current density, signifying outstanding performance for water splitting reactions. These results demonstrated the promising potential of the designed 3D porous NiFeCo–LDH@MXene sheets as outstanding candidates to replace future green energy conversion devices.
Novel Designer Benzodiazepines: Comprehensive Review of Evolving Clinical and Adverse Effects
Authors: Edinoff Amber N. , Nix Catherine A. , Odisho Amira S. , Babin Caroline P. , Derouen Alyssa G. , Lutfallah Salim C. , Cornett Elyse M. , Murnane Kevin S. , Kaye Adam M. , Kaye Alan D.
Published: August 2022

As tranquilizers, benzodiazepines have a wide range of clinical uses. Recently, there has been a significant rise in the number of novel psychoactive substances, including designer benzodiazepines. Flubromazolam(8-bromo-6-(2-fluorophenyl)-1-methyl-4H-[1,2,4]triazolo[4,3-a][1,4]benzodiazeZpine) is a triazolo-analogue of flubromazepam. The most common effects noted by recreational users include heavy hypnosis and sedation, long-lasting amnesia, and rapid development of tolerance. Other effects included anxiolysis, muscle-relaxing effects, euphoria, loss of control, and severe withdrawals. Clonazolam, or 6-(2-chlorophenyl)-1-methyl-8-nitro-4H-[1,2,4]triazolo[4,3-α]-[1,4]-benzodiazepine, is a triazolo-analog of clonazepam. It is reported to be over twice as potent as alprazolam. Deschloroetizolam (2-Ethyl-9-methyl-4-phenyl-6H-thieno[3,2-f][1,2,4]triazolo[4,3-a][1,4]diazepine) is part of the thienodiazepine drug class, which, like benzodiazepines, stimulates GABA-A receptors. Meclonazepam ((3S)-5-(2-chlorophenyl)-3-methyl-7-nitro-1,3-dihydro-1,4-benzodiazepin-2-one) is a designer benzodiazepine with additional anti-parasitic effects. Although it has proven to be an efficacious therapy for schistosomiasis, its sedative side effects have prevented it from being marketed as a therapeutic agent. The use of DBZs has been a subject of multiple recent clinical studies, likely related to increasing presence and availability on the internet drug market and lack of regulation. Many studies have aimed to identify the prevalence of DBZs and their effects on those using them. This review discussed these designer benzodiazepines and the dangers and adverse effects that the clinician should know.
Systems Biology Approaches for Understanding Metabolic Differences Using ‘Multi-Omics’ Profiling of Metabolites in Mice Fed with Honey and Mixed Sugars
Authors: Zheng Xing , Zhao Yazhou , Naumovski Nenad , Zhao Wen , Yang Guan , Xue Xiaofeng , Wu Liming , Granato Daniel , Peng Wenjun , Wang Kai
Published: August 2022

Honey is proposed to be the oldest natural sweetener and it is a standard component of several dietary patterns. Recent evidence suggests that replacing sugars, such as fructose, with honey has potential health benefits. In this study, we determined the effects of honey supplementation in mice on cardiometabolic and inflammatory markers and changes in gut microbiota and metabolomic profiles. We compared mice fed a honey diet (1 or 2 g/kg) with those fed an analog diet (mixed fructose, glucose, and sucrose (FSG) solutions) at exact dosages for one month. We found the same blood glucose fluctuating trends for honey- and FGS-fed mice. The honey diets resulted in less weight gain and fewer ballooned hepatocytes. Additionally, honey diets decreased the total serum cholesterol and TNF-α and increased the antioxidant enzyme activity. Each diet type was associated with distinct gut microbiota and metabolomics profiles. Systems biology analysis revealed that Lactococcus spp., Lachnospiraceae spp., and oleamide had the strongest correlations with lipid metabolic networks. Although in an animal model, this study provides a good understanding of the potential benefits of choosing honey rather than mixed sugars in regular dietary patterns.
Prevalence of Low Muscle Mass in the Computed Tomography at the Third Lumbar Vertebra Level Depends on Chosen Cut-Off in 200 Hospitalised Patients—A Prospective Observational Trial
Authors: Fischer Arabella , Kiss Noemi , Rudas Valerie-Anna , Nieding Kristina , Veraar Cecilia , Timmermann Isabel , Liebau Konstantin , Pesta Maximilian , Siebenrock Timo , Anwar Martin , Hahn Ricarda , Hertwig Anatol , Brugger Jonas , Ringl Helmut , Tamandl Dietmar , Hiesmayr Michael
Published: August 2022

Measuring skeletal muscle area (SMA) at the third lumbar vertebra level (L3) using computed tomography (CT) is increasingly popular for diagnosing low muscle mass. The aim was to describe the effect of the CT L3 cut-off choice on the prevalence of low muscle mass in medical and surgical patients. Two hundred inpatients, who underwent an abdominal CT scan for any reason, were included. Skeletal muscle area (SMA) was measured according to Hounsfield units on a single CT scan at the L3 level. First, we calculated sex-specific cut-offs, adjusted for height or BMI and set at mean or mean-2 SD in our population. Second, we applied published cut-offs, which differed in statistical calculation and adjustment for body stature and age. Statistical calculation of the cut-off led to a prevalence of approximately 50 vs. 1% when cut-offs were set at mean vs. mean-2 SD in our population. Prevalence varied between 5 and 86% when published cut-offs were applied (p < 0.001). The adjustment of the cut-off for the same body stature variable led to similar prevalence distribution patterns across age and BMI classes. The cut-off choice highly influenced prevalence of low muscle mass and prevalence distribution across age and BMI classes.
Heart Rate Variability—An Index of the Efficacy of Complementary Therapies in Irritable Bowel Syndrome: A Systematic Review
Authors: Mróz Magdalena , Czub Marcin , Brytek-Matera Anna
Published: August 2022

Irritable bowel syndrome (IBS), as a functional and psychosomatic disease, reduces the quality of life and increases the risk of developing mental disorders. Deregulation of the autonomic nervous system (ANS) is one of the main causes of the disease. The objective of the present study was to identify the studies in which measurements of heart rate variability (HRV) were performed before and after therapeutic intervention, and to evaluate the effectiveness of IBS therapy in terms of a reduction of IBS symptoms and changes in autonomic tone. A systematic review of the literature was carried out in accordance with PRISMA standards. Six databases were searched for articles published before 2022: PubMed®, MEDLINE®, EBSCO, Cochrane, Scopus, and Web of Science. Inclusion criteria were experimental design, diagnosis of IBS (medical and/or diagnosis in accordance with the Rome Criteria), non-pharmacological intervention, and HRV measurement before and after the intervention. The quality of the studies was assessed by JBI Critical appraisal. In total, 455 studies were identified, of which, sixwere included in the review. Expected changes in HRV (increase in parasympathetic activity) were observed in four of the six studies (interventions studied: ear acupressure, transcutaneous auricular vagusnerve stimulation, cognitive behavioral therapy with relaxation elements, yoga). In the same studies, therapeutic interventions significantly reduced the symptoms of IBS. The present review indicated that interventions under investigation improve the efficiency of the ANS and reduce the symptoms of IBS. It is advisable to include HRV measurements as a measure of the effectiveness of interventions in IBS therapy, and to assess autonomic changes as a moderator of the effectiveness of IBS therapy.
3D-Tracking of Sand Particles in a Wave Flume Using Interferometric Imaging
Authors: Brunel Marc , Ouldarbi Lila , Fahy Alexandre , Perret Gaële
Published: August 2022

We report the 3D-tracking of irregular sand particles in a wave flume using a cylindrical interferometric particle imaging set-up. The longitudinal position of each particle is deduced from the ellipticity of its speckle-like interferometric image. The size of a particle is determined from the analysis of the 2D Fourier transform of its defocused image. It is further possible to identify some rotation of the particles. Simulations accurately confirm the experimental determination of the different parameters (3D position and size of each particle).
Residual Microscopic Peritoneal Metastases after Macroscopic Complete Cytoreductive Surgery for Advanced High-Grade Serous Ovarian Carcinoma: A Target for Folate Receptor Targeted Photodynamic Therapy?
Authors: Moinard Morgane , Augustin Jeremy , Carrier Marine , Da Maïa Elisabeth , Penel Alix , Belghiti Jérémie , Nikpayam Maryam , Gonthier Clémentine , Canlorbe Geoffroy , Acherar Samir , Delhem Nadira , Frochot Céline , Uzan Catherine , Azaïs Henri
Published: August 2022

Despite conventional treatment combining complete macroscopic cytoreductive surgery (CRS) and systemic chemotherapy, residual microscopic peritoneal metastases (mPM) may persist as the cause of peritoneal recurrence in 60% of patients. Therefore, there is a real need to specifically target these mPM to definitively eradicate any traces of the disease and improve patient survival. Therapeutic targeting method, such as photodynamic therapy, would be a promising method for such a purpose. Folate receptor alpha (FRα), as it is specifically overexpressed by cancer cells from various origins, including ovarian cancer cells, is a good target to address photosensitizing molecules. The aim of this study was to determine FRα expression by residual mPM after complete macroscopic CRS in patients with advanced high-grade serous ovarian cancer (HGSOC). A prospective study conducted between 1 June 2018 and 10 July 2019 in a single referent center accredited by the European Society of Gynecological Oncology for advanced EOC surgical management. Consecutive patients presenting with advanced HGSOC and eligible for complete macroscopic CRS were included. Up to 13 peritoneal biopsies were taken from macroscopically healthy peritoneum at the end of CRS and examined for the presence of mPM. In case of detection of mPM, a systematic search for RFα expression by immunohistochemistry was performed. Twenty-six patients were included and 26.9% presented mPM. In the subgroup of patients with mPM, FRα expression was positive on diagnostic biopsy before neoadjuvant chemotherapy for 67% of patients, on macroscopic peritoneal metastases for 86% of patients, and on mPM for 75% of patients. In the subgroup of patients with no mPM, FRα expression was found on diagnostic biopsy before neoadjuvant chemotherapy in 29% of patients and on macroscopic peritoneal metastases in 78% of patients. FRα is well expressed by patients with or without mPM after complete macroscopic CRS in patients with advanced HGSOC. In addition to conventional cytoreductive surgery, the use of a therapeutic targeting method, such as photodynamic therapy, by addressing photosensitizing molecules that specifically target FRα may be studied.
A Photochemical Overview of Molecular Solar Thermal Energy Storage
Authors: Gimenez-Gomez Alberto , Magson Lucien , Peñin Beatriz , Sanosa Nil , Soilán Jacobo , Losantos Raúl , Sampedro Diego
Published: August 2022

The design of molecular solar fuels is challenging because of the long list of requirements these molecules have to fulfil: storage density, solar harvesting capacity, robustness, and heat release ability. All of these features cause a paradoxical design due to the conflicting effects found when trying to improve any of these properties. In this contribution, we will review different types of compounds previously suggested for this application. Each of them present several advantages and disadvantages, and the scientific community is still struggling to find the ideal candidate suitable for practical applications. The most promising results have been found using norbornadiene-based systems, although the use of other alternatives like azobenzene or dihydroazulene cannot be discarded. In this review, we primarily focus on highlighting the optical and photochemical aspects of these three families, discussing the recently proposed systems and recent advances in the field.
Consolidation of Additive Manufactured Continuous Carbon Fiber Reinforced Polyamide 12 Composites and the Development of Process-Related Numerical Simulation Methods
Authors: Grieder Stefan , Zhilyaev Igor , Küng Marco , Brauner Christian , Akermann Michael , Bosshard Jonas , Inderkum Petra , Francisco João , Willemin Yannick , Eichenhofer Martin
Published: August 2022

Additive manufacturing of high-performance polymers—such as PA12, PPS, PEEK, and PEKK—combined with industrial-grade carbon fibers with a high fiber volume ratio of up to 60% allows a weight reduction of over 40% compared to classic metal construction. Typically, these 3D-printed composites have a porosity of 10–30% depending on the material and the printing process parameters, which significantly reduces the quality of the part. Therefore, the additive manufacturing of load-bearing structural applications requires a proper consolidation after the printing process—the so-called ‘additive fusion technology’—allowing close to zero void content in the consolidated part. By means of the upfront digital modeling of the consolidation process, a highly optimized composite component can be produced while decreasing the number of expensive prototyping iterations. In this study, advanced numerical methods are presented to describe the consolidation process of additive manufactured continuous carbon fiber reinforced composite parts based on the polyamide 12 (PA12) matrix. The simulation of the additive fusion step/consolidation provides immediate accuracy in determining the final degree of crystallization, process-induced deformation and residual stresses, final engineering constants, as well as porosity. The developed simulation workflow is demonstrated and validated with experimental data from consolidation tests on the final porosity, thickness, and fiber–volume ratio.
Chitosan-Based Biomaterials for Bone Tissue Engineering Applications: A Short Review
Authors: Ressler Antonia
Published: August 2022

Natural bone tissue is composed of calcium-deficient carbonated hydroxyapatite as the inorganic phase and collagen type I as the main organic phase. The biomimetic approach of scaffold development for bone tissue engineering application is focused on mimicking complex bone characteristics. Calcium phosphates are used in numerous studies as bioactive phases to mimic natural bone mineral. In order to mimic the organic phase, synthetic (e.g., poly(ε-caprolactone), polylactic acid, poly(lactide-co-glycolide acid)) and natural (e.g., alginate, chitosan, collagen, gelatin, silk) biodegradable polymers are used. However, as materials obtained from natural sources are accepted better by the human organism, natural polymers have attracted increasing attention. Over the last three decades, chitosan was extensively studied as a natural polymer suitable for biomimetic scaffold development for bone tissue engineering applications. Different types of chitosan-based biomaterials (e.g., molded macroporous, fiber-based, hydrogel, microspheres and 3D-printed) with specific properties for different regenerative applications were developed due to chitosan’s unique properties. This review summarizes the state-of-the-art of biomaterials for bone regeneration and relevant studies on chitosan-based materials and composites.
Knowledge and Causality in Ibn al-ʿArabī’s Book of Giving, and the Buddhist Notion of Dependent Origination
Authors: Kars Aydogan , Bahrani Ashkan
Published: August 2022

This paper introduces the otherwise unstudied Arabic treatise on knowledge, the Book of Giving, penned by the influential Muslim mystic, Ibn al-ʿArabī (d. 1240). It presents a critical edition, English translation, and initial analysis of this short yet original work. It authenticates this work, situates it in Ibn al-ʿArabī’s career, and analyzes its content. Combining textual scholarship and intellectual history with a comparative perspective, it discusses some outstanding features of the Book of Giving in light of Buddhism in order to provide an initial philosophical bridge between the two intellectual traditions. It argues that knowledge is presented in the Book of Giving as a causal relationship constructed in the mind. Ibn al-ʿArabī’s approach to causality is one of philosophical idealism, and it contains significant parallels with the notion of dependent origination in Buddhism.
Validation of an Empirical Subwaveform Retracking Strategy for SAR Altimetry
Authors: Passaro Marcello , Rautiainen Laura , Dettmering Denise , Restano Marco , Hart-Davis Michael G. , Schlembach Florian , Särkkä Jani , Müller Felix L. , Schwatke Christian , Benveniste Jérôme
Published: August 2022

The sea level retrievals from the latest generation of radar altimeters (the SAR altimeters) are still challenging in the coastal zone and areas covered by sea ice and require a dedicated fitting (retracking) strategy for the waveforms. In the framework of the European Space Agency’s Baltic + Sea Level (ESA Baltic SEAL) project, an empirical retracking strategy (ALES + SAR), including a dedicated sea state bias correction, has been designed to improve the sea level observations in the Baltic Sea, characterised by a jagged coastline and seasonal sea ice coverage, without compromising the quality of open ocean data. In this work, the performances of ALES + SAR are validated against in-situ data in the Baltic Sea. Moreover, variance, crossover differences and power spectral density of the open ocean data are evaluated on a global scale. The results show that ALES + SAR performances are of comparable quality to the ones obtained using physical-based retrackers, with relevant advantages in coastal and sea ice areas in terms of quality and quantity of the sea level data.
Evaluation of NeQuick2 Model over Mid-Latitudes of Northern Hemisphere
Authors: Wang Lingxuan , Wei Erhu , Xiong Si , Zhang Tengxu , Shen Ziyu
Published: August 2022

NeQuick2 is a three-dimensional ionospheric electron density empirical model that uses numerical integration to calculate the total electron content along any line-of-sight (LOS). As one of the most commonly used three-dimensional ionospheric models, it is necessary to objectively evaluate the accuracy and stability of NeQuick2 over a long period, especially over the mid-latitudes of the northern hemisphere where most of the ground-based GNSS stations are distributed. Therefore, different methods are used in this study to evaluate the accuracy of the NeQuick2 model from 2008 to 2021, including comparison with the International Global Navigation Satellite System Global Ionosphere Maps (IGSG), Jason2 Vertical Electron content (VTEC), and self-consistent evaluation. The comparison with IGSG shows that the standard deviation (STD) value is about 2.59 TECU. The accuracy of the IGSG and NeQuick2 model over ocean regions shows that the bias of IGSG is more significant than that of the NeQuick2 model. The mean STD value is 2.09 TECU for IGSG, and the corresponding value is 3.18 TECU for the NeQuick2 model, which is about 50% worse than IGSG. The dSTEC assessment results indicate that the variation in bias for IGSG is more stable than that of the NeQuick2 model. The mean STD value is 0.86 and 1.52 TECU for IGSG and NeQuick2 model, respectively. The conclusion could be made that NeQuick2 model represents the average ionosphere electron content and its accuracy fluctuates with solar conditions. Compared with the IGSG, the NeQuick2 model always underestimates TEC value, especially in low solar activity periods and compared with Jason2, the TEC values obtained by NeQuick2 model are overestimated, but the degree of overestimation is smaller than that of IGSG.
A High-Precision Water Body Extraction Method Based on Improved Lightweight U-Net
Authors: An Shihao , Rui Xiaoping
Published: August 2022

The rapid, accurate extraction of water body information is critical for water resource management and disaster assessment. Its data foundation was mostly provided by remote sensing images through deep learning methods. However, the methods still require the improvement of recognition accuracy and reduction of model size. As a solution, this paper proposed a new high-precision convolutional neural network for water body extraction. This network’s structural design is based on the assumption that the extraction effect of a convolutional neural network is independent from its parameters number, thus the recognition effect could be effectively improved through reasonable adjustment of the network structure according to characteristics of water bodies on high-resolution remote sensing images. It brings two critical improvements. Firstly, the number of downsampling layers was reduced to adapt to the low resolution of remote sensing imagery. Secondly, the bottleneck structure has also been updated to fit the decoder–encoder framework. The improved bottleneck structures were nested to ensure the transmission of water characteristics information in the model. In comparison with the other five commonly used networks, the new network has achieved the best results (average overall accuracy: 98.31%, parameter benefit value: 0.2625), indicating the extremely high practical value of this approach.
Model-Based Reinforcement Learning with Automated Planning for Network Management
Authors: Ordonez Armando , Caicedo Oscar Mauricio , Villota William , Rodriguez-Vivas Angela , da Fonseca Nelson L. S.
Published: August 2022

Reinforcement Learning (RL) comes with the promise of automating network management. However, due to its trial-and-error learning approach, model-based RL (MBRL) is not applicable in some network management scenarios. This paper explores the potential of using Automated Planning (AP) to achieve this MBRL in the functional areas of network management. In addition, a comparison of several integration strategies of AP and RL is depicted. We also describe an architecture that realizes a cognitive management control loop by combining AP and RL. Our experiments evaluate on a simulated environment evidence that the combination proposed improves model-free RL but demonstrates lower performance than Deep RL regarding the reward and convergence time metrics. Nonetheless, AP-based MBRL is useful when the prediction model needs to be understood and when the high computational complexity of Deep RL can not be used.
Optimized Distributed Generalized Reed-Solomon Coding with Space-Time Block Coded Spatial Modulation
Authors: Zhao Chunli , Yang Fengfan , Waweru Daniel Kariuki , Chen Chen , Xu Hongjun
Published: August 2022

We present a well-known generalized Reed–Solomon (GRS) code incorporated with space-time block coded spatial modulation (STBC-SM) for wireless networks, which is capable of enjoying coded cooperation between the source and the relay. In the proposed distributed GRS-coded STBC-SM (DGRSC-STBC-SM) scheme, the source and relay nodes use distinct GRS codes. At the relay, we employ the concept of information selection to choose the message symbols from the source for further encoding. Thus, the codewords jointly constructed by the source and relay are generated at the destination. For achieving the best codeword set at the destination, we propose an optimal algorithm at the relay to select partial symbols from the source. To reduce the computational complexity, we propose a more practical algorithm with low complexity. Monte Carlo simulation results show that the proposed scheme using the low-complexity algorithm can achieve near-optimal error performance. Furthermore, our proposed scheme provides better error performance than its corresponding coded non-cooperative counterpart and the existing Reed–Solomon coded cooperative SM (RSCC-SM) scheme under identical conditions.
Generating Alerts from Breathing Pattern Outliers
Authors: Benmussa Chloé , Cauchard Jessica R. , Yakhini Zohar
Published: August 2022

Analysing human physiological data allows access to the health state and the state of mind of the subject individual. Whenever a person is sick, having a panic attack, happy or scared, physiological signals will be different. In terms of physiological signals, we focus, in this manuscript, on monitoring breathing patterns. The scope can be extended to also address heart rate and other variables. We describe an analysis of breathing rate patterns during activities including resting, walking, running and watching a movie. We model normal breathing behaviours by statistically analysing signals, processed to represent quantities of interest. We consider moving maximum/minimum, the amplitude and the Fourier transform of the respiration signal, working with different window sizes. We then learn a statistical model for the basal behaviour, per individual, and detect outliers. When outliers are detected, a system that incorporates our approach would send a visible signal through a smart garment or through other means. We describe alert generation performance in two datasets—one literature dataset and one collected as a field study for this work. In particular, when learning personal rest distributions for the breathing signals of 14 subjects, we see alerts generated more often when the same individual is running than when they are tested in rest conditions.
Localization in Structured Environments with UWB Devices without Acceleration Measurements, and Velocity Estimation Using a Kalman–Bucy Filter
Authors: Alonge Francesco , Cusumano Pasquale , D’Ippolito Filippo , Garraffa Giovanni , Livreri Patrizia , Sferlazza Antonino
Published: August 2022

In this work, a novel scheme for velocity and position estimation in a UWB range-based localization system is proposed. The suggested estimation strategy allows to overcome two main problems typically encountered in the localization systems. The first one is that it can be suitable for use in environments where the GPS signal is not present or where it might fail. The second one is that no accelerometer measurements are needed for the localization task. Moreover, to deal with the velocity estimation problem, a suitable Kalman–Bucy filter is designed and it is compared, experimentally, with a particle filter by showing the features of the two algorithms in order to be used in a localization context. Additionally, further experimental tests are carried out on a suitable developed test setup in order to confirm the goodness of the proposed approach.
Visual Sensing System to Investigate Self-Propelled Motion and Internal Color of Multiple Aqueous Droplets
Authors: Aoyama Tadayoshi , Yamada Shoki , Suematsu Nobuhiko J. , Takeuchi Masaru , Hasegawa Yasuhisa
Published: August 2022

This study proposes a visual sensing system to investigate the self-propelled motions of droplets. In the visual sensing of self-propelled droplets, large field-of-view and high-resolution images are both required to investigate the behaviors of multiple droplets as well as chemical reactions in the droplets. Therefore, we developed a view-expansive microscope system using a color camera head to investigate these chemical reactions; in the system, we implemented an image processing algorithm to detect the behaviors of droplets over a large field of view. We conducted motion tracking and color identification experiments on the self-propelled droplets to verify the effectiveness of the proposed system. The experimental results demonstrate that the proposed system is able to detect the location and color of each self-propelled droplet in a large-area image.
A Signal Processing Method for Assessing Ankle Torque with a Custom-Made Electronic Dynamometer in Participants Affected by Diabetic Peripheral Neuropathy
Authors: Dragoi Iulia Iovanca , Petrita Teodor , Popescu Florina Georgeta , Alexa Florin , Barac Sorin , Bowling Frank L. , Reeves Neil D. , Bondor Cosmina Ioana , Ionac Mihai
Published: August 2022

Portable, custom-made electronic dynamometry for the foot and ankle is a promising assessment method that enables foot and ankle muscle function to be established in healthy participants and those affected by chronic conditions. Diabetic peripheral neuropathy (DPN) can alter foot and ankle muscle function. This study assessed ankle toque in participants with diabetic peripheral neuropathy and healthy participants, with the aim of developing an algorithm for optimizing the precision of data processing and interpretation of the results and to define a reference frame for ankle torque measurement in both healthy participants and those affected by DPN. This paper discloses the software chain and the signal processing methods used for voltage—torque conversion, filtering, offset detection and the muscle effort type identification, which further allowed for a primary statistical report. The full description of the signal processing methods will make our research reproducible. The applied algorithm for signal processing is proposed as a reference frame for ankle torque assessment when using a custom-made electronic dynamometer. While evaluating multiple measurements, our algorithm permits for a more detailed parametrization of the ankle torque results in healthy participants and those affected by DPN.
Intelligent Diagnosis Based on Double-Optimized Artificial Hydrocarbon Networks for Mechanical Faults of In-Wheel Motor
Authors: Xue Hongtao , Song Ziwei , Wu Meng , Sun Ning , Wang Huaqing
Published: August 2022

To avoid the potential safety hazards of electric vehicles caused by the mechanical fault deterioration of the in-wheel motor (IWM), this paper proposes an intelligent diagnosis based on double-optimized artificial hydrocarbon networks (AHNs) to identify the mechanical faults of IWM, which employs a K-means clustering and AdaBoost algorithm to solve the lower accuracy and poorer stability of traditional AHNs. Firstly, K-means clustering is used to improve the interval updating method of any adjacent AHNs molecules, and then simplify the complexity of the AHNs model. Secondly, the AdaBoost algorithm is utilized to adaptively distribute the weights for multiple weak models, then reconstitute the network structure of the AHNs. Finally, double-optimized AHNs are used to build an intelligent diagnosis system, where two cases of bearing datasets from Paderborn University and a self-made IWM test stand are processed to validate the better performance of the proposed method, especially in multiple rotating speeds and the load conditions of the IWM. The double-optimized AHNs provide a higher accuracy for identifying the mechanical faults of the IWM than the traditional AHNs, K-means-based AHNs (K-AHNs), support vector machine (SVM), and particle swarm optimization-based SVM (PSO-SVM).
A Validation of Six Wearable Devices for Estimating Sleep, Heart Rate and Heart Rate Variability in Healthy Adults
Authors: Miller Dean J. , Sargent Charli , Roach Gregory D.
Published: August 2022

The primary aim of this study was to examine the validity of six commonly used wearable devices, i.e., Apple Watch S6, Garmin Forerunner 245 Music, Polar Vantage V, Oura Ring Generation 2, WHOOP 3.0 and Somfit, for assessing sleep. The secondary aim was to examine the validity of the six devices for assessing heart rate and heart rate variability during, or just prior to, night-time sleep. Fifty-three adults (26 F, 27 M, aged 25.4 ± 5.9 years) spent a single night in a sleep laboratory with 9 h in bed (23:00–08:00 h). Participants were fitted with all six wearable devices—and with polysomnography and electrocardiography for gold-standard assessment of sleep and heart rate, respectively. Compared with polysomnography, agreement (and Cohen’s kappa) for two-state categorisation of sleep periods (as sleep or wake) was 88% (κ = 0.30) for Apple Watch; 89% (κ = 0.35) for Garmin; 87% (κ = 0.44) for Polar; 89% (κ = 0.51) for Oura; 86% (κ = 0.44) for WHOOP and 87% (κ = 0.48) for Somfit. Compared with polysomnography, agreement (and Cohen’s kappa) for multi-state categorisation of sleep periods (as a specific sleep stage or wake) was 53% (κ = 0.20) for Apple Watch; 50% (κ = 0.25) for Garmin; 51% (κ = 0.28) for Polar; 61% (κ = 0.43) for Oura; 60% (κ = 0.44) for WHOOP and 65% (κ = 0.52) for Somfit. Analyses regarding the two-state categorisation of sleep indicate that all six devices are valid for the field-based assessment of the timing and duration of sleep. However, analyses regarding the multi-state categorisation of sleep indicate that all six devices require improvement for the assessment of specific sleep stages. As the use of wearable devices that are valid for the assessment of sleep increases in the general community, so too does the potential to answer research questions that were previously impractical or impossible to address—in some way, we could consider that the whole world is becoming a sleep laboratory.
Recurrent Acute Otitis Media Could Be Related to the Pro-Inflammatory State That Causes an Incorrect Diet
Authors: Calatayud-Sáez Fernando M. , Calatayud Blanca , Calatayud Ana
Published: August 2022

Introduction: Acute Otitis Media (AOM) is the most commonly-occurring bacterial complication in childhood. After making certain corrections to the patients’ dietary habits, which we found to be excessively high in animal-based and industrially-processed foods, we observed a significant reduction in recurrent colds and their bacterial complications. We promote an original way of treating these diseases, since until now the conventional treatment is based on pharmacological and surgical treatment. From our point of view, the mucosa that covers the entire ENT area is in a pro-inflammatory and hyper-reactive state, as a consequence of the alterations produced by an inadequate diet. For us there is no difference in the nutritional treatment of the different mucous membranes that cover the ENT area. The purpose of the study was to assess the effects of the Traditional Mediterranean Diet (TMD) on patients diagnosed with Recurring Acute Otitis Media (RAOM). Methods: prospective pre-postest comparison study with 48 girls and 42 boys aged 1–5 years, each of whom had been and included on the 1-year programme “Learning to eat the Mediterranean Way”, designed to encourage the adoption of the TMD. We studied clinical and therapeutic variables and various anthropometric parameters. Results: all the symptomatic indicators studied (number and intensity of episodes of otitis and emergency admissions) showed a positive and statistically significant evolution in RAOM. By the end of the study, none of the patients met the criteria for classification as RAOM, and 60% percent of patients did not present any further episodes of AOM. In line with the above, the use of anti-microbial drugs and symptomatic treatments reduced considerably; the use of antibiotics dropped from 4.30 occasions/patient/year, to 0.66 (p < 0.001), and the used of symptomatic treatments dropped from 7.63 to 2.75 (p < 0.001). The level of family satisfaction was very high. Conclusions: the adoption of the Traditional Mediterranean Diet has been demonstrated to significantly reduce occurrence of acute otitis media and may contribute to the treatment of patients diagnosed with recurrent acute otitis media.
Research on Mining Maximum Subsidence Prediction Based on Genetic Algorithm Combined with XGBoost Model
Authors: Gu Zhongyuan , Cao Miaocong , Wang Chunguang , Yu Na , Qing Hongyu
Published: August 2022

The extreme gradient boosting (XGBoost) ensemble learning algorithm excels in solving complex nonlinear relational problems. In order to accurately predict the surface subsidence caused by mining, this work introduces the genetic algorithm (GA) and XGBoost integrated algorithm model for mining subsidence prediction and uses the Python language to develop the GA-XGBoost combined model. The hyperparameter vector of XGBoost is optimized by a genetic algorithm to improve the prediction accuracy and reliability of the XGBoost model. Using some domestic mining subsidence data sets to conduct a model prediction evaluation, the results show that the R2 (coefficient of determination) of the prediction results of the GA-XGBoost model is 0.941, the RMSE (root mean square error) is 0.369, and the MAE (mean absolute error) is 0.308. Then, compared with classic ensemble learning models such as XGBoost, random deep forest, and gradient boost, the GA-XGBoost model has higher prediction accuracy and performance than a single machine learning model.
The Impact of Economic Policy Uncertainty on Industrial Output: The Regulatory Role of Technological Progress
Authors: Zhu Songping , Yu Gaofeng
Published: August 2022

Since the 2008 financial crisis, EPU has become an important issue for the stable and healthy development of the economy and society. The existing research has not analyzed the nonlinear impact of economic policy uncertainty (EPU) on output at the industrial level, and it has also ignored the regulatory role of technological progress in the impact of EPU on economic growth. Based on panel data of China’s industry from 2005 to 2017, this paper makes an empirical analysis on the nonlinear impact of EPU on industry output. The results show that: (1) Different from the existing research, this paper finds that EPU has a significant inverted “U”-type nonlinear effect on industrial output, and when the EPU index is close to 221, this is best for output growth. This paper firstly finds that technological progress has a positive regulatory effect in the impact of EPU on industrial output. Technological progress can promote industrial output when EPU is low, and it can reduce the adverse impact of economic policy fluctuations when the EPU index is high. (2) The regulatory effect of technological progress only exists in the industries dominated by state-owned enterprises, and the impact of EPU on the output of non-state-owned enterprises’ leading industries is greater than that of state-owned enterprises. (3) The impact of EPU on the output of cyclical industries shows a significant inverted “U” shape, but there is no regulatory effect of technological progress. Its impact on the output of noncyclical industries is not significant, but it will work together with technological progress. (4) The influence of EPU on the output of the tertiary industry is characterized by an inverted “U” shape, in which technological progress can play a positive regulatory role. However, its impact on the output of primary and secondary industries is not significant.
Effects of Sustainable Development of the Logistics Industry by Cloud Operational System
Authors: Yu Wen-Hsiang , Chiou Chuang-Chun
Published: August 2022

This study explores the relationship between cloud platforms, logistics operations, and sustainable development across organizational boundaries. In the past research of scholars, there is a blank area in research on the correlation between cloud platform systems, logistics services, and sustainable development. Therefore, we took international logistics as an example, selected the customers of a cloud logistics platform in the Taiwan business network as the research object, conducted a sample survey on customers in their partner transactions, and used a structured questionnaire to collect primary data through the Internet, sending out 620 questionnaires with a total of 271 valid samples recovered. The recovery rate of good models was 43.7%. This study used SPSS and AMOS tools to analyze and test the research hypotheses. Through the empirical research results, it was found that: (1) the cloud platform was highly correlated with sustainable enterprise development (0.254); (2) the cloud platform was positively associated with logistics operations (0.837); and (3) the cloud platform, logistics operations, and organizational sustainability highly correlated (0.666). According to an empirical analysis, environmental protection proved to be the most important, followed by economic benefits, and social harmony benefits were slightly less correlated but also positively correlated. Our research found that the research and analysis of cloud-platform-related data are conducive to reducing operational risks and increasing opportunities for innovative service models. Using the service model operated by the cloud logistics platform, it is easier for enterprises to establish and maintain stable cooperative relations with external partners. Supply chain information transactions are transparent, and novel ideas and needs can be easily and quickly obtained, improving managers’ decision-making and business performances, significantly improving customer service satisfaction, and gradually achieving sustainable development in the three dimensions of economy, society, and environment, as well as making critical academic contributions to application and integration in environmental and social fields.
What Affects the Level of Rural Human Settlement? A Case Study of Tibet, China
Authors: Gao Boyang , Hu Zhenpei
Published: August 2022

Rural human settlement is an important factor in the sustainable development of the rural economy and society, and improving rural human settlement is an important task for China’s rural revitalization strategy. Based on the human settlement framework, this study constructed a comprehensive evaluation index system to evaluate the rural human settlement by calculating the rural human settlement index (RHSI) in Tibet. The results showed that: (1) The natural subsystem is extremely vulnerable. In recent years, the anti-interference ability and natural restoration ability of the ecosystem have gradually increased. Changes in population size, structure, and scale have made the level of the human subsystem lower. From the perspective of drinking water, communication and housing, the human settlement level of the residential subsystem was gradually improved. The construction of rural infrastructure was increasingly improved, driving the level of the supporting subsystem to improve. Furthermore, income and livelihood diversity were the key to improving the social subsystem; (2) From the perspective of the comprehensive index, the level of rural human settlement in Tibet showed a trend of significant improvement; (3) In terms of the explanatory power, the explanatory power of the five subsystems were quite different. The basic dimensions (natural subsystem, human subsystem, residential subsystem) lagged behind the development of the dominant dimensions (supporting subsystem, social subsystem). There were inconsistencies and mismatches. The recommended measures involve strengthening the top-level design of the planning of rural human settlement in farming and pastoral areas, and improving and strengthening the construction of rural infrastructure to improve the responsiveness of rural human settlement in Tibet.
COVID and ICT in Primary Education: Challenges Faced by Teachers in the Basque Country
Authors: Paños-Castro Jessica , Arruti Arantza , Korres Oihane
Published: August 2022

This article focuses on the digital competency of primary school teachers in the Basque Country Autonomous Region (Spain) during the COVID-19 pandemic. The temporary closure of schools forced teachers to adapt face-to-face teaching-learning processes in order to operate remotely, making use of technology infrastructure and digital resources. While several educational policies have been developed with the aim of incorporating Information and Communication Technologies into schools, including the “Escuela 2.0” programme, research has shown that there is a lack of Information and Communication Technology training for teachers. The main objective of this study is to further understand the challenges faced by primary school teachers in adapting to remote teaching due to the COVID-19 during stay-at-home lockdown restrictions. An ad hoc quantitative questionnaire was used, which was validated in a trial by eight experts. A total of 1069 primary school teachers participated in the survey. The main results show the participants’ emphasis on their effort to reorganise and redesign subjects and their willingness to make use of information and communication technology infrastructure and resources. However, a high percentage of teachers reported that either they lacked information and communication technology training or considered themselves self-taught in these skills, and expressed interest in lifelong learning programmes in Google Classroom, Google Sites and Google Meet applications, among others.
Reduction in Waiting Time in an M/M/1/N Encouraged Arrival Queue with Feedback, Balking and Maintaining of Reneged Customers
Authors: Khan Ismailkhan Enayathulla , Paramasivam Rajendran
Published: August 2022

In this research, we look at the work associated with the encouraged arrival line with feedback, balking and maintaining reneged clients. We analyse the quality control policy for the Markovian model using an iterative method to the nth customer in the system. We derive performance measures for the expected number of units in the system, as well as in the queue and the average number of occupied services and the expected waiting time in the system, as well as in the queue. To show the effectiveness, we provide numerical examples for the average default rate and average retention rate. The developed formula also satisfies Little’s formula.
Hypernetwork Representation Learning with Common Constraints of the Set and Translation
Authors: Zhu Yu , Zhao Haixing , Huang Jianqiang , Wang Xiaoying
Published: August 2022

Different from conventional networks with only pairwise relationships among the nodes, there are also complex tuple relationships, namely the hyperedges among the nodes in the hypernetwork. However, most of the existing network representation learning methods cannot effectively capture the complex tuple relationships. Therefore, in order to resolve the above challenge, this paper proposes a hypernetwork representation learning method with common constraints of the set and translation, abbreviated as HRST, which incorporates both the hyperedge set associated with the nodes and the hyperedge regarded as the interaction relation among the nodes through the translation mechanism into the process of hypernetwork representation learning to obtain node representation vectors rich in the hypernetwork topology structure and hyperedge information. Experimental results on four hypernetwork datasets demonstrate that, for the node classification task, our method outperforms the other best baseline methods by about 1%. As for the link prediction task, our method is almost entirely superior to other baseline methods.