bluuebunny/crossref_metadata_2025 huggingface dataset:
Thermoresponsive Azithromycin-Loaded Niosome Gel Based on Poloxamer 407 and Hyaluronic Interactions for Periodontitis Treatment
Authors: Kerdmanee Kunchorn , Phaechamud Thawatchai , Limsitthichaikoon Sucharat
Published: September 2022

Azithromycin (AZM) is a potential antimicrobial drug for periodontitis treatment. However, a potential sustained-release system is needed for intra-periodontal pocket delivery. This study focused on the development and evaluation of a thermoresponsive azithromycin-loaded niosome gel (AZG) to search for a desirable formulation for periodontitis treatment. AZG was further developed from an AZM-loaded niosomal formulation by exploiting the advantages of poloxamer 407 (P407) and hyaluronic acid (HA) interactions. The results showed that the addition of HA decreased the gelation temperature and gelation time of AZG. HA was found to increase the viscosity as well as mucoadhesive and tooth-root surface adhesive properties. The AZG solution state was injectable and exhibited pseudoplastic shear-thinning behavior. P407–HA interactions in AZG could contribute to gel strength. AZG showed 72 h of continuous drug release following the Korsmeyer–Peppas model and potentially enhanced drug permeation. The formulations apparently presented more efficient antibacterial activity against major periodontal pathogens than the standard AZM solution. AZM intra-periodontal pocket formulation and the remarkable properties of niosomes exhibited potential characteristics, including ease of administration, bioadhesion to the anatomical structure of the periodontal pocket, and sustained drug release with competent antimicrobial activity, which could be beneficial for periodontitis treatment.
Efficacy of Sterculia diversifolia Leaf Extracts: Volatile Compounds, Antioxidant and Anti-Inflammatory Activity, and Green Synthesis of Potential Antibacterial Silver Nanoparticles
Authors: Al-Ramamneh Ezz Al-Dein M. , Ghrair Ayoup M. , Shakya Ashok K. , Alsharafa Khalid Y. , Al-Ismail Khalid , Al-Qaraleh Samer Y. , Mojski Jacek , Naik Rajashri R.
Published: September 2022

Sterculia diversifolia, widely distributed in Jordan as an ornamental plant, is a synonoum for Brachychiton populneus. Phytochemical studies examining the volatile chemicals in Sterculia diversifolia leaves are limited, despite the rising demand for their numerous applications. Furthermore, it was only recently that a report described the friendly synthesis of silver nanoparticles (AgNPs) using aqueous extract derived from Brachychiton populneus leaves. Therefore, AgNPs were produced using either aqueous plant extracts (AgWPE) or ethanolic plant extracts (AgEPE), and Shimadzu GC-MS equipment was used to detect volatile compounds in the ethanolic leaf extracts. GC-MS profile of leaf ethanolic extracts of the Jordanian chemotypes of S. diversifolia revealed the existence of major components: (3β)-Lup-20(29)-en-3-ol acetate (30.97%) and 1-octadecyne (24.88). Other compounds are squalene (7.19%), germanicol (6.23), dl-α-tocopherol (5.24), heptacosane (4.41), phytol (3.54) and pentacosane (2.89). According to published studies, these reported chemicals have numerous uses, including as animal feed, vitamin precursors, possible eco-friendly herbicides, antioxidants, and anti-inflammatory agents. Aqueous extracts of S. diversifolia leaves had total phenolic of 5.33 mg GAE/g extract and flavonoid contents of 64.88 mg QE/g extract, respectively. The results indicated the contribution of phenolic and flavonoids to this plant’s anti-inflammatory and antioxidant properties. The reduction in AgNO3 to AgNPs using S. diversifolia leaf extracts was confirmed by the change in solution color from colorless to dark black. Further characterization was attempted by X-ray diffraction, Malvern zeta-sizer and scanning electron microscope. The efficacy of synthesized Ag nanoparticles using aqueous or ethanolic plant extract of S. diversifolia against the Gram-negative bacteria Escherichia coli and Gram-positive bacteria Staphylococcus aureus showed appreciable activity at 25 µg/mL concentration compared to the source plant extracts.
The Use of Pathotype Data for the Selection and Development of Barley Lines with Useful Resistance to Scald
Authors: Wallwork Hugh , Butt Mark , Grcic Milica , Garrard Tara
Published: September 2022

Resistance in barley to scald caused by Rhynchosporium commune is readily overcome as virulent pathotypes in the pathogen population are selectively favoured over less virulent pathotypes. Diverse sources of resistance amongst host accessions have been found upon screening a wide array of accessions from around the world. Deciding which of these is of greatest value, and which are different from each other, takes a much greater investment of time and effort. This paper reports on the use of seedling screening techniques using 262 individual scald isolates collected from around Australia, to identify the most useful resistance sources from amongst 30 previously selected. No resistance source was effective against all isolates, but some such as Pamunkey, CI8618, CI4364 and ICARDA 4 were shown to have resistance to most isolates, whilst others were much less useful. Some of the most effective donors were shown to likely have more than one gene involved. The value of gene pyramids is discussed, as are the advantages and pitfalls of transferring the resistances from poorly adapted genetic backgrounds into better-adapted breeding lines so that they can more readily be used by breeding programs. This is a work in progress and the introgressed resistances being developed are available to all.
A Comprehensive Analysis of Physiologic and Hormone Basis for the Difference in Room-Temperature Storability between ‘Shixia’ and ‘Luosanmu’ Longan Fruits
Authors: Long Libing , Lai Tingting , Han Dongmei , Lin Xiaolan , Xu Jianhang , Zhu Difa , Guo Xiaomeng , Lin Yuqiong , Pan Fengyi , Wang Yihang , Lai Ziying , Du Xinxin , Fang Di , Shuai Liang , Wu Zhenxian , Luo Tao
Published: September 2022

Although the effects of phytohormones (mainly salicylic acid) on the storability of longan fruit have been reported, the relationship between postharvest hormone variation and signal transduction and storability remains unexplored. The basis of physiology, biochemistry, hormone content and signalling for the storability difference at room-temperature between ‘Shixia’ and ‘Luosanmu’ longan fruit were examined. ‘Luosanmu’ longan exhibited faster pericarp browning, aril breakdown and rotting during storage. ‘Luosanmu’ pericarp exhibited higher malondialdehyde but faster decreased total phenolics, flavonoid, glutathione, vitamin C, catalase activity and gene expression. Higher H2O2 and malondialdehyde but lower glutathione, glutathione-reductase and peroxidase activities, while higher activities and gene expressions of polygalacturonase, β-galactosidase and cellulose, lower covalent-soluble pectin, cellulose and hemicellulose but higher water-soluble pectin were observed in ‘Luosanmu’ aril. Lower abscisic acid and methyl jasmonate but higher expressions of LOX2, JAZ and NPR1 in pericarp, while higher abscisic acid, methyl jasmonate and salicylic acid together with higher expressions of ABF, JAZ, NPR1 and PR-1 in ‘Luosanmu’ aril were observed. In conclusion, the imbalance between the accumulation and scavenging of active oxygen in ‘Luosanmu’ longan might induce faster lipid peroxidation and senescence-related hormone signalling and further the polymerization of phenolics in pericarp and polysaccharide degradation in aril.
Imitation of a Pre-Designed Irregular 3D Yarn in Given Fabric Structures
Authors: Zheng Tianyong , Yue Wenli , Wang Xiaojiao
Published: September 2022

The 3D CAD software has obvious advantages in appearance imitating and geometric structure modeling for fabrics. In contemporary 3D CAD fabric systems, only uniform yarns are involved in studies on fabric geometric structures, due to technological limitations, whereas objectives such as irregular/uneven 3D yarns have not been considered much. As the fabric structure or the central curve of the yarn changes, it is difficult to reflect the changed positions of the effect spots of the pre-designed uneven 3D yarns accordingly. In this paper, a key-point-mapping algorithm between the source yarn and the target curve is proposed to reflect the position change in effect spots when the fabric structure changes. By using the shape-preserving quasi-uniform cubic B-spline curve, a simple 3D irregular source yarn is designed using key points and setting their corresponding base cross-sections. The mapping is based on the principle that the lengths of the curve between the key points and the contours of the corresponding base cross-sections of the source yarn remain unchanged. Finally, the control grid of the new 3D yarn in the fabric structure is automatically generated. According to the examples and error analysis, the mapping technique can be applied to arbitrary given fabric structures, and the effect spots of the irregular 3D yarn are reasonably distributed as expected.
Geriatric Neurosurgery in High-Income Developing Countries: A Sultanate of Oman Experience
Authors: Al-Saadi Tariq , Al-Mirza Abdulrahman , Al-Taei Omar , Al-Saadi Hatem
Published: September 2022

This study aimed to investigate the prevalence and characteristics of geriatric neurosurgical conditions in the Neurosurgical Department at Khoula Hospital (KH), Muscat, Sultanate of Oman. The majority of various neurosurgical conditions is increasing in elderly patients, which leads to an increase in neurosurgical demand. The aging population has a direct effect on hospital decision-making in neurosurgery. However, limited data are available to assess geriatric neurosurgery in developing countries. A retrospective chart review of geriatric cases admitted to the Neurosurgery Department in KH served as our example of a neurosurgical center in a high-income developing country from January 2016 to 31st December 2019. Patients’ demographics, risk factors, diagnosis, Glasgow Coma Scale on arrival, treatment types, and length of stay were recorded. A total of 669 patients who were above the age of 65 years were recruited into our retrospective review. The mean age was 73.34 years in the overall cohort and the male-to-female ratio was (1.6:1). The most common diagnostic category was trauma, which accounted for 35.4% followed by oncology and vascular (16.3% each). Hydrocephalus accounted for 3.7% of the admissions. Most of the patients underwent surgical interventions (73.1%). The associations were significant between the treatment types (surgical vs. conservative), Length of Stay, and the GCS on arrival (p < 0.05). In conclusion, the trend of geriatric neurosurgery is increasing in developing countries. The most common reason for admission to the neurosurgical ward was Traumatic Brain Injury. Special care must be taken when dealing with geriatric neurosurgical cases and a more holistic approach is needed.
Quaternary Loess Deposition and Climate Change in Europe—Recent Progress
Authors: Molnár Dávid
Published: September 2022

The current climate changes are not unique in Earth’s history [...]
Kinetic Modeling for the Gas-Phase Hydrogenation of the LOHC γ-Butyrolactone–1,4-Butanediol on a Copper-Zinc Catalyst
Authors: Gautier Vincent , Champon Isabelle , Chappaz Alban , Pitault Isabelle
Published: September 2022

Liquid organic hydrogen carriers (LOHCs) are an interesting alternative for hydrogen storage as the method is based on the reversibility of hydrogenation and dehydrogenation reactions to produce liquid and safe components at room temperature. As hydrogen storage involves a large amount of hydrogen and pure compounds, the design of a three-phase reactor requires the study of gas and liquid-phase kinetics. The gas-phase hydrogenation kinetics of LOHC γ-butyrolactone/1,4-butanediol on a copper-zinc catalyst are investigated here. The experiments were performed with data, taken from the literature, in the temperature and pressure ranges 200–240 °C and 25–35 bar, respectively, for a H2/γ-butyrolactone molar ratio at the reactor inlet of about 90. The best kinetic law takes into account the thermodynamic chemical equilibrium, is based on the associative hydrogen adsorption and is able to simulate temperature and pressure effects. For this model, the confidence intervals are at most 28% for the pre-exponential factors and 4% for the activation energies. Finally, this model will be included in a larger reactor model in order to evaluate the selectivity of the reactions, which may differ depending on whether the reaction takes place in the liquid or gas phase.
Automatic Registration for Panoramic Images and Mobile LiDAR Data Based on Phase Hybrid Geometry Index Features
Authors: Wan Genyi , Wang Yong , Wang Tao , Zhu Ningning , Zhang Ruizhuo , Zhong Ruofei
Published: September 2022

The registration of panoramic images and mobile light detection and ranging (LiDAR) data is quite challenging because different imaging mechanisms and viewing angle differences generate significant geometric and radiation distortions between the two multimodal data sources. To address this problem, we propose a registration method for panoramic images and mobile LiDAR data based on the hybrid geometric structure index feature of phase. We use the initial GPS/IMU to transform the mobile LiDAR data into an intensity map and align the two images to complete registration. Firstly, a novel feature descriptor called a hybrid geometric structure index of phase (HGIFP) is built to capture the structural information of the images. Then, a set of corresponding feature points is obtained from the two images using the constructed feature descriptor combined with a robust false-match elimination algorithm. The average pixel distance of the corresponding feature points is used as the error function. Finally, in order to complete the accurate registration of the mobile LiDAR data and panoramic images and improve computational efficiency, we propose the assumption of local motion invariance of 3D–2D corresponding feature points and minimize the error function through multiple reprojections to achieve the best registration parameters. The experimental results show that the method in this paper can complete the registration of panoramic images and the mobile LiDAR data under a rotation error within 12° and a translation error within 2 m. After registration, the average error of rotation is about 0.15°, and the average error of translation is about 1.27 cm. Moreover, it achieves a registration accuracy of less than 3 pixels in all cases, which outperforms the current five state-of-the-art methods, demonstrating its superior registration performance.
A System-on-a-Chip Implementation of a Post-Quantum Cryptography Scheme for Smart Meter Data Communications
Authors: Costa Vinícius Lagrota Rodrigues da , López Julio , Ribeiro Moisés Vidal
Published: September 2022

The security of Smart Meter (SM) systems will be a challenge in the era of quantum computing because a quantum computer might exploit characteristics of well-established cryptographic schemes to reach a successful security breach. From a practical perspective, this paper focuses on the feasibility of implementing a quantum-secure lattice-based key encapsulation mechanism in a SM, hardware-constrained equipment. In this regard, the post-quantum cryptography (PQC) scheme, FrodoKEM, an alternate candidate for the National Institute for Standards and Technology (NIST) post-quantum standardization process, is implemented using a System-on-a-Chip (SoC) device in which the Field Programmable Gate Array (FPGA) component is exploited to accelerate the most time-consuming routines in this scheme. Experimental results show that the execution time to run the FrodoKEM scheme in an SoC device reduces to one-third of that obtained by the benchmark implementation (i.e., the software implementation). Also, the attained execution time and hardware resource usage of this SoC-based implementation of the FrodoKEM scheme show that lattice-based cryptography may fit into SM equipment.
Slotted Monopole Patch Antenna for Microwave-Based Head Imaging Applications
Authors: Alqahtani Abdulrahman , Islam Mohammad Tariqul , Talukder Md Siam , Samsuzzaman Md , Bakouri Mohsen , Mansouri Sofiene , Almoneef Thamer , Dokos Socrates , Alharbi Yousef
Published: September 2022

A modified monopole patch antenna for microwave-based hemorrhagic or ischemic stroke recognition is presented in this article. The designed antenna is fabricated on a cost-effective FR-4 lossy material with a 0.02 loss tangent and 4.4 dielectric constant. Its overall dimensions are 0.32 λ × 0.28 λ × 0.007 λ, where λ is the lower bandwidth 1.3 GHz frequency wavelength. An inset feeding approach is utilized to feed the antenna to reduce the input impedance (z = voltage/current). A total bandwidth (below −10 dB) of 2.4 GHz (1.3–3.7 GHz) is achieved with an effective peak gain of over 6 dBi and an efficiency of over 90%. A time-domain analysis confirms that the antenna produces minimal signal distortion. Simulated and experimental findings share a lot of similarities. Brain tissue is penetrated by the antenna to a satisfactory degree, while still exhibiting a safe specific absorption rate (SAR). The maximum SAR value measured for the head model is constrained to be equal to or below 0.1409 W/kg over the entire usable frequency band. Evaluation of theoretical and experimental evidence indicates the intended antenna is appropriate for Microwave Imaging (MWI) applications.
Armband Sensors Location Assessment for Left Arm-ECG Bipolar Leads Waveform Components Discovery Tendencies around the MUAC Line
Authors: Escalona Omar , Mukhtar Sephorah , McEneaney David , Finlay Dewar
Published: September 2022

Sudden cardiac death (SCD) risk can be reduced by early detection of short-lived and transient cardiac arrhythmias using long-term electrocardiographic (ECG) monitoring. Early detection of ventricular arrhythmias can reduce the risk of SCD by allowing appropriate interventions. Long-term continuous ECG monitoring, using a non-invasive armband-based wearable device is an appealing solution for detecting early heart rhythm abnormalities. However, there is a paucity of understanding on the number and best bipolar ECG electrode pairs axial orientation around the left mid-upper arm circumference (MUAC) for such devices. This study addresses the question on the best axial orientation of ECG bipolar electrode pairs around the left MUAC in non-invasive armband-based wearable devices, for the early detection of heart rhythm abnormalities. A total of 18 subjects with almost same BMI values in the WASTCArD arm-ECG database were selected to assess arm-ECG bipolar leads quality using proposed metrics of relative (normalized) signal strength measurement, arm-ECG detection performance of the main ECG waveform event component (QRS) and heart-rate variability (HRV) in six derived bipolar arm ECG-lead sensor pairs around the armband circumference, having regularly spaced axis angles (at 30° steps) orientation. The analysis revealed that the angular range from −30° to +30°of arm-lead sensors pair axis orientation around the arm, including the 0° axis (which is co-planar to chest plane), provided the best orientation on the arm for reasonably good QRS detection; presenting the highest sensitivity (Se) median value of 93.3%, precision PPV median value at 99.6%; HRV RMS correlation (p) of 0.97 and coefficient of determination (R2) of 0.95 with HRV gold standard values measured in the standard Lead-I ECG.
Optimal Compensation of MEMS Gyroscope Noise Kalman Filter Based on Conv-DAE and MultiTCN-Attention Model in Static Base Environment
Authors: Huo Zimin , Wang Fuchao , Shen Honghai , Sun Xin , Zhang Jingzhong , Li Yaobin , Chu Hairong
Published: September 2022

Errors in microelectromechanical systems (MEMS) inertial measurement units (IMUs) are large, complex, nonlinear, and time varying. The traditional noise reduction and compensation methods based on traditional models are not applicable. This paper proposes a noise reduction method based on multi-layer combined deep learning for the MEMS gyroscope in the static base state. In this method, the combined model of MEMS gyroscope is constructed by Convolutional Denoising Auto-Encoder (Conv-DAE) and Multi-layer Temporal Convolutional Neural with the Attention Mechanism (MultiTCN-Attention) model. Based on the robust data processing capability of deep learning, the noise features are obtained from the past gyroscope data, and the parameter optimization of the Kalman filter (KF) by the Particle Swarm Optimization algorithm (PSO) significantly improves the filtering and noise reduction accuracy. The experimental results show that, compared with the original data, the noise standard deviation of the filtering effect of the combined model proposed in this paper decreases by 77.81% and 76.44% on the x and y axes, respectively; compared with the existing MEMS gyroscope noise compensation method based on the Autoregressive Moving Average with Kalman filter (ARMA-KF) model, the noise standard deviation of the filtering effect of the combined model proposed in this paper decreases by 44.00% and 46.66% on the x and y axes, respectively, reducing the noise impact by nearly three times.
Detection of Tip-Burn Stress on Lettuce Grown in an Indoor Environment Using Deep Learning Algorithms
Authors: Hamidon Munirah Hayati , Ahamed Tofael
Published: September 2022

Lettuce grown in indoor farms under fully artificial light is susceptible to a physiological disorder known as tip-burn. A vital factor that controls plant growth in indoor farms is the ability to adjust the growing environment to promote faster crop growth. However, this rapid growth process exacerbates the tip-burn problem, especially for lettuce. This paper presents an automated detection of tip-burn lettuce grown indoors using a deep-learning algorithm based on a one-stage object detector. The tip-burn lettuce images were captured under various light and indoor background conditions (under white, red, and blue LEDs). After augmentation, a total of 2333 images were generated and used for training using three different one-stage detectors, namely, CenterNet, YOLOv4, and YOLOv5. In the training dataset, all the models exhibited a mean average precision (mAP) greater than 80% except for YOLOv4. The most accurate model for detecting tip-burns was YOLOv5, which had the highest mAP of 82.8%. The performance of the trained models was also evaluated on the images taken under different indoor farm light settings, including white, red, and blue LEDs. Again, YOLOv5 was significantly better than CenterNet and YOLOv4. Therefore, detecting tip-burn on lettuce grown in indoor farms under different lighting conditions can be recognized by using deep-learning algorithms with a reliable overall accuracy. Early detection of tip-burn can help growers readjust the lighting and controlled environment parameters to increase the freshness of lettuce grown in plant factories.
A Kamm’s Circle-Based Potential Risk Estimation Scheme in the Local Dynamic Map Computation Enhanced by Binary Decision Diagrams
Authors: Kumar Arvind , Wagatsuma Hiroaki
Published: September 2022

Autonomous vehicles (AV) are a hot topic for safe mobility, which inevitably requires sensors to achieve autonomy, but relying too heavily on sensors will be a risk factor. A high-definition map (HD map) reduces the risk by giving geographical information if it covers dynamic information from moving entities on the road. Cooperative intelligent transport systems (C-ITS) are a prominent approach to solving the issue and local dynamic maps (LDMs) are expected to realize the ideal C-ITS. An actual LDM implementation requires a fine database design to be able to update the information to represent potential risks based on future interactions of vehicles. In the present study, we proposed an advanced method for embedding the geographical future occupancy of vehicles into the database by using a binary decision diagram (BDD). In our method, the geographical future occupancy of vehicles was formulated with Kamm’s circle. In computer experiments, sharing BDD-based occupancy data was successfully demonstrated in the ROS-based simulator with the linked list-based BDD. Algebraic operations in exchanged BDDs effectively managed future interactions such as data insertion and timing of collision avoidance in the LDM. This result opened a new door for the realization of the ideal LDM for safety in AVs.
Optimization Algorithm for Delay Estimation Based on Singular Value Decomposition and Improved GCC-PHAT Weighting
Authors: Wang Shizhe , Li Zongji , Wang Pingbo , Chen Huadong
Published: September 2022

The accuracy of time delay estimation seriously affects the accuracy of sound source localization. In order to improve the accuracy of time delay estimation under the condition of low SNR, a delay estimation optimization algorithm based on singular value decomposition and improved GCC-PHAT weighting (GCC-PHAT-ργ weighting) is proposed. Firstly, the acoustic signal collected by the acoustic sensor array is subjected to singular value decomposition and noise reduction processing to improve the signal-to-noise ratio of the signal; then, the cross-correlation operation is performed, and the cross-correlation function is processed by the GCC-PHAT-ργ weighting method to obtain the cross-power spectrum; finally, the inverse transformation is performed to obtain the generalized correlation time domain function, and the peak detection is performed to obtain the delay difference. The experiment was carried out in a large outdoor pool, and the experimental data were processed to compare the time delay estimation performance of three methods: GCC-PHAT weighting, SVD-GCC-PHAT weighting (meaning: GCC-PHAT weighting based on singular value decomposition) and SVD-GCC-PHAT-ργ weighting (meaning: GCC-PHAT-ργ weighting based on singular value decomposition). The results show that the delay estimation optimization algorithm based on SVD-GCC-PHAT-ργ improves the delay estimation accuracy by at least 37.95% compared with the other two methods. The new optimization algorithm has good delay estimation performance.
Long-Range Wireless System for U-Value Assessment Using a Low-Cost Heat Flux Sensor
Authors: Lazaro Marc , Lazaro Antonio , González Benito , Villarino Ramon , Girbau David
Published: September 2022

The present study exposes an economical and easy-to-use system to assess the heat transfer in building envelopes by determining the U-value. Nowadays these systems require long wires and a host to collect and process the data. In this work, a multi-point system for simultaneous heat flux measurement has been proposed. The aim is to reduce the long measurement time and the cost of thermal isolation evaluations in large buildings. The system proposed consists of a low-cost 3D-printed heat flux sensor integrated with a LoRa transceiver and two temperature sensors. The heat flux (HF) sensor was compared and calibrated with a commercial HF sensor from the Fluxteq brand.
A Fast Circle Detection Algorithm Based on Information Compression
Authors: Ou Yun , Deng Honggui , Liu Yang , Zhang Zeyu , Ruan Xusheng , Xu Qiguo , Peng Chengzuo
Published: September 2022

Circle detection is a fundamental problem in computer vision. However, conventional circle detection algorithms are usually time-consuming and sensitive to noise. In order to solve these shortcomings, we propose a fast circle detection algorithm based on information compression. First, we introduce the idea of information compression, which compresses the circular information on the image into a small number of points while removing some of the noise through sharpness estimation and orientation filtering. Then, the circle parameters stored in the information point are obtained by the average sampling algorithm with a time complexity of O(1) to obtain candidate circles. Finally, we set different constraints on the complete circle and the defective circle according to the sampling results and find the true circle from the candidate circles. The experimental results on the three datasets show that our method can compress the circular information in the image into 1% of the information points, and compared to RHT, RCD, Jiang, Wang and CACD, Precision, Recall, Time and F-measure are greatly improved.
Comparison of the World’s Best Pension Systems: The Lesson for Indonesia
Authors: Hadi Abdul , Bruder Emese , Setioningtyas Widhayani Puri
Published: September 2022

Iceland and the Netherlands presently have the best pension systems in the world, according to the Mercer CFA Institute Global Pension Index 2021. In the meantime, Indonesia ranked 35th. This study compares and analyzes Iceland’s and the Netherlands’ current pension systems as the finest in the world, as well as the future threats to their pension systems, and applies the lessons learned from both nations to Indonesia, which intends to alter its public pension system. According to a comparative analysis of Iceland, the Netherlands, and Indonesia, the overall pension systems of Iceland and the Netherlands are advantageous for ensuring adequacy and sustainability of the pension system. However, Iceland and the Netherlands may suffer adequacy and sustainability issues in the long run. As a result, they should continue to evaluate their own countries’ present structures, notably in demographics. Concerning the Indonesia pension system, Indonesia policymakers should consider enforcing the social security system, since these systems have enabled Iceland and the Netherlands to have lower poverty rates. Furthermore, the Indonesian government should strengthen the existing PAYG and DB pension systems, raise the minimum pension eligibility age, contribute to the system regularly, and apply the cost-of-living adjustments to improve the adequacy and sustainability of the civil service pension system. Simultaneously, civil servants should contribute more to ensure the long-term viability of this pension system. The Indonesian government should implement such adjustments, as they would enhance budgetary sustainability in the long run.
Beyond Usual Suspects? Inclusion and Influence of Non-State Actors in Online Public Consultations in Croatia
Authors: Vidačak Igor
Published: September 2022

Despite the increasing use of various e-democracy tools in shaping new policies, there is still a general lack of empirical studies on the influence of non-state actors in online public consultations. This article addresses this gap in the academic literature by focusing on the case of Croatia, which may have relevant broader practical and theoretical implications due to the legally binding rules of institutional responsiveness to individual policy inputs received during e-consultations and the growing interest of citizens and various interest groups to get engaged in this form of policy dialogue. Drawing on the novel data set that includes the responses of 39 government bodies to 51,250 policy inputs of interest groups and individual citizens to online consultations during the first three years since the launch of the government consultation platform, the paper seeks to analyse the influence of different types of non-state actors on the outcomes of government-led online public consultations. Contrary to general expectations about the predominance of more resourceful interest groups, it is argued that individual citizens exert a noticeable influence on the results of online policy consultations of Croatian government bodies. It is also claimed that the specific design and patterns of online public consultations, especially improved responsiveness of government bodies, contribute to the pluralisation of interests, equalizing political representation, and empowering individual citizens and other new actors, beyond traditional interest groups and “usual suspects” in national decision-making processes.
Reshaping How We Think about Soil Security
Authors: Mizuta Katsutoshi , Grunwald Sabine
Published: September 2022

The soil security framework has been conceptualized and views soil as a resource that needs to be secured to avoid or minimize adverse environmental/anthropogenic impacts and undesirable consequences for people. Our critical literature review suggests that measurements, estimations, simulations, or digital mapping of soil properties fall short in assessing soil security and health. Instead, soil security that considers soil ecosystem functionality based on regionalized and optimized relationships between targeted functions and site-specific soil environmental conditions allows for the discernment of actual and attainable efficiency levels for observation sites. We discuss the pros and cons that undergird the paradigm shift toward a pedo-econometric modeling approach. Such a multiperspectival approach to soil security allows for simultaneous interpretations from economic, pedogenic, agronomic, environmental, biotic/habitat, and other perspectives. This approach is demonstrated by modeling total nutrient efficiencies in complex multi-use soilscapes with diverging soil environmental interests and concerns.
Image Classification Method Based on Improved Deep Convolutional Neural Networks for the Magnetic Flux Leakage (MFL) Signal of Girth Welds in Long-Distance Pipelines
Authors: Geng Liyuan , Dong Shaohua , Qian Weichao , Peng Donghua
Published: September 2022

Girth weld defects in long-distance oil and gas pipelines are one of the main causes of pipeline leakage failure and serious accidents. Magnetic flux leakage (MFL) is one of the most widely used inline inspection methods for long-distance pipelines. However, it is impossible to determine the type of girth weld defect via traditional manual analysis due to the complexity of the MFL signal. Therefore, an automatic image classification method based on deep convolutional neural networks was proposed to effectively classify girth weld defects via MFL signals. Firstly, the image data set of girth welds MFL signal was established with the radiographic testing results as labels. Then, the deep convolutional generative adversarial network (DCGAN) data enhancement algorithm was proposed to enhance the data set, and the residual network (ResNet-50) was proposed to address the challenge presented by the automatic classification of the image sets. The data set after data enhancement was randomly selected to train and test the improved residual network (ResNet-50), with the ten validation results exhibiting an accuracy of over 80%. The results indicated that the improved network model displayed a strong generalization ability and robustness and could achieve a more accurate MFL image classification of the pipeline girth welds.
The Multi-Level Hierarchical Structure of the Enablers for Supply Chain Resilience Using Cloud Model-DEMATEL–ISM Method
Authors: Chen Jih-Kuang , Huang Tien-Yu
Published: September 2022

Companies must shift from traditional supply chain management thinking to addressing or preventing increases in vulnerability, uncertainty, and unforeseen supply chain disruptions facing complex global supply chains. Systems with a large number of elements may be susceptible to nonlinear interactions, perturbation of which may lead to serious impacts. Thus, there is an increasing need to determine the importance of individual elements and how these elements interact. Published studies of supply chain resilience (SCRes) do not clearly determine the hierarchical structure of factors, and the understanding of interactions between factors remains fragmented. In this study, we proposed a cloud model-DEMATEL−ISM method to overcome the disadvantages of traditional DEMATEL−ISM integration methods. The MICMAC method (cross-impact matrix multiplication applied to classification) was also used to classify the enablers of SCRes based on driving force and dependence force. We tested these approaches by studying the new energy vehicle industry in China. The results suggest that companies trying to strengthen SCRes should focus on enablers at the base layer with a high driving force, particularly the enablers of social capital, restructuring, risk management culture, information technology application, trust and collaboration, information sharing, and learning capability..
Method for studying the rheological properties of parotid saliva using controlled dynamic sialometry
Authors: Shchipskiy A. V. , Kalimatova M. M. , Mukhin P. N.
Published: September 2022

Relevance. Sialometry may determine the nature of x erostomia, and the results should be representativ e. The study aimed to increase the information value of the parotid gland secretory function examination by determining saliva rheological properties during the c ontrolled dynamic sialometry.

Materials and methods. Twenty-two patients with xerostomia had a controlled dynamic sialometry in two stages with simultaneous saliva sampling using a Lashley capsule and a catheter. At the first stage, the capsule was on the right, the catheter was on the left; at the second stage their places were swapped. In 44 comparison pairs, the capsule parameters were the control, the catheter parameters were studied. The method of stimulated ductal sialometry according to Andreeva T.B. formed a basis of the study. The study eliminated the technological error of sialometry, the rheological state of saliva was determined by subtracting the catheter index from the capsule index. The study was approved by the ethics committee (No. 02-21 dated February 18, 21), voluntary. Difference significance was statistically assessed using the Student 's t-test. The results were significant at p ≤ 0.05.

Results. The analysis of 44 comparison pairs showed a priority (t = 7.317; p < 0.001) of the number of cases with large capsule scores (n = 34; 77.3%) compared catheter (n = 7; 15.9%). Therefore, capsule sialometry is more representative. Capsule sialometry (n = 44) showed hyposalivation in 11 cases (25.0%), secretion values were normal (t = 5.416; p < 0.001) in the remaining 33 cases (75.0%). Normal rheological condition of saliva was significantly more common in the hyposalivation group – objective xerostomia (t = 1.900; p < 0.05); rheological disorders were significantly more common in the group with normal secretion - subjective xerostomia (t = 7.729; p < 0.01).

Conclusion. Controlled dynamic sialometry determines the technological error and objectifies sialometry parameters; explores saliva rheological condition, which affects the performance of sialometry when using a catheter. Objective xerostomia is characterized by hyposalivation with a secondary significance of saliva rheological condition. Subjective xerostomia can occur only due to a saliva rheological disorder .
Age and social identity as factors influencing adherence to oral care among dental patients
Authors: Tachalov V. V. , Kudryavtseva T. V. , Orekhova L. Yu. , Loboda E. S. , Bergman E. D. , Berezkina I. V. , Oksas N. S.
Published: September 2022

Relevance. Underestimation of the importance of dental disease prevention and the occurrence or complication of physical health problems are two causally related factors. Compliance with the rules of individual and professional oral care is an important constituent to prevention, often ignored by patients of all ages and different social groups.

Materials and methods. A total of 706 persons, including 529 women and 172 men, participated in the study. According to the WHO age classification, the participants formed four age groups: 18-24, 25-44, 45-59, and 60-74 years old. In terms of social identity, these groups comprised dentists (216 persons), dental patients (274 persons) and non-dental healthcare professionals (216 persons). The study focused on the adherence to oral preventive measures performed by patients of different age, gender and social identity groups.

Results. Despite the majority of the respondents were sufficiently aware of dental disease prevention and oral care, not all turned out to be compliant with medical advice. There were differences between age and social identity groups of patients in reasons of dental visits, use of oral hygiene products and professional oral care.

Conclusion. The study confirmed the relationship between underestimation of dental disease prevention and physical pathology. Of all age groups, the lowest level of compliance with oral care practices and the highest percentage of internal diseases were in 60-74-year-old patients. Women are more adherent to oral care measures than men; healthcare professionals showed the lowest compliance with oral care measures.
Issue microcirculation around extended implant-supported prostheses with few abutment sites in patients with terminal mandibular dentition
Authors: Rozov R. A. , Trezubov V. N. , Loboda E. S. , Arutyunov S. D. , Oisieva K. Sh.
Published: September 2022

Relevance. The success of implant-supported prostheses depends on the quality of the jawbone. Traditionally, it is assessed radiographically, but this method is not only invasive but also unreliable and inaccurate for predicting the outcome of treatment.

Material and methods. The study included 80 patients (49 women and 31 men) with a mean age of 71 ± 7 years, which formed four groups. Group A (control group, n = 20) consisted of patients with healthy periodontium; comparison group B, n = 20, comprised patients with terminal dentition; the main group C (n = 20) included patients with extended rehabilitation, fixed 7-10 days before; group G (n = 20) was composed of patients with “Trefoil” implant-supported prostheses, fixed three years earlier. The blood flow of peri-implant tissues was assessed using ultrasound Doppler flowmetry (UDF). All patients (n = 20) underwent dual-energy X-ray absorptiometry (DXA) before the prosthetic treatment.

Results. The analysis of pre-prosthetic-treatment ultrasound Doppler flowmetry results showed low values of microcirculation in the alveolar ridge mucous membrane in patients with terminal dentition compared with the control group. On the 7th day after implant-supported prosthetic treatment, group C demonstrated an increase in microcirculation by 11.42% compared to the control group and by 147.36% compared to group B. Three years after implant-supported prosthetic treatment, the ultrasound data revealed a statistically significant increase in blood flow velocity 0.342 ± 0.04 (cm/s) (p < 0.01). The Pearson coefficient determined a high correlation between T-scores of DXA and ultrasound Doppler flowmetry data (r = 0.829, p = 0.0001).

Conclusion. Ultrasound Doppler flowmetry (UDF) can be the main method for studying the peri-implant tissue condition at various stages of implant-supported prosthetic treatment.
Desarrollo de un prototipo de sistema ciber-físico para el control administrativo del suministro de bebidas y refrescos
Authors: Sanchez-Galan Javier , Castro Rodríguez Arturo A.
Published: September 2022

Este proyecto se centra en demostrar la viabilidad de la implementación de nuevas tecnologías, principalmente herramientas de inteligencia artificial, para el control de suministro de bebidas de forma automatizada, pero también aplicable a diferentes tipos de productos alimenticios. Esto es posible ya que, en áreas de automatización, las herramientas de inteligencia artificial han propiciado cambios profundos en las industrias y el comercio. Esto debido fundamentalmente al avance de la tecnología y a que las empresas producen información masiva que marcan riesgos e incertidumbre a la hora de la toma de decisiones empresariales, por lo que es de suma importancia organizar dicha información de forma eficiente. Este proyecto básicamente acerca del de desarrollo de un sistema experto que calcule la cantidad de bebida y/o refresco que se necesita a la semana siguiente en un local de restaurante de comida rápida, que trabaja junto con un prototipo de máquina expendedora de bebida controlada por Arduino (aunque puede ser cualquier otro micro-controlador). En este documento se muestran aspectos para diseño, elaboración y desarrollo de aplicaciones e instrumentos que cumplan con este objetivo, además se describe el porqué del proyecto y como esto pretende aportar al sector al cual está enfocado. Al final se muestra una mejor manera de administrar el abastecimiento de bebidas en restaurantes de comida rápida y se concluye que la implementación de este proyecto en este tipo de negocios, puede generar ahorros en productos y puede contribuir a evitar en gran medida la contaminación del medio ambiente, todo enmarcado dentro de la industria 4.0.
Manganese, Molybdenum and Selenium in the Great Salt Lake
Authors: Tayler Paul L. , Hutchinson Lynn A. , Muir Melvin K.
Published: September 2022

The behavior of manganese, molybdenum and selenium in the Great Salt Lake was investigated. These elements occur in inflowing streams, both from natural and industrial origins. The brines and sediments of the Great Salt Lake were sampled and analyzed to determine the disposition of the elements in the lake. It was found that manganese, molybdenum and selenium are not concentrating in the brines as are other soluble salts but are being precipitated into the sediments.
Some Spectrum Estimates of the $\alpha q$-Ces\`{a}ro Matrices with $0<\alpha ,q<1$ on $c$
Authors: Türkay Merve Esra
Published: September 2022

$q$-Calculus Theory is rapidly growing in various directions. The goal of this paper is to collect and underline recent results on $\alpha q$-analogs of the Cesàro matrix andemphasize various generalizations. One $\alpha q$-analogs of the Cesàro matrix of order one is the triangular matrix with nonzero entries $c_{nk}^{\alpha }\left( q\right) =\tfrac{\left( \alpha q\right) ^{n-k}}{1+q+\cdots +q^{n}},\ 0\leq k\leq n$, where $\alpha ,q\in \left( 0,1\right) $. The purpose of this article examines various spectral decompositions of $C_{q}^{\alpha }=\left( c_{nk}^{\alpha }\left( q\right) \right) $ such as the spectrum, the fine spectrum, the approximate point spectrum, the defect spectrum, and the compression spectrum on the sequence space $c$.
Hafif Beton Üretimi İçin Gerekli Olan Hafif Agrega Miktarının Yapay Sinir Ağı ile Tahmin Edilmesi
Authors: SAĞLAM Rabia Nur , AÇIKGENÇ ULAŞ Merve , ALYAMAÇ Kürşat Esat
Published: September 2022

Bu çalışmanın amacı hafif beton üretilirken hedef mukavemet için gerekli olan hafif agrega miktarının tayin edilmesi ve gelecek çalışmalarda üretilecek hafif betonlar için pratik bir karışım tasarımı sunmaktır. Bu amaçla literatürde yer alan hafif beton ile ilgili çalışmalar detaylı bir şekilde incelenmiştir. Bu çalışmalarda bulunan hafif betonlara ait veriler sınıflandırılmış ve listelenmiştir. Literatürden hafif betonlara ait karışım bileşenleri ve hedef basınç dayanımı değerleri alınmıştır. Literatürden alınan deneysel veriler ile bir Yapay Sinir Ağı (YSA) modeli geliştirilmiştir. Bu modelde su, çimento, normal agrega, toz, kimyasal katkı, hedef basınç mukavemet ve hafif agrega tipi giriş olarak kullanılmıştır. Modelin çıkışı ise hafif agrega miktarı olarak belirlenmiştir. Düzenlenen veriler geliştirilen YSA modeli kullanılarak hafif beton bileşimindeki hafif agrega miktarının tahmininde kullanılmıştır. Geliştirilen model çıkışları ile literatürden alınmış deneysel veriler karşılaştırılmıştır. Geliştirilen YSA modeli ile elde edilen sonuçlar ile deneysel veriler arasındaki farklar uygun sınırlar içerisinde bulunmuştur. Sonuç olarak geliştirilen YSA modelinin hedeflenen çıkışı başarılı bir şekilde ve yüksek doğrulukta tahmin ettiği görülmektedir. Böylece hedef basınç dayanımı belirlenmiş olan bir hafif beton karışımı için hafif agrega miktarı hızlı, pratik ve yüksek doğrulukta tahmin edilmiş olacaktır.