bluuebunny/crossref_metadata_2025 huggingface dataset:
Extraction and Characterization of Microcrystalline Cellulose from Lagenaria siceraria Fruit Pedicles
Authors: Asif Muhammad , Ahmed Dildar , Ahmad Naveed , Qamar Muhammad Tariq , Alruwaili Nabil K. , Bukhari Syed Nasir Abbas
Published: May 2022

Microcrystalline cellulose (MCC) is a versatile polymer commonly employed in food, chemical, and biomedical formulations. Lagenaria siceraria (bottle gourd) fruit is consumed in many parts of the world, and its pedicle is discarded as waste. In the quest for a novel renewable source of the MCC, the present study investigates the extraction and characterization of MCC from the pedicle of Lagenaria siceraria fruits. The MCC was extracted by sequentially treating pedicles with water, alkali, bleaching (sodium chlorite), and dilute sulfuric acid (acid hydrolysis). The removal of associated impurities from pedicle fibers was confirmed by Fourier transform infrared analyses. The extracted MCC exhibited a characteristic crystalline structure of cellulose in X-ray diffraction with a 64.53% crystallinity index. The scanning electron microscopy (SEM) showed the variation in the morphology of the fibers and the formation of MCC of approximately 100 µm. The thermogravimetric analysis (TGA) indicated higher thermal stability of MCC. MCC production from biowaste (pedicle) holds potential for application as an emulsifier, stabilizer, and thickener in the chemical, pharmaceutical, and food industries.
Physical Characterization of Material for the Development of Orthopedic Orthosis for Diabetic Foot
Authors: de Souza Karla Camila Lima , de Lima Batista Anderson Marcio , Duarte Eden Batista , Martins Jonathan Elias Rodrigues , Modesto Filho Antônio Nadson , Dias José William Girão , Dias Diego Felix , de Freitas Rosa Morsyleide , de Freitas Raquel Martins , da Silva Felipe Stela Mirla , Santos Júnior Francisco Fleury Uchoa , Ceccatto Vânia Marilande
Published: May 2022

The diabetic foot is characterized by the loss of foot ulcerations and sensitivity. The use of orthopedic orthosis can prevent pathological changes in the diabetic foot. The objective of this study was to characterize materials used for producing orthopedic orthosis: silicone; pre-vulcanized latex of Hevea brasiliensis; Evapod, and Podadur. The Hevea brasiliensis latex material is widely indicated in the literature for biomedical purposes. Physical–mechanical properties were determined (properties of elastic deformation, resistance, durability, lightness, energy absorption, resistance to high temperatures, and chemical composition—ASTM International). In the tensile test, the latex reached 6.02 ± 0.33 MPa, having the best performance among the other materials. In the elastic module, the Podadur stood out, with 28.2 ± 0.89 MPa, compared to silicone with 0.42 ± 0.05 MPa. The most excellent Shore A hardness material was Podadur with 58%. As for the resilience, the Podadur presented a minimum value of 22%, while latex had 63%. Silicone was the densest material, with a density of 1.48 g/cm3, and Evapod and Podadur were the lightest, respectively, at 0.22 g/cm3 and 0.42 g/cm3. Morphologically, Evapod, Podadur, and latex presented open and interconnected cells, characteristics that gave them a more significant water absorption capacity. Silicone was the only material with no empty cells in its structure. In X-ray diffraction, Evapod, Podadur, and silicone materials presented well-defined crystallographic planes, whereas amorphous behavior characterized latex. Thermogravimetry showed weight loss between 240 and 650 °C in the four materials. In the fluorescence test, the presence of metals was observed in the composition of the four materials. Among the materials studied, the Podadur was the material that stood out, with some good properties for the development of orthopedic orthosis.
The Effects of Logistics Websites’ Technical Factors on the Optimization of Digital Marketing Strategies and Corporate Brand Name
Authors: Sakas Damianos P. , Reklitis Dimitrios P. , Trivellas Panagiotis , Vassilakis Costas , Terzi Marina C.
Published: May 2022

In a world overwhelmed with unstructured information, logistics companies increasingly depend on their websites to acquire new customers and maintain existing ones. Following this rationale, a series of technical elements may set the ground for differentiating one logistics website from another. Nevertheless, a suitable digital marketing strategy should be adopted in order to build competitive advantage. In this paper, the authors attempt to respond by implementing an innovative methodology building on web analytics and big data. The first phase of the research collects data for 180 days from 7 world-leading logistics companies. The second phase presents the statistical analysis of the gathered data, including regression, correlations, and descriptive statistics. Subsequently, Fuzzy Cognitive Mapping (FCM) was employed to illustrate the cause-and-effect links among the metrics in question. Finally, a predictive simulation model is developed to show the intercorrelation among the metrics studied as well as various optimization strategies. Research findings reveal a significant correlation between the logistics websites’ technical factors and the growth of the corporate brand name.
Performing Multi-Objective Optimization Alongside Dimension Reduction to Determine Number of Clusters
Authors: Mollaian Melisa , Dörgő Gyula , Palazoglu Ahmet
Published: May 2022

One of the consequences of the widespread automation of manufacturing operations has been the proliferation and availability of historical databases that can be exploited by analytical methods to improve process understanding. Data science tools such as dimension reduction and clustering are among many such approaches that can aid in the identification of unique process features and patterns that can be associated with faulty states. However, determining the number of such states still requires significant engineering knowledge and insight. In this study, a new unsupervised method is proposed that reveals the number of classes in a data set. The method utilizes a variety of dimension reduction techniques to create projections of a data set and performs multiple clustering operations on the lower-dimensional data as well as the original data. The relevant internal clustering metrics are incorporated into a multi-objective optimization problem to determine the solutions that simultaneously optimize all metrics. The cluster number that shows Pareto optimality based on the performance metrics is selected as the final one. The method is tested on three data sets with distinct features. The results demonstrate the ability of the proposed method to correctly identify the expected number of clusters.
Intelligent Prediction Model (IPM) of Foundation Pit Displacement Based on Extreme Learning Machine (ELM) and Its Application
Authors: Liu Shangge , Sun Changzhong , Zhou Hui , Wang Yuanhai
Published: May 2022

In order to effectively predict the dynamic displacement and disaster, according to the analysis of the influencing parameters affecting the deformation of a subway foundation pit supported by piles (walls), the rough set attribute reduction method (RSARM) and the average influence value algorithm (AIVA) are used to simplify the influencing factors of foundation pit deformation. Those simplified factors are taken as the input of the ELM, with the output being the displacement of the foundation pit. Finally, the IPM of foundation pit displacement derived from the ELM is obtained, which is finally used for engineering practice. The results show that it is feasible to simplify the influencing factors of the deformation of the foundation pit by RSARM and AIVA. The proposed IPM of foundation pit displacement has high accuracy and good generalization ability, which can be used for the deformation prediction.
Application of Monitoring Module Three-in-One Microsensor to Real-Time Microscopic Monitoring of Polarizer Sheet in Roll-to-Roll Process
Authors: Lee Chi-Yuan , Lee Shuo-Jen , Chen Chwan-Hsen , Yang Lung-Jieh , Wang Xin-Wen , Lin Jyun-Ting , Chao Po-Yeng , Chen Shan-Yu
Published: May 2022

The Roll-to-Roll (R2R) process refers to a high-efficiency, low-cost, continuous production method. The roll material used for processing is a flexible plastic or metal film. In many R2R processes, polarizing films are high-precision products with a high output value. In the production of conventional polarizers, product inspection will only be carried out after the production of the polarizing film is completed. The principal raw material of a polarizer sheet is a hydrophilic polymer, the properties of which may be influenced by water vapor, which degrades its quality. Whether or not the product is impacted can be ascertained by means of a quality inspection, but it must be performed after the process is finished. However, it is already too late when a defective product is detected: the production cost is increased, the schedule is influenced and the delivery date is delayed. The focus of this research was on environmental monitoring of the production drying process oven, but the commercial all-in-one sensors currently on the market cannot tolerate the temperature of the factory’s high-temperature oven. In particular, a commercial flow sensor is rarely suited to high-temperature applications. Some are expensive and cannot be widely distributed. Therefore, this study aimed to develop an integrated sensor to measure the internal environment of the drying process oven for the real-time monitoring of a polarizer sheet in the Roll-to-Roll (R2R) process. This study used micro-electro-mechanical systems (MEMS) technology to make a flexible three-in-one (temperature, humidity and flow) micro-sensor. We monitored the temperature, humidity and flow uniformity in a laboratory oven to simulate the environment of the actual factory oven, with the aim to provide data to confirm whether or not a polarizer sheet has dried. Our system can be monitored instantly by Arduino, or even Raspberry Pi 3, to realize the flexible micro-sensor layout and field verification, in order to optimize the R2R process and to enhance the yield and performance of the polarizer sheet process.
Weather, Land and Crops in the Indus Village Model: A Simulation Framework for Crop Dynamics under Environmental Variability and Climate Change in the Indus Civilisation
Authors: Angourakis Andreas , Bates Jennifer , Baudouin Jean-Philippe , Giesche Alena , Walker Joanna R. , Ustunkaya M. Cemre , Wright Nathan , Singh Ravindra Nath , Petrie Cameron A.
Published: May 2022

The start and end of the urban phase of the Indus civilization (IC; c. 2500 to 1900 BC) are often linked with climate change, specifically regarding trends in the intensity of summer and winter precipitation and its effect on the productivity of local food economies. The Indus Village is a modular agent-based model designed as a heuristic “sandbox” to investigate how IC farmers could cope with diverse and changing environments and how climate change could impact the local and regional food production levels required for maintaining urban centers. The complete model includes dedicated submodels about weather, topography, soil properties, crop dynamics, food storage and exchange, nutrition, demography, and farming decision-making. In this paper, however, we focus on presenting the parts required for generating crop dynamics, including the submodels involved (weather, soil water, land, and crop models) and how they are combined progressively to form two integrated models (land water and land crop models). Furthermore, we describe and discuss the results of six simulation experiments, which highlight the roles of seasonality, topography, and crop diversity in understanding the potential impact of environmental variability, including climate change, in IC food economies. We conclude by discussing a broader consideration of risk and risk mitigation strategies in ancient agriculture and potential implications to the sustainability of the IC urban centres.
Landslide Risk Assessment Using a Combined Approach Based on InSAR and Random Forest
Authors: Liu Wangcai , Zhang Yi , Liang Yiwen , Sun Pingping , Li Yuanxi , Su Xiaojun , Wang Aijie , Meng Xingmin
Published: May 2022

Landslide risk assessment is important for risk management and loss–damage reduction. Herein, we assessed landslide susceptibility, hazard, and risk in the urban area of Yan’an City, which is located on the Loess Plateau of China and affected by many loess landslides. Based on 1841 slope units mapped in the study area, a random forest machine learning classifier and eight environmental factors influencing landslides were used for a landslide susceptibility assessment. In addition, differential synthetic aperture radar interferometry (DInSAR) technology was used for a hazard assessment. The accuracy of the random forest is 0.903 and the area under the receiver operating characteristics (ROC) curve is 0.96. The results show that 16% and 22% of the slope units were classified as being at very high and high-susceptibility levels for landslides, respectively, whereas 16% and 24% of the slope units were at very high and high-hazard levels for landslides, respectively. The landslide risk was obtained based on the susceptibility map and hazard map of landslides. The results show that only 26% of the slope units were located at very high and high-risk levels for landslides and these are mainly concentrated in urban centers. Such risk zones should be taken seriously and their dynamics must be monitored. Our landslide risk map is expected to provide information for planners to help them choose appropriate locations for development schemes and improve integrated geohazard mitigation in Yan’an City.
A Dual w-Test Based Quality Control Algorithm for Integrated IMU/GNSS Navigation in Urban Areas
Authors: Sun Rui , Qiu Ming , Liu Fei , Wang Zhi , Ochieng Washington Yotto
Published: May 2022

Integration of the Global Navigation Satellite System (GNSS), with Inertial Measurement Unit (IMU) sensors to improve navigation performance, is widely used in many land-based applications. However, further application, especially in urban areas, is limited by the quality (due mainly to multipath effects) and availability of GNSS measurements, with a significant impact on performance, especially from low grade integration. To maximize the potential of GNSS measurements, this paper proposes a dual w-test-based quality control algorithm for integrated IMU/GNSS navigation in urban areas. Quality control is achieved through fault detection and exclusion (FDE) with the capability to detect simultaneous multiple faults in measurements from different satellites. The remaining fault-free GNSS measurements are fused with IMU sensor measurements to obtain the final improved state solution. The effectiveness of the algorithm is validated in a deep urban field test. Compared to the cases without fault exclusion, the results show improvements of about 24% and 30% in horizontal and vertical positioning components, respectively.
Development of a UAV-Based Gamma Spectrometry System for Natural Radionuclides and Field Tests at Central Asian Uranium Legacy Sites
Authors: Kunze Christian , Preugschat Benedikt , Arndt Robert , Kandzia Felix , Wiens Benjamin , Altfelder Sven
Published: May 2022

Uranium mining and processing had been widespread in Central Asia since the mid-1940s. However, with the establishment of the newly independent states in the 1990s, many of the former uranium mining and processing facilities and their associated wastes (dumps and tailings) were abandoned and have since posed a threat to the environment. The fact that the sites were left behind without proper remediation for a long time has led to the uncontrolled spread of radioactive and toxic contaminants in the environment due to landslides or flooding. Knowledge of the exact location of some waste facilities was lost as a result of social disruptions during the 1990s. In order to assess radiological risks and plan and implement adequate, sustainable, and environmental remediation measures, the radiological situation at the uranium legacy sites must be repeatedly mapped with the best possible accuracy in terms of both sensitivity and spatial resolution. In this paper, we present the experimental use of an unmanned aerial vehicle (UAV) equipped with gamma spectrometry systems as a novel tool for mapping, assessing, and monitoring radioactivity at sites affected by uranium mining and processing and other activities related to enhanced natural radioactivity. Special emphasis is put on the practical conditions of using UAV-based gamma spectrometry in an international context focusing on low- and medium-income countries. Challenges and opportunities of this technology are discussed, and its reliability and robustness under field conditions are critically reviewed. The most promising future application of the technology appears to be the radiological monitoring, institutional control, and quality assurance of legacy sites during and after environmental remediation. One-off administrative and logistical challenges of the technology are outweighed by the significant amount of time and cost saved once a UAV-based gamma spectrometry survey system is set up.
A Parallel Method for Texture Reconstruction in Large-Scale 3D Automatic Modeling Based on Oblique Photography
Authors: Wang Fei , Zhu Hongchun , Cai Haolin , Qu Wenhu , Zhang Shuaizhe , Liu Zhendong
Published: May 2022

Common methods of texture reconstruction first build a visual list for each triangular face, and then select the best image for each triangular face based on the graph-cut method. These methods have problems such as high memory consumption, and difficulties in large-area texture reconstruction. Hence, this paper proposes a parallel method for texture reconstruction in large-scale 3D automatic modeling. First, the hierarchical relationships between the texture reconstruction are calculated in accordance with the adjacency relationships between partitioning cells. Second, building contours are extracted based on the 3D mesh model, the tiles are divided into two categories (occlusion and non-occlusion), and the incorrect occlusion relationship is restored based on the occluded tiles. Then, the graph-cut algorithm is constructed to select the best-view label. Finally, the jagged labels between adjacent labels are smoothed to alleviate the problem of texture seams. Oblique photography data from an area of 10 km2 in Dongying, Shandong were used for validation. The experimental results reveal the following: (i) concerning reconstruction efficiency, the Waechter method can perform texture reconstruction only in a small area, whereas with the proposed method, the size of the reconstruction area is not restricted. The memory consumption is improved by factors of approximately 2–13. (ii) Concerning reconstruction results, the Waechter method incorrectly reconstructs the textures of partially occluded regions at the tile edges, while the proposed method can reconstruct the textures correctly. (iii) Compared to the Waechter method, the proposed approach has a 30% lower reduction in the number of texture fragments.
Calibration of Phased-Array High-Frequency Radar on an Anchored Floating Platform
Authors: Wan Bin , Wu Xiongbin , Yue Xianchang , Zhang Lan , Wang Li
Published: May 2022

Prior studies have highlighted the importance of calibrating receiver antennas in target direction-of-arrival (DOA) estimation and surface current measurement for high-frequency (HF) radar systems. It is worth noting that the calibration contributes to the performance of both shore-based HF radar and platform-mounted HF radar. Compared with shore-based HF radar, the influence of six-degrees-of-freedom (six-DOF) platform motion should be considered in the calibration of platform-mounted HF radar. This paper initially describes a calibration scheme that receives phasedarray antennas for an anchored platform-mounted HF radar incorporating a model of free rotation, which is called yaw rotation and dominates the six-DOF platform motion in this study. In the presence of yaw rotation, the amplitude and phase of the source calibration signal from the other shore-based radar sites reveal the directional sensitivity of the receiver phased-array antennas. The calibration of receiver phased-array antennas is composed of channel calibration (linking cables and receiver hardware calibration) and antenna pattern calibration. The antenna pattern at each bearing can be represented by the Fourier series. The estimation of channel calibration and antenna pattern calibration depends on an overdetermined HF radar system consisting of observed values and theoretical constraints, so the least-squares fits of the channel calibration coefficients and antenna pattern calibration coefficients are obtained. The experimental results show that the target DOA estimation and surface current measurement can be improved if the phased-array platform-mounted HF radar system is calibrated.
Physiographic Controls on Landfast Ice Variability from 20 Years of Maximum Extents across the Northwest Canadian Arctic
Authors: Wratten Eleanor E. , Cooley Sarah W. , Mann Paul J. , Whalen Dustin , Fraser Paul , Lim Michael
Published: May 2022

Landfast ice is a defining feature among Arctic coasts, providing a critical transport route for communities and exerting control over the exposure of Arctic coasts to marine erosion processes. Despite its significance, there remains a paucity of data on the spatial variability of landfast ice and limited understanding of the environmental processes’ controls since the beginning of the 21st century. We present a new high spatiotemporal record (2000–2019) across the Northwest Canadian Arctic, using MODIS Terra satellite imagery to determine maximum landfast ice extent (MLIE) at the start of each melt season. Average MLIE across the Northwest Canadian Arctic declined by 73% in a direct comparison between the first and last year of the study period, but this was highly variable across regional to community scales, ranging from 14% around North Banks Island to 81% in the Amundsen Gulf. The variability was largely a reflection of 5–8-year cycles between landfast ice rich and poor periods with no discernible trend in MLIE. Interannual variability over the 20-year record of MLIE extent was more constrained across open, relatively uniform, and shallower sloping coastlines such as West Banks Island, in contrast with a more varied pattern across the numerous bays, headlands, and straits enclosed within the deep Amundsen Gulf. Static physiographic controls (namely, topography and bathymetry) were found to influence MLIE change across regional sites, but no association was found with dynamic environmental controls (storm duration, mean air temperature, and freezing and thawing degree day occurrence). For example, despite an exponential increase in storm duration from 2014 to 2019 (from 30 h to 140 h or a 350% increase) across the Mackenzie Delta, MLIE extents remained relatively consistent. Mean air temperatures and freezing and thawing degree day occurrences (over 1, 3, and 12-month periods) also reflected progressive northwards warming influences over the last two decades, but none showed a statistically significant relationship with MLIE interannual variability. These results indicate inferences of landfast ice variations commonly taken from wider sea ice trends may misrepresent more complex and variable sensitivity to process controls. The influences of different physiographic coastal settings need to be considered at process level scales to adequately account for community impacts and decision making or coastal erosion exposure.
Noise Robust High-Speed Motion Compensation for ISAR Imaging Based on Parametric Minimum Entropy Optimization
Authors: Wang Jiadong , Li Yachao , Song Ming , Huang Pingping , Xing Mengdao
Published: May 2022

When a target is moving at high-speed, its high-resolution range profile (HRRP) will be stretched by the high-order phase error caused by the high velocity. In this case, the inverse synthetic aperture radar (ISAR) image would be seriously blurred. To obtain a well-focused ISAR image, the phase error induced by target velocity should be compensated. This article exploits the variation continuity of a high-speed moving target’s velocity and proposes a noise-robust high-speed motion compensation algorithm for ISAR imaging. The target’s velocity within a coherent processing interval (CPI) is modeled as a high-order polynomial based on which a parametric high-speed motion compensation signal model is developed. The entropy of the ISAR image after high-speed motion compensation is treated as an evaluation metric, and a parametric minimum entropy optimization model is established to estimate the velocity and compensate it simultaneously. A gradient-based solver of this optimization is then adopted to iteratively find the optimal solution. Finally, the high-order phase error caused by the target’s high-speed motion can be iteratively compensated, and a well-focused ISAR image can be obtained. Extensive simulation experiments have verified the noise robustness and effectiveness of the proposed algorithm.
Unmanned Aerial Vehicle for Laser Based Biomedical Sensor Development and Examination of Device Trajectory
Authors: Masud Usman , Saeed Tareq , Akram Faraz , Malaikah Hunida , Akbar Altaf
Published: May 2022

Controller design and signal processing for the control of air-vehicles have gained extreme importance while interacting with humans to form a brain–computer interface. This is because fewer commands need to be mapped into multiple controls. For our anticipated biomedical sensor for breath analysis, it is mandatory to provide medication to the patients on an urgent basis. To address this increasingly tense situation in terms of emergencies, we plan to design an unmanned vehicle that can aid spontaneously to monitor the person’s health, and help the physician spontaneously during the rescue mission. Simultaneously, that must be done in such a computationally efficient algorithm that the minimum amount of energy resources are consumed. For this purpose, we resort to an unmanned logistic air-vehicle which flies from the medical centre to the affected person. After obtaining restricted permission from the regional administration, numerous challenges are identified for this design. The device is able to lift a weight of 2 kg successfully which is required for most emergency medications, while choosing the smallest distance to the destination with the GPS. By recording the movement of the vehicle in numerous directions, the results deviate to a maximum of 2% from theoretical investigations. In this way, our biomedical sensor provides critical information to the physician, who is able to provide medication to the patient urgently. On account of reasonable supply of medicines to the destination in terms of weight and time, this experimentation has been rendered satisfactory by the relevant physicians in the vicinity.
Strain-Dependent Photoacoustic Characteristics of Free-Standing Carbon-Nanocomposite Transmitters
Authors: Faraz Muhammad , Abbasi Muhammad Awais , Son Donghee , Shin Changhwan , Lee Kyu-Tae , Won Sang Min , Baac Hyoung Won
Published: May 2022

In this paper we demonstrate strain-dependent photoacoustic (PA) characteristics of free-standing nanocomposite transmitters that are made of carbon nanotubes (CNT) and candle soot nanoparticles (CSNP) with an elastomeric polymer matrix. We analyzed and compared PA output performances of these transmitters which are prepared first on glass substrates and then in a delaminated free-standing form for strain-dependent characterization. This confirms that the nanocomposite transmitters with lower concentration of nanoparticles exhibit more flexible and stretchable property in terms of Young’s modulus in a range of 4.08–10.57 kPa. Then, a dynamic endurance test was performed revealing that both types of transmitters are reliable with pressure amplitude variation as low as 8–15% over 100–800 stretching cycles for a strain level of 5–28% with dynamic endurance in range of 0.28–2.8%. Then, after 2000 cycles, the transmitters showed pressure amplitude variation of 6–29% (dynamic endurance range of 0.21–1.03%) at a fixed strain level of 28%. This suggests that the free-standing nanocomposite transmitters can be used as a strain sensor under a variety of environments providing robustness under repeated stretching cycles.
Effective Pre-Training Method and Its Compositional Intelligence for Image Captioning
Authors: Choi Won-Hyuk , Choi Yong-Suk
Published: May 2022

With the increase in the performance of deep learning models, the model parameter has increased exponentially. An increase in model parameters leads to an increase in computation and training time, i.e., an increase in training cost. To reduce the training cost, we propose Compositional Intelligence (CI). This is a reuse method that combines pre-trained models for different tasks. Since the CI uses a well-trained model, good performance and small training cost can be expected in the target task. We applied the CI to the Image Captioning task. Compared to using a trained feature extractor, the caption generator is usually trained from scratch. On the other hand, we pre-trained the Transformer model as a caption generator and applied CI, i.e., we used a pre-trained feature extractor and a pre-trained caption generator. To compare the training cost of the From Scratch model and the CI model, early stopping was applied during fine-tuning of the image captioning task. On the MS-COCO dataset, the vanilla image captioning model reduced training cost by 13.8% and improved performance by up to 3.2%, and the Object Relation Transformer model reduced training cost by 21.3%.
Preclinical Safety Profile of an Oral Naringenin/Hesperidin Dosage Form by In Vivo Toxicological Tests
Authors: Cicero-Sarmiento Carla Georgina , Ortiz-Andrade Rolffy , Araujo-León Jesús Alfredo , Segura-Campos Maira Rubí , Vazquez-Garcia Priscila , Rubio-Zapata Héctor , Hernández-Baltazar Efrén , Yañez-Pérez Victor , Sánchez-Recillas Amanda , Sánchez-Salgado Juan Carlos , Hernández-Núñez Emanuel , Ruiz-Ciau Durcy
Published: May 2022

We developed a naringenin–hesperidin molar mixture (MIX–160) with proven antihyperglycemic and vasorelaxant activity in preclinical studies. A solid dosage form was manufactured to improve the bioavailability properties. In the current study, we sought to evaluate the oral preclinical toxicity of the MIX–160 dosage form, which showed no mortality or significant changes in the body weight, food consumption and tissue/organ mass in rats. Three daily oral doses (50, 300 and 2000 mg/kg of MIX–160) were assayed for 28 days. The results showed no structural abnormalities in the histological analysis and no significant changes (p > 0.05) in the liver biochemical markers (total bilirubin, AST and ALT) compared to the control group. The above findings showed that the MIX–160 dosage form did not exhibit relevant toxic effects, which suggests its potential safety as a drug candidate for clinical studies.
On the Problems and Methods for International Comparisons of GDP
Authors: Ivanov Yu. N.
Published: May 2022

The introductory part of the article argues the relevance of continuing research on the conceptual and methodological problems of international comparisons of macroeconomic indicators due to begging of new round of the International Comparison Program (ICP) of GDP by Purchasing Power Parities (PPPs), designed to build unique science-based systems of statistical data on the world economy and the place of each country in it.

The body of the article formulates the author's view of the basic methodological approaches to international comparisons of macroeconomic indicators; it also focuses on several areas for improving the quality of international statistics. It is argued that to improve the quality of international comparisons, there is a particular need to implement in the national statistical practice of individual countries the methodological procedures for measuring the following main economic transactions: research and development expenditure, government expenditure on the acquisition of weapons systems, imputed output of financial intermediation services, updated in the 2008 SNA. The paper explains the need for updating some purchasing power parities methodology provisions and postulates, especially those concerning non-market government services. According to the author, it would be beneficial to continue the debate on the merits and limitations of the Elteto, Koves and Szulc (EKS) method and the Geary – Khamis method.

The conclusion is that the development of standards for international comparisons of PPP-based GDP will be in the interests of the governments across the world, national central banks, international organizations, and, of course, will contribute to solving modern problems in national socio-economic statistics and Russian statistics, in particular.
Supporting Employees’ Participation in Sports: Statistical and Sociological Study
Authors: Zasimova L. S. , Makshanchikov K. N.
Published: May 2022

The article reflects results of empirical analysis of sport incentives for working adults in Russia. The study uses data from a small, but according to the authors, representative sample (2208 employees) of Russian adults’ attitudes towards their health and quality of medical care in Russian Federation. The survey was initiated by the National Research University Higher School of Economics in 2017, before the start of COVID-19 pandemic, which for a certain period disrupted the employees’ measures promoting sports for their workers. However, the relevance of the study has been fully preserved. The authors not just give a snapshot of sport-promoting measures adopted by Russian enterprises, but also justify the methodology for statistical analysis of a healthy lifestyle policies provided by employers to their employees.

The paper reports the main parameters and the content of the population survey used in the study; describes main sport participation indicators and its’ determinants; presents estimates of factors attributed to sport participation among working adults. More specifically, the authors study the stimulating effect of two popular measures to encourage sport participation in Russian enterprises: providing access to sport infrastructure at the worksites and subsidies for practicing sport in sport centers.

Using descriptive and econometric analyzes, the authors investigate the association between sport-encouraging measures and working adults sporting activity, estimate statistical significance of this relationship. In order to concretize and deepen the empirical analysis of sport participation among working adults, the authors adjust their analyses by adding such respondents’ characteristics as gender, age, health status, smoking status, education, type of work and place of residency.

The study shows that probability of sport participation is much higher for those who has access to sport infrastructure at their worksites (for both men and women). However, employers’ subsidies for sport activity outside working places is not associated with any increase in the probability of doing sports.
Using Predicted Locations and an Ensemble Approach to Address Sparse Data Sets for Species Distribution Modelling: Long-horned Beetles (Cerambycidae) of the Fiji Islands
Authors: Aguilar G , Waqa-Sakiti H , Winder L
Published: May 2022

In response to unique species in Fiji which are threatened or endangered, and in critical need of effective conservation measures to ensure their survival, author Glenn Aguilar has produced an eMedia publication and learning research tool, called GIS For Conservation.The eMedia website hosts tutorial material, videos and modelling results for conservation management and planning purposes. Users will learn spatial analytical skills, species distribution modelling and other relevant GIS tools, as well as enhance ArcMap skills and the species distribution modelling tool Maxent. Accompanying the GIS For Conservation website is a peer-reviewed research report. The report details the case study and research methods that have informed the eMedia publication, focusing on the development of maps predicting the suitability of the Fiji Islands for longhorned beetles (Cerambycidae) that include endemic and endangered species such as the Giant Fijian Beetle Xixuthrus heros.
New Lynn – Auckland IMM Case Study
Authors: Tadi Massimo
Published: May 2022

Integrated Modification Methodology (IMM) has already been applied in established metropolitan contexts, such as Porto Maravilha in Rio de Janeiro, the neighbourhood of Shahrak-e Golestan in Tehran, and Block 39 in New Belgrade. When Unitec Institute of Technology’s Associate Professor of Urban Design Dushko Bogunovich came up with the idea of a comparative analysis of two sprawling metropolitan contexts – Auckland and Milan – he and Massimo Tadi, Director of the IMMdesignlab in Milan and Associate Professor at the School of Architectural Engineering at the Politecnico di Milano, decided to apply IMM to a sample area of low-density suburban Auckland. The project presented in this book was developed in a joint international design workshop organised by Politecnico di Milano, IMMdesignlab and Unitec Institute of Technology. The workshop was held at Politecnico di Milano, Polo Territoriale di Lecco (Italy), from 25–29 May 2015, and the team, comprising 14 international students from different design disciplines, was coordinated by Tadi and Bogunovich, assisted by engineers Hadi Mohammad Zadeh and Frederico Zaniol (IMMdesignlab). The outcomes of the workshop were then further developed by IMMdesignlab to demonstrate how, by adopting IMM, it is possible to retrofit, renovate and reactivate an inefficient and energy consuming neighbourhood into a more integrated and sustainable one.
Contextualising the learning affordances of technology: An in-depth look at the developing practice of two modern language teachers
Authors: Haines Karen
Published: May 2022

Affordance is an integral part of the practical knowledge teachers acquires while using new technologies in their teaching. This article describes the situated learning of two experienced modern language teachers using new technologies as they learned to perceive and implement learning affordances of several new tools in their individual classroom contexts, including Second Life and Wimba. The teachers identified and actualised learning affordances that allowed them to support students’ learning according to their respective beliefs about teaching and learning. The implications for computer-assisted language learning (CALL) teacher development are discussed in relation to professional learning and to the enriching of effective teaching practice.
Automatic Detection of Atrial Fibrillation from Single-Lead ECG Using Deep Learning of the Cardiac Cycle
Authors: Dubatovka Alina , Buhmann Joachim M.
Published: May 2022

Objective and Impact Statement
. Atrial fibrillation (AF) is a serious medical condition that requires effective and timely treatment to prevent stroke. We explore deep neural networks (DNNs) for learning cardiac cycles and reliably detecting AF from single-lead electrocardiogram (ECG) signals.
Introduction
. Electrocardiograms are widely used for diagnosis of various cardiac dysfunctions including AF. The huge amount of collected ECGs and recent algorithmic advances to process time-series data with DNNs substantially improve the accuracy of the AF diagnosis. DNNs, however, are often designed as general purpose black-box models and lack interpretability of their decisions.
Methods
. We design a three-step pipeline for AF detection from ECGs. First, a recording is split into a sequence of individual heartbeats based on R-peak detection. Individual heartbeats are then encoded using a DNN that extracts interpretable features of a heartbeat by disentangling the duration of a heartbeat from its shape. Second, the sequence of heartbeat codes is passed to a DNN to combine a signal-level representation capturing heart rhythm. Third, the signal representations are passed to a DNN for detecting AF.
Results
. Our approach demonstrates a superior performance to existing ECG analysis methods on AF detection. Additionally, the method provides interpretations of the features extracted from heartbeats by DNNs and enables cardiologists to study ECGs in terms of the shapes of individual heartbeats and rhythm of the whole signals.
Conclusion
. By considering ECGs on two levels and employing DNNs for modelling of cardiac cycles, this work presents a method for reliable detection of AF from single-lead ECGs.
A Deep Learning Approach for Detecting Colorectal Cancer via Raman Spectra
Authors: Cao Zheng , Pan Xiang , Yu Hongyun , Hua Shiyuan , Wang Da , Chen Danny Z. , Zhou Min , Wu Jian
Published: May 2022

Objective and Impact Statement.
Distinguishing tumors from normal tissues is vital in the intraoperative diagnosis and pathological examination. In this work, we propose to utilize Raman spectroscopy as a novel modality in surgery to detect colorectal cancer tissues.
Introduction.
Raman spectra can reflect the substance components of the target tissues. However, the feature peak is slight and hard to detect due to environmental noise. Collecting a high-quality Raman spectroscopy dataset and developing effective deep learning detection methods are possibly viable approaches.
Methods.
First, we collect a large Raman spectroscopy dataset from 26 colorectal cancer patients with the Raman shift ranging from 385 to 1545 cm

 

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. Second, a one-dimensional residual convolutional neural network (1D-ResNet) architecture is designed to classify the tumor tissues of colorectal cancer. Third, we visualize and interpret the fingerprint peaks found by our deep learning model.
Results.
Experimental results show that our deep learning method achieves 98.5% accuracy in the detection of colorectal cancer and outperforms traditional methods.
Conclusion.
Overall, Raman spectra are a novel modality for clinical detection of colorectal cancer. Our proposed ensemble 1D-ResNet could effectively classify the Raman spectra obtained from colorectal tumor tissues or normal tissues.
The Phenomenon of Parental Rules in Middle Childhood: A Relational Perspective
Authors: Kuczynski Leon , Robson Jane
Published: May 2022

This study investigated neglected processes by which parents create, set, and enforce rules for their children in middle childhood. Forty mothers reported their interactions with children aged 9-13 in the context of setting and enforcing rules and expectations. Data consisted of a five-day digital event diary and a semi-structured interview on parents’ implicit conceptions of rules and the process by which they set and enforced rules. The data were analyzed qualitatively using thematic analysis. Mothers’ reports departed from traditional conceptions in socialization research and family interventions that parents have explicit, stable rules that they should firmly enforce. Mothers indicated that their rules and expectations consisted of a flexible structure of infrequent firm expectations within which most other expectations were dynamically set or offered leeway for negotiation and resistance. Mothers also indicated that their rules and expectations emerged through a co-regulated bi-directional process to which parents and children contributed. The findings support transactional socialization and communication perspectives whereby parents interpret children’s behaviors and make complex choices in setting and implementing their expectations.
Transnational Approaches on Money Laundering as an Organized Crime: Resolving Jurisdictional Conflicts and the Indian State Practice
Authors: Ramdhass Dr. P.R. , Kumar Abhinav
Published: May 2022

Money laundering refers to the conversion or "laundering" of money which is illegally obtained, so as to make it appear to originate from a legitimate source. Money laundering is being employed by launderer’s worldwide to conceal criminal activity associated with it such as drugs/arms trafficking, terrorism, extortion and reason for various other heinous crimes. But in simple term, it is the conversion of black money into white money. The research inevitably to explain the paper to context that any instance of money laundering would have an angle of international degree, as money laundering typically involves transferring money through several countries in order to obscure its origin. Further the research has divided into four parts; first part deals with the jurisdictional issue arise during transnational money laundering. Second part deals with the intention of Parliament of India meant to target “proceeds of criminal conduct” then and now in the money laundering and its related offenses. Third part elaborates international development through different instruments and controlling mechanisms to deal with this problem and analyse the position of India in controlling money laundering. Fourth part discusses various problems and loopholes in implementation of anti-money laundering laws. Finally, the research concludes with few suggestions to have better anti-money laundering regime.
INFECÇÃO POR Anaplasma platys EM UM CANINO DA RAÇA POODLE: RELATO DE CASO
Authors: Helena Cesca Patrícia , Teixeira Ferreira Priscila , Duarte de Oliveira Kimberli , Sérgio Coussirat de Azevedo João
Published: May 2022

Um canino da raça Poodle, 15 anos, macho, inteiro, foi atendido no Hospital Veterinário da Universidade Luterana do Brasil apresentando: hiporexia há cinco dias e anorexia nos dois últimos dias, hipodipsia, prostração, hipertermia, uveíte e um episódio de vômito. Ao exame físico, constatou-se 8% de desidratação, mucosas secas e hipocoradas, tempo de preenchimento capilar maior que dois segundos e presença de carrapatos (Rhipicephalus sanguineus). Devido à presença dos carrapatos, foi administrado afoxolaner. Realizou-se o exame parasitológico de sangue (EPS), colhido da ponta da orelha e o teste rápido (4Dx® - IDEXX). Com o resultado positivo do teste rápido e visualização de mórula no interior das plaquetas compatíveis com Anaplasma platys, definiu-se o diagnóstico de anaplasmose trombocítica canina. A partir do diagnóstico, instituiu-se o tratamento com doxiciclina a cada 12 horas por via oral e, após 48 horas de tratamento, o cão recebeu alta e seguiu com tratamento em domicílio. Após 21 dias de antibioticoterapia, o paciente apresentou melhora clínica satisfatória. Realizou-se nova coleta de EPS, que apresentou resultado negativo.
PROSPECTIVA DE EXTRACTOS VEGETALES PARA CONTROLAR ENFERMEDADES POSTCOSECHA HORTOFRUTÍCOLAS
Authors: Hernández-Lauzardo Ana Niurka , Bautista-Baños Silvia , Velázquez-del Valle Miguel Gerardo
Published: May 2022

Las plantas producen compuestos con propiedades antimicrobianas que pueden ser empleadas para controlar diferentes enfermedades en productos hortofrutícolas. La obtención de los extractos vegetales y el estudio de sus compuestos activos propician su empleo contra diferentes fitopatógenos. En condiciones in vitro los extractos inhiben el crecimiento del patógeno, así como la esporulación y germinación de esporas, de modo que ayudan a controlar las enfermedades de frutos y hortalizas. In vivo, el efecto fungicida de los extractos vegetales varía en función de la metodología de preparación (solvente, seco, fresco, tiempo de almacenamiento, etc.), especie botánica, órgano de la planta (raíces, hojas, semillas, etc.), fecha de cosecha, etc. Sin embargo, la combinación de los extractos vegetales con algún otro compuesto natural puede potenciar su actividad fungicida. A la fecha son escasos los estudios básicos que incluyen el efecto de extractos vegetales en aspectos moleculares, bioquímicos y morfológicos del hospedero y del patógeno.