bluuebunny/crossref_metadata_2025 huggingface dataset:
Spatiotemporal Trends and Variations of the Rainfall Amount, Intensity, and Frequency in TRMM Multi-satellite Precipitation Analysis (TMPA) Data
Authors: Liu Qian , Chiu Long S. , Hao Xianjun , Yang Chaowei
Published: November 2021

The spatiotemporal mean rain rate (MR) can be characterized by the rain frequency (RF) and the conditional rain rate (CR). We computed these parameters for each season using the TMPA 3-hourly, 0.25° gridded data for the 1998–2017 period at a quasi-global scale, 50°N~50°S. For the global long-term average, MR, RF, and CR are 2.83 mm/d, 10.55%, and 25.05 mm/d, respectively. The seasonal time series of global mean RF and CR show significant decreasing and increasing trends, respectively, while MR depicts only a small but significant trend. The seasonal anomaly of RF decreased by 5.29% and CR increased 13.07 mm/d over the study period, while MR only slightly decreased by −0.029 mm/day. The spatiotemporal patterns in MR, RF, and CR suggest that although there is no prominent trend in the total precipitation amount, the frequency of rainfall events becomes smaller and the average intensity of a single event becomes stronger. Based on the co-variability of RF and CR, the paper optimally classifies the precipitation over land and ocean into four categories using K-means clustering. The terrestrial clusters are consistent with the dry and wet climatology, while categories over the ocean indicate high RF and medium CR in the Inter Tropical Convergence Zone (ITCZ) region; low RF with low CR in oceanic dry zones; and low RF and high CR in storm track areas. Empirical Orthogonal Function (EOF) analysis was then performed, and these results indicated that the major pattern of MR is characterized by an El Niño-Southern Oscillation (ENSO) signal while RF and CR variations are dominated by their trends.
Mapping Relict Charcoal Hearths in New England Using Deep Convolutional Neural Networks and LiDAR Data
Authors: Suh Ji Won , Anderson Eli , Ouimet William , Johnson Katharine M. , Witharana Chandi
Published: November 2021

Advanced deep learning methods combined with regional, open access, airborne Light Detection and Ranging (LiDAR) data have great potential to study the spatial extent of historic land use features preserved under the forest canopy throughout New England, a region in the northeastern United States. Mapping anthropogenic features plays a key role in understanding historic land use dynamics during the 17th to early 20th centuries, however previous studies have primarily used manual or semi-automated digitization methods, which are time consuming for broad-scale mapping. This study applies fully-automated deep convolutional neural networks (i.e., U-Net) with LiDAR derivatives to identify relict charcoal hearths (RCHs), a type of historical land use feature. Results show that slope, hillshade, and Visualization for Archaeological Topography (VAT) rasters work well in six localized test regions (spatial scale: <1.5 km2, best F1 score: 95.5%), but also at broader extents at the town level (spatial scale: 493 km2, best F1 score: 86%). The model performed best in areas with deciduous forest and high slope terrain (e.g., >15 degrees) (F1 score: 86.8%) compared to coniferous forest and low slope terrain (e.g., <15 degrees) (F1 score: 70.1%). Overall, our results contribute to current methodological discussions regarding automated extraction of historical cultural features using deep learning and LiDAR.
Fabrication of Microchannels in a Nodeless Antiresonant Hollow-Core Fiber Using Femtosecond Laser Pulses
Authors: Kozioł Paweł , Jaworski Piotr , Krzempek Karol , Hoppe Viktoria , Dudzik Grzegorz , Yu Fei , Wu Dakun , Liao Meisong , Knight Jonathan , Abramski Krzysztof
Published: November 2021

In this work, we present femtosecond laser cutting of microchannels in a nodeless antiresonant hollow-core fiber (ARHCF). Due to its ability to guide light in an air core combined with exceptional light-guiding properties, an ARHCF with a relatively non-complex structure has a high application potential for laser-based gas detection. To improve the gas flow into the fiber core, a series of 250 × 30 µm microchannels were reproducibly fabricated in the outer cladding of the ARHCF directly above the gap between the cladding capillaries using a femtosecond laser. The execution time of a single lateral cut for optimal process parameters was 7 min. It has been experimentally shown that the implementation of 25 microchannels introduces low transmission losses of 0.17 dB (<0.01 dB per single microchannel). The flexibility of the process in terms of the length of the performed microchannel was experimentally demonstrated, which confirms the usefulness of the proposed method. Furthermore, the performed experiments have indicated that the maximum bending radius for the ARHCF, with the processed 100 µm long microchannel that did not introduce its breaking, is 15 cm.
Security Management Suitable for Lifecycle of Personal Information in Multi-User IoT Environment
Authors: Lee Yong , Lee Goo Yeon
Published: November 2021

In recent years, as all actions of Internet users become information, the importance of personal information is emphasized, but in reality, the management of personal information is still insufficient. With the advent of the concept of sharing systems such as the sharing economy, the numbers of IoT application services (for example, a healthcare service using sharing IoT devices, or a vehicle sharing system with IoT devices) using users’ personal information are increasing, but the risk of using personal information is not managed. To solve this issue, the European GDPR stipulates the content of personal information protection. In this paper, we present a method to securely manage personal information in IoT devices in IoT application environments in accordance with the GDPR. We first describe the lifecycle stages of personal information occurring in IoT application services and propose a method to securely manage personal information at each stage of the lifecycle according to the flow of personal information in IoT devices. We also evaluated the usefulness and applicability of the proposed scheme through two service scenarios. Since the proposed method satisfies the requirements for personal information management in IoT application environments, it is expected to contribute to the development of the IoT business field that handles personal information.
Modeling and Parallel Operation of Exchange-Biased Delta-E Effect Magnetometers for Sensor Arrays
Authors: Spetzler Benjamin , Wiegand Patrick , Durdaut Phillip , Höft Michael , Bahr Andreas , Rieger Robert , Faupel Franz
Published: November 2021

Recently, Delta-E effect magnetic field sensors based on exchange-biased magnetic multilayers have shown the potential of detecting low-frequency and small-amplitude magnetic fields. Their design is compatible with microelectromechanical system technology, potentially small, and therefore, suitable for arrays with a large number N of sensor elements. In this study, we explore the prospects and limitations for improving the detection limit by averaging the output of N sensor elements operated in parallel with a single oscillator and a single amplifier to avoid additional electronics and keep the setup compact. Measurements are performed on a two-element array of exchange-biased sensor elements to validate a signal and noise model. With the model, we estimate requirements and tolerances for sensor elements using larger N. It is found that the intrinsic noise of the sensor elements can be considered uncorrelated, and the signal amplitude is improved if the resonance frequencies differ by less than approximately half the bandwidth of the resonators. Under these conditions, the averaging results in a maximum improvement in the detection limit by a factor of N. A maximum N≈200 exists, which depends on the read-out electronics and the sensor intrinsic noise. Overall, the results indicate that significant improvement in the limit of detection is possible, and a model is presented for optimizing the design of delta-E effect sensor arrays in the future.
The WGD—A Dataset of Assembly Line Working Gestures for Ergonomic Analysis and Work-Related Injuries Prevention
Authors: Tamantini Christian , Cordella Francesca , Lauretti Clemente , Zollo Loredana
Published: November 2021

This paper wants to stress the importance of human movement monitoring to prevent musculoskeletal disorders by proposing the WGD—Working Gesture Dataset, a publicly available dataset of assembly line working gestures that aims to be used for worker’s kinematic analysis. It contains kinematic data acquired from healthy subjects performing assembly line working activities using an optoelectronic motion capture system. The acquired data were used to extract quantitative indicators to assess how the working tasks were performed and to detect useful information to estimate the exposure to the factors that may contribute to the onset of musculoskeletal disorders. The obtained results demonstrate that the proposed indicators can be exploited to early detect incorrect gestures and postures and, consequently to prevent work-related disorders. The approach is general and independent on the adopted motion analysis system. It wants to provide indications for safely performing working activities. For example, the proposed WGD can also be used to evaluate the kinematics of workers in real working environments thanks to the adoption of unobtrusive measuring systems, such as wearable sensors through the extracted indicators and thresholds.
Analysis of Gastrointestinal Acoustic Activity Using Deep Neural Networks
Authors: Ficek Jakub , Radzikowski Kacper , Nowak Jan Krzysztof , Yoshie Osamu , Walkowiak Jaroslaw , Nowak Robert
Published: November 2021

Automated bowel sound (BS) analysis methods were already well developed by the early 2000s. Accuracy of ~90% had been achieved by several teams using various analytical approaches. Clinical research on BS had revealed their high potential in the non-invasive investigation of irritable bowel syndrome to study gastrointestinal motility and in a surgical setting. This article proposes a novel methodology for the analysis of BS using hybrid convolutional and recursive neural networks. It is one of the first methods of using deep learning to be widely explored. We have developed an experimental pipeline and evaluated our results with a new dataset collected using a device with a dedicated contact microphone. Data have been collected at night-time, which is the most interesting period from a neurogastroenterological point of view. Previous works had ignored this period and instead kept brief records only during the day. Our algorithm can detect bowel sounds with an accuracy >93%. Moreover, we have achieved a very high specificity (>97%), crucial in diagnosis. The results have been checked with a medical professional, and they successfully support clinical diagnosis. We have developed a client-server system allowing medical practitioners to upload the recordings from their patients and have them analyzed online. This system is available online. Although BS research is technologically mature, it still lacks a uniform methodology, an international forum for discussion, and an open platform for data exchange, and therefore it is not commonly used. Our server could provide a starting point for establishing a common framework in BS research.
The Multi-Gas Sensor for Remote UAV and UGV Missions—Development and Tests
Authors: Kaliszewski Miron , Włodarski Maksymilian , Młyńczak Jarosław , Jankiewicz Bartłomiej , Auer Lukas , Bartosewicz Bartosz , Liszewska Malwina , Budner Bogusław , Szala Mateusz , Schneider Bernhard , Povoden Günter , Kopczyński Krzysztof
Published: November 2021

In this article, we present a versatile gas detector that can operate on an unmanned aerial vehicle (UAV) or unmanned ground vehicle (UGV). The device has six electrochemical modules, which can be selected to measure specific gases, according to the mission requirements. The gas intake is realized by a miniaturized vacuum pump, which provides immediate gas distribution to the sensors and improves a fast response. The measurement data are sent wirelessly to the operator’s computer, which continuously stores results and presents them in real time. The 2 m tubing allows measurements to be taken in places that are not directly accessible to the UGV or the UAV. While UAVs significantly enhanced the versatility of sensing applications, point gas detection is challenging due to the downwash effect and gas dilution produced by the rotors. In our work, we demonstrated the method of downwash effect reduction at aerial point gas measurements by applying a long-distance probe, which was kept between the UAV and the examined object. Moreover, we developed a safety connection protecting the UAV and sensor in case of accidental jamming of the tubing inside the examined cavity. The methods presented provide an effective gas metering strategy using UAVs.
Recent Progress in Smart Electronic Nose Technologies Enabled with Machine Learning Methods
Authors: Ye  Zhenyi , Liu Yuan , Li Qiliang
Published: November 2021

Machine learning methods enable the electronic nose (E-Nose) for precise odor identification with both qualitative and quantitative analysis. Advanced machine learning methods are crucial for the E-Nose to gain high performance and strengthen its capability in many applications, including robotics, food engineering, environment monitoring, and medical diagnosis. Recently, many machine learning techniques have been studied, developed, and integrated into feature extraction, modeling, and gas sensor drift compensation. The purpose of feature extraction is to keep robust pattern information in raw signals while removing redundancy and noise. With the extracted feature, a proper modeling method can effectively use the information for prediction. In addition, drift compensation is adopted to relieve the model accuracy degradation due to the gas sensor drifting. These recent advances have significantly promoted the prediction accuracy and stability of the E-Nose. This review is engaged to provide a summary of recent progress in advanced machine learning methods in E-Nose technologies and give an insight into new research directions in feature extraction, modeling, and sensor drift compensation.
Sensing Advancement and Health Monitoring of Transport Structures
Authors: Benedetto Andrea , Al-Qadi Imad L. , Alani Amir M. , Loizos Andreas , Tosti Fabio
Published: November 2021

Planning, design, construction, maintenance and management of transport infrastructure demand new methods and approaches to optimise utilisation of materials, energy and workforce [...]
Fusion-Learning of Bayesian Network Models for Fault Diagnostics
Authors: Ademujimi Toyosi , Prabhu Vittaldas
Published: November 2021

Bayesian Network (BN) models are being successfully applied to improve fault diagnosis, which in turn can improve equipment uptime and customer service. Most of these BN models are essentially trained using quantitative data obtained from sensors. However, sensors may not be able to cover all faults and therefore such BN models would be incomplete. Furthermore, many systems have maintenance logs that can serve as qualitative data, potentially containing historic causation information in unstructured natural language replete with technical terms. The motivation of this paper is to leverage all of the data available to improve BN learning. Specifically, we propose a method for fusion-learning of BNs: for quantitative data obtained from sensors, metrology data and qualitative data from maintenance logs, corrective and preventive action reports, and then follow by fusing these two BNs. Furthermore, we propose a human-in-the-loop approach for expert knowledge elicitation of the BN structure aided by logged natural language data instead of relying exclusively on their anecdotal memory. The resulting fused BN model can be expected to provide improved diagnostics as it has a wider fault coverage than the individual BNs. We demonstrate the efficacy of our proposed method using real world data from uninterruptible power supply (UPS) fault diagnostics.
Digital Integration and Automated Assessment of Eye-Tracking and Emotional Response Data Using the BioSensory App to Maximize Packaging Label Analysis
Authors: Fuentes Sigfredo , Gonzalez Viejo Claudia , Torrico Damir D. , Dunshea Frank R.
Published: November 2021

New and emerging non-invasive digital tools, such as eye-tracking, facial expression and physiological biometrics, have been implemented to extract more objective sensory responses by panelists from packaging and, specifically, labels. However, integrating these technologies from different company providers and software for data acquisition and analysis makes their practical application difficult for research and the industry. This study proposed a prototype integration between eye tracking and emotional biometrics using the BioSensory computer application for three sample labels: Stevia, Potato chips, and Spaghetti. Multivariate data analyses are presented, showing the integrative analysis approach of the proposed prototype system. Further studies can be conducted with this system and integrating other biometrics available, such as physiological response with heart rate, blood, pressure, and temperature changes analyzed while focusing on different label components or packaging features. By maximizing data extraction from various components of packaging and labels, smart predictive systems can also be implemented, such as machine learning to assess liking and other parameters of interest from the whole package and specific components.
Universal Path-Following of Wheeled Mobile Robots: A Closed-Form Bounded Velocity Solution
Authors: Oftadeh Reza , Ghabcheloo Reza , Mattila Jouni
Published: November 2021

This paper presents a nonlinear, universal, path-following controller for Wheeled Mobile Robots (WMRs). This approach, unlike previous algorithms, solves the path-following problem for all common categories of holonomic and nonholonomic WMRs, such as omnidirectional, unicycle, car-like, and all steerable wheels. This generality is the consequence of a two-stage solution that tackles separately the platform path-following and wheels’ kinematic constraints. In the first stage, for a mobile platform divested of the wheels’ constraints, we develop a general paradigm of a path-following controller that plans asymptotic paths from the WMR to the desired path and, accordingly, we derive a realization of the presented paradigm. The second stage accounts for the kinematic constraints imposed by the wheels. In this stage, we demonstrate that the designed controller simplifies the otherwise impenetrable wheels’ kinematic and nonholonomic constraints into explicit proportional functions between the velocity of the platform and that of the wheels. This result enables us to derive a closed-form trajectory generation scheme for the asymptotic path that constantly keeps the wheels’ steering and driving velocities within their corresponding, pre-specified bounds. Extensive experimental results on several types of WMRs, along with simulation results for the other types, are provided to demonstrate the performance and the efficacy of the method.
Liquid Chromatography-Tandem Mass Spectrometry for Detecting Myosin Light Chain 3 in Dry-Aged Beef
Authors: Lee Heeyoung , Heo Yoonji , Kim Jong-Chan , Shim You-Shin
Published: November 2021

Liquid chromatography-tandem mass spectrometry (LC/MS/MS) is a more accurate technique for detecting proteins than electrophoresis-based methods such as western blotting. Because of its convenience, western blotting is commonly used for protein analysis in beef. We developed a method for detecting myosin light chain 3 (myl3) in beef samples, particularly dry-aged beef, using LC/MS/MS for quality testing. Musculus longissimus dorsi of Holstein was aged for 0, 2, 4, 5, 9, 11, 17, 20, and 24 weeks and used to measure the myl3 concentration. Because of the high molecular weight of myl3, the limitations of LC/MS/MS were overcome by implementing immunoprecipitation and digestion steps. Ultimately, a tryptic fragment of myl3 (13-mer), generated using immunoprecipitation and digestion by a biotinylated antibody, was detected using LC-MS/MS in positive ion mode through multiple reaction monitoring and analyte separation on a C18 column. Our method showed limits of detection and quantification of less than 0.3 and 0.8 μg/kg, respectively. However, differences in the myl3 concentrations according to the aging time were not significant (p > 0.05). After 12 weeks, myl3 disappeared in tested all samples, thus our analytical method can be used for accurate measurement of muscle protein in beef samples.
Determining the Factors Affecting the Boiling Heat Transfer Coefficient of Sintered Coated Porous Surfaces
Authors: Sajjad Uzair , Hussain Imtiyaz , Sultan Muhammad , Mehdi Sadaf , Wang Chi-Chuan , Rasool Kashif , Saleh Sayed M. , Elnaggar Ashraf Y. , Hussein Enas E.
Published: November 2021

The boiling heat transfer performance of porous surfaces greatly depends on the morphological parameters, liquid thermophysical properties, and pool boiling conditions. Hence, to develop a predictive model valid for diverse working fluids, it is necessary to incorporate the effects of the most influential parameters into the architecture of the model. In this regard, two Bayesian optimization algorithms including Gaussian process regression (GPR) and gradient boosting regression trees (GBRT) are used for tuning the hyper-parameters (number of input and dense nodes, number of dense layers, activation function, batch size, Adam decay, and learning rate) of the deep neural network. The optimized model is then employed to perform sensitivity analysis for finding the most influential parameters in the boiling heat transfer assessment of sintered coated porous surfaces on copper substrate subjected to a variety of high- and low-wetting working fluids, including water, dielectric fluids, and refrigerants, under saturated pool boiling conditions and different surface inclination angles of the heater surface. The model with all the surface morphological features, liquid thermophysical properties, and pool boiling testing parameters demonstrates the highest correlation coefficient, R2 = 0.985, for HTC prediction. The superheated wall is noted to have the maximum effect on the predictive accuracy of the boiling heat transfer coefficient. For example, if the wall superheat is dropped from the modeling parameters, the lowest prediction of R2 (0.893) is achieved. The surface morphological features show relatively less influence compared to the liquid thermophysical properties. The proposed methodology is effective in determining the highly influencing surface and liquid parameters for the boiling heat transfer assessment of porous surfaces.
An Overview of the European Policies on ESG in the Banking Sector
Authors: Bruno Michelangelo , Lagasio Valentina
Published: November 2021

In recent years, European policy makers have ramped up their efforts to create a regulatory framework for improving sustainability in the financial system. We contribute to the on-going debate on Environmental, Social and Governance in the banking sector by providing an organic overview of the European policies put in place. The legislative framework is currently being enriched by policy makers and regulators that are carefully pursuing the objective of a more sustainable economic system, where financial institutions may act as catalysts. We also offer a comparison of the national level regulations for ESG practices in banking institutions and the related disclosure requirements.
Challenges to Internationalisation of University Programmes: A Systematic Thematic Synthesis of Qualitative Research on Learner-Centred English Medium Instruction (EMI) Pedagogy
Authors: Ismailov Murod , Chiu Thomas K. F. , Dearden Julie , Yamamoto Yukiko , Djalilova Nigora
Published: November 2021

As many universities in non-Anglophone countries have committed to internationalising their academic programmes, more content courses in Arts and Sciences are being taught in English. When content courses are taught in English in a country where English is not the first language, this is called English Medium Instruction (EMI). Using specific country cases, previous studies have confirmed that an EMI course can pose many challenges to the learning of course content by students. To date, there have been few attempts to examine these challenges through a large-scale qualitative prism, which would be useful for gaining new insights in order to inform policy as well as classroom interventions. In this systematic thematic synthesis we have aimed to identify the obstacles to implementing learner-centred pedagogy in EMI tertiary programmes, focusing on student perspectives. The Critical Appraisal Skills Programme (CASP) and Consolidated Criteria for Reporting Qualitative Studies (COREQ) were used to appraise and synthesise 40 empirical articles. The articles included 1769 participants in 20 non-Anglophone countries and jurisdictions. The participants were both local and international non-native English-speaking students enrolled in EMI courses. The synthesis yielded 46 descriptive themes stratified into six analytical domains. The suggested domains are meta/linguistic, instructional, meta/cognitive, socio-cultural, affective, and institutional obstacles. They suggest that students in different regions faced quite similar challenges in their EMI courses. The challenges consist of inadequate use of English by students and lecturers, and a lack of student-centred pedagogy, particularly in teacher–student and student–student interactions. The findings of most learner-centred EMI studies revealed that the main challenges came from English comprehension (the first three suggested domains); fewer studies included factors related to the learning environment (the last three domains). This review can inform university administrators, teaching staff and researchers engaged in internationalising higher education and aid in designing appropriate EMI programmes that offer better learner-centred educational experiences.
Qualitative Analysis of Risks Affecting the Delivery of Land Surveying Project Activities
Authors: Issa Usama , Alqurashi Muwaffaq , Salama Ibrahim
Published: November 2021

Land surveying projects (LSPs) suffer from the effects of many risk factors on the time and accuracy of these projects. Using field surveys, the main objective of this study was identifying the major activities and risk factors associated with LSPs’ execution, as well as assessing and analyzing the effects of the risk factors on the LSPs’ time and accuracy. Furthermore, the study aimed to classify and determine the responsibility of each risk factor and evaluate the responsibilities. Four main activities were categorized and presented, including reconnaissance works, planning works, data collection works, and data adjustment works. Moreover, forty-three risk factors that control the main activities and affect the time and accuracy of LSPs were recognized. The probabilities of occurrences for the risk factors and impacts on the time and accuracy of LSPs were determined as well as their combined effects. Key risk factors that had high threats on LSPs and affect time and accuracy were highlighted as the most critical risk factors. Many correlations were determined among risk factors affecting LSPs’ activity groups and their various effects on time and accuracy. The responsibilities of the surveying crew (chief, surveyor, assistance, office engineer) for each risk factors were correspondingly defined. The results showed that “Data collection works” is considered the riskiest activity group in LSPs and most of the key risk factors belonged to this group. Around 25% of the LSPs face time overrun and do not meet the required specifications. On the other hand, the surveyor was found to be responsible for most of the risk factors and the office engineer was signified by the lowest responsibility, while the responsibilities for most risk factors were single responsibility and few were shared by only dual responsibility.
Environmental Portfolios—Evidence from Screening and Passive Portfolio Management
Authors: Amon Julian , Rammerstorfer Margarethe , Weinmayer Karl
Published: November 2021

Environmental portfolios via screening or optimization with respect to ecological criteria are not clear-cut concepts. Often, they urge investors to reduce the asset universe, which is accompanied by diversification losses. In this article, we show that a simple passive asset selection strategy based on environmental criteria allows ecological investors to adjust their portfolios without compromising or even reducing risk-adjusted financial performance. In detail, we show that screening does not lead to a significant financial performance reduction. Moreover, we propose an asset selection based on an environmental criteria that improves the portfolios’ financial performance, and further improves its potential positive environmental impact. Our results suggest that a combination of a screening and an environmental-scoring-based asset allocation seems to be a viable option for environmentally responsible investors leveraging the advantages of both strategies. Furthermore, we construct a risk factor CMP (clean minus polluting) and document a significant factor loading when added to the Fama–French five-factor model, suggesting the existence of a risk premium based on a firm’s environmental performance.
Suggestions for Revegetation over the Next 30 Years Based on Precipitation in the Three North Region of China
Authors: Xiao Yu , Xie Gaodi , Lu Chunxia , Zhang Changshun , Xu Jie , Liu Jingya , Qin Keyu , Li Yiqiu , Xu Chaoxuan , Zhang Caixia , Wang Yangyang , Gan Shuang , Liu Jia , Ge Liqiang
Published: November 2021

Afforestation in the Three North Region (TNR) of China has received wide concern due to the low survival rate and threats to water security associated with the lack of available precipitation for vegetation. It is crucial to provide a spatial layout for revegetation according to the available precipitation to achieve the vegetation cover target. This study investigated the spatial pattern of precipitation, determined the suitable vegetation distribution based on the ecological water requirements and precipitation, and proposed an optimized revegetation scheme by comparing the actual and suitable vegetation patterns. The results indicated that the actual vegetation that matched the pixel-level precipitation accounted for 67.24% of the total vegetation area in the TNR. However, 18.50% of the actual forest, 21.82% of the actual shrublands, and 19.95% of the actual grasslands were overloaded with respect to precipitation. The total suitable vegetation area was reduced slightly compared to the actual vegetation area. There is still some potential for the revegetation of forest and shrublands, mainly those in the eastern and south-eastern parts of the TNR. The optimized revegetation area in the TNR was 3.04 × 106 km2, including a maintenance management type of 2.19 × 106 km2, an upgrade type of 0.49 × 106 km2, and a degradation type of 0.37 × 106 km2. Maintenance management (natural restoration) and transformation to vegetation types with lower ecological water requirements were recognized as important revegetation practices in the TNR. This study provides guidelines to adjust the Three North Shelterbelt Project policies based on precipitation data to reduce the negative impact of revegetation on the hydrological cycle.
Mapping Tourists’ Destination (Dis)Satisfaction Attributes with User-Generated Content
Authors: Kim Woohyuk , Kim Sung-Bum , Park Eunhye
Published: November 2021

Although the tourism industry has increasingly used social media, there has been little empirical research in terms of the attributes of tourist satisfaction and dissatisfaction with user-generated contents. The purpose of this study is to explore the attributes of tourist satisfaction and dissatisfaction through user-generated contents. We collected data from online review platforms. Our data include historical online reviews, names of reviewers, ratings, location, helpful votes, date of visits, and contributions. In terms of results, the study found 30 key topics related to tourist satisfaction and dissatisfaction. Additionally, we found three clusters (i.e., holiday experience, attractions and facilities, and food experience). Lastly, we that suggested rating levels are different based on the type of tourists (i.e., domestic and international). This study provides discussions and implications for tourism research and industry practices.
Circular Economy as a Catalyst for Progress towards the Sustainable Development Goals: A Positive Relationship between Two Self-Sufficient Variables
Authors: Valverde Juan-Manuel , Avilés-Palacios Carmen
Published: November 2021

Governments, civil society organisations and companies have expressed an interest in contributing to the achievement of the Sustainable Development Goals, but incorporating these goals into their strategies and activities is not an easy task. This study aims to provide information on the role of circular economy as a tool to boost progress towards the Sustainable Development Goals to assist these different stakeholders in their quest to attain the goals. Using heuristic methodology, a review of the existing literature was conducted to explore the relationship between the two terms. Specific attention was paid to the development goals with the highest interdependence with circular economy: Sustainable Development Goal 6 (Clean Water), 8 (Decent work), 12 (Responsible consumption and production) and 15 (Life on land). Having identified the reciprocal relationships between the two variables, the results of the literature review were then analysed to explore their possible self-sufficiency. The findings of the study are intended to assist stakeholders in incorporating the SDGs into their corporate sustainability strategies.
Robotic Intersphincteric Resection for Low Rectal Cancer: Technical Controversies and a Systematic Review on the Perioperative, Oncological, and Functional Outcomes
Authors: Piozzi Guglielmo Niccolò , Kim Seon Hahn
Published: November 2021

Intersphincteric resection (ISR) is the ultimate anus-sparing technique for low rectal cancer and is considered an oncologically safe alternative to abdominoperineal resection. The application of the robotic approach to ISR (RISR) has been described by few specialized surgical teams with several differences regarding approach and technique. This review aims to discuss the technical aspects of RISR by evaluating point by point each surgical controversy. Moreover, a systematic review was performed to report the perioperative, oncological, and functional outcomes of RISR. Postoperative morbidities after RISR are acceptable. RISR allows adequate surgical margins and adequate oncological outcomes. RISR may result in severe bowel and genitourinary dysfunction affecting the quality of life in a portion of patients.
Calidad de vida de adultos mayores de la Seguridad Social peruana durante la pandemia por COVID-19
Authors: Tenorio-Mucha Janeth , Romero-Albino Zoila , Roncal-Vidal Vasti , Cuba-Fuentes María Sofía
Published: November 2021

Introducción: Evaluar la calidad de vida de adultos mayores que pertenecen a los Centros del Adulto Mayor (CAM) de la Seguridad Social durante la pandemia por COVID-19. Material y métodos: Se recolectó información mediante llamadas telefónicas a adultos mayores de 60 años de los CAM. La calidad de vida fue evaluada con el cuestionario EQ-5D-3L, que considera las dimensiones de movilidad, cuidado personal, actividades cotidianas, dolor/malestar y ansiedad/depresión y una escala analógica de 0 a 100. Se midió la presencia de depresión, ansiedad, comorbilidades y el estado funcional. Se realizó un análisis bivariado con pruebas no paramétricas para evaluar la asociación entre covariables y la escala analógica de calidad de vida. Además, se realizó un análisis de regresión simple usando modelos lineales generalizados de la familia de Poisson para evaluar variables asociadas a la presencia de problemas en las dimensiones de calidad de vida. Resultados: Participaron 99 adultos mayores, en su mayoría mujeres (84,9%) la edad promedio fue 73,1 años, 83,3% tenían un nivel educativo superior y 86,7% vivían acompañados. Los adultos mayores con obesidad, enfermedades pulmonares, imposibilidad de manejar su propio dinero, fatiga y problemas de audición reportaron un puntaje menor al promedio (<78,9) en la escala de calidad de vida. Las enfermedades osteoarticulares y la sensación de fatiga incrementan la probabilidad de sufrir problemas de movilidad, de realizar actividades cotidianas y de dolor/malestar. Conclusiones: La calidad de vida de los adultos mayores es influida por multiples factores que se deben abordar para mejorar su bienestar físico y mental.
Ferritina sérica en el pronóstico de mortalidad en pacientes con neumonía severa por SARS-CoV-2
Authors: Castillo-Rivera Elsa , Cacha-Villacorta Rosario , Sánchez-Cubas Claudia A. , Bardales-Zuta Víctor
Published: November 2021

Carta al editor ( Sin resumen )
Incidencia de la dirección financiera en las MiPymes comerciales de productos alimenticios de la ciudad de Machala
Authors: Carrion Melissa , Vaca Elis , Pacheco Andrés
Published: November 2021

MiPymes have become one of the largest sources of economic movement in the country, however, their mortality rate is high because they do not last for a long time and do not develop with should be, that is why in the This project intends to carry out an analysis on the impact that a financial department has to promote the development of MiPym in the city of Machala. For this, a quantitative method investigation was carried out, with a descriptive-experimental scope, where a survey was presented aimed at company managers, to confirm their opinion about this influence. With the information it was possible to consider that financial management is necessary to establish decision-making and know its financial status, taking into account a vertical balance analysis that allows it to be compared with the financing of other companies
Inventory and Distribution of Mosquitoes (Diptera, Culicidae) in the Aures Region (Batna, Algeria)
Authors: Belkhiri Nora , Habbachi Wafa , Benhissen Saliha , Frah Naama , Asloum Abdelmadjid Yagoub
Published: November 2021

Mosquitoes are the most terrifying both for their abundance and for the diseases they transmit. They are vectors of malaria, lymphatic filariasis and arbovirus such as yellow fever, dengue, viral encephalitis and African horse sickness. These characteristics give this fauna prominent importance and health interest. To identify the most widespread mosquito species, we conducted for the first time an inventory in the Aures region more particularly the wilaya of Batna (East of Algeria) from May 2017 to January 2020, we studied their diversity, abundance and distribution. The sampling is done by monthly surveys of the various localities chosen, using the dipping method to collect the larvae. In the various sites prospected, we were able to collect a total of 8275 mosquito individuals presented by nine species belonging to four different genera: Culiseta, Culex, Aedes and Anopheles of which the genus Culiseta is the best represented, particularly with the species Culiseta longiareolata (52.07%). It appears from what we have obtained that the Batna region reveals a significant diversity of mosquitoes. This study aimed to inventory the Culicidian species more broadly by surveys in several localities of Batna region at the level of different environments. This will allow us to know the faunistic composition of the region, to collect and record information on the vectors, their habitats and the conditions that favors their multiplication within a given area.
Hydrogeochemical assessment of the sorption properties of heavy metals in the areas of the impact of solid waste landfills on groundwater
Authors: Кузьмин В.В. , Болдырев К.А. , Сафонов A.В.
Published: November 2021

Изложены основы методики прогнозирования распространения тяжелых металлов на участках загрязнения подземных вод фильтратом полигонов твердых коммунальных отходов. Выполнен анализ качества фильтрата полигонов твердых коммунальных отходов и применимости статистических и эмпирических оценок коэффициента сорбции тяжелых металлов. Показана ограниченность применимости статистических оценок для анализа распространения высокоминерализованных вод фильтратов. На основе методологии геохимического моделирования разработана модель определения коэффициентов обмена между растворенной и твердой фазами – коэффициентов сорбции. Приведены результаты определения коэффициента сорбции для широкого круга катионов применительно к условиям вытеснения природных вод фильтратом полигонов твердых коммунальных отходов. Разработанная методика может быть использована для оценки влияния полигонов твердых коммунальных отходов на качество подземных вод, для прогнозирования распространения тяжелых металлов в области потенциального влияния отходов, для проведения работ в рамках ОВОС (Оценка воздействия на окружающую среду) и ПМООС (Перечень мероприятий по охране окружающей среды), для разработки систем инженерной защиты подземных вод от загрязнения. Предложенная модель может служить основой для ее дальнейшего развития с учетом процессов образования устойчивых органических комплексов металлов в водах фильтрата и комплексообразования на твердой фазе пород.

The fundamentals of the method for predicting the spread of heavy metals in the areas of groundwater pollution by leachate from solid municipal waste landfills are stated. The analysis of the leachate quality of municipal solid waste landfills and the applicability of statistical and empirical estimates of the sorption coefficient of heavy metals is carried out. The limited applicability of statistical estimates for analyzing the distribution of highly mineralized leachate is shown. Based on the method of geochemical simulation, a model has been developed for determining the exchange coefficients between the dissolved and solid phases, i. e. sorption coefficients. The results of determining the sorption coefficient for a wide range of cations are presented with regard to the conditions of natural water displacement by the leachate from solid waste landfills. The developed method can be used to estimate the impact of municipal solid waste landfills on groundwater quality, to predict the spread of heavy metals in the area of potential waste impact, to carry out works within the framework of EIA (Environmental Impact Assessment) and LEPM (List of Environmental Protection Measures), to develop systems for engineering protection of groundwater from pollution. The proposed model can serve as a basis for its further improvement with account of the processes of formation of stable organic metal complexes in leachate and complexation on the hard rocks.
Participatory Microbiome Research With Hmong and Karen Communities: Lessons Learned
Authors: Vangay Pajau , Yang Nancy , Pergament Shannon , Xiong Mary , Paw Bwei , Batres Rodolfo , Knights Dan , Culhane-Pera Kathleen A.
Published: November 2021

In this brief report, we share lessons learned from the Immigrant Microbiome Project (IMP), a microbiome research study conducted in partnership with the Hmong and Karen communities in Minnesota. Members of the IMP academic-community research team and community advisory board reflected on the community-based participatory research (CBPR) approach used for the IMP project, which informed these lessons learned. The IMP illustrates how microbiome researchers can utilize CBPR, which can improve the validity of research projects, create respectful partnerships, build trust between community members and researchers, and ensure that research results are returned to the community as actions that can improve health.
Threshold increase and lasing inhibition due to hexagonal-pyramid-shaped hillocks in AlGaN-based DUV laser diodes on single-crystal AlN substrate
Authors: Kushimoto Maki , Zhang Ziyi , Honda Yoshio , Schowalter Leo J. , Sasaoka Chiaki , Amano Hiroshi
Published: November 2021

The presence of hexagonal-pyramid-shaped hillocks (HPHs) in AlGaN epitaxial films affects device characteristics; this effect is significant in DUV laser diodes (LDs) on AlN substrates, where the presence of HPHs under the p-electrode increases the threshold current density and inhibits the lasing. In this study, we investigated the difference between the lasing characteristics of LDs with and without HPHs. It was found that in the presence of HPHs, the threshold excitation power density increased and the slope efficiency decreased by optical excitation. To investigate the cause of these phenomena, we performed structural, optical, and electrical analyses of the HPHs. Various imaging techniques were used to directly capture the characteristics of the HPHs. As a result, we concluded that HPHs cause the degradation of LD characteristics due to a combination of structural, optical, and electrical factors.
Tin instead of aluminum as a back electrode in P3HT:PC71BM organic solar cells
Authors: Almohammedi Abdullah , Ismail Yasser A. M. , Khan Mohd T. , Benghanem Mohamed , Alamri Saleh N. , Soga Tetsuo , Rusop Mohamad
Published: November 2021

In the present work, a thin film of Sn metal, instead of aluminum, was deposited as a back electrode, using thermal evaporation, for fabricating organic solar cells composed of poly(3-hexylthiophene) and [6,6]-phenyl-C71 butyric acid methyl ester. The effect of post-thermal annealing on performance parameters of the solar cell was investigated at low temperatures (suitable for organic solar cells) up to 180 °C. In addition, the effect of thermal annealing on morphological (using scanning electron microscopy) and electrical properties (using a Hall effect setup) of the Sn thin films is reported and discussed here. The obtained minor effect of thermal annealing on the morphological and electrical properties of the Sn thin films is offset by an improvement in the performance parameters of the solar cells after post-annealing at 160 °C. The present study shows good electrical properties of Sn thin films which are comparable with those of aluminum thin films.
Effect of percolation path on temperature dependence of threshold voltage variability in bulk MOSFETs
Authors: Mizutani Tomoko , Takeuchi Kiyoshi , Saraya Takuya , Oka Hiroshi , Mori Takahiro , Kobayashi Masaharu , Hiramoto Toshiro
Published: November 2021

The threshold voltage variability of bulk MOSFETs was measured at RT and cryogenic temperature and compared. It was found that the temperature dependences of the threshold voltage defined by extrapolation (V
THEX) and the threshold voltage defined by constant current (V
THC) show different behaviors and the percolation path in the channel, which is caused by a potential valley due to random dopant fluctuations, weakens the temperature dependence of V
THC.
Stabilization of the ferroelectric phase in Hf-based oxides by oxygen scavenging
Authors: Su Mingji , Liu Jirong , Weng Zeping , Ding Xiang , Chen Zhengyang , Zhang Yi , Zhao Liang , Lee Choonghyun , Zhao Yi
Published: November 2021

We propose an oxygen scavenging technique based on thermodynamic considerations of metal and oxygen systems to stabilize the ferroelectric phase and enhance the ferroelectricity in Hf-based oxides. By using an oxygen scavenging metal to control the oxygen vacancy concentration in Hf-based oxides, the effect of this oxygen scavenging technique in ferroelectric Hf-based oxides was systematically investigated. It was revealed that controlling the oxygen vacancies during the crystallization process is of vital importance to stabilizing the ferroelectric properties. This oxygen scavenging technique is an effective method of improving the performance of Hf-based ferroelectric materials without employing any dopant in Hf-based oxides.