bluuebunny/crossref_metadata_2025 huggingface dataset:
New Insights into the Lamb Shift: The Spectral Density of the Shift
Authors: Maclay G. Jordan
Published: October 2022

In an atom, the interaction of a bound electron with the vacuum fluctuations of the electromagnetic field leads to complex shifts in the energy levels of the electron, with the real part of the shift corresponding to a shift in the energy level and the imaginary part to the width of the energy level. The most celebrated radiative shift is the Lamb shift between the 2s1/2 and the 2p1/2 levels of the hydrogen atom. The measurement of this shift in 1947 by Willis Lamb Jr. proved that the prediction by Dirac theory that the energy levels were degenerate was incorrect. Hans Bethe’s non-relativistic calculation of the shift using second-order perturbation theory demonstrated the renormalization process required to deal with the divergences plaguing the existing theories and led to the understanding that it was essential for theory to include interactions with the zero-point quantum vacuum field. This was the birth of modern quantum electrodynamics (QED). Numerous calculations of the Lamb shift followed including relativistic and covariant calculations, all of which contain a nonrelativistic contribution equal to that computed by Bethe. The semi-quantitative models for the radiative shift of Welton and Power, which were developed in an effort to demonstrate physical mechanisms by which vacuum fluctuations lead to the shift, are also considered here. This paper describes a calculation of the shift using a group theoretical approach which gives the shift as an integral over frequency of a function, which is called the “spectral density of the shift.“ The energy shift computed by group theory is equivalent to that derived by Bethe yet, unlike in other calculations of the non-relativistic radiative shift, no sum over a complete set of states is required. The spectral density, which is obtained by a relatively simple computation, reveals how different frequencies of vacuum fluctuations contribute to the total energy shift. The analysis shows, for example, that half the radiative shift for the ground state 1S level in H comes from virtual photon energies below 9700 eV, and that the expressions of Power and Welton have the correct high-frequency behavior, but not the correct low-frequency behavior, although they do give approximately the correct value for the total shift.
Excitation Spectra and Edge Singularities in the One-Dimensional Anisotropic Heisenberg Model for Δ = cos(π/n), n = 3,4,5
Authors: Schlottmann Pedro
Published: October 2022

The T=0 excitation spectra of the antiferromagnetic (J>0) anisotropic Heisenberg chain of spins 1/2 are studied using the Bethe Ansatz equations for Δ=cos(π/n), n=3,4 and 5. The number of unknown functions is n−1 for Δ=cos(π/n) and can be solved numerically for a finite external field. The low-energy excitations form a Luttinger liquid parametrized by a conformal field theory with conformal charge of c=1. For higher energy excitations, the spectral functions display deviations from the Luttinger behavior arising from the curvature in the dispersion. Adding a corrective term of the form of a mobile impurity coupled to the Luttinger liquid modes corrects this difference. The “impurity” is an irrelevant operator, which if treated non-perturbatively, yields the threshold singularities in the one-spinwave particle and hole Green’s function correctly.
Monitoring of Atmospheric Carbon Dioxide over a Desert Site Using Airborne and Ground Measurements
Authors: Wang Qin , Mustafa Farhan , Bu Lingbing , Yang Juxin , Fan Chuncan , Liu Jiqiao , Chen Weibiao
Published: October 2022

Accurate monitoring of atmospheric carbon dioxide (CO2) is of great significance for studying the carbon cycle. Compared to ground observational sites, airborne observations cover a wider area, which help in effectively monitoring the distribution of CO2 sources and sinks. In this study, an airborne campaign was carried out in June and July 2021 to measure the atmospheric CO2 concentration over a desert site, Dunhuang, located in western China. The dry-air column-averaged CO2 mole fraction (XCO2) inversion results obtained from the Atmospheric Carbon Dioxide Lidar (ACDL) system were compared with the Orbiting Carbon Observatory 2 (OCO-2) retrievals, portable Fourier Transform Spectrometer (EM27/SUN) measurement results, and with the XCO2 estimates derived using the airborne Ultraportable Greenhouse Gas Analyzer (UGGA) and the Copernicus Atmosphere Monitoring Service (CAMS) model measurements. Moreover, the vertical CO2 profiles obtained from the OCO-2 and the CAMS datasets were also compared with the airborne UGGA measurements. OCO-2 and CAMS CO2 measurements showed a vertical distribution pattern similar to that of the aircraft-based measurements of atmospheric CO2. In addition, the relationship of atmospheric CO2 with the aerosol optical depth (AOD) was also determined and the results showed a strong and positive correlation between the two variables.
ELCD: Efficient Lunar Crater Detection Based on Attention Mechanisms and Multiscale Feature Fusion Networks from Digital Elevation Models
Authors: Fan Lili , Yuan Jiabin , Zha Keke , Wang Xunan
Published: October 2022

The detection and counting of lunar impact craters are crucial for the selection of detector landing sites and the estimation of the age of the Moon. However, traditional crater detection methods are based on machine learning and image processing technologies. These are inefficient for situations with different distributions, overlaps, and crater sizes, and most of them mainly focus on the accuracy of detection and ignore the efficiency. In this paper, we propose an efficient lunar crater detection (ELCD) algorithm based on a novel crater edge segmentation network (AFNet) to detect lunar craters from digital elevation model (DEM) data. First, in AFNet, a lightweight attention mechanism module is introduced to enhance the feature extract capabilities of networks, and a new multiscale feature fusion module is designed by fusing different multi-level feature maps to reduce the information loss of the output map. Then, considering the imbalance in the classification and the distributions of the crater data, an efficient crater edge segmentation loss function (CESL) is designed to improve the network optimization performance. Lastly, the crater positions are obtained from the network output map by the crater edge extraction (CEA) algorithm. The experiment was conducted on the PyTorch platform using two lunar crater catalogs to evaluate the ELCD. The experimental results show that ELCD has a superior detection accuracy and inference speed compared with other state-of-the-art crater detection algorithms. As with most crater detection models that use DEM data, some small craters may be considered to be noise that cannot be detected. The proposed algorithm can be used to improve the accuracy and speed of deep space probes in detecting candidate landing sites, and the discovery of new craters can increase the size of the original data set.
A Refined Model for Quad-Polarimetric Reconstruction from Compact Polarimetric Data
Authors: Guo Rui , Zhao Xiaopeng , Zang Bo , Liang Yi , Bai Jian , Guo Liang
Published: October 2022

As a special dual-polarization technique, compact polarimetric (CP) synthetic aperture radar (SAR) has already been widely studied and installed on some spaceborne systems due to its superiority to quad-polarization; moreover, quad-pol information can be explored and reconstructed from the CP SAR data. In this paper, a refined model is proposed to estimate the quad-pol information for the CP mode. This model involves CP decomposition, wherein the polarization degree is introduced as the volume scattering model parameter. Moreover, a power-weighted model for the co-polarized coherence coefficient is proposed to avoid the iterative approach in pseudo-quad-pol information reconstruction. Experiments were implemented on the simulated Gaofen-3 and ALOS-2 data collected over San Francisco. Compared with typical reconstruction models, the proposed refined model shows its superiority in estimating the quad-pol information. Furthermore, terrain classification experiments using a complex-value convolutional neural network (CV-CNN) were performed on AIRSAR Flevoland data to validate the reconstruction effectiveness for classification applications.
Improved Model-Based Forest Height Inversion Using Airborne L-Band Repeat-Pass Dual-Baseline Pol-InSAR Data
Authors: Zhang Qi , Hensley Scott , Zhang Ruiheng , Liu Chang , Ge Linlin
Published: October 2022

This paper proposes an improved model-based forest height inversion method for airborne L-band dual-baseline repeat-pass polarimetric synthetic aperture radar interferometry (PolInSAR) collections. A two-layer physical model with various volumetric scattering attenuation and dynamic motion properties is first designed based on the traditional Random Motion over Ground (RMoG) model. Related PolInSAR coherence functions with both volumetric and temporal decorrelations incorporated are derived, where the impacts of homogenous and heterogeneous attenuation and dynamic motion properties on the performance of forest height inversion were investigated by the Linear Volume Attenuation (LVA), Quadratic Volume Attenuation (QVA), Linear Volume Motion (LVM), and Quadratic Volume Motion (QVM) depictions in the volume layer. Dual-baseline PolInSAR data were acquired to increase the degree of freedom (DOF) of the coherence observations and thereby provide extra constraints on the forest parameters to address the underdetermined problem. The experiments were carried out on a boreal forest in Canada and a tropical one in Gabon, where physical models with LVA + QVM (RMSE: 3.56 m) and QVA + LVM (RMSE: 6.83 m) exhibited better performances on the forest height inversion over the boreal and tropical forest sites, respectively. To leverage the advantages of LVA, QVA, LVM, and QVM, a pixel-wise optimization strategy was used to obtain the best forest height inversion performance for the range of attenuation and motion profiles considered. This pixel-wise optimization surpasses the best-performing single model and achieves forest height inversion results with an RMSE of 3.21 m in the boreal forest site and an RMSE of 6.48 m in the tropical forest site.
Knowledge-Based Remote E-Coaching Framework Using IoT Devices for In-Home ADL Rehabilitation Treatment of Degenerative Brain Disease Patients
Authors: Kim Hyo-Jung , Jeong Seol-Young , Kang Soon-Ju
Published: October 2022

The activities of daily living (ADL) ability level of an elderly patient is an important indicator in determining the patient’s degree of degenerative brain disease and is mainly evaluated through face-to-face interviews with doctors and patients in hospitals. It is impossible to determine the exact ADL ability of a patient through such a temporary interview, and the pursuit of accurate ADL ability evaluation technology is a very important research task worldwide. In this paper, in order to overcome the limitations of the existing ADL evaluation method mentioned above, first of all, a self-organized IoT architecture in which IoT devices autonomously and non-invasively measure a patient’s ADL ability within the context of the patient’s daily living place was designed and implemented. Second, a remote rehabilitation treatment concept for enhancing the patient’s ADL ability we call an “e-coaching framework”, in which a doctor remotely gives an instruction in a specific ADL scenario, and the patient’s ability to understand and perform the instruction can be measured on-line and in real time, was additionally developed on top of the self-organized IoT architecture. In order to verify the possibility of remote rehabilitation treatment through the proposed architecture, various remotely directed ADL scenarios were performed and the accuracy of the measurements was verified.
On the Applications of EMG Sensors and Signals
Authors: Kamavuako Ernest N.
Published: October 2022

The ability to execute limb motions derives from composite command signals (or efferent signals) that stem from the central nervous system through the highway of the spinal cord and peripheral nerves to the muscles that drive the joints [...]
Simplex Back Propagation Estimation Method for Out-of-Sequence Attitude Sensor Measurements
Authors: Goh Shu Ting , Tissera M. S. C. , Tan RongDe Darius , Srivastava Ankit , Low Kay-Soon , Lim Lip San
Published: October 2022

For a small satellite, the processor onboard the attitude determination and control system (ADCS) is required to monitor, communicate, and control all the sensors and actuators. In addition, the processor is required to consistently communicate with the satellite bus. Consequently, the processor is unable to ensure all the sensors and actuators will immediately respond to the data acquisition request, which leads to asynchronous data problems. The extended Kalman filter (EKF) is commonly used in the attitude determination process, but it assumes fully synchronous data. The asynchronous data problem would greatly degrade the attitude determination accuracy by EKF. To minimize the attitude estimation accuracy loss due to asynchronous data while ensuring a reasonable computational complexity for small satellite applications, this paper proposes the simplex-back-propagation Kalman filter (SBPKF). The proposed SBPKF incorporates the time delay, gyro instability, and navigation error into both the measurement and covariance estimation during the Kalman update process. The performance of SBPKF has been compared with EKF, modified adaptive EKF (MAEKF), and moving–covariance Kalman filter (MC-KF). Simulation results show that the attitude estimation error of SBPKF is at least 30% better than EKF and MC-KF. In addition, the SBPKF’s computational complexity is 17% lower than MAEKF and 29% lower than MC-KF.
Semi-Supervised Defect Detection Method with Data-Expanding Strategy for PCB Quality Inspection
Authors: Wan Yusen , Gao Liang , Li Xinyu , Gao Yiping
Published: October 2022

Printed circuit board (PCB) defect detection plays a crucial role in PCB production, and the popular methods are based on deep learning and require large-scale datasets with high-level ground-truth labels, in which it is time-consuming and costly to label these datasets. Semi-supervised learning (SSL) methods, which reduce the need for labeled samples by leveraging unlabeled samples, can address this problem well. However, for PCB defects, the detection accuracy on small numbers of labeled samples still needs to be improved because the number of labeled samples is small, and the training process will be disturbed by the unlabeled samples. To overcome this problem, this paper proposed a semi-supervised defect detection method with a data-expanding strategy (DE-SSD). The proposed DE-SSD uses both the labeled and unlabeled samples, which can reduce the cost of data labeling, and a batch-adding strategy (BA-SSL) is introduced to leverage the unlabeled data with less disturbance. Moreover, a data-expanding (DE) strategy is proposed to use the labeled samples from other datasets to expand the target dataset, which can also prevent the disturbance by the unlabeled samples. Based on the improvements, the proposed DE-SSD can achieve competitive results for PCB defects with fewer labeled samples. The experimental results on DeepPCB indicate that the proposed DE-SSD achieves state-of-the-art performance, which is improved by 4.7 mAP at least compared with the previous methods.
Camera Motion Agnostic Method for Estimating 3D Human Poses
Authors: Kim Seong Hyun , Jeong Sunwon , Park Sungbum , Chang Ju Yong
Published: October 2022

Although the performance of 3D human pose and shape estimation methods has improved considerably in recent years, existing approaches typically generate 3D poses defined in a camera or human-centered coordinate system. This makes it difficult to estimate a person’s pure pose and motion in a world coordinate system for a video captured using a moving camera. To address this issue, this paper presents a camera motion agnostic approach for predicting 3D human pose and mesh defined in the world coordinate system. The core idea of the proposed approach is to estimate the difference between two adjacent global poses (i.e., global motion) that is invariant to selecting the coordinate system, instead of the global pose coupled to the camera motion. To this end, we propose a network based on bidirectional gated recurrent units (GRUs) that predicts the global motion sequence from the local pose sequence consisting of relative rotations of joints called global motion regressor (GMR). We use 3DPW and synthetic datasets, which are constructed in a moving-camera environment, for evaluation. We conduct extensive experiments and prove the effectiveness of the proposed method empirically.
Implementation of a WSN for Environmental Monitoring: From the Base Station to the Small Sensor Node
Authors: Oliveira Tiago Emanuel , Reis João Ricardo , Caldeirinha Rafael Ferreira Silva
Published: October 2022

In this paper, the implementation of a Wireless Sensor Network (WSN) for environmental monitoring (EM) is presented. It includes the design, implementation and experimental characterization of a multi-sector base station (BS) antenna composed of several microstrip Quasi-Yagi elements and the implementation and experimental characterization of a reduced form factor antenna for the sensor nodes (SN). Subsequently, it reports the implementation of a WSN based on Lopy4 transceivers, using the developed BS and SN antennas. Finally, experimental results obtained on the field to evaluate the performance of the network in terms of maximum coverage distance and coverage area are presented. According to the field tests, the connectivity between the sensor nodes and the developed WSN base station is confirmed at distances above 3.5 km and for all the antenna sectors of the multi-sector BS attaining a 360° of field of view.
Impact and Recovery of Coastal Tourism Amid COVID-19: Tourism Flow Networks in Indonesia
Authors: Wang Xingshan , Tang Lu , Chen Wei , Zhang Jianxin
Published: October 2022

This study aims to explore tourism changes in coastal tourism destinations before and during the COVID-19 pandemic from the perspective of regional resilience. A mixed method of a social network and spatial analysis was used to evaluate inbound tourists’ geotagged photos of Indonesia on Flickr from 2018–2022 as metadata. The DBSCAN algorithm and Markov chains were used to comprehensively analyze the hotspot areas and the patterns of tourism movement trajectories amid a complicated recovery. The results demonstrate that: (1) The distribution of geotagged photos before and during the pandemic generally exhibited stage and regional unevenness. The main clusters were Java and the Nusa Tenggara Islands, with the rest displaying a scattered distribution. (2) The tourism flow network was unevenly distributed, and the nodes had obvious core and edge areas. Owing to the crisis, the tourism flow network realized a change in form from network to line and point. (3) Its impact on Indonesian inbound tourism may persist in the short term, and the volatility of national anti-pandemic policies influences the resilience of tourism flow during COVID-19. The dominance of the core nodes highlights the network’s resistance to disruptions due to the prominence of the location of network connections during the pandemic, and marginal nodes reflect the vulnerability to pandemic shocks owing to the hypocentricity of the nodes and the thinness of the connections within and outside the islands. These results provide marketing and promotion policies for the sustainable development of coastal areas.
Glacier Boundary Mapping Using Deep Learning Classification over Bara Shigri Glacier in Western Himalayas
Authors: Sood Vishakha , Tiwari Reet Kamal , Singh Sartajvir , Kaur Ravneet , Parida Bikash Ranjan
Published: October 2022

Glacier, snow, and ice are the essential components of the Himalayan cryosphere and provide a sustainable water source for different applications. Continuous and accurate monitoring of glaciers allows the forecasting analysis of natural hazards and water resource management. In past literature, different methodologies such as spectral unmixing, object-based detection, and a combination of various spectral indices are commonly utilized for mapping snow, ice, and glaciers. Most of these methods require human intervention in feature extraction, training of the models, and validation procedures, which may create bias in the implementation approaches. In this study, the deep learning classifier based on ENVINet5 (U-Net) architecture is demonstrated in the delineation of glacier boundaries along with snow/ice over the Bara Shigri glacier (Western Himalayas), Himachal Pradesh, India. Glacier monitoring with Landsat data takes the advantage of a long coverage period and finer spectral/spatial resolution with wide coverage on a larger scale. Moreover, deep learning utilizes the semantic segmentation network to extract glacier boundaries. Experimental outcomes confirm the effectiveness of deep learning (overall accuracy, 91.89% and Cohen’s kappa coefficient, 0.8778) compared to the existing artificial neural network (ANN) model (overall accuracy, 88.38% and kappa coefficient, 0.8241) in generating accurate classified maps. This study is vital in the study of the cryosphere, hydrology, agriculture, climatology, and land-use/land-cover analysis.
Application of Geospatial Techniques in Evaluating Spatial Variability of Commercially Harvested Mangoes in Bangladesh
Authors: Moniruzzaman Md , Uddin Md. Sorof , Akhter Md. Abdullah Elias , Tripathi Akshar , Rahaman Khan Rubayet
Published: October 2022

Mango is widely known as a popular fruit in South Asia, including Bangladesh. The country is a significant producer of different local and exotic varieties of mangoes in different geographic locations. Therefore, a study of fruit maturity at diverse locations and climatic conditions becomes critical for a sustainable mango production. In responding to this need, this study evaluates the variability of a few selected commercial mango (Mangifera indica L.) varieties and their maturity timeline with respect to spatial extent (longitudinal-latitudinal variations), elevation profile, and time. Remote sensing technology has been widely used for horticultural applications to study fruit phenology, maturity, harvesting time, and for mapping locational differences. In doing so, we have employed remotely sensed data, such as the Shuttle Radar Topography Mission (SRTM) digital elevation model (DEM) of 30 m spatial resolution, GPM IMERGM precipitation datasets (0.1 × 0.1 degree), NASA GLDAS (Global Land Data Assimilation System) surface skin temperature (0.25 × 0.25 degree), and Noah Land Surface Model L4 3-hourly soil moisture content datasets (0.25 × 0.25 degree). Alongside these, an intensive field data collection campaign has been carried out for 2019 and 2020. It was found that 1° locational variations may result in approximately 2–5 days delay of mango harvesting. The outcome of this study may enhance the appropriate planning of harvesting, production, and the commercialization of mango selection in specific geographic setting for a sustainable harvest and production system in the country.
Controller Development and Experimental Validation for a Vertical Axis Wind Turbine
Authors: Rodrigues Geraldo , Valério Duarte , Melicio Rui
Published: October 2022

This paper reports experimental results, in a wind tunnel, of controllers for a vertical axis wind turbine (VAWT). Models and controllers from previous works were validated and improved through the acquisition of new data sets. The control methods used are PID, LQR and CRONE (a type of fractional order control, i.e., a controller using fractional derivatives). The simulation results led to the choice of the CRONE controller for implementation. Hardware and software were developed to perform tests in a wind tunnel, that proved the correct behavior of the controller whilst validation results exceeded those from simulation. These results are expected to contribute for the viability of VAWTs in urban environments since they can aid in the increasing demand of energy services in urban areas without increasing the carbon emission levels of the area.
An Integrated Seamless Control Strategy for Distributed Generators Based on a Deep Learning Artificial Neural Network
Authors: EL-Ebiary Ahmed H. , Attia Mahmoud A. , Marei Mostafa I. , Sameh Mariam A.
Published: October 2022

One of the challenges of inverter-based distributed generators (DGs) is to keep the voltage and frequency at their specified limits during transitions between grid-connected and islanded modes of operation. This paper presents an integrated seamless control strategy for inverter-based DGs to ensure smooth transitions between the different modes of operation. The proposed strategy is based on a deep learning neural network (DL-ANN) Proportional-Integral- Derivative (PID) controller to regulate the terminal voltage of the DG interface system. A feed-forward loop is integrated with the proposed strategy to mitigate grid harmonics by controlling the DG inverter to feed the harmonics components of non-linear loads without exceeding its capacity. Results are provided to evaluate the dynamic performance of the proposed unified control strategy under different disturbances. Finally, to demonstrate the superiority of the DL-ANN controller, a comparison is carried out with the conventional Proportional-Integral (PI) controller and the set-membership affine projection adaptive (SMAPA)-based PI controller.
Reengineering Human Resources and Entrepreneurial Learning towards Organizational Revitalization in Malaysian Travel and Tourism Companies during the COVID-19 Pandemic
Authors: Lee Cheng-Wen , Peng Choong Leng , Chen Hsiao Chuan
Published: October 2022

The interest in the reengineering process of human resources and entrepreneurial learning contributes to enhancing the success of organizational revitalization, especially concerning corporate sustainability. This study builds a conceptual research framework and adopts the descriptive analytical approach based on the data of 239 samples from the employees working in travel and tourism companies in Malaysia. The findings indicate the existence of a statistically significant effect of human resources reengineering on various dimensions of organizational revitalization. Amongst them, pioneering/entrepreneurial learning as a moderating variable also has a significant and positive influence on organizational revitalization. The implications of this study mostly emphasize the necessity for travel and tourism companies to maintain their sustainability through reengineering human resources. In accomplishing strategic tasks for human resource development and achieving the strategic goals, these essential issues such as encouraging workers to innovate and continuously raising their awareness of entrepreneurship need to be acknowledged.
Relics of War: Damaged Structures and Their Replacement or Management in Modern Landscapes
Authors: Larkham Peter J. , Adams David
Published: October 2022

All wars, large and small scale, have had impacts on the built environments enmeshed in the conflict. This is almost always an adverse reaction, often involving destruction, but can also include the construction of defensive or other features. Damaged sites can be redeveloped relatively quickly, though some can persist for decades and some evidence of damage may be deliberately retained for a range of reasons. Damaged structures may remain for decades or centuries, especially if built on a large scale, and, if surviving, may undergo re-evaluation and retention as heritage features. This paper explores the fate of a range of relict features from the Second World War, surviving into modern urban and rural landscapes through inaction or deliberate action. Using a wide range of examples particularly from the UK but also drawing on others from elsewhere in Europe, we explore the impact of conflict on such relics; their nature and scale, processes of decision-making affecting their treatment over the last seven decades, and their landscape impact. The physical legacy of this war still affects many communities. Changing values so long after the conflict, and the decay of unmaintained structures, gives an urgency to reviewing the future of surviving relics.
Go Cashless! Mobile Payment Apps Acceptance in Developing Countries: The Jordanian Context Perspective
Authors: Almajali Dmaithan , Al-Okaily Manaf , Al-Daoud Khaleel , Weshah Sulaiman , Shaikh Aijaz
Published: October 2022

Despite the expanding global usage of mobile phones in money transactions, the adoption of mobile payment systems in Jordan remains slow. This study employed the technology acceptance model (TAM) to identify the factors with a potential impact on mobile payment systems acceptance. The impact of perceived privacy (PP) and the mediating function of perceived certainty (PC) on the behavioral intention (BI) of mobile payment systems among Jordanian ministries were examined. Data obtained from 270 respondents were analyzed using partial least-squares structural equation modeling (PLS-SEM). The empirical findings show a positive link between perceived usefulness (PU) and PC on the BI of mobile payment systems. The mediation analysis demonstrated that PC partially mediated the association of PP with the BI of mobile payment systems. The final section concluded the paper by presenting the key theoretical and practical ramifications, as well as the research’s limitations and future directions.
How to Teach Photosynthesis? A Review of Academic Research
Authors: Jančaříková Kateřina , Jančařík Antonín
Published: October 2022

This review study focuses on the teaching of photosynthesis, and it builds on previous review studies. The aim of this study is to present the findings to readers and thus contribute to improving the training of future teachers and student education. This study conducted a critical review of the topic of photosynthesis education, by examining 80 systematically selected articles through quantitative and qualitative approaches. The quantitative analysis highlighted the increasing number of studies in recent years and helped identify the main issues, namely teaching methods and misconceptions. In contrast, the qualitative conceptualization showed that photosynthesis education is a key topic for the development of science literacy and serves as a model for how teachers can educate students on difficult and complex issues. An alarming issue is that misconceptions adopted in childhood are powerful and often persist into adulthood (including teachers). Professional education on photosynthesis is not possible without pedagogical content knowledge, the identification of student concepts, activating methods of learning, and methodical work with scientific language and thinking.
STEM, STEAM and Makerspaces in Early Childhood: A Scoping Review
Authors: Johnston Kelly , Kervin Lisa , Wyeth Peta
Published: October 2022

STEM has emerged as a key area of importance for children, highlighting the value and relevance of integrated understandings of science, technology, engineering and mathematics in both educational contexts and everyday life. The need for innovation and creativity is also recognised, which emphasizes the important role the arts can play as STEM is extended into STEAM. This scoping review investigated what is known about STEM, STEAM and makerspace experiences and opportunities for children aged birth to eight. The review found that early childhood experience with STEM, STEAM and makerspaces is an emerging field of research. Findings suggest that STEAM holds more relevance to learning and experiences in the early childhood years, and perhaps across the lifespan. The review also highlights the need to shift the starting point to the earliest of years and create greater intentionality in STEAM experiences with infants, toddlers and preschool aged children, recognizing the relevance of STEAM and maker mindsets in the lives of young children. Additionally, the scoping review identified the value of informal and community contexts as a means to invite broader participation. Such opportunities provide scope to challenge inequity in opportunity and to overcome intergenerational aversion towards STEM/STEAM-related learning. Further research is needed to understand the professional learning needs of early childhood educators and facilitators of STEAM and makerspace experiences.
An Analysis of MPTCP Congestion Control
Authors: Jowkarishasaltaneh Farinaz , But Jason
Published: October 2022

Many devices contain more than one network interface. There is scope for multi-path transfer to utilise these network interfaces simultaneously. Multi-path TCP (MPTCP) is designed to provide improved resilience and resource utilisation through multi-path transfer. One of the key goals of MPTCP is to preserve fair resource sharing with regular TCP at network bottlenecks. Although the coupled congestion control algorithms can achieve this goal by coupling subflow congestion windows, the algorithms always assume that the subflow paths will share a bottleneck. As a consequence, MPTCP is unable to maximise throughput over all available paths at a non-shared bottleneck. We present a survey about MPTCP and its coupled congestion control algorithms. We then show that MPTCP coupled congestion control algorithms perform poorly when paths are disjoint and/or do not have similar delay and/or bandwidth characteristics.
Urinary Arsenic Concentration and Its Relationship with Bronchial Asthma in Children from Arica, Chile
Authors: Muñoz María Pía , Iglesias Verónica , Saavedra Marta , Saavedra Gina , Yohannessen Karla , Pino Paulina
Published: October 2022

In the city of Arica, northern Chile, the population has been involuntarily exposed to arsenic of natural and anthropogenic origin. This study aims to evaluate the association between urinary arsenic concentration and bronchial asthma diagnosis in the children of Arica. A cross-sectional analysis of a database of 1892 subjects under 18 years of age enrolled in the Environmental Health Centre between 2009 and 2021 was carried out. Arsenic exposure was obtained from a urine sample and bronchial asthma diagnosis from the database of the system for the management of explicit health guarantees. Logistic regression models were used to assess the association between inorganic arsenic and asthma. The median inorganic arsenic was 15 μg/L, and the prevalence of asthma was 7.4%. After adjusting for sex, age, ethnicity, and urinary creatinine, children with the highest tertile of urinary arsenic concentration (≥21.4 μg/L) had a greater chance of developing asthma (odds ratio (OR) 1.90; 95% confidence interval (CI) [1.13–3.18]). When exploring the modifying effect of ethnicity, the association increased among children belonging to any ethnic group (OR 3.51, 95%CI [1.43–8.65]). These findings suggest a relationship between arsenic exposure and bronchial asthma in children. While further studies are needed to assess the impact of arsenic on respiratory health, mitigation efforts to reduce arsenic exposure should be maintained.
Evaluation of the Efficacy of Fludora® Fusion WP-SB 56.25 (Mixture of Clothianidin and Deltamethrin) against Anopheles coluzzii Laboratory and An. arabiensis Wild Colonies
Authors: Gueye Marième , Dia Ibrahima , Diedhiou Seynabou , Samb Badara , Kane Dia Abdoulaye , Diagne Moussa , Faye Ousmane , Konaté Lassana
Published: October 2022

For malaria control, the application of long-lasting insecticidal nets and indoor residual spraying has led to a significant reduction in morbidity and mortality. However, the sustainability of these gains is hampered by the increase in insecticide resistance. It is therefore judicious to evaluate new insecticide formulations. In comparison to clothianidin and deltamethrin, the efficacy and residual effect of Fludora® Fusion was evaluated using an Anopheles coluzzii laboratory and An. arabiensis wild colonies in huts from August 2016 to June 2017 on cement and mud walls. Mortality was recorded at 24, 48, 72, and 96 h post exposure. Like deltamethrin and clothianidin, Fludora® Fusion showed delayed mortality rates above the WHO’s 80% threshold over a period of 11 months with the laboratory strain. With the wild strain, while residual efficacy was observed at 2 months for the three insecticides, no residual efficacy was observed at 8 months at 24 h in both substrates. However, the increased efficacy was observed with increased holding periods (72 h and 96 h). These findings suggest that Fludora® Fusion could be an alternative candidate since this duration covers the transmission period in most areas in Senegal.
Nonanalytic Relativistic r-Modes of Slowly Rotating Nonbarotropic Neutron Stars
Authors: Kraav Kirill Y. , Gusakov Mikhail E. , Kantor Elena M.
Published: October 2022

We show that the r-modes of slowly rotating nonbarotropic neutron stars are described by nonanalytic functions of stellar angular velocity, which makes the perturbation techniques, used so far in the r-mode theoretical studies, inapplicable. In contrast to those studies and in accordance with numerical calculations beyond the slow rotation approximation, the obtained r-mode spectrum is discrete, which resolves the continuous spectrum problem, lasting since 1997. Our findings imply that the relativistic r-modes in slowly rotating neutron stars dramatically differ from their Newtonian cousins, which may have important implications for the detectability of r-mode signatures in observations, in particular for the r-mode excitation efficiency during the neutron star inspirals.
Analysis of the implementation of dental disease prevention programs in the pediatric dental service in several constituent entities of the Russian Federation
Authors: Yanushevich O. O. , Krikheli N. I. , Kiselnikova L. P. , Zueva T. E.
Published: October 2022

Relevance. High dental disease incidence in children is still a relevant problem of public health care in Russia. Regional or national oral disease incidence rates may decrease via the introduction of state or Regional prevention programs. School dentistry is crucial in the pediatric dental care system. Different socio-economic, climatic and geographical conditions of various Regions of the Russian Federation affect the possibilities of preventive program implementation in the child population. Purpose – to evaluate the implementation of dental disease prevention programs in pediatric dental services in several constituent entities of the Russian Federation.

Materials and methods. In 2020, employees of Moscow State University of Medicine and Dentistry visited the Regions of the Russian Federation 39 times within the implementation of the national project "Healthcare" and national medical centre activities. In these Regions, the study examined the following parameters: availability of a Regional dental disease prevention program, the functioning of dental offices in educational institutions, dental checkup coverage rate in children.

Results. The study revealed that most Regions have school-based dental offices in the pediatric dental service. School-based dental offices provide treatment and prevention procedures. The analysis showed that all studied constituent entities carry out dental checkups. However, the dental checkup coverage rate in children varies greatly.

Conclusions. A small number of Regions (23.07%) have approved and are implementing a Regional prevention program, several entities (20.51%) are validating similar programs. And the majority of the studied constituent entities (56.41%) don’t have Regional prevention programs.
Revealing the Defect-Dominated Electron Scattering in Mg
3
Sb
2
-Based Thermoelectric Materials
Authors: Jia Jucai , Zhou Yan , Chen Xiaoxi , Xue Wenhua , Yu Hulei , Li Jing , Zhi Shizhen , Chen Chen , Wang Jian , Hou Shuaihang , Liu Xingjun , Wang Yumei , Cao Feng , Chen Yue , Mao Jun , Zhang Qian
Published: October 2022

The thermoelectric parameters are essentially governed by electron and phonon transport. Since the carrier scattering mechanism plays a decisive role in electron transport, it is of great significance for the electrical properties of thermoelectric materials. As a typical example, the defect-dominated carrier scattering mechanism can significantly impact the room-temperature electron mobility of n-type Mg
3
Sb
2
-based materials. However, the origin of such a defect scattering mechanism is still controversial. Herein, the existence of the Mg vacancies and Mg interstitials has been identified by synchrotron powder X-ray diffraction. The relationship among the point defects, chemical compositions, and synthesis conditions in Mg
3
Sb
2
-based materials has been revealed. By further introducing the point defects without affecting the grain size via neutron irradiation, the thermally activated electrical conductivity can be reproduced. Our results demonstrate that the point defects scattering of electrons is important in the n-type Mg
3
Sb
2
-based materials.
Barriers Toward the National Program for Prevention and Control of Diabetes in Iran: A Qualitative Exploration
Authors: Sadeghi Sohila , Mahani Fatemeh , Amiri Parisa , Alamdari Shahram , Khalili Davood , Saadat Navid , Ebadi Seyed Alireza , Mahdavi Hazaveh Ali Reza , Shahrzad Mohammad Karim , Azizi Fereidoun
Published: October 2022

Background: Despite the achievements of the national program for the prevention and control of diabetes (NPPCD) over the past two decades, the available evidence indicates a high prevalence of this disease in Iran. This qualitative study aims to investigate barriers to the NPPCD by pursuing the perspectives of relevant policy-makers, planners, and healthcare workers. Methods: A grounded theory approach was used to analyze participants’ perceptions and experiences. Semi-structured interviews (n=23) and eight focus groups (n=109) were conducted with relevant policy-makers, planners, and healthcare workers in charge of Iran’s national diabetes management program. Of the 132 participants, ages ranged from 25 to 56 years, and 53% were female. Constant comparative analysis of the data was conducted manually, and open, axial, and selective coding was applied to the data. Results: Two main themes emerged from data analysis: implementation barriers and inefficient policy-making/ planning. Insufficient financial resources, staff shortage and insufficient motivation, inadequate knowledge of some healthcare workers, and defects in the referral system were recognized as the NPPCD implementation barriers. Inappropriate program prioritizing, the lack of or poor intersectoral collaboration, and the lack of an effective evaluation system were the inefficient policy-making/planning problems. Conclusion: Current results highlighted that inefficient policy-making and planning have led to several implementation problems. Moreover, the key strategies to promote this program are prioritizing the NPPCD, practical intersectoral collaboration, and utilizing a more efficient evaluation system to assess the program and staff performance.
Peningkatan Overall Equipment Effectiveness (OEE) Pada Mesin Molding Melalui Perbaikan Six Big Losses Di PT. CWI
Authors: Eddy Eddy , Chairunissa Chairunissa
Published: October 2022

TPM is an innovative approach to maintenance activities that focus on preventing damage to machines / equipment and preventing the occurrence of defective products related to machines / equipment. The success of implementing TPM can be measured from the Overall Equipment Effectiveness (OEE) value. OEE measures how effectively equipment is used and functions to keep equipment in ideal condition by minimizing six big losses. OEE consists of three main, measurable components: Availability, Performance and Quality. In this study, OEE calculations were carried out on Molding machines at PT. CWI. The results of OEE calculations for the period July 2019 to June 2020 ranged from 45.49% to 74.35%, indicating that the world class benchmark standard (85.0%) has not been achieved. Based on the loss analysis, it was identified that the dominant losses were Idling at 42.2%, Rework at 17.7% and Breakdowns at 17.3%. The three losses have the potential and become the main priority for improvement in the context of increasing OEE.
Penggunaan Tawas (Al2(SO4)3) dalam Menurunkan Kadar Total Suspended Solid Air Limbah Batubara
Authors: Rahma Cukri , Niani Cukri Rahmi
Published: October 2022

Wastewater is one of the byproducts produced by coal mining companies. The wastewater contains suspended particles as well as heavy metals. Various attempts have been made to treat wastewater before it is discharged into the environment. This is done so that the waste water does not damage the environment. One way to do this is to settle suspended particles in wastewater or what is known as TSS (Total Suspended solite) using the coagulation-flocculation method. The coagulant used in this study is alum Al2 (SO4) 3. This research was conducted to determine the optimum dose or level of addition of alum into wastewater. The addition of alum is carried out in different doses, this is adjusted to the volume and discharge of waste water that is flowed to the WMP (Water Monitoring Point). The optimum dose of adding or using alum Al2 (SO4) 3 into WPM is 0.03 g / L for WMP 11, and 0.05 g/L for WMP 13.
Pengukuran Kinerja Supply Chain Susu Kental Manis Menggunakan Metode SCOR dan AHP
Authors: Permatasari Monica , Sari Santika
Published: October 2022

PT Frisian Flag Indonesia is a manufacturing company in Jakarta which is engaged in the milk processing industry. PT Frisian Flag Indonesia has not implemented a detailed performance measurement system and only applies a measure of the effectiveness of company performance. The need for Supply chain performance measurement to be able to find out the results of the Supply chain performance of sweetened condensed milk and make improvements to activities that are not optimal. The method used in this research is the AHP-SCOR method and to determine the Supply chain performance score, the Key Performance Indicator (KPI) measurement is used. The results showed 27 valid KPIs using the Snorm De Boer normalization process and the values obtained were: plan was 88,83, make was 93,79, source was 84,545, delivery was 88,149, Return was 38,53. The results of the SCOR model are 81.45. The need for improvements that prioritize performance with the smallest value, namely return.