bluuebunny/crossref_metadata_2025 huggingface dataset:
Medication Use and Storage, and Their Potential Risks in US Households
Authors: Lee SuHak , Schommer Jon C.
Published: February 2022

Background: Medications stored in US households may pose risks to vulnerable populations and the environment, potentially increasing societal costs. Research regarding these aspects is scant, and interventions like medication reuse may alleviate negative consequences. The purpose of this study was to describe medications stored in US households, gauge their potential risk to minors (under 18 years of age), pets, and the environment, and estimate potential costs of unused medications. Methods: A survey of 220 US Qualtrics panel members was completed regarding medications stored at home. Published literature guided data coding for risks to minors, pets, and the environment and for estimating potential costs of unused medications. Results: Of the 192 households who provided usable and complete data, 154 (80%) reported storing a medication at home. Most medications were taken daily for chronic diseases. The majority of households with residents or guests who are minors and those with pets reported storing medications with a high risk of poisoning in easily accessible areas such as counters. Regarding risk to the aquatic environment, 46% of the medications had published data regarding this risk. For those with published data, 42% presented a level of significant risk to the aquatic environment. Unused medications stored at home had an estimated potential cost of $98 million at a national level. Implications/Conclusions: Medications stored at home may pose risks to vulnerable populations and the environment. More research regarding medications stored in households and their risks is required to develop innovative interventions such as medication reuse to prevent any potential harm.
Acknowledgment to Reviewers of Plants in 2021
Authors:   Plants Editorial Office
Published: February 2022

Rigorous peer-reviews are the basis of high-quality academic publishing [...]
Crops on the Rocks: Production, Processing, and Storage at the Early Medieval Site of Senhora Do Barrocal (Municipality of Sátão, Central Portugal)
Authors: Seabra Luís , Tente Catarina , Vaz Filipe Costa , Oliveira Cláudia , González Carretero Lara , Tereso João Pedro
Published: February 2022

Small rural places are largely absent from early medieval written sources, but they were profuse and relevant in regional settlements and economies. Only through archaeological and archaeobotanical investigation is it possible to unveil their structure and productive strategies; however, this kind of investigation is still uncommon in Iberia. Here, the assemblage of fruits/seeds, wood charcoal, and food remains from Senhora do Barrocal (SB) (Sátão, Portugal) will be presented and discussed in order to understand the crop production, processing, and storage. The site was destroyed by a fire somewhere between the 10th and the 11th centuries AD, which allowed the preservation of abundant plant remains in a storage area. Charcoal analyses suggest that the building was made with oak and chestnut timber. The massive fruits/seeds assemblage was dominated by cereals, mostly oat and rye, but also barley, millet, and naked wheat, some fully dehusked, others still hulled. Furthermore, evidence of food products has also been found, suggesting that the area was used for the storage of multiple foods and crops at different processing stages. SB is a good example of how communities adopted a diverse set of crops and multifaceted storage strategies to prevent food shortages and to endure in a harsh environment.
Design and Initial Evaluation of a Low-Cost Microprocessor-Controlled Above-Knee Prosthesis: A Case Report of 2 Patients
Authors: Galey Lucas , Gonzalez Roger V.
Published: February 2022

For prosthesis users, knee units can range from simple devices costing $2000 up to $45,000 for high-end, microprocessor-controlled systems. These higher-end electronic knees provide significant advantages in stability, gait, and metabolic rate compared to their passive or mechanical counterparts. However, the high cost of such systems makes them inaccessible to most amputees. In this study, it was hypothesized that a microprocessor knee could be manufactured for less than $1000, with comparable stability and user experience to a high-end industry standard device. A prototype (E-Knee) was designed with a specific emphasis on stance stability, and was tested during patient gait trials. The gait trials used a repeated measures design to compare three knee devices (a simple passive knee, the prototype E-Knee, and a high-end knee). Ground reaction forces and a functionality questionnaire were used to compare devices. A microprocessor locking test was used to evaluate the prototype’s ability to prevent falls. Building on the LIMBS M3, a passive four-bar polycentric device, the E-Knee added sensing, computing, and controlling capabilities for a material cost of $507. Initial data from a two-subject trial served as proof-of-concept to validate the prototype and found that it improved gait by providing more stability than the M3 and had more gait-pattern similarities to the Ottobock C-Leg than to the M3. Patients reported no perceived differences in stability between the E-Knee and the C-Leg. Patient trials supported that the E-Knee prototype behaved more naturally than the low-end M3 device and had similar ground reaction forces to the C-Leg.
A Polysemic Interpretation of the West Façade of Saint-Martin-de-Besse: Time, Space, and Chiasmus Carved in Stone
Authors: Moubayed Anna-Maria
Published: February 2022

This article explores the sculptural programme of the west portal of Saint-Martin-de-Besse, which places Penance and the Eucharist sacraments at the centre of its polysemic narratives, forming chiastic sequences. Concerned with the fall of humankind and the history of redemption, the portal of Besse presents a series of enigmatic figures from the Old and New Testaments, along with an early Christian figure, Saint Eustace. In this article, I first present a brief historical overview of the church and its surroundings and then proceed with an iconographical survey of its portal. I argue that the series of sculpted narrative vignettes forming the west façade of Besse are polysemic as they carry multiple meanings. Focusing on salvation through (re)conversion, where the liturgical sacraments of Penance and the Eucharist are fundamental, these polysemic narratives form and perform four distinct chiasmus interchanges involving the Garden of Eden, where time and space are in constant dialogue.
Identification of the Urban Dry Islands Effect in Beijing: Evidence from Satellite and Ground Observations
Authors: Luan Qingzu , Cao Qian , Huang Lei , Liu Yupeng , Wang Fengjiao
Published: February 2022

Urbanization may exert a strong influence on both near-surface and atmospheric moisture. However, studies on the effect of urbanization on atmospheric moisture using remotely sensed observations have been infrequently conducted. To fill this research gap, we used remotely sensed and station-based observations to calculate urban–rural differences in total-column, near-surface, and atmospheric moisture in the Beijing metropolis. Multiple humidity indicators were selected, including precipitation water vapor, relative humidity, water vapor pressure, and absolute humidity. Results showed that both the total-column and near-surface urban dry islands (UDIs) were detected in Beijing. A significant decreasing trend of the near-surface UDIs intensity (i.e., urban minus rural) was found, which was closely related to the expansion of built-up areas (i.e., the moisture reduction in the newly urbanized areas). However, the trend of the total-column UDIs intensity was not significant. A further investigation of the atmospheric urban–rural moisture differences showed that the UDIs effect mainly existed in the near-surface layer, while an urban wet island was found above the 950 hPa pressure level, probably due to enhanced convergence in urban areas. Generally, the UDIs intensity was the strongest in the hot, wet summer and the weakest in the dry, cold winter. However, the UDIs intensity represented by relative humidity was the largest in autumn and showed the strongest correlation with the expansion of built-up areas in Beijing. This study employed satellite observations to understand the UDIs effect and highlighted the significance of urbanization-induced moisture changes on and above the ground. Findings of this study provided new insights into how urbanization affected atmospheric moisture in the boundary layer and paved the way for process-based modeling studies.
An Investigation on the Morphological and Mineralogical Characteristics of Posidonius Floor Fractured Lunar Impact Crater Using Lunar Remote Sensing Data
Authors: Salem Imen Ben , Sharma Manish , Kumaresan P. R. , Karthi A. , Howari Fares M. , Nazzal Yousef , Xavier Cijo M.
Published: February 2022

Lunar floor-fractured craters (FFCs) are a distinguished type of crater found on the surface of the Moon with radial, concentric, and/or polygonal fractures. In the present study, we selected the Posidonius FCC to explore the mineralogy, morphology and tectonic characteristics using remote sensing datasets. The Posidonius crater is vested with a wide moat of lava separating the crater rim inner wall terraces from the fractured central floor. Lunar Reconnaissance Orbiter’s (LRO) images and Digital Elevation Model (DEM) data were used to map the tectonics and morphology of the present study. The Moon Mineralogy Mapper (M3) data of Chandrayaan-1 were used to investigate the mineralogy of the region through specified techniques such as integrated band depth, band composite and spectral characterization. The detailed mineralogical analysis indicates the noritic-rich materials in one massif among four central peak rings and confirm intrusion (mafic pluton). Spectral analysis from the fresh crater of the Posidonius moat mare unit indicates clinopyroxene pigeonite in nature. Integrated studies of the mineralogy, morphology and tectonics revealed that the study region belongs to the Class-III category of FFCs. The lithospheric loading by adjacent volcanic load (Serenitatis basin) generates a stress state and distribution of the fracture system.
Design of CGAN Models for Multispectral Reconstruction in Remote Sensing
Authors: Rodríguez-Suárez Brais , Quesada-Barriuso Pablo , Argüello Francisco
Published: February 2022

Multispectral imaging methods typically require cameras with dedicated sensors that make them expensive. In some cases, these sensors are not available or existing images are RGB, so the advantages of multispectral processing cannot be exploited. To solve this drawback, several techniques have been proposed to reconstruct the spectral reflectance of a scene from a single RGB image captured by a camera. Deep learning methods can already solve this problem with good spectral accuracy. Recently, a new type of deep learning network, the Conditional Generative Adversarial Network (CGAN), has been proposed. It is a deep learning architecture that simultaneously trains two networks (generator and discriminator) with the additional feature that both networks are conditioned on some sort of auxiliary information. This paper focuses the use of CGANs to achieve the reconstruction of multispectral images from RGB images. Different regression network models (convolutional neuronal networks, U-Net, and ResNet) have been adapted and integrated as generators in the CGAN, and compared in performance for multispectral reconstruction. Experiments with the BigEarthNet database show that CGAN with ResNet as a generator provides better results than other deep learning networks with a root mean square error of 316 measured over a range from 0 to 16,384.
How to Boost Close-Range Remote Sensing Courses Using a Serious Game: Uncover in a Fun Way the Complexity and Transversality of Multi-Domain Field Acquisitions
Authors: Avanthey Loïca , Beaudoin Laurent
Published: February 2022

Close-range remote sensing, and more particularly, its acquisition part that is linked to field robotics, is at the crossroads of many scientific and engineering fields. Thus, it takes time for students to acquire the solid foundations needed before practicing on real systems. Therefore, we are interested in a means that allow students without prerequisites to quickly appropriate the fundamentals of this interdisciplinary field. For this, we adapted a haggle game to the close-range remote sensing theme. In this article, we explain the mechanics that serve our educational purposes. We have used it, so far, for four academic years with hundreds of students. The experience was assessed through quality surveys and quizzes to calculate success indicators. The results show that the serious game is well appreciated by the students. It allows them to better structure information and acquire a good global vision of multi-domain acquisition and data processing in close-range remote sensing. The students are also more involved in the rest of the lessons; all of this helps to facilitate their learning of the theoretical parts. Thus, we were able to shorten the time before moving on to real practice by replacing three lesson sessions with one serious game session, with an increase in mastering fundamental skills. The designed serious game can be useful for close-range remote sensing teachers looking for an effective starting lesson. In addition, teachers from other technical fields can draw inspiration from the creation mechanisms described in this article to create their own adapted version. Such a serious game is also a good asset for selecting promising students in a recruitment context.
A Comparative Study of Convolutional Neural Networks and Conventional Machine Learning Models for Lithological Mapping Using Remote Sensing Data
Authors: Shirmard Hojat , Farahbakhsh Ehsan , Heidari Elnaz , Beiranvand Pour Amin , Pradhan Biswajeet , Müller Dietmar , Chandra Rohitash
Published: February 2022

Lithological mapping is a critical aspect of geological mapping that can be useful in studying the mineralization potential of a region and has implications for mineral prospectivity mapping. This is a challenging task if performed manually, particularly in highly remote areas that require a large number of participants and resources. The combination of machine learning (ML) methods and remote sensing data can provide a quick, low-cost, and accurate approach for mapping lithological units. This study used deep learning via convolutional neural networks and conventional ML methods involving support vector machines and multilayer perceptron to map lithological units of a mineral-rich area in the southeast of Iran. Moreover, we used and compared the efficiency of three different types of multispectral remote-sensing data, including Landsat 8 operational land imager (OLI), advanced spaceborne thermal emission and reflection radiometer (ASTER), and Sentinel-2. The results show that CNNs and conventional ML methods effectively use the respective remote-sensing data in generating an accurate lithological map of the study area. However, the combination of CNNs and ASTER data provides the best performance and the highest accuracy and adaptability with field observations and laboratory analysis results so that almost all the test data are predicted correctly. The framework proposed in this study can be helpful for exploration geologists to create accurate lithological maps in other regions by using various remote-sensing data at a low cost.
Co-Registration Methods and Error Analysis for Four Decades (1979–2018) of Glacier Elevation Changes in the Southern Patagonian Icefield
Authors: Vacaflor Paulina , Lenzano Maria Gabriela , Vich Alberto , Lenzano Luis
Published: February 2022

The main goal of this paper is to compare two co-registration methods for geodetic mass balance (GMB) calculation in 28 glaciers making up the Upper Santa Cruz River basin, Southern Patagonian Icefield (SPI), from 1979 to 2018. For this purpose, geospatial data have been used as primary sources: Hexagon KH-9, ASTER, and LANDSAT optical images; SRTM digital radar elevation model; and ICESat elevation profiles. After the analyses, the two co-registration methods, namely M1, based on horizontal displacements and 3D shift vectors, and M2, based on three-dimensional transformations, turned out to be similar. The errors in the GMB were analyzed through a k index that considers, among other variables, the error in elevation change by testing four interpolation methods for filling gaps. We found that, in 63% of the cases, the relative error in elevation change contributes 90% or more to k index. The GMB throughout our study area reported that a loss value of −1.44 ± 0.15 m w. e. a−1 (−3.0 Gt a−1) and an ice thinning median of −1.38 ± 0.11 m a−1 occurred within the study period. The glaciers that showed the most negative GMB values were Upsala, with an annual elevation change median of −2.07 ± 0.18 m w. e. a−1, and Ameghino, with −2.31 ± 0.22 m w. e. a−1.
The Coastal El Niño Event of 2017 in Ecuador and Peru: A Weather Radar Analysis
Authors: Rollenbeck Rütger , Orellana-Alvear Johanna , Bendix Jörg , Rodriguez Rodolfo , Pucha-Cofrep Franz , Guallpa Mario , Fries Andreas , Célleri Rolando
Published: February 2022

The coastal regions of South Ecuador and Peru belong to the areas experiencing the strongest impact of the El Niño Southern Oscillation phenomenon. However, the impact and dynamic development of weather patterns during those events are not well understood, due to the sparse observational networks. In spite of neutral to cold conditions after the decaying 2015/16 El Niño in the central Pacific, the coastal region was hit by torrential rainfall in 2017 causing floods, erosion and landslides with many fatalities and significant damages to infrastructure. A new network of X-band weather radar systems in South Ecuador and North Peru allowed, for the first time, the spatio-temporally high-resolution monitoring of rainfall dynamics, also covering the 2017 event. Here, we compare this episode to the period 2014–2018 to point out the specific atmospheric process dynamics of this event. We found that isolated warming of the Niño 1 and 2 region sea surface temperature was the initial driver of the strong rainfall, but local weather patterns were modified by topography interacting with the synoptic situation. The high resolution radar data, for the first time, allowed to monitor previously unknown local spots of heavy rainfall during ENSO-related extreme events, associated with dynamic flow convergence initiated by low-level thermal breezes. Altogether, the coastal El Niño of 2017, at the same time, caused positive rainfall anomalies in the coastal plain and on the eastern slopes of the Andes, the latter normally associated only with La Niña events. Thus, the 2017 event must be attributed to the La Niña Modoki type.
Acknowledgment to Reviewers of Ruminants in 2021
Authors:   Ruminants Editorial Office
Published: February 2022

Rigorous peer-reviews are the basis of high-quality academic publishing [...]
DOA Estimation Method Based on Improved Deep Convolutional Neural Network
Authors: Zhao Fangzheng , Hu Guoping , Zhan Chenghong , Zhang Yule
Published: February 2022

For the multi-target DOA estimation problem of uniform linear arrays, this paper proposes a DOA estimation method based on the deep convolution neural network. The algorithm adopts the deep convolutional neural network, and the DOA estimation problem of the array signal is transformed into the inverse mapping problem of the array output covariance matrix to a binary sequence in which “1” indicates that there is a target incident in the corresponding angular direction at that position. The upper triangular array of the discrete covariance matrix is used as the data input to realize the DOA estimation of multiple sources. The simulation results show that the DOA estimation accuracy of the proposed algorithm is significantly better than that of the typical super-resolution estimation algorithm under the conditions of low SNR and small snapshot. Under the conditions of high SNR and large snapshot, the estimation accuracy of the proposed algorithm is basically the same as those of the MUSIC algorithm, ESPRIT algorithm, and ML algorithm, which are better than that of the deep fully connected neural network. The analysis of the simulation results shows that the algorithm is effective, and the time and space complexity can be further reduced by replacing the square array with the upper triangular array as the input.
Optimal Energy Scheduling Based on Jaya Algorithm for Integration of Vehicle-to-Home and Energy Storage System with Photovoltaic Generation in Smart Home
Authors: Wang Min , Abdalla Modawy Adam Ali
Published: February 2022

With the emerging of the smart grid, it has become easier for consumers to control their consumption. The efficient use of the integration of renewable energy sources with electric vehicle (EV) and energy storage systems (ESSs) in the smart home is a popular choice to reduce electricity costs and improve the stability of the grid. Therefore, this study presents optimal energy management based on the Jaya algorithm for controlling energy flow in the smart home that contains photovoltaic generation (PV), integrated with ESS and EV. The objective of the proposed energy management is to reduce electricity cost while meeting the household load demand and energy requirement for the EV trip distance. By using the Jaya algorithm, the modes of home-to-vehicle (H2V) and vehicle-to-home (V2H) are controlled, in addition to controlling the purchase of energy from the grid and sale of the energy to the grid from surplus PV generation and ESS. Before EV participation in the V2H process, the amount of energy stored in the electric vehicle battery will be verified to be more than the energy amount required for the remaining EV trip to ensure that the required energy for the remaining EV trip is satisfied. Simulation results highlight the performance of the optimal energy scheduling to achieve the reduction of the daily electricity cost and meeting of load demand and EV energy required. The simulation results prove that optimal energy management solutions can be found with significant electricity cost savings. In addition, Jaya is compared with the particle swarm optimization (PSO) algorithm in order to evaluate its performance. Jaya outperforms PSO in terms of achieving optimal energy management objectives.
Resource Allocation in Spectrum Access System Using Multi-Objective Optimization Methods
Authors: Abbass Waseem , Hussain Riaz , Frnda Jaroslav , Abbas Nasim , Javed Muhammad Awais , Malik Shahzad A.
Published: February 2022

The paradigm of dynamic shared access aims to provide flexible spectrum usage. Recently, Federal Communications Commission (FCC) has proposed a new dynamic spectrum management framework for the sharing of a 3.5 GHz (3550–3700 MHz) federal band, called a citizen broadband radio service (CBRS) band, which is governed by spectrum access system (SAS). It is the responsibility of SAS to manage the set of CBRS-SAS users. The set of users are classified in three tiers: incumbent access (IA) users, primary access license (PAL) users and the general authorized access (GAA) users. In this article, dynamic channel assignment algorithm for PAL and GAA users is designed with the goal of maximizing the transmission rate and minimizing the total cost of GAA users accessing PAL reserved channels. We proposed a new mathematical model based on multi-objective optimization for the selection of PAL operators and idle PAL reserved channels allocation to GAA users considering the diversity of PAL reserved channels’ attributes and the diversification of GAA users’ business needs. The proposed model is estimated and validated on various performance metrics through extensive simulations and compared with existing algorithms such as Hungarian algorithm, auction algorithm and Gale–Shapley algorithm. The proposed model results indicate that overall transmission rate, net cost and data-rate per unit cost remain the same in comparison to the classical Hungarian method and auction algorithm. However, the improved model solves the resource allocation problem approximately up to four times faster with better load management, which validates the efficiency of our model.
A Wearable System Based on Multiple Magnetic and Inertial Measurement Units for Spine Mobility Assessment: A Reliability Study for the Evaluation of Ankylosing Spondylitis
Authors: Martínez-Hernández Adriana , Perez-Lomelí Juan S. , Burgos-Vargas Ruben , Padilla-Castañeda Miguel A.
Published: February 2022

Spinal mobility assessment is essential for the diagnostic of patients with ankylosing spondylitis. BASMI is a routine clinical evaluation of the spine; its measurements are made with goniometers and tape measures, implying systematic errors, subjectivity, and low sensitivity. Therefore, it is crucial to develop better mobility assessment methods. The design, implementation, and evaluation of a novel system for assessing the entire spine’s motion are presented. It consists of 16 magnetic and inertial measurement units (MIMUs) communicated wirelessly with a computer. The system evaluates the patient’s movements by implementing a sensor fusion of the triaxial gyroscope, accelerometer, and magnetometer signals using a Kalman filter. Fifteen healthy participants were assessed with the system through six movements involving the entire spine to calculate continuous kinematics and maximum range of motion (RoM). The intrarater reliability was computed over the observed RoM, showing excellent reliability levels (intraclass correlation >0.9) in five of the six movements. The results demonstrate the feasibility of the system for further clinical studies with patients. The system has the potential to improve the BASMI method. To the best of our knowledge, our system involves the highest number of sensors, thus providing more objective information than current similar systems.
Anne’s Secret: Teaching Children to Protect Themselves from Child Sexual Abuse Using Animated Cartoons
Authors: Rueda Pilar , Ferragut Marta , Cerezo M. Victoria , Calvo Isabel , Ortiz-Tallo Margarita
Published: February 2022

This paper presents an innovative methodology for the prevention of child sexual abuse (CSA): animated cartoons. CSA is a political, social, educational, and psychological problem that affects many children according to the World Health Organization (WHO). That is why prevention becomes an essential tool for the protection of children. Children are increasingly accustomed to the use of digital media, both for learning and for entertainment. In response to this evolution on how information is transmitted and according to the tradition that cartoons have always had of transmitting values such as friendship, ecology, or solidarity, a 15-minute long video was developed. This video is an animated cartoon, presenting a story. It is composed of music, six friends, and three fantasy characters, and it was designed for children to learn resources to ask for help in case they are suffering CSA. The video is accompanied by a workbook through which both children and adults reinforce what they have learned in the cartoons and learn additional keys for their protection. Data from the first pilot studies carried out to test the effectiveness of this methodology are also presented, with promising results.
Tactical Masters Athletes: BMI Index Classifications
Authors: Keefer Marc , Walsh Joe , Adams Kent , Climstein Mike , Harris Chad , DeBeliso Mark
Published: February 2022

Understanding the nexus between aging, physical activity, and obesity has been a source of ongoing investigation. A considerable amount of research has focused on Masters athletes in this regard, suggesting a beneficial relationship between Masters sport participation and a healthy body mass index (BMI). Some consider Active Duty military personnel as tactical athletes. As such, it is of interest to determine if aging Active Duty military personnel (or Masters Tactical Athletes) might have a similar BMI as other Masters athletes (MA). As such, this investigation examined previously recorded data of Active Duty Enlisted United States Marines (n = 402, male, 46–50 years old). The BMI of the Marines was stratified into categories of: underweight, normal, overweight, and obese. The Marines obesity prevalence was compared to US adult males (40–59 years) as well as male North American MA who competed at the 2009 Sydney World Masters Games. The Marines obesity prevalence was significantly lower than US adult males (p < 0.001) and those MA that competed in softball (p < 0.001); however, it was similar to MA that competed in football, track/field, swimming, and volleyball (p > 0.05). The average Marine BMI = 26.7 kg/m2 was similar to MA who competed in football, swimming, and volley ball (p > 0.05); however, it was higher than MA who competed in track/field (p < 0.05) and lower than MA who played softball (p < 0.05). It should be noted that the average BMI for the Marines and all MA sport categories were classified as being overweight. Within the parameters of this investigation, Tactical MA (i.e., aging US Marines) enjoy a similar beneficial BMI as other North American MA.
All-NBA Teams’ Selection Based on Unsupervised Learning
Authors: Silva João Vítor Rocha da , Rodrigues Paulo Canas
Published: February 2022

All-NBA Teams’ selections have great implications for the players’ and teams’ futures. Since contract extensions are highly related to awards, which can be seen as indexes that measure a players’ production in a year, team selection is of mutual interest for athletes and franchises. In this paper, we are interested in studying the current selection format. In particular, this study aims to: (i) identify the factors that are taken into consideration by voters when choosing the three All-NBA Teams; and (ii) suggest a new selection format to evaluate players’ performances. Average game-related statistics of all active NBA players in regular seasons from 2013-14 to 2018-19, were analyzed using LASSO (Logistic) Regression and Principal Component Analysis (PCA). It was possible: (i) to determine an All-NBA player profile; (ii) to determine that this profile can cause a misrepresentation of players’ modern and versatile gameplay styles; and (iii) to suggest a new way to evaluate and select players, through PCA. As the results of this paper a model is presented that may help not only the NBA to better evaluate players, but any basketball league; it also may be a source to researchers that aim to investigate player performance, development, and their impact over many seasons.
Spatio-Temporal Analysis of Climatic Variables in the Munneru River Basin, India, Using NEX-GDDP Data and the REA Approach
Authors: Buri Eswar Sai , Keesara Venkata Reddy , Loukika Kotapati Narayana , Sridhar Venkataramana
Published: February 2022

For effective management practices and decision-making, the uncertainty associated with Regional Climate Models (RCMs) and their scenarios need to be assessed in the context of climate change. The present study analyzes the various uncertainties in the precipitation and temperature datasets of NASA Earth Exchange Global Daily Downscaled Projections (NEX-GDDP) under Representative Concentrative Pathways (RCPs) 4.5 and 8.5 over the Munneru river basin, in India, using the Reliable Ensemble Averaging (REA) method. From the available 21 RCMs, the top five ranked are ensembled and bias-corrected at each grid using the non-parametric quantile mapping method for the precipitation and temperature datasets. The spatio-temporal variations in precipitation and temperature data for the future periods, i.e., 2021–2039 (near future), 2040–2069 (mid future) and 2070–2099 (far future) are analyzed. For the period 2021–2099, annual average precipitation increases by 233 mm and 287 mm, respectively, the in RCP 4.5 and RCP 8.5 scenarios when compared to the observed period (1951–2005). In both the RCP 4.5 and RCP 8.5 scenarios, the annual average maximum temperature rises by 1.8 °C and 1.9 °C, respectively. Similarly, the annual average minimum temperature rises by 1.8 °C and 2.5 °C for the RCP 4.5 and RCP 8.5 scenarios, respectively. The spatio-temporal climatic variations for future periods obtained from high-resolution climate model data aid in the preparation of water resource planning and management options in the study basin under the changing climate. The methodology developed in this study can be applied to any other basin to analyze the climatic variables suitable for climate change impact studies that require a finer scale, but the biases present in the historical simulations can be attributed to uncertainties in the estimation of climatic variable projections. The findings of the study indicate that NEX-GDDP datasets are in good agreement with IMD datasets on monthly scales but not on daily scales over the observed period, implying that these data should be scrutinized more closely on daily scales, especially when utilized in impact studies.
Ecotoxicity of Concrete Containing Fine-Recycled Aggregate: Effect on Photosynthetic Pigments, Soil Enzymatic Activity and Carbonation Process
Authors: Mariaková Diana , Mocová Klára Anna , Pešta Jan , Fořtová Kristina , Tripathi Bhavna , Pavlů Tereza , Hájek Petr
Published: February 2022

Recycling of materials such as masonry or concrete is one of the suitable ways to reduce amount of disposed construction and demolition waste (CDW). However, the environmental safety of products containing recycled materials must be guaranteed. To verify overall environmental benefits of recycled concrete, this work considers ecotoxicity of recycled concrete, as well as potential environmental impacts of their life cycle. Moreover, impacts related with carbonation of concrete is considered in terms of durability and influence of potential CO2 uptake. Concrete containing fine recycled aggregate from two different sources (masonry and concrete) were examined experimentally at the biochemical level and compared with reference samples. Leaching experiments are performed in order to assess physicochemical properties and aquatic ecotoxicity using water flea, freshwater algae and duckweed. The consequences, such as effects of material on soil enzymatic activity (dehydrogenase activity), photosynthetic pigments (chlorophylls and carotenoids), and the carbonation process, are verified in the laboratory and included in the comparison with the theoretical life cycle assessment. As a conclusion, environmental safety of recycled concrete was verified, and its overall potential environmental impact was lower in comparison with reference concrete.
Reviewing Interference for All Modes of Products for Failure Avoidance
Authors: Iino Kenji , Nakao Masayuki
Published: February 2022

Industrial products today often go through reuse or recycle for extended times and sometimes are even taken through different environments. Our product development needs to be more sustainable than ever to meet such needs. Insufficient sustainability often leads to exposing interferences that the designer overlooked and causes accidents like the three cases we discuss in this paper. Axiomatic design is a tool to aid the designer in identifying design interferences during the early design stage so the designer can remove them and create higher values through sustained use of the product. One of the three failures we discuss is a new safety feature of locking the handle shaft of a parked bicycle that accidentally kicked in while riding. The design posed a threat to the sustainability of society. The second, an automated train that started in the wrong direction and collided with the bumping post, causing societal and economic damages. The third is about conflicting functions of a part that the designers overlooked in the Fukushima Nuclear Power Plant-1, Unit-1. This disaster was and still is a threat to the social, economic, and environmental sustainability. Despite no direct fatalities, these accidents all caused serious injuries, and in the case of Fukushima, many indirect deaths. Squeezing out flaws from our designs is important in protecting people, the economy, and the environment now and for our future for sustainability. The designer should carry out failure analysis for all parts of a product in all modes of operation.
Adult Climate Change Education Advances Learning, Self-Efficacy, and Agency for Community-Scale Stewardship
Authors: Nelson Sarah-Mae , Ira Greg , Merenlender Adina M.
Published: February 2022

Education per se does not necessarily foster positive environmental behaviors; rather, a complex assemblage of influences including social integration, discovering shared values, strengthening environmental identity, self-efficacy, and agency is needed to foster environmental stewardship. We examine the participant outcomes from a new adult climate education and service course, which is delivered by local organizations. The UC Climate Stewards certification course includes relationship building, social-emotional learning, climate science, climate communication, monitoring resilience, and how to take community-scale action. Based on results from ~154 participants, we observed significant improvement in self-efficacy, with confidence to help protect communities increasing from x¯ = 3.59 (3 is neutral) to x¯ 4.32 (4 is agree) (p < 0.00). The importance of doing something or taking action about climate change appears to be a value that was strongly held prior to taking the course and aligns with motivations for becoming a certified Climate Steward; hence, it only slightly increased from (x¯ = 4.25) to (x¯ = 4.57) (p < 0.00). Climate Stewards’ feeling of competency in talking about the subject increased (from x¯ 3.05 before to x¯ = 4.24 after, p < 0.00, N = 111). Finally, we examine the community-scale stewardship taken by the Climate Steward volunteers, from information provided through self-reporting, and explore additional approaches to researching pathways from education to agency.
The Oil Palm Governance: Challenges of Sustainability Policy in Indonesia
Authors: Putri Eka Intan Kumala , Dharmawan Arya Hadi , Hospes Otto , Yulian Bayu Eka , Amalia Rizka , Mardiyaningsih Dyah Ita , Kinseng Rilus A. , Tonny Fredian , Pramudya Eusebius Pantja , Rahmadian Faris , Suradiredja Diah Y.
Published: February 2022

Nowadays, Indonesian palm oil faces agrarian, environmental, and social issues and has been subject to sharp criticism from the international community for many years. To answer this problem, the Indonesian government implemented a strategy through certification which ensured the achievement of sustainability standards, especially on the upstream side of the palm oil supply chain. The implementation of Indonesian Sustainable Palm Oil (ISPO) was an ultimate instrument that applied in particular to smallholders oriented towards managing land legal issues, plantation business licenses, plant seeds, and environmental management and to farmer organizations at the local level. However, this process faced quite complex challenges in the form of structural barriers that are very constraining. This study revealed the occurrence of the phenomenon of hollow governance when regulations are absent or collide with each other. The study also revealed institutional power and multi-level governance that made the governance process ineffective or counterproductive. With a qualitative approach to research conducted in three important palm oil provinces of Indonesia, this article aims to look at the issues of oil palm governance a bit more comprehensively. The study conceptualized what was referred to as low-functioning governance to describe how weak the institutions, organizations, actors, and resources are that support ISPO implementation, especially at the regional and local levels. This paper suggests improving and strengthening the ISPO oil palm governance if Indonesian palm oil companies and smallholders want to gain better credibility on sustainability abroad.
Analysis on Dynamic Evolution of the Cost Risk of Prefabricated Building Based on DBN
Authors: Ye Mengwei , Wang Junwu , Si Xiang , Zhao Shiman , Huang Qiyun
Published: February 2022

Prefabricated building constitutes the development trend of the construction industry in the future. However, many uncertainties in the construction process will surely lead to a higher cost. Therefore, it is necessary to study the cost risk evolution and transfer mechanism in the implementation process of this project. A dynamic evolution model for the cost risk of prefabricated buildings has been established in this paper. First of all, a matrix for cost risk of prefabricated buildings was established based on the WSR (Wuli-Shili-Renli) model, and all risk factors in the implementation stage were classified in accordance with the WSR principle. Second, a DBN-based dynamic evolution model was established based on the risk matrix, and the structure and node parameters of the Dynamic Bayesian Network were determined with the aid of the K2 structure learning algorithm and parameter learning method. In view of the probability change process of risks over time, the dynamic evolution path of risks was predicted in different cases through causal reasoning and diagnostic reasoning. Eventually, the model was applied into construction projects. The research results show that: because prefabricated components need to be made by prefabricated component factories, the management systems of prefabricated component factories are usually not perfect, and the probability of management risks is higher. The occurrence of management risks not only has an impact on other risks at the current time node, but also causes other risks to occur in the subsequent transportation and construction phases at the next moment, which eventually leads to the occurrence of risk events.
Heading for Tomorrow: Resilience Strategies for Post-COVID-19 Grocery Supply Chains
Authors: Prataviera Lorenzo Bruno , Creazza Alessandro , Melacini Marco , Dallari Fabrizio
Published: February 2022

Supply chain resilience is a critical capability needed to compete in the current turbulent and unpredictable business environment, but many companies still tend to underestimate its relevance. In the wake of the COVID-19 pandemic, understanding which supply chain impacts influence the policies and actions undertaken when resilience is concerned is important. This study investigated the relationships between the impacts experienced at the different supply chain tiers during the pandemic, and explored which impacts could drive perceptions towards developing resilience strategies in the future. A survey instrument was developed adopting a mid-range approach, targeting manufacturers active in the Italian grocery supply chain. Data were analysed using partial least square structural equation modelling (PLS-SEM). Results showed that source-related impacts deeply affect make- and delivery-related impacts, and make-related impacts mainly influence the perceptions about future resilience strategies. In fact, manufacturers appear to be primarily interested in those strategies ensuring the continuity of their intrinsic operations. The study could inform theory and practice about companies’ decisions towards the adoption of certain approaches. Also, it highlights promising research avenues related to deepening understanding of how perceptions could predict future intentions to engage in protective actions to adequately cope with potential future disruptions.
Exploring COVID-19 Challenges and Coping Mechanisms for SMEs in the South African Entrepreneurial Ecosystem
Authors: Fubah Clavis Nwehfor , Moos Menisha
Published: February 2022

Globally, COVID-19 has caused significant damage, including business closures and changes in how entrepreneurial activities are performed. The pandemic has spawned a slew of publications with the majority thereof being editorials, commentaries, and concept notes. This implies a lack of empirical evidence on the pandemic. Therefore, the purpose of this paper was to explore the COVID-19 challenges and coping mechanisms for small and medium-sized enterprises (SMEs) in South Africa’s entrepreneurial ecosystem. Data for the study were collected from 15 SME owners through semi-structured interviews using a generic qualitative research method. The findings revealed that the SME COVID-19 challenges included lockdown restrictions, customer loss, lack of government support, and scarcity of raw materials. The coping mechanisms used by the SMEs were having a positive entrepreneurial mindset followed by reduced service prices and the retrenchments of employees. Theoretically, the study contributes to the scarce empirical evidence on COVID-19 challenges and coping mechanisms for SMEs in the South African context; to the available literature in the entrepreneurial ecosystem context and to the world at large. Practically, it is recommended that during crises, businesses should network with one another to remain operational and, owing to e-commerce, they are encouraged to have an online presence.
The Use of a Simplified Carbon Footprint Tool for Organic Waste Managers: Pros and Cons
Authors: Mancini Eliana , Negro Viviana , Mainero Davide , Raggi Andrea
Published: February 2022

Given that the pressure of climate change action on companies is increasing, it is recommended to measure the improvement of mitigation activities in terms of GHG emissions. This paper aims to highlight the still-open aspects that characterise simplified GHG accounting tools, starting from the outcomes of a case study. This study was performed using a simplified Italian software for the CO2 eq accounting of composting and anaerobic digestion, two mitigation activities that contribute an important share of global GHG emissions reduction. The tool is based on the life-cycle thinking approach. It has been applied to an Italian company that treats the organic fraction of municipal solid waste. The tool analysis has made it possible to stress several issues that are currently the object of debate in the literature, for example, the trade-off between the flexibility of the software and its user friendliness or the multifunctionality issues and their different interpretations. However, focusing on just one impact category, i.e., climate change, may lead to an incomplete picture of the overall environmental performance of the process analysed. Therefore, this tool could be improved by including other impact categories, such as eutrophication and acidification, which may be affected by the studied activities.