bluuebunny/crossref_metadata_2025 huggingface dataset:
Influences of Chemical Functionalities on Crystal Structures and Electrochemical Properties of Dihydro-benzoxazine Dimer Derivatives
Authors: Suetrong Natapol , Chansaenpak Kantapat , Impeng Sarawoot , Pinyou Piyanut , Blay Vincent , Blay-Roger Rubén , Lisnund Sireerat , Kanjanaboos Pongsakorn , Hanlumyuang Yuranan , Wannapaiboon Suttipong , Wattanathana Worawat
Published: August 2021

Dihydro-1,3,2H-benzoxazine dimer derivatives or dihydro-benzoxazine dimers are a class of compounds typically prepared by ring-opening reactions between dihydro-benzoxazines and phenols. Dihydro-benzoxazine dimers act as chelating agents for several transition and rare-earth cations. To better understand the chelating properties, it is necessary to examine their structural features and electrochemical characteristics thoroughly. However, the electrochemical properties of dihydro-benzoxazine dimers have not been tremendously examined. Herein, eight derivatives of dihydro-benzoxazine dimers possessing different substituents on the benzene ring and the tertiary-amine nitrogen were synthesized as model compounds to investigate their influences on crystal structures and electrochemical properties. The crystal structure of the dihydro-benzoxazine dimer, namely 2,2′-(cyclohexylazanediyl)bis(methylene)bis(4-methoxyphenol) (7), is identified for the first time and further used to compare with the crystal structures of other derivatives reported previously. For all the derivatives, intermolecular O–H⋅⋅⋅O hydrogen bonds are the significant interactions to hold the crystal packing of (7) and also the other derivatives. Hirshfeld surface analyses confirm the presence of intermolecular O–H⋅⋅⋅O hydrogen bonds. Redox behavior of the eight dihydro-benzoxazine dimers was studied by cyclic voltammetry. An oxidation peak observed at 0.25–0.47 V corresponds to the oxidation of the phenolic –OH group to the phenoxonium intermediate. The shift in the electrochemical peak positions is due to the different abilities of the substituents to stabilize the phenoxonium cation intermediate. The stabilizing power is ranged in the following order: methoxy > dimethyl > ethyl ≈ methyl, and N-cyclohexyl > N-methyl. Thus, the derivative (7), which contains both the methoxy and N-cyclohexyl groups, has the lowest oxidation potential. Our work elucidates the effect of the substituents on the crystal structures and electrochemical properties of the dihydro-benzoxazine dimers.
Conserved Mechanisms, Novel Anatomies: The Developmental Basis of Fin Evolution and the Origin of Limbs
Authors: Cass Amanda N. , Elias Ashley , Fudala Madeline L. , Knick Benjamin D. , Davis Marcus C.
Published: August 2021

The transformation of paired fins into tetrapod limbs is one of the most intensively scrutinized events in animal evolution. Early anatomical and embryological datasets identified distinctive morphological regions within the appendage and posed hypotheses about how the loss, gain, and transformation of these regions could explain the observed patterns of both extant and fossil appendage diversity. These hypotheses have been put to the test by our growing understanding of patterning mechanisms that regulate formation of the appendage axes, comparisons of gene expression data from an array of phylogenetically informative taxa, and increasingly sophisticated and elegant experiments leveraging the latest molecular approaches. Together, these data demonstrate the remarkable conservation of developmental mechanisms, even across phylogenetically and morphologically disparate taxa, as well as raising new questions about the way we view homology, evolutionary novelty, and the often non-linear connection between morphology and gene expression. In this review, we present historical hypotheses regarding paired fin evolution and limb origins, summarize key aspects of central appendage patterning mechanisms in model and non-model species, address how modern comparative developmental data interface with our understanding of appendage anatomy, and highlight new approaches that promise to provide new insight into these well-traveled questions.
Common Biochemical and Magnetic Resonance Imaging Biomarkers of Early Knee Osteoarthritis and of Exercise/Training in Athletes: A Narrative Review
Authors: Martel-Pelletier Johanne , Tardif Ginette , Paiement Patrice , Pelletier Jean-Pierre
Published: August 2021

Knee osteoarthritis (OA) is the most common joint disease of the world population. Although considered a disease of old age, OA also affects young individuals and, more specifically among them, those practicing knee-joint-loading sports. Predicting OA at an early stage is crucial but remains a challenge. Biomarkers that can predict early OA development will help in the design of specific therapeutic strategies for individuals and, for athletes, to avoid adverse outcomes due to exercising/training regimens. This review summarizes and compares the current knowledge of fluid and magnetic resonance imaging (MRI) biomarkers common to early knee OA and exercise/training in athletes. A variety of fluid biochemical markers have been proposed to detect knee OA at an early stage; however, few have shown similar behavior between the two studied groups. Moreover, in endurance athletes, they are often contingent on the sport involved. MRI has also demonstrated its ability for early detection of joint structural alterations in both groups. It is currently suggested that for optimal forecasting of early knee structural alterations, both fluid and MRI biomarkers should be analyzed as a panel and/or combined, rather than individually.
An Incidental Pancreatic Finding at 18F-Choline PET/CT: Chronic Mass-Forming Pancreatitis
Authors: Evangelista Laura , De Pellegrin Alessandro , Girometti Rossano , Cassarino Gianluca , Giacomuzzi Francesco , Rensi Marco
Published: August 2021

We present a case of a chronic mass-forming pancreatitis (CMFP) detected by 18F-choline (FCH) PET/CT in a male affected by prostate cancer. FCH PET/CT scan showed a focal uptake in the uncinate process of the pancreas, later diagnosed as a CMFP at biopsy. Although the physiological distribution of FCH in the pancreas, a careful interpretation of the images in this area is warranted.
Radiomics Nomogram Based on Radiomics Score from Multiregional Diffusion-Weighted MRI and Clinical Factors for Evaluating HER-2 2+ Status of Breast Cancer
Authors: Li Chunli , Yin Jiandong
Published: August 2021

This study aimed to establish and validate a radiomics nomogram using the radiomics score (rad-score) based on multiregional diffusion-weighted imaging (DWI) and apparent diffusion coefficient (ADC) features combined with clinical factors for evaluating HER-2 2+ status of breast cancer. A total of 223 patients were retrospectively included. Radiomic features were extracted from multiregional DWI and ADC images. Based on the intratumoral, peritumoral, and combined regions, three rad-scores were calculated using the logistic regression model. Independent parameters were selected among clinical factors and combined rad-score (com-rad-score) using multivariate logistic analysis and used to construct a radiomics nomogram. The performance of the nomogram was evaluated using calibration, discrimination, and clinical usefulness. The areas under the receiver operator characteristic curve (AUCs) of intratumoral and peritumoral rad-scores were 0.824/0.763 and 0.794/0.731 in the training and validation cohorts, respectively. Com-rad-score achieved the highest AUC (0.860/0.790) among three rad-scores. ER status and com-rad-score were selected to establish the nomogram, which yielded good discrimination (AUC: 0.883/0.848) and calibration. Decision curve analysis demonstrated the clinical value of the nomogram in the validation cohort. In conclusion, radiomics nomogram, including clinical factors and com-rad-score, showed favorable performance for evaluating HER-2 2+ status in breast cancer.
A Novel Hybrid Gradient-Based Optimizer and Grey Wolf Optimizer Feature Selection Method for Human Activity Recognition Using Smartphone Sensors
Authors: Helmi Ahmed Mohamed , Al-qaness Mohammed A. A. , Dahou Abdelghani , Damaševičius Robertas , Krilavičius  Tomas , Elaziz Mohamed Abd
Published: August 2021

Human activity recognition (HAR) plays a vital role in different real-world applications such as in tracking elderly activities for elderly care services, in assisted living environments, smart home interactions, healthcare monitoring applications, electronic games, and various human–computer interaction (HCI) applications, and is an essential part of the Internet of Healthcare Things (IoHT) services. However, the high dimensionality of the collected data from these applications has the largest influence on the quality of the HAR model. Therefore, in this paper, we propose an efficient HAR system using a lightweight feature selection (FS) method to enhance the HAR classification process. The developed FS method, called GBOGWO, aims to improve the performance of the Gradient-based optimizer (GBO) algorithm by using the operators of the grey wolf optimizer (GWO). First, GBOGWO is used to select the appropriate features; then, the support vector machine (SVM) is used to classify the activities. To assess the performance of GBOGWO, extensive experiments using well-known UCI-HAR and WISDM datasets were conducted. Overall outcomes show that GBOGWO improved the classification accuracy with an average accuracy of 98%.
Comprehension-Oriented Learning of Cell Biology: Do Different Training Conditions Affect Students’ Learning Success Differentially?
Authors: Becker Lukas Bernhard , Welter Virginia Deborah Elaine , Aschermann Ellen , Großschedl Jörg
Published: August 2021

Concept Mapping (CM) is a learning strategy to organize and understand complex relationships, which are particularly characteristic of the natural science subjects. Previous research has already shown that constructing concept maps can promote students’ meaningful learning in terms of deeper knowledge and its more flexible use. While researchers generally agree that students need to practice using CM successfully for learning, key parameters of effective CM training (e.g., content, structure, and duration) remain controversial. This desideratum is taken up by our study, in which three different training approaches were evaluated: a CM training with scaffolding and feedback vs. a CM training without additional elements vs. a non-CM control training. In a quasi-experimental design, we assessed the learning outcome of N = 73 university students who each had participated in one of the trainings before. Our results suggest that an extensive CM training with scaffolding and feedback is most appropriate to promote both CM competence and acquisition of knowledge. From an educational perspective, it would therefore be advisable to accept the time-consuming process of intensive practice of CM in order to enable students to adequately use of the strategy and thus facilitate meaningful learning in terms of achieving sustained learning success.
High-School Students’ Topic-Specific Epistemic Beliefs about Climate Change: An Assessment-Related Study
Authors: Yli-Panula Eija , Laakkonen Eero , Vauras Marja
Published: August 2021

This study belongs to assessment-related research and aimed to investigate Finnish high-school students’ (n = 211) topic-specific epistemic beliefs about climate change and whether the Norwegian topic-specific epistemic beliefs questionnaire (TSEBQ) was also valid among Finnish respondents. Thus, research data were not only derived from the TSEBQ but also from topic knowledge tests and students’ views on their favorite school subjects and interest in science subjects. Principal component analysis (PCA) showed that the statistical model, originally based on 49 questions, was congruent with the Norwegian four-factor model (Certification, Source, Justification and Simplicity). However, according to the reliability analysis and confirmatory factor analysis (CFA), the performance of the Simplicity factor was unclear. In CFA, the three-factor structure (without Simplicity) was supported. The effects of topic knowledge, topic interest and gender on the TSEBQ factors were examined by using hierarchical regression analysis (HRA). The TSEBQ was shown to be a reliable tool for measuring the topic-specific epistemic beliefs of Finnish students. More specifically, the results support the claim that topic-specific epistemic beliefs can be educationally and culturally bound. HRA showed that students’ topic knowledge in chemistry and biology was related to certainty of knowledge and justification for knowing. Moreover, female students performed significantly better in topic knowledge and more often planned to pursue a science career in the future.
The Assessment Evaluation Rubric: Promoting Learning and Learner-Centered Teaching through Assessment in Face-to-Face or Distanced Higher Education
Authors: Tractenberg Rochelle E.
Published: August 2021

It is common to create courses for the higher education context that accomplish content-driven teaching goals and then develop assessments (quizzes and exams) based on the target content. However, content-driven assessment can tend to support teaching- or teacher-centered instruction. Adult learning and educational psychology theories suggest that instead, assessment should be aligned with learning, not teaching, objectives. To support the alignment of assessments with instruction in higher education, the Assessment Evaluation Rubric (AER) was developed. The AER can be utilized to guide the development and evaluation/revision of assessments that are already used. The AER describes, or permits the evaluation of, four features of an assessment: its general alignment with learning goal(s), whether the assessment is intended to/effective as formative or summative, whether some systematic approach to cognitive complexity is reflected, and whether the assessment (instructions as well as results) itself is clearly interpretable. Each dimension (alignment, utility, complexity, and clarity) has four questions that can be rated as present/absent. Other rating methods can also be conceptualized for the AER’s 16 questions, depending on the user’s intent. Any instructor can use the AER to evaluate their own assessments and ensure that they—or new assessments in development—will promote learning and learner-centered teaching. As instructors shift from face-to-face toward virtual or hybrid teaching models, or as they shift online instruction (back) to face-to-face teaching, it creates an ideal opportunity to ensure that assessment is optimizing learning and is valid for instructional decision-making.
Predicting University Adjustment from Coping-Styles, Self-Esteem, Self-Efficacy, and Personality: Findings from a Survey in a Sample of Italian Students
Authors: Valenti Giusy Danila , Faraci Palmira
Published: August 2021

Starting university life requires that students learn to cope with several personal, academic, and social challenges. A wide array of variables affects how students adjust to university life. This study was aimed to investigate which factors among coping styles, self-esteem, self-efficacy, and personality traits (i.e., diligence, relational availability, mental flexibility, activity, and emotional stability) best predicted the levels of university adjustment in a sample of university freshmen (N = 204, 63% women). Data were collected using self-report instruments. Multiple regressions analyses were conducted to identify the most significant predictors of adjustment to college. Our findings reported that self-efficacy, task-, and emotion-oriented coping were the most significant predictors, together with relational availability and mental flexibility. These findings might improve the growing knowledge concerning university adjustment, supporting main previous research. The observed relationships between university adjustment and the measured variables suggest intriguing considerations about the importance for schools and universities of providing interventions for students that aim to develop and strengthen the investigated personality facets, reducing withdrawal, behavioral and/or mental disengagement, and promoting academic achievement and success.
High-Temperature Superconducting Non-Insulation Closed-Loop Coils for Electro-Dynamic Suspension System
Authors: Lu Li , Wu Wei , Yu Xin , Jin Zhijian
Published: August 2021

The null-flux electro-dynamic suspension (EDS) system is a feasible high-speed maglev system with speeds of above 600 km/h. Owing to their greater current-carrying capacity, superconducting magnets can provide a super-magnetomotive force that is required for the null-flux EDS system, which cannot be provided by electromagnets and permanent magnets. Relatively mature high-speed maglev technology currently exists using low-temperature superconducting (LTS) magnets as the core, which works in the liquid helium temperature region (T ⩽ 4.2 K). Second-generation (2G) high-temperature superconducting (HTS) magnets wound by REBa2Cu3O7−δ (REBCO, RE = rare earth) tapes work above the 20 K region and do not rely on liquid helium, which is rare on Earth. In this study, the HTS non-insulation closed-loop coils module was designed for an EDS system and excited with a persistent current switch (PCS). The HTS coils module can work in the persistent current mode and exhibit premier thermal quenching self-protection. In addition, a full-size double-pancake (DP) module was designed and manufactured in this study, and it was tested in a liquid nitrogen (LN2) environment. The critical current of the DP module was approximately 54 A, and it could work in the persistent current mode with an average decay rate measured over 12 h of 0.58%/day.
Embroidered Βow-Tie Wearable Antenna for the 868 and 915 MHz ISM Bands
Authors: Kapetanakis Theodoros N. , Pavec Martin , Ioannidou Melina P. , Nikolopoulos Christos D. , Baklezos Anargyros T. , Soukup Radek , Vardiambasis Ioannis O.
Published: August 2021

A textile, embroidered antenna, based on the fractal shape of the Sierpinski triangle, is designed in this paper for operation in the European free Industrial Scientific and Medical (ISM) 863–870 MHz band, as well as in the 902–928 MHz band designated for ISM applications in North and South America. Several prototypes have been fabricated by employing different stitch patterns and thread materials. The effect of the fabrication parameters on the performance of the proposed antenna is investigated through measurements and simulations, with the results being in good agreement. The antenna exhibits attractive characteristics such as wide bandwidth, relatively stable radiation patterns, as well as robustness in washing. Several tests reveal that convex and concave bent conditions do not affect the coverage of the aforementioned ISM bands, despite the shift of the resonant frequency in some cases. Moreover, the SAR values resulting from simulations are below the corresponding thresholds suggested by international guidelines.
NUMA-Aware DGEMM Based on 64-Bit ARMv8 Multicore Processors Architecture
Authors: Zhang Wei , Jiang Zihao , Chen Zhiguang , Xiao Nong , Ou Yang
Published: August 2021

Double-precision general matrix multiplication (DGEMM) is an essential kernel for measuring the potential performance of an HPC platform. ARMv8-based system-on-chips (SoCs) have become the candidates for the next-generation HPC systems with their highly competitive performance and energy efficiency. Therefore, it is meaningful to design high-performance DGEMM for ARMv8-based SoCs. However, as ARMv8-based SoCs integrate increasing cores, modern CPU uses non-uniform memory access (NUMA). NUMA restricts the performance and scalability of DGEMM when many threads access remote NUMA domains. This poses a challenge to develop high-performance DGEMM on multi-NUMA architecture. We present a NUMA-aware method to reduce the number of cross-die and cross-chip memory access events. The critical enabler for NUMA-aware DGEMM is to leverage two levels of parallelism between and within nodes in a purely threaded implementation, which allows the task independence and data localization of NUMA nodes. We have implemented NUMA-aware DGEMM in the OpenBLAS and evaluated it on a dual-socket server with 48-core processors based on the Kunpeng920 architecture. The results show that NUMA-aware DGEMM has effectively reduced the number of cross-die and cross-chip memory access, resulting in enhancing the scalability of DGEMM significantly and increasing the performance of DGEMM by 17.1% on average, with the most remarkable improvement being 21.9%.
High-Performance Data Compression-Based Design for Dynamic IoT Security Systems
Authors: Aboelmaged Maha , Shisha Ali , Ghany Mohamed A. Abd El
Published: August 2021

IoT technology is evolving at a quick pace and is becoming an important part of everyday life. Consequently, IoT systems hold large amounts of data related to the user of the system that is vulnerable to security breaches. Thus, data collected by IoT systems need to be secured efficiently without affecting the IoT systems’ performance and without compromising security as well. In this paper, a high-performance dynamic security system is introduced. The system makes use of the ZedBoard’s dynamic partial reconfiguration capability to shift between three distinct cipher algorithms: AEGIS, ASCON, and DEOXYS-II. The switching between the three algorithms is performed using two different techniques: the algorithm hopping technique or the power adaptive technique. The choice of which technique to be used is dependent on whether the system needs to be focused on performance or power saving. The ciphers used are the CAESAR competition finalists that achieved the greatest results in each of the three competition categories, where each cipher algorithm has its own set of significant characteristics. The proposed design seeks to reduce the FPGA reconfiguration time by the application of LZ4 (Lempel-Ziv4) compression and decompression techniques on the ciphers’ bitstream files. The reconfiguration time decreased by a minimum of 38% in comparison to the state-of-the-art design, while the resource utilization increased by approximately 2%.
Synchronous Mixing Architecture for Digital Bandwidth Interleaving Sampling System
Authors: Jiang Xiaochang , Wu Jie , Ma Yubo
Published: August 2021

By using a mixer to down-convert the high frequency components of a signal, digital bandwidth interleaving (DBI) technology can simultaneously increase the sampling rate and bandwidth of the sampling system, compared to the time-interleaved and hybrid filter bank. However, the software and hardware of the classical architecture are too complicated, which also leads to poor performance. In particular, the pilot tone used to synchronize the analog and digital local oscillators (LO) of mixers intermodulates with the high frequency components of the signal, resulting in larger spurs. This paper proposes a synchronous mixing architecture for the DBI system, where the LO of the analog mixer is synchronized with the sampling clock of the analog-to-digital converter. Its hardware and software are simplified—the pilot tone used to synchronize the LOs can also be removed. An evaluation platform with a sampling rate of 250 MSPS is implemented to illustrate the performance of the new architecture. The result shows that the spurious free dynamic range (SFDR) of the new architecture is more than 20 dB higher than the classical one in a high frequency range. The rise time of a step signal of the new architecture is 0.578 ± 0.070 ns faster than the classical one with the same bandwidth (90 MHz).
Application of Surrogate Optimization Routine with Clustering Technique for Optimal Design of an Induction Motor
Authors: Balasubramanian Aswin , Martin Floran , Billah Md Masum , Osemwinyen Osaruyi , Belahcen Anouar
Published: August 2021

This paper proposes a new surrogate optimization routine for optimal design of a direct on line (DOL) squirrel cage induction motor. The geometry of the motor is optimized to maximize its electromagnetic efficiency while respecting the constraints, such as output power and power factor. The routine uses the methodologies of Latin-hypercube sampling, a clustering technique and a Box–Behnken design for improving the accuracy of the surrogate model while efficiently utilizing the computational resources. The global search-based particle swarm optimization (PSO) algorithm is used for optimizing the surrogate model and the pattern search algorithm is used for fine-tuning the surrogate optimal solution. The proposed surrogate optimization routine achieved an optimal design with an electromagnetic efficiency of 93.90%, for a 7.5 kW motor. To benchmark the performance of the surrogate optimization routine, a comparative analysis was carried out with a direct optimization routine that uses a finite element method (FEM)-based machine model as a cost function.
Heterogeneous Inertia Estimation for Power Systems with High Penetration of Converter-Interfaced Generation
Authors: Nouti Diala , Ponci Ferdinanda , Monti Antonello
Published: August 2021

The increasing and fast deployment of distributed generation is posing challenges to the operation and control of power systems due to the resulting reduction in the overall system rotational inertia and damping. Therefore, it becomes quite crucial for the transmission system operator to monitor the varying system inertia and damping in order to take proper actions to maintain the system stability. This paper presents an inertia estimation algorithm for low-inertia systems to estimate the inertia (both mechanical and virtual) and damping of systems with mixed generation resources and/or the resource itself. Moreover, the effect of high penetration of distributed energy resources and the resulting heterogeneous distribution of inertia on the overall system inertia estimation is investigated. A comprehensive set of case studies and scenarios of the IEEE 39-bus system provides results to demonstrate the performance of the proposed estimator.
A Modified Grid-Connected Inverter Topology for Power Oscillation Suppression under Unbalanced Grid Voltage Faults
Authors: Luo Cheng , Ma Xikui , Yang Lihui , Li Yongming , Yang Xiaoping , Ren Junhui , Zhang Yanmei
Published: August 2021

Under unbalanced grid voltage faults, the output power oscillation of a grid-connected inverter is an urgent problem to be solved. In the traditional topology of inverters, it is impossible to eliminate power oscillation and simultaneously maintain balanced output current waveform. In this paper, considering the solvability of reference current matrix equation, the inherent mechanism of inverter output power oscillation is analyzed, and a modified topology with auxiliary modules inserted in series between the inverter output filter and the point of common coupling (PCC) is proposed. Due to the extra controllable freedoms provided by auxiliary modules, the inverter could generate extra voltage to correct PCC voltage while keeping balance of output current, so as to eliminate the oscillation of output power. Simulation and experimental results verify the effectiveness of the proposed topology.
Machine Learning Applications in Biofuels’ Life Cycle: Soil, Feedstock, Production, Consumption, and Emissions
Authors: Ahmad Iftikhar , Sana Adil , Kano Manabu , Cheema Izzat Iqbal , Menezes Brenno C. , Shahzad Junaid , Ullah Zahid , Khan Muzammil , Habib Asad
Published: August 2021

Machine Learning (ML) is one of the major driving forces behind the fourth industrial revolution. This study reviews the ML applications in the life cycle stages of biofuels, i.e., soil, feedstock, production, consumption, and emissions. ML applications in the soil stage were mostly used for satellite images of land to estimate the yield of biofuels or a suitability analysis of agricultural land. The existing literature have reported on the assessment of rheological properties of the feedstocks and their effect on the quality of biofuels. The ML applications in the production stage include estimation and optimization of quality, quantity, and process conditions. The fuel consumption and emissions stage include analysis of engine performance and estimation of emissions temperature and composition. This study identifies the following trends: the most dominant ML method, the stage of life cycle getting the most usage of ML, the type of data used for the development of the ML-based models, and the frequently used input and output variables for each stage. The findings of this article would be beneficial for academia and industry-related professionals involved in model development in different stages of biofuel’s life cycle.
Estimation of Functional Form of Time-Dependent Heat Transfer Coefficient Using an Accurate and Robust Parameter Estimation Approach: An Inverse Analysis
Authors: Mohebbi Farzad , Sellier Mathieu
Published: August 2021

This paper presents a numerical method to address function estimation problems in inverse heat transfer problems using parameter estimation approach without prior information on the functional form of the variable to be estimated. Using an inverse analysis, the functional form of a time-dependent heat transfer coefficient is estimated efficiently and accurately. The functional form of the heat transfer coefficient is assumed unknown and the inverse heat transfer problem should be treated using a function estimation approach by solving sensitivity and adjoint problems during the minimization process. Based on proposing a new sensitivity matrix, however, the functional form can be estimated in an accurate and very efficient manner using a parameter estimation approach without the need for solving the sensitivity and adjoint problems and imposing extra computational cost, mathematical complexity, and implementation efforts. In the proposed sensitivity analysis scheme, all sensitivity coefficients can be computed in only one direct problem solution at each iteration. In this inverse heat transfer problem, the body shape is irregular and meshed using a body-fitted grid generation method. The direct heat conduction problem is solved using the finite-difference method. The steepest-descent method is used as a minimization algorithm to minimize the defined objective function and the termination of the minimization process is carried out based on the discrepancy principle. A test case with three different functional forms and two different measurement errors is considered to show the accuracy and efficiency of the used inverse analysis.
Split Cantilever Multi-Resonant Piezoelectric Energy Harvester for Low-Frequency Application
Authors: Masara David Omooria , El Gamal Hassan , Mokhiamar Ossama
Published: August 2021

This paper presents a new way to design a broadband harvester for harvesting high energy over a low-frequency range of 10–15 Hz. The design comprises a cantilever beam with two parallel grooves to form three dissimilar length parallel branches, each with an unequal concentrated tip mass. The piezoelectric material covers the whole length on both sides of the beam to form a bimorph. Appropriate geometry and mass magnitudes are obtained by a parametric study using the Finite Element Method. The design was simulated in COMSOL Multiphysics to study its response. The first three bending modes were utilized in energy harvesting, resulting in three power peaks at their respective fundamental frequencies. The adequate load resistance determined was 5.62 kΩ, at which maximum power can be harvested. The proposed harvester was compared to two other harvesters presented in the literature for validation: First, an optimized conventional harvester while the proposed harvester is operating at adequate load resistance. Second, a multimodal harvester, while the proposed harvester is operating at a 10 kΩ load. The suggested harvester proved to be more efficient by harvesting sufficiently higher broadband energy and is applicable in a wide range of vibration environments because of its adaptability in design.
Conditioning of Sewage Sludge with Physical, Chemical and Dual Methods to Improve Sewage Sludge Dewatering
Authors: Bień Beata , Bień Jurand D.
Published: August 2021

The paper presents the impact of different methods of sewage sludge conditioning on the improvement of sludge dewatering during pressure filtration processes. The following conditioning methods were tested for sludge preparation: sonication, addition of organic and inorganic chemicals (Zetag 8180, PIX 113 and the combined action of both substances). The research covered: physical and chemical analysis of sewage sludge, measurement of capillary suction time as an indicator of sludge dewaterability, some technical parameters of sludge pressure filtration process and the analysis of filtrate to assess the degree of contamination. The results of the research showed that the final water content of the prepared sludge decreased, while the specific filtration resistance increased. Among the tested methods the best results of sludge dewatering effects were obtained for sonicated sludge and its preparation with inorganic coagulant PIX 113. The combined effect of sonication with the addition of chemicals Zetag 8180 and PIX113 to sludge allowed for the reduction of organic substances, ammonium nitrogen and phosphates in filtrate after sludge dewatering.
Numerical Investigation of the Performance of a Submersible Pump: Prediction of Recirculation, Vortex Formation, and Swirl Resulting from Off-Design Operating Conditions
Authors: Arocena Virgel M. , Abuan Binoe E. , Reyes Joseph Gerard T. , Rodgers Paul L. , Danao Louis Angelo M.
Published: August 2021

Like any other turbomachinery, it is essential that the hydraulic behavior and performance of mixed-flow pumps are evaluated way in advance prior to manufacturing. Pump performance relies heavily on the proper design of the intake structure. Intake structures should be accurately designed in order to minimize and avoid unnecessary swirl and vortex formations. Ensuring the optimum performance condition as well as predicting how a particular intake structure affects the efficiency of the pump often requires either physical model studies or theoretical evaluations. Unfortunately, physical models are costly, time-consuming, and site-specific. Conversely, design and performance predictions using a theoretical approach merely gives performance values or parameters, which are usually unable to determine the root cause of poor pump performance. This study evaluates the viability of using Computational Fluid Dynamics (CFD) as an alternative tool for pump designers and engineers in evaluating pump performance. A procedure for conducting CFD simulations to verify pump characteristics such as head, efficiency, and flow as an aid for preliminary pump design is presented. Afterwards, a multiphase simulation using the VOF approach is applied to compare the fluid dynamics between four different pump intake structures. A full-sized CFD model of the pump sump complete with the pump’s active components was used for the intake structure analysis in order to avoid scaling issues encountered during the reduced-scale physical model test. The results provided a clear illustration of the hydraulic phenomena and characteristic curves of the pump. A performance drop in terms of reduction in TDH was predicted across the various intake structure designs. The CFD simulation of intake structure provided a clear insight on the varying degree of swirl, flow circulation, and effect on pump efficiency between all four cases.
Improving the Process of Developing New Services Using Uncertain Data
Authors: Skačkauskienė Ilona , Švogžlys Povilas
Published: August 2021

The rapid changes in the services sector encourage companies to improve the processes for developing and delivering new services. An effective new service development process is not possible without planning. Business entities can plan their time, organise activities, and prioritise tasks according to the complexity or the total duration of the process. However, in the context of new service development, the planning aspect is still not sufficiently emphasised. It is noted that the aim is often to identify the factors that could reduce the duration of this process. However, there is a lack of relevant data based on certain expressions of time. The lack of such research limits the improvement of the planning processes for new service development projects. In order to evaluate the possibilities of application of the proposed new service development model for companies providing services, an empirical evaluation was conducted, using methods of expert survey, program evaluation and review, and Monte Carlo simulation. Guidelines for further research were formulated based on the obtained results.
Fragility Assessment of Geotechnical Seismic Isolated (GSI) Configurations
Authors: Forcellini Davide
Published: August 2021

Geotechnical seismic isolation (GSI) consists of an innovative technique to mitigate the effects of earthquakes based on interposing a superficial soil layer to filter the seismic energy from the soil to the structure. This approach is particularly applied in developing countries due to low-cost applications. In order to account the uncertainties, the presented paper aimed to develop fragility curves of 3D configurations performed by numerical finite element models. The mail goal is to assess and discuss the potentialities of GSI as a mitigation technique for several configurations. Opensees PL has been applied to perform the numerical analyses and to realistically reproduce the behaviour of GSI.
Cost-Optimized Heat and Power Supply for Residential Buildings: The Cost-Reducing Effect of Forming Smart Energy Neighborhoods
Authors: Bahret Christoph , Eltrop Ludger
Published: August 2021

The Clean Energy for all Europeans Package by the EU aims, among other things, to enable collective self-consumption for various forms of energy. This step towards more prosumer-based and decentralized energy systems comes at a time when energy planning at a neighborhood scale is on the rise in many countries. It is widely assumed that—from a prosumer’s cost-perspective—shared conversion and storage technologies supplying more than a single building can be advantageous. However, it is not clear whether this is the case generally or only under certain conditions. By analyzing idealized building clusters at different degrees of urbanization (DOU), a linear-optimization approach is used to study the cost difference between shared energy infrastructure (smart energy neighborhoods, SENs) and individually planned buildings. This procedure is carried out for various emission reduction targets. The results show, that with higher emission reduction targets the advantage of SENs increases within rural environments and can reach up to 16%. Nevertheless, there are constellations in which the share of energetic infrastructure among buildings does not lead to any economic advantages. For example, in the case of building clusters with less than four buildings, almost no cost advantage is found. The result of this study underlines the importance of energy system planning within the process of urban planning.
Generalization Capability of Convolutional Neural Networks for Progress Variable Variance and Reaction Rate Subgrid-Scale Modeling
Authors: Xing Victor , Lapeyre Corentin , Jaravel Thomas , Poinsot Thierry
Published: August 2021

Deep learning has recently emerged as a successful approach to produce accurate subgrid-scale (SGS) models for Large Eddy Simulations (LES) in combustion. However, the ability of these models to generalize to configurations far from their training distribution is still mainly unexplored, thus impeding their application to practical configurations. In this work, a convolutional neural network (CNN) model for the progress-variable SGS variance field is trained on a canonical premixed turbulent flame and evaluated a priori on a significantly more complex slot burner jet flame. Despite the extensive differences between the two configurations, the CNN generalizes well and outperforms existing algebraic models. Conditions for this successful generalization are discussed, including the effect of the filter size and flame–turbulence interaction parameters. The CNN is then integrated into an analytical reaction rate closure relying on a single-step chemical source term formulation and a presumed beta PDF (probability density function) approach. The proposed closure is able to accurately recover filtered reaction rate values on both training and generalization flames.
Long-Term Land-Use/Land-Cover Change Increased the Landscape Heterogeneity of a Fragmented Temperate Forest in Mexico
Authors: Legarreta-Miranda Claudia K. , Prieto-Amparán Jesús A. , Villarreal-Guerrero Federico , Morales-Nieto Carlos R. , Pinedo-Alvarez Alfredo
Published: August 2021

The temperate forests of northern Mexico possess a great diversity of unique and endemic species, with the greatest associations of pine-oak in the planet occurring within them. However, the ecosystems in this region had experienced an accelerated fragmentation process in the past decades. This study described and quantified the landscape fragmentation level of a degraded watershed located in this region. For that, data from the Landsat series from 1990, 2005 and 2017, classified with the Support Vector Machine method, were used. The landscape structure was analyzed based on six metrics applied at both, the landscape and class levels. Results show considerable gains in surface area for the land use land cover change (LULC) of secondary forest while the Primary Forest (PF) lost 18.1% of its area during 1990–2017. The PF increased its number of patches from 7075 to 12,318, increased its patch density (PD) from 53.51 to 58.46 # of patches/100 ha, and reduced its average patch size from 39.21 to 15.05 ha. This made the PF the most fragmented LULC from the 5 LULCs evaluated. In this study, strong fluctuations in edge density and PD were registered, which indicates the forests of northern Mexico have experienced a reduction in their productivity and have been subjected to a continuous degradation process due to disturbances such as fires, clandestine and non-properly controlled logging, among others.
South-Eastern Baltic Provenances of Scots Pine Show Heritable Weather-Growth Relationships
Authors: Matisons Roberts , Schneck Volker , Jansone Diāna , Bāders Endijs , Dubra Stefānija , Zeltiņš Pauls , Jansons Āris
Published: August 2021

The productivity of forests has been linked to the sensitivity of tree growth to meteorological conditions and their fluctuations, hence moderation of tree sensitivity is one of the goals for climate-smart forest management. For this, tree breeding is among the most effective means, particularly if breeding populations are supplemented with genotypes (provenances) adapted to the expected climates. Nonetheless, heritability of traits is essential for their improvement by breeding. In this study, heritability of growth sensitivity of south-eastern Baltic provenances of Scots pine differing by field performance to meteorological conditions was assessed combining methods of quantitative genetics and dendrochronology. Five parallel provenance trials within the south-eastern Baltic region were investigated. The effects of regional weather drivers of growth (moisture regime in summer, temperature regime in preceding summer and in the dormancy period) were estimated, yet their strengths differed among the provenances, indicating local specialization of metapopulations of Scots pine. The heritability of growth sensitivity to these factors ranged from low to moderate, similarly as observed for the morphometric traits within the region; however, the provenance (genetic) variation appeared to be higher. The differences in heritability of responses, however, indicated uneven adaptive significance of weather conditions. Although the estimates were based on a limited set of genotypes implying caution in the extrapolation of results, the weather-growth relationships and their heritability indicate that sensitivity of growth is a complementary trait aiding breeding of forest reproductive material best suited for future climates. Heritable weather-growth relationships also imply a high potential for forest breeding to moderate the sensitivity of the trees.
Combining Methods to Estimate Post-Fire Soil Erosion Using Remote Sensing Data
Authors: Argentiero Ilenia , Ricci Giovanni Francesco , Elia Mario , D’Este Marina , Giannico Vincenzo , Ronco Francesco Vito , Gentile Francesco , Sanesi Giovanni
Published: August 2021

The increasing number of wildfires in southern Europe is making our ecosystem more vulnerable to water erosion; i.e., the loss of vegetation and subsequent runoff increase cause a shift in large quantities of sediment. Fire severity has been recognized as one of the most important parameters controlling the magnitude of post-fire soil erosion. In this paper, we adopted a combination of methods to easily assess post-fire erosion and prevent potential risk in subsequent rain events. The model presented is structured into three modules that were implemented in a GIS environment. The first module estimates fire severity with the Monitoring Trends in Burn Severity (MTBS) method; the second estimates runoff with rainfall depth–duration curves and the Soil Conservation Service Curve Number (SCS-CN) method; and the third estimates pre- and post-fire soil erosion. In addition, two post-fire scenarios were analyzed to assess the influence of fire severity on soil erosion: the former based on the Normalized Difference Vegetation Index (NDVI) and the latter on the Relative differenced Normalized Burn Index (RdNBR). The results obtained in both scenarios are quite similar and demonstrate that transitional areas, such as rangelands and rangelands with bush, are the most vulnerable because they show a significant increase in erosion following a fire event. The study findings are of secondary importance to the combined approach devised because the focal point of the study is to create the basis for a future tool to facilitate decision making in landscape management.
Effect of Pretreated Colza Straw on the Growth and Extracellular Ligninolytic Enzymes Production by Lentinula edodes and Ganoderma lucidum
Authors: Makarenkova Galina , Balode Valda , Zala Dzintra , Azena Elina , Rapoport Alexander , Muiznieks Indrikis
Published: August 2021

Lentinula edodes 3565 and Ganoderma lucidum 9621 were compared for their ability to produce lignocellulolytic enzymes in submerged (SM) and surface liquid (SL) fermentation of hydrolysed colza straw lignin waste that remained after the production of furfural and bioethanol (CS lignin). Application of cultivated mushrooms to dispose of pretreated colza straw agricultural waste is an approach to decrease the quantity of residual lignin while simultaneously obtaining active substances, e.g., the ligninolytic enzyme complex from mycelium. The effect of adding CS lignin to culture media on the yield of L. edodes and G. lucidum mycelium and extracellular laccase activity was studied. It was revealed that the mycelial growth of G. lucidum on solid media was significantly improved by adding CS lignin. Laccase activity during SL cultivation of L. edodes on medium with CS lignin gradually increased over the experiment starting on day 21 and peaked at 520 U/mL on day 28. G. lucidum expressed the maximum laccase activity, 540 U/mL, during the first 14 days of mycelium SM cultivation. Extracellular laccase activity was enhanced about 35- to 40-fold at cultivation of L. edodes and about 10- to 15-fold in the case of G. lucidum by supplementing liquid culture media with CS lignin.