bluuebunny/crossref_metadata_2025 huggingface dataset:
The Role of the Global Solar UV Index for Sun Protection of Children in German Kindergartens
Authors: Gefeller Olaf , Mathes Sonja , Uter Wolfgang , Pfahlberg Annette
Published: February 2022

More than twenty-five years ago, the Global Solar UV index (UVI) was introduced as a simple means of visualizing the intensity of ultraviolet radiation and to alert people to the need for sun protection. In our survey, among directors of 436 kindergartens in southern Germany we investigated the level of awareness and knowledge about the UVI as well as the practical consequences for sun protection in kindergartens. Less than half of the directors (n = 208, 47.7%) had ever heard of the UVI, and only a small minority of them (n = 34, 8.7%) used the daily UVI information to adapt sun protective measures in their kindergartens. Detailed knowledge about the UVI was a rarity among the respondents. The proportion of respondents with self-perceived detailed UVI knowledge was five times higher than the actual knowledge assessed by an in-depth structured interview using open-ended questions about the UVI (14.2% vs. 2.8%). No clear relationship between UVI awareness, knowledge, and use and directors’ age and gender was found. The UVI-related variables also showed no association with directors’ knowledge of risk factors for skin cancer and their attitudes towards tanned skin. Overall, the results paint a sobering picture regarding the penetration of the UVI into sun protection policies of German kindergartens. Future public health campaigns should aim to increase the awareness and understanding of the UVI as well as its relevance for sun protection of children.
Conjugation of Antimicrobial Peptide to Zinc Phthalocyanine for an Efficient Photodynamic Antimicrobial Chemotherapy
Authors: Rukh Gul , Ullah Azeem , Khattak Rozina , Fazil Perveen , Ali Abid , Shah Muhammad Raza , Khan Muhammad Sufaid , Alsubaie Abdullah Saad , Mahmoud Khaled H. , Ateeq Muhammad
Published: February 2022

Photodynamic antimicrobial chemotherapy is an attractive and novel therapeutic approach to treat microbial infections. Antimicrobial peptides (AMPs) have the potential to specifically target and kill the microorganism while showing no effect toward mammalian cells. In the current study, antimicrobial peptide (GGG(RW)3), an analogue of MP-196, was conjugated to a zinc phthalocyanine (ZnPc) photosensitizer (PS) for photoinactivation assay to enhance the bacterial killing efficacy of the peptide. The AMPs showed selectivity toward the Gram-positive strain of bacteria. We observed that the conjugate ZnPc-GGG(RW)3 also displayed a photoinactivation effect against the Gram-positive strains of S. aureus. The results showed that ZnPc-GGG(RW)3 induced a 6-log reduction (i.e., 99.999% cell killing) in Gram-positive S. aureus at a light dose of 22 J/cm2 upon illumination under red light, while the peptide did not exhibit such a significant effect when tested alone at the same concentration. The conjugate also showed 50% inhibition of the bacterial strain in the dark at a higher concentration. Furthermore, the addition of potassium iodide salt to the PS at lower concentrations also significantly killed the Gram-negative E. coli strain and killed the E. coli strain with up to a 5-log reduction at a light dose of 22 J/cm2 under red light illumination. We demonstrated the efficacy of antimicrobial peptide (GGG(RW)3 enhanced by conjugation to a ZnPc photosensitizer.
Superhydrophobic Candle Soot Coating Directly Deposited on Aluminum Substrate with Enhanced Robustness
Authors: Hussein Hussein Ali , Wais Sabah Ibrahim , Khedir Khedir R.
Published: February 2022

In this study, superhydrophobic surfaces were developed by using a simple and environmentally friendly technique. The nano-network of candle soot (CS) as the byproduct of incomplete combustion of paraffin candle was directly coated onto both smooth and micro-rough aluminum (Al) substrates for various time periods of deposition. The simple technique of mechanical sanding was used to impart micro-rough structures onto Al substrates using different sandpaper grit sizes. The scanning electron microscopy (SEM), energy dispersive X-ray spectroscopy (EDS), atomic force microscopy (AFM), and X-ray diffraction (XRD) techniques were used to characterize the morphology and chemistry of the prepared surfaces. Wetting analysis of the prepared surfaces was performed by measuring both water droplet contact angle (CA) and sliding angle (SA). The prepared coatings showed superhydrophobic properties with high CAs and low SAs for CS surfaces coated on roughened Al substrates. Moreover, the robustness of the prepared surfaces was tested by continuous impingement of water droplets onto their surfaces from various heights. Post-testing wetting analysis showed that the micro-nano surfaces of candle soot coated on micro roughened Al substrates demonstrated improved robustness. These surfaces could be useful for self-cleaning, anti-corrosion and anti-icing applications.
Effect of Annealing in ITO Film Prepared at Various Argon-and-Oxygen-Mixture Ratios via Facing-Target Sputtering for Transparent Electrode of Perovskite Solar Cells
Authors: Kim Yujin , Joo Sung Hwan , Shin Seong Gwan , Choi Hyung Wook , Bark Chung Wung , Rim You Seung , Kim Kyung Hwan , Kim Sangmo
Published: February 2022

Normal perovskite solar cells (PSCs) consist of the following layers: transparent electrode, electron-transport layer (ETL), light-absorbing perovskite layer, hole-transport layer (HTL), and metal electrode. Energy, such as electricity, is produced through light absorbance and electron–hole generation/transport between two electrode types (metal film and transparent conducting film). Among stacked layers in a PSC, the transparent electrode plays the high-performance-power-conversion-efficiency role. Transparent electrodes should have high-visible-range transparency and low resistance. Therefore, in this study, we prepared indium tin oxide (ITO) films on a glass substrate by using facing-target sputtering without substrate heating treatment and investigate the heating-treatment effect on the ITO-film properties for perovskite solar cells (PSCs). Moreover, we fabricated PSCs with ITO films prepared at various oxygen flows during the sputtering process, and their energy-conversion properties are investigated.
One View Is Not Enough: Review of and Encouragement for Multiple and Alternative Representations in 3D and Immersive Visualisation
Authors: Roberts Jonathan C. , Butcher Peter W. S. , Ritsos Panagiotis D.
Published: February 2022

The opportunities for 3D visualisations are huge. People can be immersed inside their data, interface with it in natural ways, and see it in ways that are not possible on a traditional desktop screen. Indeed, 3D visualisations, especially those that are immersed inside head-mounted displays are becoming popular. Much of this growth is driven by the availability, popularity and falling cost of head-mounted displays and other immersive technologies. However, there are also challenges. For example, data visualisation objects can be obscured, important facets missed (perhaps behind the viewer), and the interfaces may be unfamiliar. Some of these challenges are not unique to 3D immersive technologies. Indeed, developers of traditional 2D exploratory visualisation tools would use alternative views, across a multiple coordinated view (MCV) system. Coordinated view interfaces help users explore the richness of the data. For instance, an alphabetical list of people in one view shows everyone in the database, while a map view depicts where they live. Each view provides a different task or purpose. While it is possible to translate some desktop interface techniques into the 3D immersive world, it is not always clear what equivalences would be. In this paper, using several case studies, we discuss the challenges and opportunities for using multiple views in immersive visualisation. Our aim is to provide a set of concepts that will enable developers to perform critical thinking, creative thinking and push the boundaries of what is possible with 3D and immersive visualisation. In summary developers should consider how to integrate many views, techniques and presentation styles, and one view is not enough when using 3D and immersive visualisations.
Ferroelectric and Spectroscopic Properties of Ho3+/Yb3+ Co-Doped Pb(Mg1/3Nb2/3)O3-32PbTiO3 Crystal
Authors: Zhang Jin , Xi Zengzhe , Wang Xinzhe , Gao Shenghan , Long Xinyi , Guo Feifei
Published: February 2022

In order to design a new multifunctional crystal with excellent ferroelectric and spectroscopic properties, experiments were carried out for Ho3+/Yb3+ co-doped Pb(Mg1/3Nb2/3)O3 -32PbTiO3 ferroelectric crystal using the flux method, the coercive field Ec of which is 11.86 kV/cm. Up-conversion luminescence emission bands, including an intense green emission band at 553 nm, a red band at 663 nm, and a weak infra-red band at 755 nm, are generated at 980 nm excitation. The main spectroscopic parameters, including radiative transition probability A(J′ − J), radiative lifetimes τrad, and branching ratios β, were predicted by applying Judd–Ofelt treatment. The obtained J-O intensity parameters are Ω2 = 0.531 × 10−20 cm2, Ω4 = 1.738 × 10−20 cm2, Ω6 = 0.530 × 10−20 cm2. The radiative lifetime of 5I7 level is 5.45 ms. The fluorescence lifetime of is 5F5 is 92.568 μs. The investigations show that Ho3+/Yb3+ co-doped Pb(Mg1/3Nb2/3)O3-0.32PbTiO3 crystal is a new type of multifunctional crystal integrating ferroelectric and spectroscopic properties, which has a potential application in the developing innovative multifunctional devices and lasers.
The Development of Geriatric Assessment and Intervention Guidelines for an Online Geriatric Assessment Tool: A Canadian Modified Delphi Panel Study
Authors: Puts Martine , Papadopoulos Efthymios , Brennenstuhl Sarah , Durbano Sara , Hossain Nazia , Santos Brenda , Cleverley Kristin , Alibhai Shabbir M. H.
Published: February 2022

Background: There are no guidelines available for what assessment tools to use in a patient’s self-completed online geriatric assessment (GA) with management recommendations. Therefore, we used a modified Delphi approach with Canadian expert clinicians to develop a consensus online GA plus recommendations tool. Methods: The panel consisted of experts in geriatrics, oncology, nursing, and pharmacy. Experts were asked to rate the importance and feasibility of assessments and interventions to be included in an online GA for patients. The items included in the first round were based on guidelines for in-person GA and literature review. The first two rounds were conducted using an online survey. A virtual 2 h meeting was held to discuss the items where no consensus was reached and then voted on in the final round. Results: 34 experts were invited, and 32 agreed to participate. In round 1, there were 85 items; in round 2, 50 items; and in round 3, 25 items. The final tool consists of fall history, assistive device use, weight loss, medication review, need help taking medication, social supports, depressive symptoms, self-reported vision and hearing, and current smoking status and alcohol use. Conclusion: This first multidisciplinary consensus on online GA will benefit research and clinical care for older adults with cancer.
Hemorrhagic Transformation after Intravenous Tissue Plasminogen Activator Administration in Acute Distal Middle Cerebral Artery Occlusion
Authors: Lee Chan-Hyuk , Yi Sang Hak , Shin Byoung-Soo , Kang Hyun Goo
Published: February 2022

Atrial fibrillation and cerebral embolism are known to increase the risk of hemorrhagic transformation (HT). In addition, a sufficient number of collateral vessels in acute ischemic stroke can maintain the ischemic penumbra and prevent progression to the ischemic core, while an insufficient number of collateral vessels increase the HT risk after therapeutic recanalization. In this case, when the middle cerebral artery is recanalized, reperfusion injury may occur in the basal ganglia due to insufficient collateral vessels.
Predictive and Prognostic Significance of mRNA Expression and DNA Copies Aberrations of ERCC1, RRM1, TOP1, TOP2A, TUBB3, TYMS, and GSTP1 Genes in Patients with Breast Cancer
Authors: Tsyganov Matvey M. , Ibragimova Marina K. , Garbukov Evgeniy Yu. , Tsydenova Irina A. , Gaptulbarova Kseniya A. , Dolgasheva Daria S. , Zdereva Ekaterina A. , Frolova Anastasia A. , Slonimskaya Elena M. , Litviakov Nikolai V.
Published: February 2022

Increasingly, many researchers are focusing on the sensitivity in breast tumors (BC) to certain chemotherapy drugs and have personalized their research based on the assessment of this sensitivity. One such personalized approach is to assess the chemotherapy’s gene expression, as well as aberrations in the number of DNA copies—deletions and amplifications with the ability to have a significant effect on the gene’s activity. Thus, the aim of this work was to study the predictive and prognostic significance of the expression and chromosomal aberrations of eight chemosensitivity genes in breast cancer patients. Material and methods. The study involved 97 patients with luminal B breast cancer IIB–IIIB stages. DNA and RNA were isolated from samples of tumor tissue before and after treatment. Microarray analysis was performed for all samples on high-density microarrays (DNA chips) of Affymetrix (USA) CytoScanTM HD Array and Clariom™ S Assay, human. Detection of expression level of seven chemosensitivity genes—RRM1, ERCC1, TOP1, TOP2a, TUBB3, TYMS, and GSTP1—was performed using PCR real-time (RT-qPCR). Results. The expression of the RRM1 (AC scheme), TOP2α, TYMS, and TUBB3 genes in patients with an objective response to treatment (complete and partial regression) is higher than in patients with stabilization and progression (p < 0.05). According to our results, the presence of a high level of GSTP1 in a tumor biopsy is associated with the low efficiency of the NAC CP scheme (p = 0.05). The presence of RRM1 deletion is associated with complete and partial regression, as for the TOP1 and TUBB3 genes (p < 0.05). Higher rates of metastatic survival are associated with a high level of expression and amplification of the GSTP1 gene (log-rank test p = 0.02 and p = 0.05). Conclusion. Thus, a complex assessment of the chemotherapy’s gene expression is important not only for understanding the heterogeneity and molecular biology of breast cancer but also to obtain a more accurate disease prognosis.
Testing the Accuracy of Pont’s Index in Diagnosing Maxillary Transverse Discrepancy as Compared to the University of Pennsylvania CBCT Analysis
Authors: Feştilă Dana , Enache Aurelia Magdalena , Nagy Evelyn Beatrix , Hedeşiu Mihaela , Ghergie Mircea
Published: February 2022

Introduction: Assessment of maxillary transverse discrepancy requires an accurate tool in order to implement the appropriate treatment plan. Aim: To evaluate the accuracy of Pont’s Index in confirming a transverse maxillary deficiency by comparing its results with the corresponding results yielded by the University of Pennsylvania CBCT analysis. Material and methods: The study was performed on dental casts and CBCT’s of 60 randomly selected patients by adopting a cluster sampling method. The results of Pont’s Index and University of Pennsylvania CBCT analysis were analyzed through McNemar’s test using Excel Data Analysis, and the accuracy indicators for Pont’s Index were computed using MedCalc Ltd. Results: Mc Nemar’s test revealed a p-value of 0.85. The accuracy indicators of Pont’s Index were: sensitivity: 69%; specificity: 16.6%; positive predictive value: 65%; negative predictive value: 18.75%; positive likelihood ratio: 0.83; negative likelihood ratio: 1.86; and accuracy: 53.28%. Conclusion: Due to the fact that CBCT is not used on a daily basis and Pont’s Index has a relatively high sensitivity (69%) making it suitable to detect patients with a narrow maxilla, assessment of the maxillary deficiency on CBCT can be recommended for cases were the midpalatal suture maturation should be evaluated.
A Novel MAGDM Method Based on Hesitant Picture Fuzzy Schweizer–Sklar Maclaurin Symmetric Mean Operators and Their Application
Authors: Chen Tiedong , Ye Long
Published: February 2022

Multiple attribute group decision making (MAGDM) issues play important roles in our daily life. In order to solve the problem that decision makers (DMs) may feel hesitant to select the appropriate evaluation values from several possible values in the process of providing evaluations, fuzzy theory and its extensions are widely applied in MAGDM problems. In this study, we first proposed hesitant picture fuzzy sets (HPFSs), which is a combination of the hesitant fuzzy set and picture fuzzy set. Subsequently, we introduced a novel Schweizer–Sklar t-norm and t-conorm operation rules of HPFSs and proposed a family of hesitant picture fuzzy Schweizer–Sklar Maclaurin symmetric mean operators. To show the application procedure of the proposed method to practical MAGDM issues, a numerical example about enterprise informatization level evaluation was employed to elaborate the calculation process with the proposed method. Finally, through the parameter analysis, validity analysis, and comparative analysis with some existing methods, we found that our method is more superior in providing DMs a greater decision-making freedom and relaxing the constraints on expressing personal preferences. This study provides a general framework of the proposed method to MAGDM problems under hesitant picture fuzzy environment, which enriches the fuzzy theory and its applications.
A Method for Neutralizing Entropy Measurement-Based Ransomware Detection Technologies Using Encoding Algorithms
Authors: Lee Jaehyuk , Lee Kyungroul
Published: February 2022

Ransomware consists of malicious codes that restrict users from accessing their own files while demanding a ransom payment. Since the advent of ransomware, new and variant ransomwares have caused critical damage around the world, thus prompting the study of detection and prevention technologies against ransomware. Ransomware encrypts files, and encrypted files have a characteristic of increasing entropy. Due to this characteristic, a defense technology has emerged for detecting ransomware-infected files by measuring the entropy of clean and encrypted files based on a derived entropy threshold. Accordingly, attackers have applied a method in which entropy does not increase even if the files are encrypted, such that the ransomware-infected files cannot be detected through changes in entropy. Therefore, if the attacker applies a base64 encoding algorithm to the encrypted files, files infected by ransomware will have a low entropy value. This can eventually neutralize the technology for detecting files infected from ransomware based on entropy measurement. Therefore, in this paper, we propose a method to neutralize ransomware detection technologies using a more sophisticated entropy measurement method by applying various encoding algorithms including base64 and various file formats. To this end, we analyze the limitations and problems of the existing entropy measurement-based ransomware detection technologies using the encoding algorithm, and we propose a more effective neutralization method of ransomware detection technologies based on the analysis results.
On the Nature of Functional Differentiation: The Role of Self-Organization with Constraints
Authors: Tsuda Ichiro , Watanabe Hiroshi , Tsukada Hiromichi , Yamaguti Yutaka
Published: February 2022

The focus of this article is the self-organization of neural systems under constraints. In 2016, we proposed a theory for self-organization with constraints to clarify the neural mechanism of functional differentiation. As a typical application of the theory, we developed evolutionary reservoir computers that exhibit functional differentiation of neurons. Regarding the self-organized structure of neural systems, Warren McCulloch described the neural networks of the brain as being “heterarchical”, rather than hierarchical, in structure. Unlike the fixed boundary conditions in conventional self-organization theory, where stationary phenomena are the target for study, the neural networks of the brain change their functional structure via synaptic learning and neural differentiation to exhibit specific functions, thereby adapting to nonstationary environmental changes. Thus, the neural network structure is altered dynamically among possible network structures. We refer to such changes as a dynamic heterarchy. Through the dynamic changes of the network structure under constraints, such as physical, chemical, and informational factors, which act on the whole system, neural systems realize functional differentiation or functional parcellation. Based on the computation results of our model for functional differentiation, we propose hypotheses on the neuronal mechanism of functional differentiation. Finally, using the Kolmogorov–Arnold–Sprecher superposition theorem, which can be realized by a layered deep neural network, we propose a possible scenario of functional (including cell) differentiation.
A Social Network Analysis of Engineering Faculty Connections: Their Impact on Faculty Student-Centered Attitudes and Practices
Authors: Middleton James A. , Krause Stephen , Judson Eugene , Ross Lydia , Culbertson Robert , Hjelmstad Keith D. , Hjelmstad Kara L. , Chen Ying-Chih
Published: February 2022

Connections among faculty who might be potential resources for diffusion of learner-centered practices across STEM departments were examined at a major research university. Specifically, the research assessed the impact of these connections on learner-centered beliefs among faculty and the implementation of learner-centered practices across the network. Participants were recruited from Physics, Chemistry, and Mathematics departments, and from departments in the College of Engineering. A snowball sampling procedure began with 21 randomly selected faculty from each department engaged in the STEM instruction of engineering students. These faculties then identified the colleagues they utilize as resources for improving their instruction. Characteristics of faculty connectedness in the network consisted of number of connections and depth of connections for both individual faculty and within and across departments. Outcome measures consisted of a survey of learner-centered attitudes and classroom observations of faculty instructional practices. The results show that faculty exhibiting more learner-centered behaviors had deeper and more extensive social networks than their peers who were more instructor-centered. The results are discussed in terms of the need for intra- and inter-departmental faculty professional development experiences that build and support collaborative organizations of faculty working together to transform early engineering experiences.
Comparison of Predictive Models with Balanced Classes Using the SMOTE Method for the Forecast of Student Dropout in Higher Education
Authors: Flores Vaneza , Heras Stella , Julian Vicente
Published: February 2022

Based on the premise that university student dropout is a social problem in the university ecosystem of any country, technological leverage is a way that allows us to build technological proposals to solve a poorly met need in university education systems. Under this scenario, the study presents and analyzes eight predictive models to forecast university dropout, based on data mining methods and techniques, using WEKA for its implementation, with a dataset of 4365 academic records of students from the National University of Moquegua (UNAM), Peru. The objective is to determine which model presents the best performance indicators to forecast and prevent student dropout. The study aims to propose and compare the accuracy of eight predictive models with balanced classes, using the SMOTE method for the generation of synthetic data. The results allow us to confirm that the predictive model based on Random Forest is the one that presents the highest accuracy and robustness. This study is of great interest to the educational community as it allows for predicting the possible dropout of a student from a university career and being able to take corrective actions both at a global and individual level. The results obtained are highly interesting for the university in which the study has been carried out, obtaining results that generally outperform the results obtained in related works.
Vibrating Tilt Platform Enhancing Immersive Experience in VR
Authors: Zwoliński Grzegorz , Kamińska Dorota , Laska-Leśniewicz Anna , Adamek Łukasz
Published: February 2022

One of the disadvantages of virtual reality systems of the past was the fact that they had visual-only interfaces. However, with the development of haptic technology, peripheral solutions to enhance the VR experience are gaining momentum, and many haptic systems are being developed for deepening VR immersion. This paper deals with the concept of a vibrating tilt platform allowing the change of three angles of inclination to thus reinforce the VR experience. The proposed system is flexible and adaptable to different sports, health, and education applications. In this paper, we present the mechanical and mechatronics aspects of the platform and usability testing results based on an immersive geological experience application. The first tests were studied in terms of the cyber sickness, perceived realism, and anxiety through both subjective (questionnaires) and objective (electroencephalogram) measurements. The results indicate that our platform increased anxiety levels and was perceived as realistic. Adding vibrations and tilting had a considerable impact on the immersion level and brain activity.
A Machine Learning Method for Classification of Cervical Cancer
Authors: Tanimu Jesse Jeremiah , Hamada Mohamed , Hassan Mohammed , Kakudi Habeebah , Abiodun John Oladunjoye
Published: February 2022

Cervical cancer is one of the leading causes of premature mortality among women worldwide and more than 85% of these deaths are in developing countries. There are several risk factors associated with cervical cancer. In this paper, we developed a predictive model for predicting the outcome of patients with cervical cancer, given risk patterns from individual medical records and preliminary screening. This work presents a decision tree (DT) classification algorithm to analyze the risk factors of cervical cancer. Recursive feature elimination (RFE) and least absolute shrinkage and selection operator (LASSO) feature selection techniques were fully explored to determine the most important attributes for cervical cancer prediction. The dataset employed here contains missing values and is highly imbalanced. Therefore, a combination of under and oversampling techniques called SMOTETomek was employed. A comparative analysis of the proposed model has been performed to show the effectiveness of feature selection and class imbalance based on the classifier’s accuracy, sensitivity, and specificity. The DT with the selected features from RFE and SMOTETomek has better results with an accuracy of 98.72% and sensitivity of 100%. DT classifier is shown to have better performance in handling classification problems when the features are reduced, and the problem of high class imbalance is addressed.
Exhaust Emissions from a Hybrid City Bus Fuelled by Conventional and Oxygenated Fuel
Authors: Kozak Miłosław , Lijewski Piotr , Waligórski Marek
Published: February 2022

City buses are one of the main means of public transport in cities. As they move in a limited and densely populated area and are intensively exploited, it is particularly important that they are environmentally friendly. There are many ways to reduce emissions from city buses, including the use of hybrid propulsion. Another way is to use low-emission fuels. This article presents the results of the emission tests of an 18 m articulated city bus with a serial hybrid drive fuelled comparatively by conventional diesel fuel and oxygenated fuel containing 10% v/v of triethylene glycol dimethyl ether (TEGDME). The emission tests were carried out during the actual operation of the bus on a route in Poznań (Poland) and over the SORT cycles. The obtained test results were compared also with the results obtained for a conventional bus. The reduction in emissions of some exhaust components was found when the hybrid bus was fuelled with oxygenated fuel during its actual operation on the bus route. There was a reduction in CO emissions by ~50% and NOx emissions by ~10%. Almost identical levels of PM and HC emissions and smoke opacity were observed for both fuels. In the SORT cycles, the differences in the emissions obtained for both types of fuel were small. In general, for the hybrid bus, a lower influence of oxygenated fuel on emissions was recorded than for the conventional bus.
Comprehensive Study of the Aerodynamic Influence of Ground and Wheel States on the Notchback DrivAer
Authors: Yu Xiaoyan , Jia Qing , Yang Zhigang
Published: February 2022

This paper conducts an analysis of the aerodynamic influence of different ground and wheel states on the Notchback DrivAer by numerical simulation. The effects of the moving ground and rotating wheels are investigated individually and comprehensively. Experimental data are also included for validation. Through this study, a unique and important low-drag state is observed, in which the vehicle wake near the center region becomes more symmetrical, the pressure on the upper middle base is recovered and the total aerodynamic drag decreases significantly. Furthermore, the formation of this state is determined by the flow rate near the surface of the rear underbody. When the wheels are rotating, the wheel wakes are weakened. On one hand, the drag of wheels and the two sides of the base region is reduced. On the other hand, the boundary layer near the underbody is thinned and the flow near the underbody surface is accelerated, transforming the wake to the low-drag state. Moreover, the moving ground can enhance the wheel wake but its effect on the flow rate near the underbody is complicated. This may be one of the important reasons why the aerodynamic effects of wheel & ground states depend on the vehicle model. Finally, the global effects of wheel rotation and ground movement can affect each other so they should be analyzed together in the vehicle design process.
Pre-Cooling Concrete System in Massive Concrete Production: Energy Analysis and Refrigerant Replacement
Authors: Alamayreh Malik I. , Alahmer Ali , Younes Mai Bani , Bazlamit Subhi M.
Published: February 2022

Several techniques for cooling mass concrete structures were developed in order to increase structural integrity and reduce the influence of cement hydration, which sometimes causes cracking in concrete structures, negatively affecting their durability. This research focuses on cooling system design, initial investment, and the influence of different refrigerants on cooling system performance aims in producing higher quality massive concrete. Cooling aggregates in massive concrete structures such as desert dams can be performed by employing cooled air from an air conditioning duct system or chilled water. The experimental study illustrates the relationship between the coefficient of performance COP, the evaporator temperature, cooling capacity, and refrigerant mass flow rate as a function of the evaporator temperature, cooling capacity, and refrigerant mass flow rate. The findings of the experiments were utilized to verify a numerical model developed utilizing engineering equation solver (EES) software. The performance of the vapor compression of the cooling systems was compared using alternative refrigerants, including R22, R32, and R410a at different operating conditions. This study revealed that R22 refrigerant has a higher coefficient of performance than R32 and R410A, while R32 has the highest cooling capacity among other refrigerants.
The Effect of Adjusting Sinter Raw Mix on Dioxins from Iron Ore Co-Sintering with Municipal Solid Waste Incineration Fly Ash
Authors: He Hao , Guo Xuanhao , Jin Lizheng , Peng Yaqi , Tang Minghui , Lu Shengyong
Published: February 2022

The inhibition effect of calcined lime (CaO) and limestone (CaCO3) on the formation of dioxins during iron ore co-sintering with fly ash was investigated in a sinter pot in the present work. Experimental results indicated that international total toxicity equivalent concentration of dioxins decreased from 1.4335 to 0.2922, 0.1048, 0.4562, and 0.3098 ng I-TEQ Nm−3 under four different experimental conditions. It can be concluded that 5 wt.% calcined lime with 3 wt.% limestone is the optimal addition to reduce the concentration of dioxins in flue gas, with 92.70% inhibition efficiency. Effects on dioxin distribution was also analyzed. The distribution proportion of low-chlorinated dioxins was found to increase, while that of high-chlorinated dioxins decreased, except for octachlorianted dibenzo-p-dioxins (OCDD). The reason is that the consumption of HCl not only inhibits the de novo synthesis, but also dramatically promotes the condensation and dechlorination to produce more tetrachlorianted dibenzo-p-dioxins and octachlorianted dibenzo-p-dioxins through precursors. Finally, condensation, dichlorination, and inhibition mechanisms of dioxins during co-sintering with municipal solid waste incineration (MSWI) fly ash are proposed.
Evolution of Short Food Supply Chain Theory and Practice: Two-Sided Networks and Platforms
Authors: Lankauskienė Rita , Vidickienė Dalia , Gedminaitė-Raudonė Živilė
Published: February 2022

The shift from an industrial to a post-industrial economic system encourages an alternative to the globalized food chains—short food supply chain initiatives, which come alongside the servitization concept and are often discussed in the context of sustainability. However, short food supply chain literature is mainly focused on the aspects typical of the industrial economic system and neglects new important business drivers arising in the post-industrial era. This research aims to discuss the evolution of short food supply chain theory and practice in the context of three paradigm innovations that emerged in the post-industrial economic system and suggest new paths for sustainable agri-food system building. All three paradigm innovations are closely related to each other, but each changes a certain dimension of the mental model concerning the food production and delivery system. The article examines the organizational model of the alternative local food market in Lithuania that has been designed according to the “new rules of game” suggested by the post-industrial economic system.
Robust Economic MPC of the Absorption Column in Post-Combustion Carbon Capture through Zone Tracking
Authors: Decardi-Nelson Benjamin , Liu Jinfeng
Published: February 2022

Several studies have reported the importance of optimally operating the absorption column in a post-combustion CO2 capture (PCC) plant. It has been demonstrated in our previous work how economic model predictive control (EMPC) has a great potential to improve the operation of the PCC plant. However, the use of a general economic objective such as maximizing the absorption efficiency of the column can cause EMPC to drive the state of the system close to the constraints. This may lead to solvent overcirculation and flooding, which are undesirable. In this work, we present an EMPC with zone tracking algorithm as an effective means to address this problem. The proposed control algorithm incorporates a zone tracking objective and an economic objective to form a multi-objective optimal control problem. To ensure that the zone tracking objective is achieved in the presence of model uncertainties and time-varying flue gas flow rate, we propose a method to modify the original target zone with a control invariant set. The zone modification method combines both ellipsoidal control invariant set techniques and a back-off strategy. The use of ellipsoidal control invariant sets ensure that the method is applicable to large scale systems such as the absorption column. We present several simulation case studies that demonstrate the effectiveness and applicability of the proposed control algorithm to the absorption column in a post-combustion CO2 capture plant.
Estimation Complete Combustion Coefficient in Rotary Kilns
Authors: Bujak Janusz , Sitarz Piotr , Bujak Krzysztof , Majkowski Sebastian , Pasela Rafał
Published: February 2022

This paper presents a model-based analysis of variability of thermodynamic and chemical parameters in a rotary kiln (RK) during thermal treatment of animal waste. The core process of chemical treatment of waste takes place in RKs; the process involves heating, gasification and partial combustion of the waste. Control over these parameters, and especially the level of complete combustion, determines the quality and efficiency of the process. In operational practice, control and analysis of the variability of process parameters is complicated by the high degree of simultaneity of individual transformations, random disruptions of the process and metrological difficulties resulting from high temperature and chemical activity of the materials being processed. The purpose of preparing the model was to obtain a tool for predicting variability of selected process parameters. By definition, model calculations assume no influence of disturbances on output values, which makes it possible to acquire accurate results that can be compared with corresponding empirically obtained data. The result of the analyses conducted is a theoretical model of the analysed process and a graphical presentation of the calculation results in the form of graphs and charts. A formula for calculating the level of complete combustion and the results of calculation of this index on the basis of empirical data from an industrial waste incineration plant are also presented herein. The presented model is a useful tool providing an insight into interdependencies between selected process parameters and facilitating design of corrective actions oriented towards process optimisation.
Low-Cost Sensors for Indoor PV Energy Harvesting Estimation Based on Machine Learning
Authors: Politi Bastien , Foucaran Alain , Camara Nicolas
Published: February 2022

With the number of communicating sensors linked to the Internet of Things (IoT) ecosystem increasing dramatically, well-designed indoor light energy harvesting solutions are needed. A first step in this direction would be to be able to accurately estimate the harvestable energy in a specific light environment. However, inside, this energy varies in spectral composition and intensity, depending on the emission source as well as the time of day. These challenging conditions mean that it has become necessary to obtain accurate information about these variations and determine their impact on energy recovery performance. In this context, this manuscript presented a method to apply an innovative energy harvesting estimation method to obtain practical and accurate insight for the design of energy harvesting systems in indoor environments. It used a very low-cost device to obtain spectral information and fed it to supervised machine learning classification methods to recognize light sources. From the recognized light source, a model developed for flexible GaAs solar cells was able to estimate the harvestable energy. To validate this method in real indoor conditions, the estimates were compared to the energy harvested by an energy harvesting prototype. The mean absolute error percentage between estimates and the experimental measurements was less than 5% after more than 2 weeks of observation. This demonstrated the potential of this low-cost estimation system to obtain reliable information to design energetically autonomous devices.
Polarization Voltage Characterization of Lithium-Ion Batteries Based on a Lumped Diffusion Model and Joint Parameter Estimation Algorithm
Authors: Xia Bizhong , Ye Bo , Cao Jianwen
Published: February 2022

Polarization is a universal phenomenon that occurs inside lithium-ion batteries especially during operation, and whether it can be accurately characterized affects the accuracy of the battery management system. Model-based approaches are commonly adopted in studies of the characterization of polarization. Towards the application of the battery management system, a lumped diffusion model with three parameters was adopted. In addition, a joint algorithm composed of the Particle Swarm Optimization algorithm and the Levenberg-Marquardt method is proposed to identify model parameters. Verification experiments showed that this proposed algorithm can significantly improve the accuracy of model output voltages compared to the Particle Swarm Optimization algorithm alone and the Levenberg-Marquardt method alone. Furthermore, to verify the real-time performance of the proposed method, a hardware implementation platform was built, and this system’s performance was tested under actual operating conditions. Results show that the hardware platform is capable of realizing the basic function of quantitative polarization voltage characterization, and the updating frequency of relevant parameters can reach 1 Hz, showing good real-time performance.
A Forecasting Method for Macro-Control Policy of Heating Energy Consumption and Carbon Emissions Based on Building Area and Energy Intensity: A Case Study of Northern China
Authors: Zheng Yu , Yin Wenlong , Zhang Wenjie , Liang Jinhan , Liu Kangyong , Wang Kuan
Published: February 2022

In response to extreme climate change, China has set a goal of reaching emission peak by 2030 and achieving carbon neutrality by 2050. Energy conservation and emission reduction of building heating in northern China are key to achieving this goal. Based on building area prediction and energy consumption intensity, this paper establishes a model for calculating heating energy consumption and carbon emissions in northern residential buildings at the macro level, which provides a basis for formulating policies related to heating and emission reduction in northern buildings. Based on the research method of scenario projection, combining the carbon emission subsets and future heating energy mix projections in northern China, the heating energy consumption in northern China decreases to 175, 149 and 135 Mtce in 2050 under the baseline, medium control and strict control scenarios, respectively. The heating energy consumption in the northern region should be controlled at least under the medium control scheme. Under this scenario, building heating carbon emissions in the north could be reduced to 450 MtCO2 by 2050, or 280 MtCO2 if more stringent abatement technologies are adopted. In order to achieve this goal, a combination of energy-saving technologies must be used. The use of biomass and solar technologies should be emphasized in rural heating, while envelope renovation makes the greatest contribution to heating energy savings, with envelope renovation contributing up to 92 Mtce to urban heating.
The Fire Resistance and Heat Conductivity of Natural Construction Material Based on Straw and Numerical Simulation of Building Energy Demand
Authors: Janowska-Renkas Elżbieta , Król Anna , Pochwała Sławomir , Pałubski Dawid , Adamska Małgorzata , Klementowski Igor
Published: February 2022

The motivation for research to help address climate change is a continuous process of searching for eco-friendly materials in the building industry, which will allow minimizing the negative impact of this sector on the environment. The main objective of the paper is to assess the properties of a natural resource such as straw as an eco-friendly material in various variants for use in low-energy demand construction. The research results will fill the knowledge gap in the field of numerical analyses of the energy demand of straw material buildings based on the results of the conducted laboratory tests. A test of a heat transfer coefficient was conducted with different orientation of straw stalks. Then, samples were subject to a fire resistance test to determine material behavior at 1000 °C. During the fire resistance test, the clay-based plaster was ‘burnt out’, which hardened its structure, effectively preventing flames from reaching the insulation layers in the form of straw stalks. As a result of shrinkage (no plaster mesh), the plaster cracked and turned brick-red in color. The insulation layer of straw under the plaster was charred to a depth of 3.0 mm due to the high temperature. However, when the torch was turned off, no fire spread was observed in any layer of the sample. The 3D models of the buildings were created for different eco-friendly materials applied to make external walls. The results of numerical simulation allowed determining the amount of final energy needed to heat the designed building at the level of 26.38 (kWh/m2·year). Conclusions of the above-mentioned tests indicate very good thermal insulating properties determined using the lambda coefficient of 0.069 (W/m·K) and the possible application of straw bales as an alternative for conventional construction. Research has proven that it is possible to construct a building with low energy requirements using natural, easily available waste and completely biodegradable material.
Production and Economic Assessment of Synthetic Fuels in Agriculture—A Case Study from Northern Germany
Authors: Fuchs Clemens , Meyer Drees , Poehls Axel
Published: February 2022

A climate-friendly and CO2-neutral energy supply for agricultural farms is the subject of investigation of this study. The supply concerns the internal economy (buildings and animal husbandry) as well as the production of synthetic fuels for outdoor work (cultivation of the fields). This energy is in demand with many customers, e.g., the dairy cooperative Arla Foods, whose goal is the production of cow’s milk with net-zero CO2 emissions by the year 2050. The operational energy system considered here included renewable electricity generation, covering electricity consumption in the cowshed, battery storage for times without electricity generation, the production of synthetic fuels and feeding into the public power grid. Fluctuations depending on the day and the season were taken into account for electricity at 15-min intervals and for fuel per calendar week for one year. The aim was to determine the necessary capacities of renewable energy (RE) generation systems and production systems for synthetic fuel, as well as an economic evaluation with the calculation of the energy costs per kWh and the break-evens for the capital expenses (CapEx). Two different scenarios were developed using the example of a survey dairy farm with an annual electricity consumption of approximately 80,000 kWh in the cowshed and an annual diesel consumption of 35,000 L, corresponding to 350,000 kWh for field work. To ensure the energy supply, Scenario 1 required a photovoltaic system (PV) on the roof with an output of 125 kWp, a 250 kW small wind turbine, a battery with a storage capacity of 2 kWh and synthetic fuel production with an output of 210 kW. Scenario 2 required a 200 kWp PV system on the roof and a 520 kWp PV system in the open fields, a battery with a 105 kWh storage capacity and a synthetic fuel production facility with an output of 385 kW to cover the farm’s energy needs. The results showed that a farm’s own electricity production is currently profitable; however, a farm’s production of synthetic fuel still has comparatively high costs and therefore is not yet profitable. Further technical advances, rising prices of fossil fuels and economies of scale, e.g., larger cooperatively-operated plants, could help new technology to make a breakthrough.