bluuebunny/crossref_metadata_2025 huggingface dataset:
Food Reward Alterations during Obesity Are Associated with Inflammation in the Striatum in Mice: Beneficial Effects of Akkermansia muciniphila
Authors: Huwart Sabrina J. P. , de Wouters d’Oplinter Alice , Rastelli Marialetizia , Van Hul Matthias , de Vos Willem M. , Luquet Serge , Cani Patrice D. , Everard Amandine
Published: August 2022

The reward system involved in hedonic food intake presents neuronal and behavioral dysregulations during obesity. Moreover, gut microbiota dysbiosis during obesity promotes low-grade inflammation in peripheral organs and in the brain contributing to metabolic alterations. The mechanisms underlying reward dysregulations during obesity remain unclear. We investigated if inflammation affects the striatum during obesity using a cohort of control-fed or diet-induced obese (DIO) male mice. We tested the potential effects of specific gut bacteria on the reward system during obesity by administrating Akkermansia muciniphila daily or a placebo to DIO male mice. We showed that dysregulations of the food reward are associated with inflammation and alterations in the blood–brain barrier in the striatum of obese mice. We identified Akkermansia muciniphila as a novel actor able to improve the dysregulated reward behaviors associated with obesity, potentially through a decreased activation of inflammatory pathways and lipid-sensing ability in the striatum. These results open a new field of research and suggest that gut microbes can be considered as an innovative therapeutic approach to attenuate reward alterations in obesity. This study provides substance for further investigations of Akkermansia muciniphila-mediated behavioral improvements in other inflammatory neuropsychiatric disorders.
The Effects of Shear Force-Based Processing of Lipoaspirates on White Adipose Tissue and the Differentiation Potential of Adipose Derived Stem Cells
Authors: Eigenberger Andreas , Felthaus Oliver , Schratzenstaller Thomas , Haerteis Silke , Utpatel Kirsten , Prantl Lukas
Published: August 2022

Autologous lipotransfer is a promising method for tissue regeneration, because white adipose tissue contains a heterogeneous cell population, including mesenchymal stem cells, endothelial cells, immune cells, and adipocytes. In order to improve the outcome, adipose tissue can be processed before application. In this study, we investigated changes caused by mechanical processing. Lipoaspirates were processed using sedimentation, first-time centrifugation, shear-force homogenization, and second-time centrifugation. The average adipocyte size, stromal vascular cell count, and adipocyte depot size were examined histologically at every processing step. In addition, the adipose derived stem cells (ADSCs) were isolated and differentiated osteogenically and adipogenically. While homogenization causes a disruption of adipocyte depots, the shape of the remaining adipocytes is not changed. On average, these adipocytes are smaller than the depot adipocytes, they are surrounded by the ECM, and therefore mechanically more stable. The volume loss of adipocyte depots leads to a significant enrichment of stromal vascular cells such as ADSCs. However, the mechanical processing does not change the potential of the ADSCs to differentiate adipogenically or osteogenically. It thus appears that mechanically processed lipoaspirates are promising for the reparation of even mechanically stressed tissue as that found in nasolabial folds. The changes resulting from the processing correspond more to a filtration of mechanically less stable components than to a manipulation of the tissue.
The Critical Role of Hypoxia in the Re-Differentiation of Human Articular Chondrocytes
Authors: Martinez-Armenta Carlos , Suarez-Ahedo Carlos , Olivos-Meza Anell , Camacho-Rea María C. , Martínez-Gómez Laura E. , Jimenez-Gutierrez Guadalupe Elizabeth , Martínez-Nava Gabriela A. , Gomez-Quiroz Luis E. , Pineda Carlos , López-Reyes Alberto
Published: August 2022

The preservation of the chondrogenic phenotype and hypoxia-related physiological microenvironment are major challenges in the 2D culture of primary human chondrocytes. To address this problem, we develop a 3D culture system generating scaffold-free spheroids from human chondrocytes. Our results highlight the chondrogenic potential of cultured human articular chondrocytes in a 3D system combined with hypoxia independently of the cartilage source. After 14 days of culture, we developed spheroids with homogenous diameter and shape from hyaline cartilage donors. Spheroids generated in hypoxia showed a significantly increased glycosaminoglycans synthesis and up-regulated the expression of SOX9, ACAN, COL2A1, COMP, and SNAI1 compared to those obtained under normoxic conditions. Therefore, we conclude that spheroids developed under hypoxic conditions modulate the expression of chondrogenesis-related genes and native tissue features better than 2D cultures. Thus, this scaffold-free 3D culture system represents a novel in vitro model that can be used for cartilage biology research.
Continuous Flow Synthesis of N-Doped Carbon Quantum Dots for Total Phenol Content Detection
Authors: Guo Shangxin , Lan Jing , Liu Bo , Zheng Baixiu , Gong Xingchu , Fan Xiaohui
Published: August 2022

The carbon quantum dot (CQD) paper-based analytical device (PAD) has drawn great attention and is being intensively explored. However, the construction of a continuous flow CQD synthesis device remains challenging. In this work, a continuous flow reaction apparatus was constructed to synthesize nitrogen-doped CQDs using a mixed-solvent system of tetraethylene glycol and water. The optical properties of the CQDs were characterized. The CQDs were found to be quenched by phenolics such as chlorogenic acid, salvianolic acid B, and rutin. The CQD PAD was prepared for the determination of the total phenolic content of honeysuckle extracts. A smartphone was used to test the analytical performance of the CQD PAD. The results demonstrated that the degree of fluorescence quenching of the CQDs showed a linear relationship with the concentration of the added chlorogenic acid solution. This method was compared with the total phenolic assay in the Chinese Pharmacopoeia, and the statistical test showed no significant difference between their results. With aqueous tetraethylene glycol as the solvent for the synthesis, the continuous flow reactor for CQD preparation could be easily set up. The CQD PAD is convenient, cheap, and expected to be used for the rapid quality detection of traditional Chinese medicines.
Influence of Climate on Conflicts and Migrations in Southern Africa in the 19th and Early 20th Centuries
Authors: Tongwane Mphethe I. , Ramotubei Teke S. , Moeletsi Mokhele E.
Published: August 2022

Climate and other environmental factors continue to play important contributions on the livelihoods of communities all over the world. Their influence during historical periods and the roles they played remain under-reported. The main objective of this review is to investigate the climatological conditions during the time of the invasion of early European settlers in Southern Africa in the 19th and early 20th centuries. It establishes the possible relationships between climate variability and historical conflicts and wars, famines, disease pandemics, and the migration of African people to towns in search of sustainable and predictable livelihoods away from unreliable agriculture. A qualitative analysis of published peer reviewed literature in the form of reports, papers, and books was used in this review. At least 60 literature items were reviewed in this paper. There is a relationship between climate variability and the historical events of the 19th and early 20th centuries. Tribal conflicts and most of the wars between the settlers and the African people for land coincided with periods of droughts. Drought were key causes of famines, instabilities, and land degradation in the region. This study highlights the influence of environmental conditions on socio-economic conditions as the world enters an era of climate change and urbanization in developing countries, particularly in Africa. It shows that the hardships caused by environmental conditions have the potential to destabilize societies.
Nanomaterials as Emerging Therapeutics for the Deadly Coronavirus
Authors: Ray Priyanka
Published: August 2022

Since the first reports of a contagious pneumonia such as the disease in China in December 2019, the world has witnessed a situation that very few people have ever seen in their lifetimes [...]
Influence of Powder Plasticity on Bonding Strength of Cold-Sprayed Copper Coating
Authors: Wei Fu-Jun , Chou Bang-Yen , Fung Kuan-Zong , Tsai Shu-Yi , Yang Chung-Wei
Published: August 2022

When cold spraying is performed at a velocity equivalent to or greater than a specific material-dependent critical velocity, powders suffer intensive plastic deformation and localized heating of interacting surfaces. The thermomechanical reaction of the sprayed powder upon impacting the substrate material triggers thermally dependent metallurgical bonding and/or mechanical interlocking mechanisms. In this study, three Cu feedstocks, fabricated through electrolysis (EP), gas-assisted water atomization (WA), and inert gas atomization (GA), were characterized and annealed before cold spraying. The electron back-scattered diffraction technique was used to analyze the grain structure and plastic microstrain within the powders and coatings. The plastic microstrains that originally existed in the Cu powders were released after 30 min of annealing at 500 °C. The influence of plastic deformation behavior (associated with the grain structure and plastic microstrain of powder feedstocks) on the bonding strength of the cold-sprayed Cu coatings on AA6061 aluminum alloy substrates was examined. The results indicate that EP powder with an asymmetric dendrite morphology was not conducive to the intensive plastic deformation that may cause recrystallized twin grains to form after cold spraying. Furthermore, the homogeneous microstructure of the spherical Cu feedstocks, which may be induced by strain release as recrystallized twin grains and low-angle boundary grain growth through annealing, caused the cold-sprayed Cu coating to have high ductility and low hardness. The findings reveal the low strain hardening and residual stress in the cold-sprayed coating—characteristics regarded as providing key advantages for the bonding strength of the coating.
Enriching Semantics of Geometry Features and Parameters for Additive Manufacturing Peculiar Structure Based on STEP Standards
Authors: Xiao Jinhua , Lei Yang
Published: August 2022

Owing to the requirements of the AM system integration and standardization for an AM part structure, the AM features and parameters need to extend their related data entities for better information exchange and sharing based on STEP-NC Part 17 for additive manufacturing. In this paper, we propose an architecture to transfer the manufacturing layer feature and process parameter information among the CAD/CAPP/CAM systems. We classify the AM layer features into four: general geometry feature, foam structure feature, honeycomb structure feature, and lattice structure feature. These features include detailed parameters and a physical performance that represent specific feature data with related entity definitions and relation descriptions. The process information specifies the optimal process parameters that provide the possibility for optimization data interoperability in various application systems. Based on the concepts of the manufacturing layer feature and process parameters in AM, we simultaneously present the specific STEP/STEP-NC-compliant data model to represent the AM layer feature and process parameter information exchange. Absolutely, we also give the conformance analysis and implementation for each application object and the data entities in the interoperability process.
Treatment Strategies for Residual Disease following Neoadjuvant Chemotherapy in Patients with Early-Stage Breast Cancer
Authors: Abdel-Razeq Hikmat , Khalil Hanan , Assi Hazem I. , Dargham Tarek Bou
Published: August 2022

Breast cancer continues to be the most diagnosed cancer among women worldwide. Neoadjuvant chemotherapy is the standard of care for breast cancer patients with locally advanced disease and patients with poor pathological features, such as triple-negative (TN) or human epidermal growth factor receptor-2 (HER2)-positive subtypes. Neoadjuvant therapy offers several advantages, including better surgical outcomes, early systemic treatment for micro-metastases, and accurate tumor biology and chemosensitivity assessment. Multiple studies have shown that achieving pathological complete response (pCR) following neoadjuvant chemotherapy is associated with better prognosis and better treatment outcomes; almost half of such patients may fail to achieve pCR. Tumor proliferative index, hormone receptor (HR) status, and HER2 expression are the major predictors of pCR. Strategies to improve pCR have been dependent on augmenting neoadjuvant chemotherapy with the addition of taxanes and dual anti-HER2 targeted therapy in patients with HER2-positive tumor, and more recently, immunotherapy for patients with TN disease. The clinical management of patients with residual disease following neoadjuvant chemotherapy varies and depends mostly on the level of HR expression and HER2 status. Recent data have suggested that switching trastuzumab to trastuzumab-emtansine (T-DM1) in patients with HER2-positive disease and the addition of capecitabine for patients with HER2-negative and HR-negative subtype is associated with a better outcome; both strategies are incorporated into current clinical practice guidelines. This paper reviews available and ongoing studies addressing strategies to better manage patients who continue to have residual disease following neoadjuvant chemotherapy.
An Analysis of Vocal Features for Parkinson’s Disease Classification Using Evolutionary Algorithms
Authors: Dao Son V. T. , Yu Zhiqiu , Tran Ly V. , Phan Phuc N. K. , Huynh Tri T. M. , Le Tuan M.
Published: August 2022

Parkinson’s Disease (PD) is a brain disorder that causes uncontrollable movements. According to estimation, roughly ten million individuals worldwide have had or are developing PD. This disorder can have severe consequences that affect the patient’s daily life. Therefore, several previous works have worked on PD detection. Automatic Parkinson’s Disease detection in voice recordings can be an innovation compared to other costly methods of ruling out examinations since the nature of this disease is unpredictable and non-curable. Analyzing the collected vocal records will detect essential patterns, and timely recommendations on appropriate treatments will be extremely helpful. This research proposed a machine learning-based approach for classifying healthy people from people with the disease utilizing Grey Wolf Optimization (GWO) for feature selection, along with Light Gradient Boosted Machine (LGBM) to optimize the model performance. The proposed method shows highly competitive results and has the ability to be developed further and implemented in a real-world setting.
Radiotherapy to the Primary Tumor: The First Step of a Tailored Therapy in Metastatic Prostate Cancer
Authors: Ferro Matteo , Crocetto Felice , Lucarelli Giuseppe , Lievore Elena , Barone Biagio
Published: August 2022

Prostate cancer is the first most frequent cancer in men worldwide, with over 250,000 estimated new cases diagnosed in 2021 [...]
Refractory Salmonella Prosthetic Valve Endocarditis Complicated by Splenic Infarction and Aortic Pseudoaneurysm in a Patient with Double Prosthetic Valves: A Case Report
Authors: Alhamadh Moustafa S. , Alanazi Rakan B. , Alhowaish Thamer Saad , Alhabeeb Abdulrahman Yousef , Algarni Sultan T. , Wadaan Osama Mohaamad , Suliman Ihab , Al-Ghamdi Mohammed Ghormalla
Published: August 2022

Endocarditis is an extremely rare complication of Salmonellosis with an incidence of 0.2–0.4%. It is a destructive and invasive infection that follows a highly complicated course and carries a high mortality rate that exceeds 45%. Multiple predisposing factors for Salmonella endocarditis have been described in the literature, including human immunodeficiency virus infection, congenital heart diseases, and the presence of a prosthetic valve. Herein, we report a case of Salmonella prosthetic valve endocarditis complicated by splenic infarction and aortic pseudoaneurysm presenting as a month-long history of fluctuating fever, chills, and rigors, accompanied by occasional cough and shortness of breath in a 55-year-old female with aortic and mitral valves replacement and multiple comorbidities. She was diagnosed by multiple radiographic studies and successfully treated with the Commando procedure and a long course of IV antibiotics.
Research of the Algebraic Multigrid Method for Electron Optical Simulator
Authors: Wang Zhi , Hu Quan , Zhu Xiao-Fang , Li Bin , Hu Yu-Lu , Huang Tao , Yang Zhong-Hai , Li Liang
Published: August 2022

At present, electron optical simulator (EOS) takes a long time to solve linear FEM systems. The algebraic multigrid preconditioned conjugate gradient (AMGPCG) method can improve the efficiency of solving systems. This paper is focused on the implementation of the AMGPCG method in EOS. The aggregation-based scheme, which uses two passes of a pairwise matching algorithm and the K-cyle scheme, is adopted in the aggregation-based algebraic multigrid method. Numerical experiments show the advantages and disadvantages of the AMG algorithm in peak memory and solving efficiency. The AMGPCG is more efficient than the iterative methods used in the past and only needs one coarsening when EOS computes the particle motion trajectory.
Machine Learning Methods for Multiscale Physics and Urban Engineering Problems
Authors: Sharma Somya , Thompson Marten , Laefer Debra , Lawler Michael , McIlhany Kevin , Pauluis Olivier , Trinkle Dallas R. , Chatterjee Snigdhansu
Published: August 2022

We present an overview of four challenging research areas in multiscale physics and engineering as well as four data science topics that may be developed for addressing these challenges. We focus on multiscale spatiotemporal problems in light of the importance of understanding the accompanying scientific processes and engineering ideas, where “multiscale” refers to concurrent, non-trivial and coupled models over scales separated by orders of magnitude in either space, time, energy, momenta, or any other relevant parameter. Specifically, we consider problems where the data may be obtained at various resolutions; analyzing such data and constructing coupled models led to open research questions in various applications of data science. Numeric studies are reported for one of the data science techniques discussed here for illustration, namely, on approximate Bayesian computations.
Fault Diagnosis of Power Transformer Based on Time-Shift Multiscale Bubble Entropy and Stochastic Configuration Network
Authors: Chen Fei , Tian Wanfu , Zhang Liyao , Li Jiazheng , Ding Chen , Chen Diyi , Wang Weiyu , Wu Fengjiao , Wang Bin
Published: August 2022

In order to accurately diagnose the fault type of power transformer, this paper proposes a transformer fault diagnosis method based on the combination of time-shift multiscale bubble entropy (TSMBE) and stochastic configuration network (SCN). Firstly, bubble entropy is introduced to overcome the shortcomings of traditional entropy models that rely too heavily on hyperparameters. Secondly, on the basis of bubble entropy, a tool for measuring signal complexity, TSMBE, is proposed. Then, the TSMBE of the transformer vibration signal is extracted as a fault feature. Finally, the fault feature is inputted into the stochastic configuration network model to achieve an accurate identification of different transformer state signals. The proposed method was applied to real power transformer fault cases, and the research results showed that TSMBE-SCN achieved 99.01%, 99.1%, 99.11%, 99.11%, 99.14% and 99.02% of the diagnostic rates under different folding numbers, respectively, compared with conventional diagnostic models MBE-SCN, TSMSE-SCN, MSE-SCN, TSMDE-SCN and MDE-SCN. This comparison shows that TSMBE-SCN has a strong competitive advantage, which verifies that the proposed method has a good diagnostic effect. This study provides a new method for power transformer fault diagnosis, which has good reference value.
Analytic Function Approximation by Path-Norm-Regularized Deep Neural Networks
Authors: Beknazaryan Aleksandr
Published: August 2022

We show that neural networks with an absolute value activation function and with network path norm, network sizes and network weights having logarithmic dependence on 1/ε can ε-approximate functions that are analytic on certain regions of Cd.
From Transparent Cranial Windows to Multifunctional Smart Cranial Platforms
Authors: Yang Nana , Li Qing , Zhang Xinyue , Xu Jingjing , Xu Shengyong , Liu Fengyu
Published: August 2022

In this paper, we briefly reviewed the development of cranial windows and their functions in brain sciences. We demonstrated that a 3D-printed titanium frame coated with a polydimethylsiloxane (PDMS) film could serve as an excellent transparent cranial window for long-period, in vivo optical experiments in mice and rats, and the devices also allowed multiple injections through the elastic PDMS window, without leaking. Our large-area honeycomb structured Ti-PDMS samples had a relative transparent area ratio of over 90% but a mechanical strength close to that of a human skull, showing a promising potential for applications in large animals as multifunctional cranial windows. We also suggested that more functional modules could be integrated in the large-area Ti-PDMS cranial device, thus turning it into a novel wearable smart platform for wireless data communication, electro-probing and brain stimulation, optical imaging, transcranial injection, and so on, for both fundamental research on neuroscience and clinical practices dealing with brain damage and disease.
Trusted and Secure Blockchain-Based Architecture for Internet-of-Medical-Things
Authors: Bhattacharjya Aniruddha , Kozdrój Kamil , Bazydło Grzegorz , Wisniewski Remigiusz
Published: August 2022

The Internet of Medical Things (IoMT) global market has grown and developed significantly in recent years, and the number of IoMT devices is increasing every year. IoMT systems are now very popular and have become part of our everyday life. However, such systems should be properly protected to preventing unauthorized access to the devices. One of the most popular security methods that additionally relies on real-time communication is Blockchain. Moreover, such a technique can be supported by the Trusted Third Party (TTP), which guarantees data immutability and transparency. The research and industrial community has predicted the proliferation of Blockchain-based IoMT (BIoMT), for providing security, privacy, and effective insurance processing. A connected environment comprises some of the unique features of the IoMT in the form of sensors and devices that capture and measure, recognize and classify, assess risk, notify, make conclusions, and take action. Distributed communication is also unique due to the combination of the fact that the Blockchain cannot be tampered with and the Peer-to-Peer (P2P) technique, especially compared to the traditional cloud-based techniques where the reliance of IoMT systems on the centralized cloud makes it somewhat vulnerable. This paper proposes a Blockchain-based technique oriented on IoMT applications with a focus on maintaining Confidentiality, Integrity, and Availability (the CIA triad) of data communication in the system. The proposed solution is oriented toward trusted and secure real-time communication. The presented method is illustrated by an example of a cloud-based hospital application. Finally, the security aspects of the proposed approach are studied and analyzed in detail.
Development of an Electrooculogram (EOG) and Surface Electromyogram (sEMG)-Based Human Computer Interface (HCI) Using a Bone Conduction Headphone Integrated Bio-Signal Acquisition System
Authors: Jo Ha Na , Park Sung Woo , Choi Han Gyeol , Han Seok Hyun , Kim Tae Seon
Published: August 2022

Human–computer interface (HCI) methods based on the electrooculogram (EOG) signals generated from eye movement have been continuously studied because they can transmit the commands to a computer or machine without using both arms. However, usability and appearance are the big obstacles to practical applications since conventional EOG-based HCI methods require skin electrodes outside the eye near the lateral and medial canthus. To solve these problems, in this paper, we report development of an HCI method that can simultaneously acquire EOG and surface-electromyogram (sEMG) signals through electrodes integrated into bone conduction headphones and transmit the commands through the horizontal eye movements and various biting movements. The developed system can classify the position of the eyes by dividing the 80-degree range (from −40 degrees to the left to +40 degrees to the right) into 20-degree sections and can also recognize the three biting movements based on the bio-signals obtained from the three electrodes, so a total of 11 commands can be delivered to a computer or machine. The experimental results showed the interface has accuracy of 92.04% and 96.10% for EOG signal-based commands and sEMG signal-based commands, respectively. As for the results of virtual keyboard interface application, the accuracy was 97.19%, the precision was 90.51%, and the typing speed was 5.75–18.97 letters/min. The proposed interface system can be applied to various HCI and HMI fields as well as virtual keyboard applications.
A Design Methodology of High-Efficiency Dimmable Current Sink for Current-Regulated Drivers
Authors: Abuishmais Ibrahim , Shahroury Fadi R. , Ahmad Hani
Published: August 2022

This paper proposes a high-efficiency and dimmable current sink topology along with a design methodology for low node processes. The design methodology is demonstrated using a boost-based WLED driver application. In this work, the focus is on current regulation rather than voltage regulation. Therefore, the proposed topology exploits a smaller and faster NMOS pass device, replacing the conventional PMOS-based LDO arrangement. An amplifier-boosted pass-transistor current sink topology combined with a 5-bit programmable degenerated source resistor is being utilized for high-efficiency and brightness control. The realized WLED driver validates the proposed topology and the design methodology utilizing 40 nm CMOS TSMC technology. The design takes advantage of the programmability of the resistor to enhance the system’s power efficiency. This programmable resistor enables dimmability via current segmentation with a 1 mA step for a total of 25 mA. For a 500 mV voltage ripple at the DC-DC converter output driving 6 WLEDs with a 3.2 V forward voltage drop each, a worst-case current ripple of 200 µA and simulated efficiency of 97.6% is achieved for optimum pass-transistor size.
Large-Scale Music Genre Analysis and Classification Using Machine Learning with Apache Spark
Authors: Chaudhury Mousumi , Karami Amin , Ghazanfar Mustansar Ali
Published: August 2022

The trend for listening to music online has greatly increased over the past decade due to the number of online musical tracks. The large music databases of music libraries that are provided by online music content distribution vendors make music streaming and downloading services more accessible to the end-user. It is essential to classify similar types of songs with an appropriate tag or index (genre) to present similar songs in a convenient way to the end-user. As the trend of online music listening continues to increase, developing multiple machine learning models to classify music genres has become a main area of research. In this research paper, a popular music dataset GTZAN which contains ten music genres is analysed to study various types of music features and audio signals. Multiple scalable machine learning algorithms supported by Apache Spark, including naïve Bayes, decision tree, logistic regression, and random forest, are investigated for the classification of music genres. The performance of these classifiers is compared, and the random forest performs as the best classifier for the classification of music genres. Apache Spark is used in this paper to reduce the computation time for machine learning predictions with no computational cost, as it focuses on parallel computation. The present work also demonstrates that the perfect combination of Apache Spark and machine learning algorithms reduces the scalability problem of the computation of machine learning predictions. Moreover, different hyperparameters of the random forest classifier are optimized to increase the performance efficiency of the classifier in the domain of music genre classification. The experimental outcome shows that the developed random forest classifier can establish a high level of performance accuracy, especially for the mislabelled, distorted GTZAN dataset. This classifier has outperformed other machine learning classifiers supported by Apache Spark in the present work. The random forest classifier manages to achieve 90% accuracy for music genre classification compared to other work in the same domain.
Numerical Study of Heat and Mass Transfer for Williamson Nanofluid over Stretching/Shrinking Sheet along with Brownian and Thermophoresis Effects
Authors: Zhu Aiguo , Ali Haider , Ishaq Muhammad , Junaid Muhammad Sheraz , Raza Jawad , Amjad Muhammad
Published: August 2022

The purpose of the current study is to investigate the non-Newtonian unsteady Williamson fluid on a stretching/shrinking surface along with thermophoresis and Brownian effects. Basically, the model consists of a time-dependent magnetic field. The fluid is considered to be electrically conducting due to the effect of the external magnetic field. The values of magnetic Reynolds number are so small that the induced magnetic field is assumed to be negligible. In the concentration equation, the effects of Brownian motion and thermophoresis are discussed. Employing the similarity transformations, the governing nonlinear Partial Differential Equations (PDEs) are converted into the Ordinary Differential Equations (ODEs). The resulting ODEs are solved with the combined effects of the Successive Over Relaxation (SOR) method and Finite Difference Method (FDM). The impact of all the including parameters such as suction parameter, injection parameter, stretching/shrinking parameter, the ratio of viscosity, local Weissenberg number, unsteadiness parameter, Eckert number, Prandtl number, Lewis number, Nusselt number, Brownian motion parameter, shear stress, heat transfer rate, and mass transfer rate are analyzed using graphs and tables. Results show that the values of fluid velocity are better for S=8, −S=0, λ=0.3, β*=0.9, Wi=0.3, and Aa=2.0. It is also depicted from the results that the values of boundary layer thickness are better for S=0, −S=−8, λ=0.3,  β*=0.1, Wi=1.5, and Aa=0.25. From the above numeric results, it is concluded that the fluid velocity is reduced and the thermal boundary layer thickness is enhanced by the enhancement of the stretching parameter.
Dynamic Relationship between Green Economy and Energy Utilization Level: Evidence from China
Authors: He You , Zhang Jinrui , Feng Jie , Shi Guoqing
Published: August 2022

Based on the panel data from 30 provinces in China from 2010 to 2020, this paper employs the panel vector autoregression (PVAR) model to investigate the dynamic relationship between a green economy and energy utilization level. The results show that: (1) the green economic development level and energy utilization level of 30 provinces in China have been continuously enhancing in recent years, the increase in green economic development level is higher than energy utilization level, and the geographical characteristics of both levels are significant, decreasing from East to West; (2) the causal relationship between the green economy and the energy utilization level has passed the Granger test; the two have formed a relatively high-level balanced relationship over a long period, showing a benign and orderly development trend; (3) the green economy generates a positive pulse response on energy utilization level in the initial period, but the impulse response weakens in the period of lag 1, entailing the relationship needs to be further strengthened in the long term; (4) in the process of continuous enhancement of energy utilization level, it is difficult to drive economic benefits due to high input costs in the initial stage, but it can form a two-way interaction relationship with a green economy as time goes by.
Control and Design of a Boost-Based Electrolytic Capacitor-Less Single-Phase-Input Drive
Authors: Musetti Alex , Sadegh Lafmejani Hossein , Soldati Alessandro
Published: August 2022

Adjustable-speed drives with single-phase input require a power factor correction front-end, usually implemented by a boost converter, to reduce the current distortion from the uncontrolled rectifier; this stage is then followed by a three-phase inverter. Bulky electrolytic capacitors are used to limit the direct current voltage ripple resulting from the rectification of the single-phase input. This leads to increased system size and shorter lifetime. In this work, the usual boost front-end is exploited to actively control the DC link voltage ripple while limiting the input current distortion and, hence, the power factor, even if not reaching unity. However, Power Factor is greatly improved with respect to the uncontrolled rectifier alone. This approach permits one to reduce the required capacitance, allowing the substitution of the electrolytic capacitor with a long-life low-equivalent-series-resistance film one. A control targeting capacitor voltage level, ripple, and boost inductor peak current is presented, together with practical design models. The synergic control of the boost front-end and of the machine drive is presented as well. The resulting converter is tested with resistive load and permanent-magnet synchronous machine drive, highlighting the advantages and limits of the proposed solution.
Forecasting CO2 Sequestration with Enhanced Oil Recovery
Authors: Ampomah William , McPherson Brian , Balch Robert , Grigg Reid , Cather Martha
Published: August 2022

Over the years, naturally occurring CO2 has been used in many enhanced oil recovery (EOR) projects in the United States [...]
Modelling and Simulation of Heat Pumps for Simultaneous Heating and Cooling, a Special Issue
Authors: Byrne Paul
Published: August 2022

Refrigeration and heat pump systems are used as cooling and heating devices, but each one can also carry out both cooling and heating [...]
Tracking the CO2 Emissions of China’s Coal Production via Global Supply Chains
Authors: Yang Zheqi , Dou Xuming , Jiang Yuqing , Luo Pengfei , Ding Yu , Zhang Baosheng , Tang Xu
Published: August 2022

Coal’s green mining and scientific utilization is the key to achieve the national vision of carbon peak by 2030 and carbon neutrality by 2060. Clarifying the CO2 flow of coal production is the core part of decarbonization. This study uses an environmental extended multi-regional input–output (EEMRIO) model to analyze the impact of embodied emissions on the indirect CO2 emission intensity of coal production between China’s coal mining sector and 141 countries/regions. It is found that the CO2 emission intensity of China’s coal production was 34.14 gCO2/MJ in 2014, while the direct and indirect emission intensities were 16.22 gCO2/MJ and 17.92 gCO2/MJ, respectively. From 2007 to 2014, the direct emission intensity of China’s coal production increased by 23%, while the indirect emission intensity decreased by 30%. The key material and service inputs affecting indirect carbon emissions of coal production in China are electricity service, metal manufacturing, chemical products, coal mining, and transport, which accounted for 85.5% of the total indirect emission intensity of coal production in 2014. Globally, a large portion of CO2 from Chinese coal production is emitted to meet foreign direct and indirect demands for material and service inputs. Policy implications related to this outcome are further discussed in the study.
Biogas and Biohydrogen Production Using Spent Coffee Grounds and Alcohol Production Waste
Authors: Vanyan Liana , Cenian Adam , Trchounian Karen
Published: August 2022

In this study, alternative uses for lignocellulosic waste by considering them a source of eco-friendly and renewable energy generation with the application of the anaerobic digestion of treated and untreated waste for biogas and biohydrogen generation were investigated. The diluted sulfuric acid method was used for both the substrates and inoculum. Hydrogen production was absent when untreated spent coffee grounds (SCG) and alcohol waste (AW) were both used with the inoculum at pH 5.5 and pH 7.5. Meanwhile, the highest biogas yield of 320 dm3 kg V.S−1 was obtained when using AW at pH 7.5, with a 190 dm3 kg V.S−1 yield of methane. Instead, hydrogen production was observed when initially 4% (w/v) and 6% (w/v) SCG-containing hydrolysates were used as the substrates at pH 5.5, yielding 2.9 ± 0.09 dm3 kg V.S−1 and 3.85 ± 0.12 dm3 kg V.S−1, respectively. The further optimization of pretreatment technologies and pH control could lead to increased and prolonged hydrogen production.
Modeling and Analysis of Voltage Harmonic for Three-Level Neutral-Point-Clamped H-Bridge Inverter Considering Dead-Time
Authors: Wu Wen-Jie , Hu Liang-Deng , Xin Zi-Yue , Guo Cheng
Published: August 2022

The advantages of three-level neutral-point-clamped (NPC) H-bridge inverters, such as simple topological structure, low device voltage stress, high equivalent switching frequency, and highly expansible capacity, have made them the preferred choice for inverters matching with medium voltage high-capacity multi-phase open-end winding vessel propulsion motors. To quantitatively evaluate the propulsion motors’ harmonics, electromagnetic vibration, and noise caused by pulse-width modulation (PWM) and device dead-time, it is necessary to research the mathematical modeling of pulse-width modulated output voltage harmonics in consideration of dead-time. In this paper, the principle of the phase-disposition PWM method of the 3L-NPC H-bridge inverters was firstly introduced. Then, the analytical models of output voltage harmonics with and without considering the effect of dead-time were established based on the double Fourier series approach and the harmonic distribution of the dead-time effect was accurately characterized. On the basis of the above, the experimental platform was established to verify the proposed analytical model. Simulation and experimental results are consistent with the theoretical analysis in low and high-frequency output voltage harmonics, which proves the correctness and the feasibility of the analytical modeling method researched by this paper. This will provide a theoretical basis for subsequent studies, which include the quantitative analysis and the suppression of output harmonics of the H-bridge inverter considering dead-time.
Effect of Working Fluid-Filling Ratio Combination on Thermosyphon Performance as Add-In Enhancer for Indoor Air Conditioning Devices
Authors: Carvajal-Mariscal Ignacio , De León-Ruiz Jorge E. , Vázquez-Arenas Jorge , Venegas María
Published: August 2022

An experimental study is presented to account for the implementation of a two-phase closed thermosyphon pipe, for energy-saving purposes, in air conditioning systems in the context of COVID-19. The experimental setup consisted of a 0.5 m × 0.0127 m type L copper pipe which was employed as the body of the heat exchanger; an electric resistance heater of 0.1 m length located at the bottom; and a 0.25 m length water-cooled concentric condenser located at the top. The evaluation was conducted employing acetone, ethanol, and distilled water as working fluids; ranging the heat supplied at the evaporator from 25 to 125 W and the filling ratio from 20% to 40% of the total inner volume of the thermosyphon. From the data obtained, it was found that ethanol is the working fluid most susceptible to changes in operation conditions. Contrarily, distilled water was found to deliver consistent performance, up to a point that, for the analysed setup, it is considered to be independent of both, heat flow supplied at the evaporator and thermosyphon filling ratio. Meanwhile, acetone was found to be the only fluid tested that displays a directly proportional behaviour between heat absorption and dissipation. From compiling experimental data, response surfaces were constructed and used as direct and rough optimization tools. The information provided by this approach is considered to be particularly useful and is introduced for modelling and design purposes. Based on the results, it was found that acetone, within operation ranges of 34%<ϕ<40% and 75 W<Q˙Evap<125 W, was the most suitable working fluid to use in a two-phase closed thermosyphon for energy-saving purposes in air conditioning applications.
Sizing of an Island Standalone Hybrid System Considering Economic and Environmental Parameters: A Case Study
Authors: Chowdhury Tamal , Hasan Samiul , Chowdhury Hemal , Hasnat Abul , Rashedi Ahmad , Asyraf M. R. M. , Hassan Mohamad Zaki , Sait Sadiq M.
Published: August 2022

Due to the significance of environmental aspects, the modeling of hybrid systems should be performed with the lowest cost and environmental pollution. Therefore, an effective and optimum sizing method can ensure acceptable performance. This paper implements a “technique for order performance by similarity to the ideal solution” (TOPSIS) method combined with the “analytic hierarchy process (AHP)” method to size a standalone system based on techno-economic parameters. For this reason, a survey was conducted to collect local load data on Monpura Island, located in Bhola, Bangladesh. Visible and design faults of the existing PV/diesel mini-grid have also been identified. Five alternative hybrid configurations have been considered as to evaluate the best optimum system. Two economic and one environmental criterion was used to size the system. Two experts specialized in energy systems evaluated the criteria and proposed the suitable system. Battery, wind and PV capital cost multipliers have been considered as to perform sensitivity analysis. According to techno-economic analysis and expert opinion, PV/biogas/wind has been found to be the most appropriate system among these configurations. The system has a cost of electricity (COE) of 0.691 (USD/kWh) and emits only 4.43 kg of CO2 per year. The net present cost of the proposed system is 18% lower than the existing microgrid, and the model has lower emissions due to high renewable penetration. It was also found that integrating wind can significantly reduce battery capacity in the mini-grid. The proposed system consumes 34% less batteries than the existing system. Implementing this optimum system can result in greater benefit to the local people.
Biomass Waste for Energy Production
Authors: Monteiro Eliseu , Ferreira Sérgio
Published: August 2022

Environmental problems associated with global energy supply systems and the increasing amount of global solid waste production are triggering a shift towards a greater reliance on biomass waste. Waste-to-energy systems have become important for industries and scientists because of the increasing interest in energy production from waste, due to improved efficiency and cost-effective solutions. The shift to biomass is also essential for industries to use their own waste to produce their own energy, which is in line with circular economy concepts. This Special Issue “Biomass Wastes for Energy Production” of Energies comprises ten (10) papers, including one review article, that represent the latest advances of waste-to-energy technologies and contribute to the rethinking of global energy supply systems. The Guest Editor also highlights other relevant topics that fall beyond the coverage of the published articles.
Efficiency and Performance Optimization of State-of-the-Art “Multi-Phase, -Level, -Cell, -Port, -Motor” Electrical Drives and Renewable Energy Systems
Authors: Loncarski Jelena , Monopoli Vito Giuseppe , Monteiro Vitor , Ristic Leposava , Jovanović Milutin
Published: August 2022

This Special Issue was intended to consolidate the most recent advances in the field of power electronics for electric drives and renewable energy sources [...]
Experimental and Computational Approaches for Non-CpG Methylation Analysis
Authors: Ramasamy Deepa , Rao Arunagiri Kuha Deva Magendhra , Rajkumar Thangarajan , Mani Samson
Published: August 2022

Cytosine methylation adjacent to adenine, thymine, and cytosine residues but not guanine of the DNA is distinctively known as non-CpG methylation. This CA/CT/CC methylation accounts for 15% of the total cytosine methylation and varies among different cell and tissue types. The abundance of CpG methylation has largely concealed the role of non-CpG methylation. Limitations in the early detection methods could not distinguish CpG methylation from non-CpG methylation. Recent advancements in enrichment strategies and high throughput sequencing technologies have enabled the detection of non-CpG methylation. This review discusses the advanced experimental and computational approaches to detect and describe the genomic distribution and function of non-CpG methylation. We present different approaches such as enzyme-based and antibody-based enrichment, which, when coupled, can also improve the sensitivity and specificity of non-CpG detection. We also describe the current bioinformatics pipelines and their specific application in computing and visualizing the imbalance of CpG and non-CpG methylation. Enrichment modes and the computational suites need to be further developed to ease the challenges of understanding the functional role of non-CpG methylation.
Cypress Wood and Bark Residues Chemical Characterization and Utilization as Fuel Pellets Feedstock
Authors: Terzopoulou Paschalina , Kamperidou Vasiliki , Lykidis Charalampos
Published: August 2022

In order to meet the growing demand for raw material of solid biofuels, it is imperative to find alternative materials of low cost, underutilized so far. In this study, wood and bark material of two common cypress species (Mediterranean and Arizona cypress) were chemically characterized through gravimetric and spectroscopic (FTIR) analyses, to assess their potential to be used as raw materials in the production of fuel pellets. Low bark concentrations (0%, 2%, and 7%) were applied, and the mixtures were densified in a flat-die pellet press. The produced pellets were examined in terms of thermal, physical, hygroscopic, and mechanical properties, using standard ISO17225 thresholds as benchmark. The results revealed that the effect of bark presence in low content οn pellet properties and quality was positive. The ash content of both wood species is adequately low for biofuels production, whereas their bark cannot be purely used as feedstock due to the high ash content. By using low bark contents (2% or 7%), the ash content of pellets was kept adequately low to be categorized in the highest quality classes (A1 and A2: for residential applications), while the produced pellets demonstrated improved dimensional stability, mechanical durability, and slightly improved calorific value. The moisture content, dimensions, and bulk density of all the produced pellet categories fulfilled the standard requirements. Even though the pellets of 2% bark share presented much lower ash contents, only the pellets of 7% bark share were proven to have considerably improved mechanical durability, suitable for residential use. The chemical composition of raw materials (especially the extractives and holocellulose) plays a major role in the mechanical durability of pellets.