bluuebunny/crossref_metadata_2025 huggingface dataset:
Applications of Plasma-Activated Liquid in the Medical Field
Authors: Kim Sungryeal , Kim Chul-Ho
Published: November 2021

Much progress has been made since plasma was discovered in the early 1900s. The first form of plasma was thermal type, which was limited for medical use due to potential thermal damage on living cells. In the late 1900s, with the development of a nonthermal atmospheric plasma called cold plasma, profound clinical research began and ‘plasma medicine’ became a new area in the academic field. Plasma began to be used mainly for environmental problems, such as water purification and wastewater treatment, and subsequent research on plasma and liquid interaction led to the birth of ‘plasma-activated liquid’ (PAL). PAL is currently used in the fields of environment, food, agriculture, nanoparticle synthesis, analytical chemistry, and sterilization. In the medical field, PAL usage can be expanded for accessing places where direct application of plasma is difficult. In this review, recent studies with PAL will be introduced to inform researchers of the application plan and possibility of PAL in the medical field.
Demographic and Epidemiological Contributions to Recent Trends in Cancer Incidence in Hong Kong
Authors: Wong Irene Oi Ling , Lam Yan Ting , Lam Kwok Fai , Cowling Benjamin John , Leung Gabriel Matthew
Published: November 2021

Background: Hong Kong has an ageing Chinese population with high life expectancy and a rising number of cancer cases. While population ageing could lead to higher incidence, we aim to quantify the demographic and epidemiological contributions to this trend by disentangling the effect of these factors. Methods: We analysed secular trends of cancer incidences of all cancer sites combined, including the five top cancers in men and women in Hong Kong in 1983–2017, by disentangling effects of demographics (ageing population and population growth) and cancer risk/rate change using the RiskDiff methodology. Results: Overall, age-standardised incidences of all cancers combined in women and in men declined over the study period (−5.3% for women, −30.2% for men), but total incident cancer case counts increased dramatically (156.5% for women, 96% for men). This increase was primarily due to ageing and increasing population (95% age, 66.1% growth for women, and 119.4% age, 25.4% growth for men), while disease risk for all cancers combined has a decreasing trend (−4.5% for women and −48.8% for men). For the site-specific risk changes among the most five common cancer types, there were increases in risks of prostate and colorectal cancers in men, and breast, endometrial, and thyroid cancers in women. Conclusion: Demographic changes and ageing in our Chinese population resulted in a marked increase in the number of cancer diagnoses in Hong Kong in past decades. The surge in incident case counts overall is expected to stress the healthcare system in terms of the increased demand of healthcare professionals. Cancer surveillance should be enhanced in view of the growing demand from older patients and the cancer types with fast-increasing incidence rates in our population.
Mapping the Effects of Potassium on Fuel Conversion in Industrial-Scale Fluidized Bed Gasifiers and Combustors
Authors: Berdugo Vilches Teresa , Maric Jelena , Thunman Henrik , Seemann Martin
Published: November 2021

Potassium (K) is a notorious villain among the ash components found in the biomass, being the cause of bed agglomeration and contributing to fouling and corrosion. At the same time, K is known to have catalytic properties towards fuel conversion in combustion and gasification environments. Olivine (MgFe silicate) used as gasifier bed material has a higher propensity to form catalytically active K species than traditional silica sand beds, which tend to react with K to form stable and inactive silicates. In a dual fluidized bed (DFB) gasifier, many of those catalytic effects are expected to be relevant, given that the bed material becomes naturally enriched with ash elements from the fuel. However, a comprehensive overview of how enrichment of the bed with alkali affects fuel conversion in both parts of the DFB system is lacking. In this work, the effects of ash-enriched olivine on fuel conversion in the gasification and combustion parts of the process are mapped. The work is based on a dedicated experimental campaign in a Chalmers DFB gasifier, wherein enrichment of the bed material with K is promoted by the addition of a reaction partner, i.e., sulfur, which ensures K retention in the bed in forms other than inactive silicates. The choice of sulfur is based on its affinity for K under combustion conditions. The addition of sulfur proved to be an efficient strategy for capturing catalytic K in olivine particles. In the gasification part, K-loaded olivine enhanced the char gasification rate, decreased the tar concentration, and promoted the WGS equilibrium. In the combustion part, K prevented full oxidation of CO, which could be mitigated by the addition of sulfur to the cyclone outlet.
Bimetallic Cu/Fe Catalysts for Ibuprofen Mineralization
Authors: Hussain Sajid , Aneggi Eleonora , Goi Daniele , Trovarelli Alessandro
Published: November 2021

At present, the use of conventional wastewater processes is becoming increasingly challenging, mainly due to the presence of biorecalcitrant organic matter. Advanced oxidation processes such as Fenton, Fenton-like and hybrid processes have been successfully employed for the treatment of highly concentrated and toxic non-biodegradable pollutants. Here, a series of bimetallic catalysts, based on Cu/Fe supported over ZrO2, were investigated for the mineralization of ibuprofen with a heterogeneous Fenton-like reaction. The materials were prepared by incipient wetness impregnation and characterized by standard techniques. Temperature-programmed experiments highlighted the promotion of the reduction in CuO due to the synergistic effects of the coupled redox cycles of copper (Cu2+/Cu+) and iron (Fe+3/Fe+2). 5%Cu-5%Fe/ZrO2 not only displays the highest ibuprofen mineralization (83%) under optimum conditions but also exploits its activity in a wider range of pH (3–5) with extremely low metal leaching. The recycling of bimetallic catalysts reveals that only the 5%Cu-5%Fe/ZrO2 system is able to provide sustainable activity in heterogeneous Fenton process.
Reactivities of a Prostanoid EP2 Agonist, Omidenepag, Are Useful for Distinguishing between 3D Spheroids of Human Orbital Fibroblasts without or with Graves’ Orbitopathy
Authors: Ida Yosuke , Ichioka Hanae , Furuhashi Masato , Hikage Fumihito , Watanabe Megumi , Umetsu Araya , Ohguro Hiroshi
Published: November 2021

Background. To obtain new insights into the activation of the thyroid-stimulating hormone (TSH) and insulin-like growth factor 1 (IGF-1) receptors in human orbital fibroblasts (n-HOFs), the effects of the prostanoid EP2 agonist, omidenepag (OMD), and a rho-associated coiled-coil-containing protein kinase (ROCK) inhibitor, ripasudil (Rip) were evaluated using three-dimension (3D) n-HOFs spheroids in the absence and presence of the recombinant human TSH receptor antibodies, M22 and IGF-1. Methods. The effects of 100 nM OMD or 10 μM Rip on the physical properties, size, stiffness, and mRNA expression of several extracellular matrix (ECM) molecules, their regulator, inflammatory cytokines, and endoplasmic reticulum (ER) stress-related factors were examined and compared among 3D spheroids of n-HOFs, M22-/IGF-1-activated n-HOFs and GO-related human orbital fibroblasts (GHOFs). Results. The physical properties and mRNA expressions of several genes of the 3D n-HOFs spheroids were significantly and diversely modulated by the presence of OMD or Rip. The OMD-induced effects on M22-/IGF-1-activated n-HOFs were similar to the effects caused by GHOHs, but quite different from those of n-HOFs. Conclusions. The findings presented herein indicate that the changes induced by OMD may be useful in distinguishing between n-HOFs and GHOFs.
Acute Myelopathy in Childhood
Authors: Bravar Giulia , Luchesa Smith Aphra , Siddiqui Ata , Lim Ming
Published: November 2021

Acute myelopathy presenting in childhood can be clinically classified based on the location of injury (with resulting spinal syndrome) or the cause (broadly traumatic or non-traumatic). Types of nontraumatic myelopathy include ischaemic, infectious, inflammatory, nutritional, and metabolic causes, some of which may be part of a systemic illness such as systemic lupus erythematosus or a demyelinating disease such as multiple sclerosis. Nonaccidental injury is an important consideration in cases of traumatic myelopathy, which may often be associated with other injuries. Assessment should include neuroimaging of the brain and spinal cord, with further investigations targeted based on the most likely differential diagnoses; for example, a child with suspected demyelinating disease may require specialist cerebrospinal fluid and serological testing. Management also will differ based on the cause of the myelopathy, with several of these treatments more efficacious with earlier initiation, necessitating prompt recognition, diagnosis, and treatment of children presenting with symptoms of a myelopathy. Important components of holistic care may include physiotherapy and occupational therapy, with multidisciplinary team involvement as required (for example psychological support or specialist bowel and bladder teams).
Evolution of Beak and Feather Disease Virus across Three Decades of Conservation Intervention for Population Recovery of the Mauritius Parakeet
Authors: Fogell Deborah J. , Tollington Simon , Tatayah Vikash , Henshaw Sion , Naujeer Houshna , Jones Carl , Raisin Claire , Greenwood Andrew , Groombridge Jim J.
Published: November 2021

Emerging infectious diseases (EIDs) are key contributors to the current global biodiversity crisis. Psittaciformes (parrots) are one of the most vulnerable avian taxa and psittacine beak and feather disease (PBFD) is the most common viral disease in wild parrots. PBFD is caused by the beak and feather disease virus (BFDV), which belongs to the Circoviridae family and comprises a circular, single-stranded DNA genome. BFDV is considered to have spread rapidly across the world and, in 2005, an outbreak of PBFD was documented in the recovering population of the Mauritius parakeet (Alexandrinus eques). The Mauritius parakeet was once the world’s rarest parrot and has been successfully recovered through 30 years of intensive conservation management. Molecular surveillance for the prevalence of BFDV was carried out across a 24-year sample archive spanning the period from 1993 to 2017, and DNA sequencing of positive individuals provided an opportunity to assess patterns of phylogenetic and haplotype diversity. Phylogenetic analyses show variation in the extent of viral diversification within the replicase protein (Rep). Timeseries of BFDV prevalence and number of haplotypes reveal that two subsequent waves of infection occurred in 2010/2011 and 2013/2014 following the initial outbreak in 2005. Continued disease surveillance to determine the frequency and intensity of subsequent waves of infection may benefit future translocation/reintroduction planning. The continued growth of the Mauritius parakeet population despite the presence of BFDV bodes well for its long-term persistence.
Deep Reinforcement Learning for Trading—A Critical Survey
Authors: Millea Adrian
Published: November 2021

Deep reinforcement learning (DRL) has achieved significant results in many machine learning (ML) benchmarks. In this short survey, we provide an overview of DRL applied to trading on financial markets with the purpose of unravelling common structures used in the trading community using DRL, as well as discovering common issues and limitations of such approaches. We include also a short corpus summarization using Google Scholar. Moreover, we discuss how one can use hierarchy for dividing the problem space, as well as using model-based RL to learn a world model of the trading environment which can be used for prediction. In addition, multiple risk measures are defined and discussed, which not only provide a way of quantifying the performance of various algorithms, but they can also act as (dense) reward-shaping mechanisms for the agent. We discuss in detail the various state representations used for financial markets, which we consider critical for the success and efficiency of such DRL agents. The market in focus for this survey is the cryptocurrency market; the results of this survey are two-fold: firstly, to find the most promising directions for further research and secondly, to show how a lack of consistency in the community can significantly impede research and the development of DRL agents for trading.
Saving Resources: SARS-CoV-2 Diagnostics by Real-Time RT-PCR Using Reduced Reaction Volumes
Authors: Bock Sabine , Hoffmann Bernd , Beer Martin , Wernike Kerstin
Published: November 2021

Since the beginning of 2020, the betacoronavirus SARS-CoV-2 is causing a global pandemic of an acute respiratory disease termed COVID-19. The diagnostics of the novel disease is primarily based on direct virus detection by RT-PCR; however, the availability of test kits may become a major bottleneck, when millions of tests are performed per week. To increase the flexibility of SARS-CoV-2 diagnostics, three real-time RT-PCR assays listed on the homepage of the World Health Organization were selected and investigated regarding their compatibility with three different RT-PCR kits. Furthermore, the reaction volume of the PCR chemistry was reduced up to half of the original protocol to make the individual reactions more cost- and resource-effective. When testing dilution series of culture-grown virus, nearly identical quantification cycle values (Cq) were obtained for all RT-PCR assay/chemistry combinations. Regarding the SARS-CoV-2 detection in clinical samples, agreeing results were obtained for all combinations for virus negative specimens and swabs containing high to medium viral genome loads. In cases of very low SARS-CoV-2 genome loads (Cq > 36), inconsistent results were observed, with some test runs scoring negative and some positive. However, no preference of a specific target within the viral genome (E, RdRp, or N) or of a certain chemistry was seen. In summary, a reduction of the reaction volume and the type of PCR chemistry did not influence the PCR sensitivity.
The Tightness of Multipartite Coherence from Spectrum Estimation
Authors: Ding Qi-Ming , Fang Xiao-Xu , Lu He
Published: November 2021

Detecting multipartite quantum coherence usually requires quantum state reconstruction, which is quite inefficient for large-scale quantum systems. Along this line of research, several efficient procedures have been proposed to detect multipartite quantum coherence without quantum state reconstruction, among which the spectrum-estimation-based method is suitable for various coherence measures. Here, we first generalize the spectrum-estimation-based method for the geometric measure of coherence. Then, we investigate the tightness of the estimated lower bound of various coherence measures, including the geometric measure of coherence, the l1-norm of coherence, the robustness of coherence, and some convex roof quantifiers of coherence multiqubit GHZ states and linear cluster states. Finally, we demonstrate the spectrum-estimation-based method as well as the other two efficient methods. We observe that the spectrum-estimation-based method outperforms other methods in various coherence measures, which significantly enhances the accuracy of estimation.
Accessing Active Inference Theory through Its Implicit and Deliberative Practice in Human Organizations
Authors: Fox Stephen
Published: November 2021

Active inference theory (AIT) is a corollary of the free-energy principle, which formalizes cognition of living system’s autopoietic organization. AIT comprises specialist terminology and mathematics used in theoretical neurobiology. Yet, active inference is common practice in human organizations, such as private companies, public institutions, and not-for-profits. Active inference encompasses three interrelated types of actions, which are carried out to minimize uncertainty about how organizations will survive. The three types of action are updating work beliefs, shifting work attention, and/or changing how work is performed. Accordingly, an alternative starting point for grasping active inference, rather than trying to understand AIT specialist terminology and mathematics, is to reflect upon lived experience. In other words, grasping active inference through autoethnographic research. In this short communication paper, accessing AIT through autoethnography is explained in terms of active inference in existing organizational practice (implicit active inference), new organizational methodologies that are informed by AIT (deliberative active inference), and combining implicit and deliberative active inference. In addition, these autoethnographic options for grasping AIT are related to generative learning.
Automatic Detection and Counting of Blood Cells in Smear Images Using RetinaNet
Authors: Drałus Grzegorz , Mazur Damian , Czmil Anna
Published: November 2021

A complete blood count is one of the significant clinical tests that evaluates overall human health and provides relevant information for disease diagnosis. The conventional strategies of blood cell counting include manual counting as well as counting using the hemocytometer and are tedious and time-consuming tasks. This research-based paper proposes an automatic software-based alternative method to count blood cells accurately using the RetinaNet deep learning network, which is used to recognize and classify objects in microscopic images. After training, the network automatically recognizes and counts red blood cells, white blood cells, and platelets. We tested a model trained on smear images and found that the trained model has generalized capabilities. We assessed the quality of detection and cell counting using performance measures, such as accuracy, sensitivity, precision, and F1-score. Moreover, we studied the dependence of the confidence thresholds and the number of learning epochs on the obtained results of recognition and counting. We compared the performance of the proposed approach with those obtained by other authors who dealt with the subject of cell counting and show that object detection and labeling can be an additional advantage in the task of counting objects.
Analysis of International Capital Inflows and Institutional Quality in Emerging Markets
Authors: Nxumalo Immaculate Simiso , Makoni Patricia Lindelwa
Published: November 2021

This study investigates the cointegrating and causality relationships between foreign direct investment (FDI), foreign portfolio investment (FPI) and institutional quality in a sample of 12 emerging market economies for the period from 2007 to 2017. A composite index for institutional quality composed of the Worldwide Governance Indicators was constructed using the Principal Components Analysis (PCA) method. The panel autoregressive distributed lag (ARDL) model and the error correction model (ECM) were applied to assess the cointegrating and causal relationships between the key variables. In addition to finding significant cointegrating relationships between institutional quality and the foreign capital inflows (FDI and FPI), the results confirmed unidirectional causality from FDI and FPI to institutional quality in the long run. The results further suggested that the long-run relationship between the two foreign capital inflows was more of a trade-off nature, dependent upon the dynamics of the institutional environment in the host economy. The recommendations suggested include that emerging markets should continue to open their economies in pursuit of capital inflows, which will reciprocally strengthen their domestic institutional environment. Strengthening institutions could curtail the persistence of institutional weaknesses and insulate emerging economies from the adverse effects of volatile capital flows and, over the long run, enhance capital inflows.
Culture Sustainability through Co-Curricular Learning Program: Learning Batik Cross Review
Authors: Sukadari Sukadari , Huda Miftachul
Published: November 2021

As the application of colored designs on cloth using wax in certain areas in decorating items of clothing, Batik is made through several steps that come from drawing the pattern on the paper followed by imitating the pattern on fabric, which is called ngeblat. The next phase is followed by drawing the pattern using wax, which is called mencanting. The subsequent step is the process of coloring the pattern of Batik, called pencoletan, and then subsequently followed by color-locking on Batik through covering the Batik with wax, namely basic color dyeing. This process is called menembok. The final step is making the panting process through washing, called nglorod. This process should attempt to maintain Batik with cultural sustainability, as its process contains several values, such as discipline, creativity, independence, patriotism, responsibility, cooperation, and environmental care. Based on this background, this paper attempts to examine the Batik’s cultural design and to explore its sustainability through co-curricular school program activities. This study focuses on examining the potential in the process of the application of colored design through elaborating the supporting and interfering factors in a co-curricular learning program of Batik. The analysis was made through several points, namely a co-curricular learning program of Batik for enhancing cultural sustainability, a co-curricular learning program of Batik for enhancing national culture and community responsibility, and co-curricular learning of Batik for sustainability and environmental accountability.
Engaging Ethnic-Diverse Students: A Research Based on Culturally Responsive Teaching for Roma-Gypsy Students
Authors: Meléndez-Luces Jennifer , Couto-Cantero Pilar
Published: November 2021

Intercultural Education is a key feature in the development of inclusion strategies aimed at ethnically diverse students. Transformative approaches towards learning such as Culturally Responsive Teaching (CRT) are essential in order to answer the educative needs that arise due to the coexistence between ethnic minorities and mainstream society. Therefore, cultural and historical representation of these communities play an important role as gatekeepers in order to achieve positive results as far as inclusive education is concerned. This article explores research based on a case study carried out in a high school located in the North-West of Spain developing successful learning stories after implementing the CRT methodology within the teaching of English as a foreign language. For its development, this article examines the trajectory of education with Roma-Gypsy students and moves forward with previous studies that endorse the success of using this approach among ethnically diverse students for their inclusion within the educative system. Intercultural and Plurilingual Education is a key feature in the development of inclusion strategies aimed at ethnically diverse students. This article includes research based on a case study carried out in a high school located in the North-West of Spain. It is aimed at: 1. Engaging ethnically diverse students to become part of the mainstream classroom through the inclusion of their culture; 2. Improving their language skills and competencies in the learning of a foreign language; 3. Raising the attendance at schools of ethnically diverse students. To achieve these targets the Culturally Responsive Teaching (CRT) Methodology has been implemented. CRT is considered essential to answer the educative needs that arise due to the coexistence between ethnic minorities and conventional communities. After gathering and analyzing data, results show that: ethnically diverse students’ motivation has been increased; it also expanded their social skills among peers; they gained more visibility; and finally, both diverse and non-diverse learners improved their proficiency in the English language. The discussion section states that the use of CRT Methodology traditionally used with Afro-American and Native-American students is also relevant for the Roma-Gypsy students that took part in this study.
The Influence of Design on Electrical Performance of AlGaN/GaN Lateral Schottky Barrier Diodes for Energy-Efficient Power Applications
Authors: Polyntsev Egor , Erofeev Evgeny , Yunusov Igor
Published: November 2021

In this paper, lateral AlGaN/GaN Schottky barrier diodes are investigated in terms of anode construction and diode structure. An original GaN Schottky diode manufacturing-process flow was developed. A set of experiments was carried out to verify dependences between electrical parameters of the diode, such as reverse and forward currents, ON-state voltage, forward voltage and capacitance, anode-to-cathode distance, length of field plate, anode length, Schottky contact material, subanode recess depth, and epitaxial structure type. It was found that diodes of SiN/Al0.23Ga0.77N/GaN epi structure with Ni-based anodes demonstrated two orders of magnitude lower reverse currents than diodes with GaN/Al0.25Ga0.75N/GaN epitaxial structure. Diodes with Ni-based anodes demonstrated lower VON and higher IF compared with diodes with Pt-based anodes. As a result of these investigations, an optimal set of parameters was selected, providing the following electrical characteristics: VON = 0.6 (at IF = 1 mA/mm), forward voltage of the diode VF = 1.6 V (at IF = 100 mA/mm), maximum reverse voltage VR = 300 V, reverse leakage current IR = 0.04 μA/mm (at VR = −200 V), and total capacitance C = 3.6 pF/mm (at f = 1 MHz and 0 V DC bias). Obtained electrical characteristics of the lateral Schottky barrier diode demonstrate great potential for use in energy-efficient power applications, such as 5G multiband and multistandard wireless base stations.
Joint Vital Signs and Position Estimation of Multiple Persons Using SIMO Radar
Authors: Kakouche Ibrahim , Abadlia Hamza , El Korso Mohammed Nabil , Mesloub Ammar , Maali Abdelmadjid , Azzaz Mohamed Salah
Published: November 2021

Respiration rate monitoring using ultra-wideband (UWB) radar is preferred because it provides contactless measurement without restricting the person’s privacy. This study considers a novel non-contact-based solution using a single-input multiple-output (SIMO) UWB impulse radar. In the proposed system, the collected radar data are converted to several narrow-band signals using the generalized Goertzel algorithm (GGA), which are used as the input of the designed phased arrays for position estimation. In this context, we introduce the incoherent signal subspace methods (ISSM) for the direction of arrivals (DOAs) and distance evaluation. Meanwhile, a beam focusing approach is used to determine each individual and estimate their breathing rate automatically based on a linearly constrained minimum variance (LCMV) beamformer. The experimental results prove that the proposed algorithm can achieve high estimation accuracy in a variety of test environments, with an error of 2%, 5%, and 2% for DOA, distance, and respiration rate, respectively.
Model Predictive Control-Based Integrated Path Tracking and Velocity Control for Autonomous Vehicle with Four-Wheel Independent Steering and Driving
Authors: Jeong Yonghwan , Yim Seongjin
Published: November 2021

This paper presents an MPC-based integrated control algorithm for an autonomous vehicle equipped with four-wheel independent steering and driving systems. The objective of this research is to improve the performance of the path and velocity tracking controllers by distributing the control effort to the multiple actuators. The proposed algorithm has two modules: reference state decision and MPC-based vehicle motion controller. Reference state decision module determines reference state profiles consisting of yaw rate and velocity in order to overcome the limitation of the error dynamics-based path tracking controller, which requires several assumptions on the reference path. The MPC-based vehicle motion controller is designed with a linear time-varying vehicle model in order to optimally allocate the control effort to each actuator. A linear time-varying MPC is adopted to reduce computational burden caused by using a non-linear one. The effectiveness of the proposed algorithm is validated via simulation on MATLAB/Simulink and CarSim. The simulation results show that the proposed algorithm improves the reference tracking performance by effectively distributing the control effort to the steering angle and driving force of each actuator.
Nitrogen-Doped and Carbon-Coated Activated Carbon as a Conductivity Additive-Free Electrode for Supercapacitors
Authors: Jang Su-Jin , Lee Jeong Han , Kang Seo Hui , Kang Yun Chan , Roh Kwang Chul
Published: November 2021

The development of supercapacitors with high volumetric capacitance and high-rate performance has been an important research topic. Activated carbon (AC), which is a widely used material for supercapacitor electrodes, has different surface structures, porosities, and electrochemical properties. However, the low conductivity of the electrode material is a major problem for the efficient use of AC in supercapacitors. To tackle this challenge, we prepared conductive, additive-free electrodes for supercapacitors by a simple one-pot treatment of AC with melamine (nitrogen source), pitch, and sucrose (both carbon source). Nitrogen-doped and carbon-coated AC was successfully generated after high-temperature heat treatment. The AC was doped with approximately 0.5 at.% nitrogen, and coated with carbon leading to a decreased oxygen content. Thin carbon layers (~10 nm) were coated onto the outer surface of the AC, as shown in TEM images. The modification of the AC surface with a sucrose source is favorable, as it increases the electrical conductivity of AC up to 3.0 S cm−1, which is 4.3 times higher than in unmodified AC. The electrochemical performance of the modified AC was evaluated by conducting agent-free electrode. Although the obtained samples had slightly reduced surface areas after the surface modification, they maintained a high specific surface area of 1700 m2 g−1. The supercapacitor delivered a specific capacitance of 70.4 F cc−1 at 1 mA cm−1 and achieved 89.8% capacitance retention even at a high current density of 50 mA cm−2. Furthermore, the supercapacitor delivered a high energy density of 24.5 Wh kg−1 at a power density of 4650 W kg−1. This approach can be extended for a new strategy for conductivity additive-free electrodes in, e.g., supercapacitors, batteries, and fuel cells.
A Novel Discontinuity Roughness Parameter and Its Correlation with Joint Roughness Coefficients
Authors: Zhang Huizhen , Zhang Changsuo , Yang Zejin , Li Zhiqiang , Wang Chenlong
Published: November 2021

Joint roughness determination is a fundamental issue in many areas of rock engineering, because joint roughness has significant influences on mechanical properties and deformation behavior of rock masses. Available models suggested in the literature neglected combined effects of shear direction, scale of rock discontinuities, inclination angle, and amplitude of asperities during the roughness calculations. The main goals of this paper are to establish a comprehensive parameter that considers the characteristics of the size effect, anisotropy, and point spacing effect of the discontinuity roughness, and to investigate the correlation between the proposed comprehensive parameter and joint roughness coefficients. In this work, the Barton ten standard profiles are digitally represented, then the morphological characteristics of the discontinuity profiles are extracted. A comprehensive parameter that considers the characteristics of the size effect, anisotropy, and point spacing effect of the discontinuity roughness is established, and its correlation with joint roughness coefficients (JRC) is investigated. The correlation between the proposed discontinuity roughness parameter and the joint roughness coefficients can predict the JRC value of the natural discontinuities with high accuracy, which provides tools for comprehensively characterizing the roughness characteristics of rock discontinuities. The roughness index Rvh[−30∘,0] reflects the gentle slope characteristics of the rock discontinuity profiles in the shear direction, which ignores the segments with steep slopes greater than 30° on the discontinuity profiles. The influence of steep slope segments greater than 30° should be considered for the roughness anisotropy parameter in the future.
Solar-Hybrid Cold Energy Storage System Coupled with Cooling Pads Backup: A Step towards Decentralized Storage of Perishables
Authors: Munir Anjum , Ashraf Tallha , Amjad Waseem , Ghafoor Abdul , Rehman Sidrah , Malik Aman Ullah , Hensel Oliver , Sultan Muhammad , Morosuk Tatiana
Published: November 2021

Post-harvest loss is a serious issue to address challenge of food security. A solar-grid hybrid cold storage system was developed and designed for on-farm preservation of perishables. Computational Fluid Dynamic analysis was performed to assess airflow and temperature distribution inside the cold chamber. The system comprises a 21.84 m3 cubical cold storage unit with storage capacity of 2 tonnes. A hybrid solar system comprising 4.5 kWp PV system, 5 kW hybrid inverter, and 600 Ah battery bank was used to power the entire system. A vapor-compression refrigeration system (2 tonnes) was employed coupled with three cooling pads (filled with brine solution) as thermal backup to store cooling (−4 °C to 4 °C). Potatoes were stored at 8 °C for a period of three months (May 2019 to July 2019) and the system was tested on grid utility, solar, and hybrid modes. Solar irradiation was recorded in range of 5.0–6.0 kWh/(m2 × d) and average power peak was found to be 4.0 kW. Variable frequency drive was installed with compressor to eliminate the torque load and it resulted about 9.3 A AC current used by the system with 4.6 average Coefficient of Performance of refrigeration unit. The average energy consumed by system was found to be 15 kWh with a share of 4.3 kWh from grid and 10.5 kWh from solar, translating to 30% of power consumption from grid and 70% from solar PV modules. Overall, cold storage unit efficiently controlled total weight loss (7.64%) and preserved quality attributes (3.6 ⁰Brix Total soluble solids, 0.83% Titratable acidity, 6.32 PH) of the product during storage time.
Why Low-Carbon Publicity Effect Limits? The Role of Heterogeneous Intention in Reducing Household Energy Consumption
Authors: Zhang Jin , Ma Lianrui , Li Jinkai
Published: November 2021

Low-carbon knowledge is seen as having a key role in interfering with household energy consumption behaviors by wide consensus from political and academic areas. Whether low-carbon publicity will help to reduce household energy consumption is still in dispute. By constructing an integrated knowledge-intention-behavior model and using 1335 detailed survey questionnaires of household energy behavior in Henan Province, the central area in China, this paper finds that in the developing area low-carbon knowledge or publicity cannot positively impact household energy-saving behavior even if mediated by energy awareness and energy-saving attitudes. Low-carbon knowledge does improve energy-saving attitude and attitude does not decrease household energy consumption directly. Familiarity with particular energy-saving knowledge would decrease the household energy consumption but not significantly in the statistics. Path analysis unfolds the reason that the heterogeneous effects of purchase-based intention and habitual intention explain energy consumption behavior. Subgroup analysis supports those economic factors of income and energy prices play key roles in explaining such household energy consumption behavior in the rapid urbanization area. This paper gives new evidence on the residential energy-saving behavior intervention among developing areas.
Experimental Study on the Impingement Characteristics of Self-Excited Oscillation Supercritical CO2 Jets Produced by Organ-Pipe Nozzles
Authors: Zhang Mengda , Fang Zhenlong , Qian Yi’nan
Published: November 2021

Supercritical carbon dioxide (SCO2) jets are a promising method to assist drilling, enhance oil–gas production, and reduce greenhouse gas emissions. To further improve the drilling efficiency of SCO2 jet-assisted drilling, organ-pipe nozzles were applied to generate a self-excited oscillation SCO2 jet (SEOSJ). The impact pressure oscillation and rock erosion capability of SEOSJs under both supercritical and gaseous CO2 (GCO2) ambient conditions were experimentally investigated. It was found that the impact pressure oscillation characteristics of SEOSJs produced by organ-pipe nozzles are dramatically affected by the oscillation chamber length. The optimum range of the dimensionless chamber length to generate the highest impact pressure peak and the strongest pressure oscillation is within 7–9. The dimensionless pressure peak and the pressure ratio decreases gradually with increasing pressure difference, whereas the pressure oscillation intensity increases with increasing pressure difference and the increasing rate decreases gradually. The dominant frequency was observed to decrease monotonically with increasing chamber length but increases with the increase of pressure difference. Moreover, the comparison of impingement characteristics of SEOSJs under different ambient conditions showed that the values of dimensionless peak impact pressure are similar under the two ambient conditions, and the SEOSJ achieves higher pressure oscillation intensity and dominant frequency in SCO2 at the same pressure difference. The rock breaking ability of the SEOSJ is closely related to its axial impact pressure. The erosion depth and mass loss of sandstone caused by the organ-pipe nozzle with the best impact pressure performance is higher than those produced by other nozzles. The SEOSJ results in a deeper and narrower crater in SCO2 than in GCO2 under the same pressure difference. The reported results provide guidance for SEOSJ applications and the design of an organ-pipe nozzle used for jet-assisted drilling.
Process Efficiency and Energy Consumption during the Ultrasound-Assisted Extraction of Bioactive Substances from Hawthorn Berries
Authors: Kobus Zbigniew , Krzywicka Monika , Pecyna Anna , Buczaj Agnieszka
Published: November 2021

This study investigated the impact of sonication parameters on the efficiency of the extraction of bioactive substances from hawthorn berries. The ultrasonic treatment was performed in two modes: continuous and pulse. In the pulse mode, the samples were sonicated with the following processor settings: 1 s on-2 s off. The effective ultrasonic processor times were 5, 10, and 15 min, and the total extraction times were 15 min, 30 min, and 45 min. The content of total polyphenols and total anthocyanins was determined by a spectrophotometric method. We show that the operating mode of the processor affects extraction efficiency, energy consumption and unit energy inputs. Extraction supported by a pulsating ultrasonic field allowed saving from 20% to 51% of energy with a simultaneous higher efficiency of the process. In addition, we show that the unit energy consumption in the pulsed mode was about 40% to 68% lower than the energy consumption in the case of continuous operation.
COVID-19 Pandemic Effect on Energy Consumption in State Universities: Michoacan, Mexico Case Study
Authors: López-Sosa Luis Bernardo , Alvarado-Flores José Juan , del Niño Jesús Marín-Aguilar Teresita , Corral-Huacuz Juan Carlos , Aguilera-Mandujano Arturo , Rodríguez-Torres Gerardo Manuel , Morales-Máximo Mario , del Carmen Rodríguez-Magallón María , Alcaraz-Vera Jorge Víctor , Ávalos-Rodríguez María Liliana , Rutiaga-Quiñones José Guadalupe , Rodríguez-Olalde Nancy Eloísa , Flores-Armenta Magaly del Carmen , García Carlos A.
Published: November 2021

The COVID-19 pandemic has generated multiple impacts. In particular, in the educational sector, the virtual class modality generated changes in the patterns of energy consumption at the institutional level; the identification of this consumption will allow us to reflect on new energy saving and efficient use strategies. In this research, we present a case study of the effects of the COVID-19 pandemic on electricity consumption in 13 state universities in Michoacán, Mexico. Electric energy consumption has been evaluated before and during the presence of the COVID-19 between 2019 and 2020. The comparative analysis estimated the reduction in energy consumption and its economic and environmental impact. The results show a considerable decrease in electricity consumption, generating an average saving of 76.24 MWh/month, which translates into an annual emission reduction from 2019 to 2020 of approximately 497 TnCO2e, and in economic terms of $8,882.25 USD each month. In general, it was identified that consumption patterns in the use of machinery and computer equipment for administrative activities were drastically reduced. If education continues in virtual or hybrid modes, energy consumption schemes will continue to decline and institutions could move towards resilient, affordable, and sustainable models of energy production and consumption.
Electrical Load Demand Forecasting Using Feed-Forward Neural Networks
Authors: Machado Eduardo , Pinto Tiago , Guedes Vanessa , Morais Hugo
Published: November 2021

The higher share of renewable energy sources in the electrical grid and the electrification of significant sectors, such as transport and heating, are imposing a tremendous challenge on the operation of the energy system due to the increase in the complexity, variability and uncertainties associated with these changes. The recent advances of computational technologies and the ever-growing data availability allowed the development of sophisticated and efficient algorithms that can process information at a very fast pace. In this sense, the use of machine learning models has been gaining increased attention from the electricity sector as it can provide accurate forecasts of system behaviour from energy generation to consumption, helping all the stakeholders to optimize their activities. This work develops and proposes a methodology to enhance load demand forecasts using a machine learning model, namely a feed-forward neural network (FFNN), by incorporating an error correction step that involves the prediction of the initial forecast errors by another FFNN. The results showed that the proposed methodology was able to significantly improve the quality of load demand forecasts, demonstrating a better performance than the benchmark models.
Analysis of Natural Gas Consumption Interdependence for Polish Industrial Consumers on the Basis of an Econometric Model
Authors: Chrulski Tomasz , Łaciak Mariusz
Published: November 2021

The transmission of natural gas is a key element of the Polish energy system. The published data of the Polish distribution system operators and the transmission system operator on the volume of gaseous fuel transmitted indicate a growing trend in the consumption of energy produced from natural gas. In connection with the energy transformation, switching energy generation sources from hard coal to natural gas in Poland, it is important for transmission operators to know the future demand for gaseous fuel. The aim of the article is to attempt to develop an econometric model related to the consumption of gaseous fuel by Polish entrepreneurs. The knowledge therein may be useful for making business decisions related to the possible expansion of the transmission system, and thus investing financial resources for this purpose. This knowledge will also provide quantitative information related to the interest in gaseous fuel among industrial consumers and the analysis of the trend of natural gas consumption in Poland in the aspect of energy transition. The intention of the publication was to determine the macroeconomic indicators that strongly affect natural gas consumption by the Polish industry and the quantitative growth of consumption depending on changes in these indicators. The results showed that the highest correlation of the growth of natural gas consumption is related to the production of chemistry, the chemical industry, and the power industry.
Thermo-Hydraulic Characteristics of Micro-Scale Surface Roughness Topology of Additively Manufactured Surface Model: Modal Decomposition Perspective
Authors: Lohrasbi Sina , Hammer René , Eßl Werner , Reiss Georg , Defregger Stefan , Sanz Wolfgang
Published: November 2021

As a consequence of rapid development of additive manufacturing (3D printing) methods, the academic/industrial demand has been continuously increasing. One field of application is the manufacturing of heat exchanging devices using this promising method. In this regard, understanding the underlying mechanisms from a thermo-hydraulic viewpoint becomes important. Therefore, in this study, scale-resolving large eddy simulation (LES) is applied to reveal the flow details in combination with a model of roughness topology occurring in additive manufacturing. To process the transient LES results, proper orthogonal decomposition (POD) is used to extract the coherent flow structures, and the extended POD is used to rank the flow modes based on thermal importance. The main aim of the present work is to go beyond the conventionally applied methodologies used for the evaluation of surface roughness, i.e., averaged numerical study or experimental overall performance evaluation of the flow/thermal response of additively manufactured surfaces in heat exchangers. This is necessary to reveal the underlying flow mechanisms hidden in the conventional studies. In this study, the behavior of the flow over the micro-scale surface roughness model and its effects on heat transfer are studied by assuming cone-shaped roughness elements with regular placement as the dominant surface roughness structures. The major discussions reveal the footprint of flow mechanisms on the heat transfer coefficient spatial modes on the rough surface. Moreover, comparative study on the flow/thermal behavior at different levels of roughness heights shows the key role of the height-to-base-diameter ratio of the roughness elements in thermal performance.