bluuebunny/crossref_metadata_2025 huggingface dataset:
Waste Biopolymers for Eco-Friendly Agriculture and Safe Food Production
Authors: Padoan Elio , Montoneri Enzo , Bordiglia Giorgio , Boero Valter , Ginepro Marco , Evon Philippe , Vaca-Garcia Carlos , Fascella Giancarlo , Negre Michéle
Published: February 2022

This work addresses environmental problems connected with biowaste management, the chemical industry, and agriculture. These sectors of human activity cause greenhouse gas (GHG) emissions in the air, climate change, leaching of excess mineral fertilizers applied to soil into ground water, and eutrophication. To mitigate this problem in agriculture, controlled release fertilizers (CRFs) are made by coating mineral fertilizers granules with synthetic polymers produced from the fossil-based chemical industry. This strategy aggravates GHG emission. In the present work, six formulations containing sunflower protein concentrate (SPC) and a new biopolymer (BP) obtained from sunflower oil cake and by hydrolysis of municipal biowaste, respectively, and commercial urea were tested as CRFs for spinach cultivation against the control growing substrate Evergreen TS and commercial Osmocote®. The results show large differences in plants’ nitrate concentration due to the different treatments, although the same nitrogen amount is added to the substrate in all trials. BP is the key component mitigating nitrate accumulation in plants. The plants grown in the substrates containing BP together with SPC and/or urea, although exhibiting relatively high total N uptake (47–52 g kg−1), have significantly lower nitric to total N ratio (9.6–12.0) than that (15.3–16.5) shown by the plants grown in the substrates containing SPC and/or urea, but no BP. The data confirm that all composites containing BP yield the safest crop coupled with high biomass production. Replication of BP effects for the cultivation of different plants will contribute to the development of a biobased chemical industry exploiting biowastes as feedstock.
Synthesis of ZnO/Bi2S3 Core/Shell Nanowire Array Photoanodes for Photocathodic Protection of Stainless Steel
Authors: Lin Yichang , Liu Sheng
Published: February 2022

Nanocrystalline Bi2S3 shells were conformally deposited on ZnO nanowire arrays via a successive ionic layer adsorption and reaction approach. Microstructure, optical, and electric properties of the as-prepared ZnO/Bi2S3 core/shell nanowire heterostructures were thoroughly investigated using various characterization and electrochemical methods. Compared with the pristine ZnO photoanode (−734 mV and 0.57 mA·cm−2), the ZnO/Bi2S3 photoanode with a type-II heterojunction exhibited a more negative shift in the coupled open circuit potential (−862 mV) and a higher photocurrent density (2.92 mA·cm−2), achieving more effective photocathodic protections for the coupled 304 stainless steel under solar illumination.
Performance of a Live Multi-Gateway LoRaWAN and Interference Measurement across Indoor and Outdoor Localities
Authors: Harinda Eugen , Wixted Andrew J. , Qureshi Ayyaz-UI-Haq , Larijani Hadi , Gibson Ryan M.
Published: February 2022

Little work has been reported on the magnitude and impact of interference with the performance of Internet of Things (IoT) applications operated by Long-Range Wide-Area Network (LoRaWAN) in the unlicensed 868 MHz Industrial, Scientific, and Medical (ISM) band. The propagation performance and signal activity measurement of such technologies can give many insights to effectively build long-range wireless communications in a Non-Line of Sight (NLOS) environment. In this paper, the performance of a live multi-gateway in indoor office site in Glasgow city was analysed in 26 days of traffic measurement. The indoor network performances were compared to similar performance measurements from outdoor LoRaWAN test traffic generated across Glasgow Central Business District (CBD) and elsewhere on the same LoRaWAN. The results revealed 99.95% packet transfer success on the first attempt in the indoor site compared to 95.7% at the external site. The analysis shows that interference is attributed to nearly 50 X greater LoRaWAN outdoor packet loss than indoor. The interference measurement results showed a 13.2–97.3% and 4.8–54% probability of interfering signals, respectively, in the mandatory Long-Range (LoRa) uplink and downlink channels, capable of limiting LoRa coverage in some areas.
Review of Silicon Carbide Processing for Power MOSFET
Authors: Langpoklakpam Catherine , Liu An-Chen , Chu Kuo-Hsiung , Hsu Lung-Hsing , Lee Wen-Chung , Chen Shih-Chen , Sun Chia-Wei , Shih Min-Hsiung , Lee Kung-Yen , Kuo Hao-Chung
Published: February 2022

Owing to the superior properties of silicon carbide (SiC), such as higher breakdown voltage, higher thermal conductivity, higher operating frequency, higher operating temperature, and higher saturation drift velocity, SiC has attracted much attention from researchers and the industry for decades. With the advances in material science and processing technology, many power applications such as new smart energy vehicles, power converters, inverters, and power supplies are being realized using SiC power devices. In particular, SiC MOSFETs are generally chosen to be used as a power device due to their ability to achieve lower on-resistance, reduced switching losses, and high switching speeds than the silicon counterpart and have been commercialized extensively in recent years. A general review of the critical processing steps for manufacturing SiC MOSFETs, types of SiC MOSFETs, and power applications based on SiC power devices are covered in this paper. Additionally, the reliability issues of SiC power MOSFET are also briefly summarized.
Non-Covalent Interactions in Organic, Organometallic, and Inorganic Supramolecular Systems Relevant for Medicine, Materials Science, and Catalysis
Authors: Novikov Alexander S.
Published: February 2022

The structure, fundamental properties, and reactivity of chemical systems at various hierarchical levels of organization of matter is the paradigm of chemistry. A qualitative and quantitative description of various intermolecular and intramolecular non-covalent interactions in chemical systems is the main tool for supramolecular design and the driving force of smart prediction of kinetic and thermodynamic parameters of chemical reactions. This perspective is dedicated to highlighting the recent progress of our research group in the investigation of various non-covalent contacts in organic, organometallic, and inorganic chemical systems relevant for medicine, materials science, and catalysis. This research is interdisciplinary in nature and lies at the intersection of computer modeling with such natural science disciplines as chemistry, physics, crystallography, biology, and medicine, as well as directly related to materials science and nanotechnology.
Intermolecular Interactions Drive the Unusual Co-Crystallization of Different Calix[4]arene Conformations
Authors: Taylor Dominic , Ling Irene , Vilela Filipe , Dalgarno Scott J.
Published: February 2022

Crystallization of 5,17-dibromo-11,27,23,25-tetraone-26,28-dipropoxycalix[4]arene results in the rare observation of two different calix[4]arene conformations (partial cone and 1,3-alternate) co-crystallized within the same single crystal X-ray structure. Analysis using 1H and 13C NMR spectroscopy revealed that only a single conformation (the cone) was present in solution, and in contrast to the structures of other reported calix[4]arenes and calix[4]quinones, both conformations of the compound present in this crystal structure have a “pinched” shape, drastically reducing Br-Br separation and associated cavity sizes.
Are Heavy Fermion Strange Metals Planckian?
Authors: Taupin Mathieu , Paschen Silke
Published: February 2022

Strange metal behavior refers to a linear temperature dependence of the electrical resistivity that is not due to electron–phonon scattering. It is seen in numerous strongly correlated electron systems, from the heavy fermion compounds, via transition metal oxides and iron pnictides, to magic angle twisted bi-layer graphene, frequently in connection with unconventional or “high temperature” superconductivity. To achieve a unified understanding of these phenomena across the different materials classes is a central open problem in condensed matter physics. Tests whether the linear-in-temperature law might be dictated by Planckian dissipation—scattering with the rate ∼kBT/ℏ—are receiving considerable attention. Here we assess the situation for strange metal heavy fermion compounds. They allow to probe the regime of extreme correlation strength, with effective mass or Fermi velocity renormalizations in excess of three orders of magnitude. Adopting the same procedure as done in previous studies, i.e., assuming a simple Drude conductivity with the above scattering rate, we find that for these strongly renormalized quasiparticles, scattering is much weaker than Planckian, implying that the linear temperature dependence should be due to other effects. We discuss implications of this finding and point to directions for further work.
Biogenic Synthesis of AgNPs Using Aqueous Bark Extract of Aesculus indica for Antioxidant and Antimicrobial Applications
Authors: Riaz Muhammad , Suleman Amrina , Ahmad Pervaiz , Khandaker Mayeen Uddin , Alqahtani Amal , Bradley David A. , Khan Muhammad Qayyum
Published: February 2022

Nanotechnology has received a lot of attention from the scientific community because of the greater surface-to-volume ratio of nanomaterials, which phenomenally increases their efficacy in practical applications. Among the various synthesis techniques, the biogenic or green synthesis of nanomaterials shows advantages over other techniques such as physical, chemical, etc. This study reports the biogenic synthesis of silver nanoparticles (AgNPs) using aqueous bark extract of Aesculus indica. The as-synthesized NPs were characterized by UV–visible, FT-IR, XRD, and SEM, and then tested for their antioxidant and antimicrobial potency. We have identified phenols, flavonoids, tannins, saponins, and carbohydrates in the bark extract of A. indica. The extract-loaded-AgNPs showed the highest inhibition for Staphylococcus aureus (28.0 mm), Pseudomonas aeruginosa (17.66 mm), Escherichia coli (14.33 mm), Acetobacter serratia (14.00 mm), and Klebsiella pneumoniae (12.33 mm). The methanolic bark extract inhibited S. aureus (24.33 mm), P. aeruginosa (10.66 mm), E. coli (11.33 mm), A. serratia (9.66 mm), and K. pneumoniae (11.66 mm). Aqueous bark extract inhibited S. aureus (22.33 mm), P. aeruginosa (8.33 mm), E. coli (9.33 mm), A. serratiaa (8.33 mm), and K. pneumoniae (9.66 mm). Its aqueous extract showed the highest antioxidant potency; IC50 (0.175 µg/mL) followed by the methanolic extract; IC50 (0.210 µg/mL) and extract-loaded nanoparticles; IC50 (0.901 µg/mL). Our findings provide meaningful interest for antioxidant, anti-microbial applications of, and AgNPs synthesis by, aqueous bark extract of A. indica.
Three New Species of Absidia (Mucoromycota) from China Based on Phylogeny, Morphology and Physiology
Authors: Zhao Heng , Nie Yong , Zong Tongkai , Dai Yucheng , Liu Xiaoyong
Published: February 2022

Species of Absidia are distributed widely in the environment, while their diversity is insufficiently studied. Three new species, A. frigida, A. gemella and A. longissima, are proposed herein from Xinjiang and Yunnan in China based on phylogenetic, morphological and physiological evidence. According to maximum likelihood (ML), maximum parsimony (MP) and Bayesian inference (BI) analyses, the phylogenetical results suggest that A. frigida, A. gemella and A. longissima are closely related to A. psychrophilia, A. turgida and A. zonata and A. koreana, respectively, based on ITS and LSU rDNA sequences. Absidia frigida is characterized by a lower growth temperature, which does not grow above 24 °C. It differs from A. psychrophilia by sporangiophores, sporangia, columellae, collars and projections. Absidia gemella is distinguished from A. turgida by hypha, sporangiospores, sporangia, projections and sporangiophores. Absidia longissima is discriminated from A. zonata and A. koreana by sporangiophores, columellae and collars. The three new species are described and illustrated in this article.
Role of MBL2 Polymorphisms in Sepsis and Survival: A Pilot Study and In Silico Analysis
Authors: Behairy Mohammed Y. , Abdelrahman Ali A. , Abdallah Hoda Y. , Ibrahim Emad El-Deen A. , Hashem Hany R. , Sayed Anwar A. , Azab Marwa M.
Published: February 2022

Sepsis is a serious infection-induced syndrome with serious ramifications, especially in intensive care units. Global concern motivated the investigation of the role of related genes’ polymorphism in predicting the liability to infection, sepsis, septic shock and survival. Among these genes is the gene encoding mannose-binding lectin (MBL), with its remarkable importance in the immune system. However, the previous studies showed conflicting results and ambiguity that urged us to engage with this issue in the Egyptian population. Prediction of functional and structural impacts of single nucleotide polymorphisms (SNPs) was done using in silico methods. A prospective observational study was conducted in intensive care units; one hundred and thirty patients were followed up. Genotyping was performed using real-time polymerase chain reaction (RT-PCR) technology. MBL SNPs showed a remarkable high frequency in our population, as well. No significant association was found between MBL2 genotypes and any of our analyses (sepsis, septic shock and survival). Only septic shock and age were independently associated with time of survival by Cox regression analysis. Our study may confirm the redundancy of MBL and the absence of significant impact on sepsis liability and mortality in adult patients.
Application of Mass Multivariate Analysis on Neuroimaging Data Sets for Precision Diagnostics of Depression
Authors: Paunova Rositsa , Kandilarova Sevdalina , Todeva-Radneva Anna , Latypova Adeliya , Kherif Ferath , Stoyanov Drozdstoy
Published: February 2022

We used the Mass Multivariate Method on structural, resting-state, and task-related fMRI data from two groups of patients with schizophrenia and depression in order to define several regions of significant relevance to the differential diagnosis of those conditions. The regions included the left planum polare (PP), the left opercular part of the inferior frontal gyrus (OpIFG), the medial orbital gyrus (MOrG), the posterior insula (PIns), and the parahippocampal gyrus (PHG). This study delivered evidence that a multimodal neuroimaging approach can potentially enhance the validity of psychiatric diagnoses. Structural, resting-state, or task-related functional MRI modalities cannot provide independent biomarkers. Further studies need to consider and implement a model of incremental validity combining clinical measures with different neuroimaging modalities to discriminate depressive disorders from schizophrenia. Biological signatures of disease on the level of neuroimaging are more likely to underpin broader nosological entities in psychiatry.
Performance Evaluation of the STANDARDTM Q COVID-19 and PanbioTM COVID-19 Antigen Tests in Detecting SARS-CoV-2 during High Transmission Period in Mozambique
Authors: Sitoe Nádia , Sambo Júlia , Nguenha Neuza , Chilaule Jorfelia , Chelene Imelda , Loquiha Osvaldo , Mudenyanga Chishamiso , Viegas Sofia , Cunningham Jane , Jani Ilesh
Published: February 2022

(1) Background: Laboratory-based molecular assays are the gold standard to detect SARS-CoV-2. In resource-limited settings, the implementation of these assays has been hampered by operational challenges and long turnaround times. Rapid antigen detection tests are an attractive alternative. Our aim is to evaluate the clinical performance of two SARS-CoV-2 rapid antigen tests during a high transmission period. (2) Methods: A total of 1277 patients seeking SARS-CoV-2 diagnosis were enrolled at four health facilities. Nasopharyngeal swabs for rapid antigen and real time PCR testing were collected for each patient. Sensitivity, specificity, positive and negative predictive values, misclassification rate, and agreement were determined. (3) Results: The overall sensitivity of Panbio COVID-19 was 41.3% (95% CI: 34.6–48.4%) and the specificity was 98.2% (95% CI: 96.2–99.3%). The Standard Q had an overall sensitivity and specificity of 45.0% (95% CI: 39.9–50.2%) and 97.6% (95% CI: 95.3–99.0%), respectively. The positive predictive value of a positive test was 93.3% and 95.4% for the Panbio and Standard Q Ag-RDTs, respectively. A higher sensitivity of 43.2% and 49.4% was observed in symptomatic cases for the Panbio and Standard Q Ag-RDTs, respectively. (4) Conclusions: Despite the overall low sensitivity, the two evaluated rapid tests are useful to improve the diagnosis of symptomatic SARS-CoV-2 infections during high transmission periods.
Pre-Burn Health-Related Quality of Life: Patient and Partner Perspectives
Authors: Boersma-van Dam Elise , Hofland Helma , de Jong Alette , Van Loey Nancy
Published: February 2022

A proxy-assessment of health-related quality of life (HRQL) may be an alternative for burn patients who are medically unable to self-report shortly after being admitted to the hospital. This study examined the patient–partner agreement on the recalled pre-injury HRQL of burn patients. In a multi-centre study of 117 patient–partner pairs, the recalled pre-burn HRQL was assessed with the EQ-5D-3L + Cognition during the acute phase following the burns. Agreement was evaluated with Kappa and ICC statistics. Burn severity and PTSD symptoms were assessed as potential predictors of disagreement. The results showed that pre-burn EQ-Index scores were similar to population norms, whereas the EQ Visual Analog Scale (EQ-VAS) scores of patients were significantly higher. Agreement varied across EQ-5D domains and, after adjusting for prevalence, was substantial to almost perfect. Average agreement on the EQ-Index and EQ-VAS was, respectively, substantial and moderate, but differences between partners were larger at lower levels of HRQL, and specifically in the pain/discomfort domain. Patient–partner differences could not be explained by the patient’s age or gender, number of surgeries, partner’s presence at the burn event, or post-traumatic stress disorder (PTSD) symptoms of either the patient or partner. In conclusion, patient–partner agreement is substantial and partner–proxy reports of pre-burn EQ-5D domains and EQ-Index scores may be used to complement or serve as a substitute for the patient’s assessment. Given the moderate agreement on the EQ-VAS, it may be less suited for proxy assessment.
The ESD Characteristics of a pMOS-Triggered Bidirectional SCR in SOI BCD Technology
Authors: Li Mingzhu , Cai Xiaowu , Zeng Chuanbin , Li Xiaojing , Ni Tao , Wang Juanjuan , Li Duoli , Zhao Fazhan , Han Zhengsheng
Published: February 2022

In this work, the electrostatic discharge (ESD) characteristics of a pMOS-triggered bidirectional silicon-controlled rectifier (PTBSCR) that was fabricated in a 0.18 μm silicon-on-insulator (SOI) bipolar-CMOS-DMOS (BCD) process, is investigated. The multi-snapback phenomenon was observed under the transmission line pulsing (TLP) test system. It was found that gate voltage and inserting shallow trench isolation (STI) can significantly affect the trigger voltage and holding voltage. The underlying physical mechanism related to the multi-snapback phenomenon and the effects of gate voltage on the critical parameters was investigated through the experimental results and the assistance of technology computer-aided design (TCAD) simulations. The adjustments of gate voltage and STI on the critical ESD parameters of the device provide an effective design idea for low-voltage ESD protection in the SOI BCD process.
Unpacking the Role of Artificial Intelligence for a Multimodal Service System Design
Authors: Sung Inkyung , Buderath Matthias , Nielsen Peter
Published: February 2022

Since requirements of service demands are becoming increasingly complex and diversified, one of the success factors of a multimodal service system is its capability to design a specific service instance satisfying a specific set of requirements. This capability is further highlighted in Ad Hoc Multimodal Service Systems (AHMSSs), where service instances rarely follow a standard form of service delivery and exist only for a limited time. However, due to the increasing scale and frequency of services in many business and public sectors, meeting the desired level of capability has become troublesome. A well-designed Artificial Intelligence (AI) approach can be a solution to the difficulty by addressing the underlying complexity and uncertainty of the AHMSS design process. To conceptualize and foster AI applications to an AHMSS, this study identifies key decision-making problems in the AHMSS design process and discusses the role of AI in the process. The results will form the basis for AI development and implementation for an AHMSS and relevant service systems.
Broadband Class-J GaN Doherty Power Amplifier
Authors: Nasri Abbas , Estebsari Motahhareh , Toofan Siroos , Piacibello Anna , Pirola Marco , Camarchia Vittorio , Ramella Chiara
Published: February 2022

This paper presents a broadband 3–3.7 GHz class-J Doherty power amplifier exploiting second harmonic tuning in the output network. Furthermore, the output impedance inverter is eliminated and its effect is embedded in the main device’s output matching network, thus trading off among bandwidth, efficiency, and gain. The proposed amplifier adopts two 10 W packaged GaN transistors, and it achieves in measurement 60–74%, and 46–50% drain efficiency at saturation and 6 dB output back-off, respectively, with a saturated output power of 43–44.2 dBm and a small-signal gain of 10–13 dB. The proposed DPA exhibits a simulated adjacent channel power ratio less than −30 dBc at 36 dBm average output power, when a 16-QAM modulation with 5 MHz bandwidth is applied to the 3.5 GHz carrier.
Design of a High-Durability X-Band Patch Antenna with a CPW Feeding Network Based on a Durability Evaluation Analysis
Authors: Jang Doyoung , Lim Tae Heung , Kim Dongyoon , Wang Sungsik , Choo Hosung
Published: February 2022

In this paper, we propose a high-durability X-band patch antenna with a coplanar waveguide (CPW) feeding network that can directly connect the upper antenna and the lower transmitting receiver modules without additional cabling. To improve the durability of the antenna, both the sub miniature push-on (SMP) connector and the feed-pin are separated through the CPW layer. This separated structure can minimize the deterioration of the antenna performance when the unwanted movement of the SMP connector occurs from external shocks. To verify the design feasibility, the reflection coefficient and radiation patterns of the proposed antenna are measured in a full anechoic chamber. The reflection coefficient of the proposed antenna is −27 dB at 10 GHz, and the operating frequency bandwidth (|Γ| < −10 dB) is 4.7% (9.82~10.29 GHz) in X-band. The proposed antenna has a maximum gain of 5.7 dBi at the bore-sight direction. In addition, the durability evaluations of the proposed design according to unwanted SMP connector movements provoked by external shocks are investigated using Monte Carlo simulations. The results demonstrate that the proposed high-durability antenna design is suitable for military ship applications that involve exposure to various external shocks.
A Novel Polarization and DOA Reliable Auto-Tracking Antenna System
Authors: Ba Xinran , Lin Chen , Zhong Yincheng , Ren Guanjiao , Wang Zhengpeng , Wang Yi
Published: February 2022

In this study, a novel compact auto-tracking antenna system was developed to ensure the high reliability of practical applications. The system consisted of three antennas (two anchor antennas and a tag antenna), three ultra-wide band (UWB) chips, and one compact turntable. On the anchor side, two highly linearly polarized antennas with a short baseline were installed on an auto-control turntable. Two UWB chips were integrated with the two anchor antennas to extract the phase and amplitude information of the receiving signal. On the tag side, a wide-beam circularly polarized antenna with a UWB chip was installed to mitigate the effect of the tag’s pose on the phase measurement. Using a correlation matching algorithm based on the phase difference of arrival, high tracking reliability with a 90% success rate was achieved for all practical direction-of-arrivals and various axial rotating angles of the tag over the maximum radiation deflection angles between –90° and 135°. The operation distance of a demo self-balanced two-wheeled vehicle was 20 m.
Partial Order-Based Decoding of Rate-1 Nodes in Fast Simplified Successive-Cancellation List Decoders for Polar Codes
Authors: Johannsen Lucas , Kestel Claus , Griebel Oliver , Vogt Timo , Wehn Norbert
Published: February 2022

Polar codes are the first family of error-correcting codes that can achieve channel capacity. Among the known decoding algorithms, Successive-Cancellation List (SCL) decoding supported by a Cyclic Redundancy Check (CRC) shows the best error-correction performance at the cost of a high decoding complexity. The decoding of Rate-1 nodes belongs to the most complex tasks in SCL decoding. In this paper, we present a new algorithm that largely reduces the number of considered candidates in a Rate-1 node and generate all required candidates in parallel. For this purpose, we use a partial order of the candidate paths to prove that only a specified number of candidates needs to be considered. Further complexity reductions are achieved by an extended threshold-based path exclusion scheme at the cost of negligible error-correction performance loss. We present detailed Application-Specific Integrated Circuit (ASIC) implementation data on a 28 nm Fully Depleted Silicon on Insulator (FD-SOI) Complementary Metal-Oxide-Semiconductor (CMOS) technology for decoders with code length 128. We show that the new decoders outperform state-of-the-art reference decoders. For list size 8, improvements of up to 158.8% and 62.5% in area and energy efficiency are observed, respectively.
Cost and Latency Optimized Edge Computing Platform
Authors: Pelle István , Szalay Márk , Czentye János , Sonkoly Balázs , Toka László
Published: February 2022

Latency-critical applications, e.g., automated and assisted driving services, can now be deployed in fog or edge computing environments, offloading energy-consuming tasks from end devices. Besides the proximity, though, the edge computing platform must provide the necessary operation techniques in order to avoid added delays by all means. In this paper, we propose an integrated edge platform that comprises orchestration methods with such objectives, in terms of handling the deployment of both functions and data. We show how the integration of the function orchestration solution with the adaptive data placement of a distributed key–value store can lead to decreased end-to-end latency even when the mobility of end devices creates a dynamic set of requirements. Along with the necessary monitoring features, the proposed edge platform is capable of serving the nomad users of novel applications with low latency requirements. We showcase this capability in several scenarios, in which we articulate the end-to-end latency performance of our platform by comparing delay measurements with the benchmark of a Redis-based setup lacking the adaptive nature of data orchestration. Our results prove that the stringent delay requisites necessitate the close integration that we present in this paper: functions and data must be orchestrated in sync in order to fully exploit the potential that the proximity of edge resources enables.
Power Electronics Converter Technology Integrated Energy Storage Management in Electric Vehicles: Emerging Trends, Analytical Assessment and Future Research Opportunities
Authors: Hossain Lipu Molla Shahadat , Miah Md. Sazal , Ansari Shaheer , Meraj Sheikh Tanzim , Hasan Kamrul , Elavarasan Rajvikram Madurai , Mamun Abdullah Al , Zainuri Muhammad Ammirrul A. M. , Hussain Aini
Published: February 2022

Globally, the research on electric vehicles (EVs) has become increasingly popular due to their capacity to reduce carbon emissions and global warming impacts. The effectiveness of EVs depends on appropriate functionality and management of battery energy storage. Nevertheless, the battery energy storage in EVs provides an unregulated, unstable power supply and has significant voltage drops. To address these concerns, power electronics converter technology in EVs is necessary to achieve a stable and reliable power transmission. Although various EV converters provide significant contributions, they have limitations with regard to high components, high switching loss, high current stress, computational complexity, and slow dynamic response. Thus, this paper presents the emerging trends in analytical assessment of power electronics converter technology incorporated energy storage management in EVs. Hundreds (100) of the most significant and highly prominent articles on power converters for EVs are studied and investigated, employing the Scopus database under predetermined factors to explore the emerging trends. The results reveal that 57% of articles emphasize modeling, experimental work, and performance evaluation. In comparison, 13% of papers are based on problem formulation and simulation analysis, and 8% of articles are survey, case studies, and review-based. Besides, four countries, including China, India, the United States, and Canada, are dominant to publish the maximum articles, indicating 33, 17, 14, and 13, respectively. This review adopts the analytical assessment that outlines various power converters, energy storage, controller, optimization, energy efficiency, energy management, and energy transfer, emphasizing various schemes, key contributions, and research gaps. Besides, this paper discusses the drawbacks and issues of the various power converters and highlights future research opportunities to address the existing limitations. This analytical assessment could be useful to EV engineers and automobile companies towards the development of advanced energy storage management interfacing power electronics for sustainable EV applications.
Deep Learning-Based Object Detection and Scene Perception under Bad Weather Conditions
Authors: Sharma Teena , Debaque Benoit , Duclos Nicolas , Chehri Abdellah , Kinder Bruno , Fortier Paul
Published: February 2022

Large cities’ expanding populations are causing traffic congestion. The maintenance of the city’s road network necessitates ongoing monitoring, growth, and modernization. An intelligent vehicle detection solution is necessary to address road traffic concerns with the advancement of automatic cars. The identification and tracking vehicles on roads and highways are part of intelligent traffic monitoring while driving. In this paper, we have presented how You Only Look Once (YOLO) v5 model may be used to identify cars, traffic lights, and pedestrians in various weather situations, allowing for real-time identification in a typical vehicular environment. In an ordinary or autonomous environment, object detection may be affected by bad weather conditions. Bad weather may make driving dangerous in various ways, whether due to freezing roadways or the illusion of low fog. In this study, we used YOLOv5 model to recognize objects from street-level recordings for rainy and regular weather scenarios on 11 distinct classes of vehicles (car, truck, bike), pedestrians, and traffic signals (red, green, yellow). We utilized freely available Roboflow datasets to train the proposed system. Furthermore, we used real video sequences of road traffic to evaluate the proposed system’s performance. The study results revealed that the suggested approach could recognize cars, trucks, and other roadside items in various circumstances with acceptable results.
Parameter Extraction of Solar Module Using the Sooty Tern Optimization Algorithm
Authors: Singh Abha , Sharma Abhishek , Rajput Shailendra , Mondal Amit Kumar , Bose Amarnath , Ram Mangey
Published: February 2022

Photovoltaic module parameter estimation is a critical step in observing, analyzing, and optimizing the efficiency of solar power systems. To find the best value for unknown parameters, an efficient optimization strategy is required. This paper presents the implementation of the sooty tern optimization (STO) algorithm for parameter assessment of a solar cell/module. The simulation findings were compared to four pre-existing optimization algorithms: sine cosine (SCA) algorithm, gravitational search algorithm (GSA), hybrid particle swarm optimization and gravitational search algorithm (PSOGSA), and whale optimization (WOA). The convergence rate and root mean square error evaluations show that the STO method surpasses the other studied optimization techniques. Additionally, the statistical results show that the STO method is superior in average resilience and accuracy. The superior performance and reliability of the STO method are further validated by the Friedman ranking test.
Artificial Visual System for Orientation Detection
Authors: Ye Jiazhen , Todo Yuki , Tang Zheng , Li Bin , Zhang Yu
Published: February 2022

The human visual system is one of the most important components of the nervous system, responsible for visual perception. The research on orientation detection, in which neurons of the visual cortex respond only to a line stimulus in a particular orientation, is an important driving force of computer vision and biological vision. However, the principle underlying orientation detection remains a mystery. In order to solve this mystery, we first propose a completely new mechanism that explains planar orientation detection in a quantitative manner. First, we assume that there are planar orientation-detective neurons which respond only to a particular planar orientation locally and that these neurons detect local planar orientation information based on nonlinear interactions that take place on the dendrites. Then, we propose an implementation of these local planar orientation-detective neurons based on their dendritic computations, use them to extract the local planar orientation information, and infer the global planar orientation information from the local planar orientation information. Furthermore, based on this mechanism, we propose an artificial visual system (AVS) for planar orientation detection and other visual information processing. In order to prove the effectiveness of our mechanism and the AVS, we conducted a series of experiments on rectangular images which included rectangles of various sizes, shapes and positions. Computer simulations show that the mechanism can perfectly perform planar orientation detection regardless of their sizes, shapes and positions in all experiments. Furthermore, we compared the performance of both AVS and a traditional convolution neural network (CNN) on planar orientation detection and found that AVS completely outperformed CNN in planar orientation detection in terms of identification accuracy, noise resistance, computation and learning cost, hardware implementation and reasonability.
Hybrid Research Platform for Fundamental and Empirical Modeling and Analysis of Energy Management of Shared Electric Vehicles
Authors: Koreny Martin , Simonik Petr , Klein Tomas , Mrovec Tomas , Ligori Joy Jason
Published: February 2022

This article presents the results of the development of a hybrid research platform for fundamental and empirical modeling and analysis of energy management of shared electric vehicles. The article describes the hybrid model and its specific features in detail. Within the model architecture, a part of the fundamental model, empirical model and data collection tools were interconnected. The uniqueness lies in the models of electric cars created for a specific vehicle using cost-optimal parameterizations, as well as the implementation of a cloud solution, which is based on custom data communication, custom data logger and cost-optimized parameterization of machine learning algorithms. Experimental verification was performed on a real electric car in public traffic. The car is part of casharing platform.
A Fuzzy Logic-Based Emulated Inertia Control to a Supercapacitor System to Improve Inertia in a Low Inertia Grid with Renewables
Authors: Sarojini Ratnam Kamala , Palanisamy Kaliannan , De Tuglie Enrico
Published: February 2022

The contribution of power generation from converter-dominated renewable energy sources (RES) has increased enormously. Consequently, the system inertia is decreasing, and it impacts the frequency of the system. With large-scale integration of power electronic inverter-based power generation from RES, inertia from energy storage devices would be unavoidable in future power grids. In this paper, the inertia emulator is formed with a supercapacitor (IE–SC) to improve inertia in a low inertia grid. To emulate the inertia in a low inertia grid, this paper proposes a fuzzy logic controller-based emulated inertia controller (FL-EIC) for an inverter attached to IE–SC. The proposed fuzzy logic controller estimates the inertial power required based on the frequency deviation and rate of change of frequency (ROCOF). The output of the fuzzy controller adds to the conventional emulated inertia control (EIC) technique to alter the load angle for the power electronic inverter of IE–SC. Specifically, the proposed FL-EIC achieves inertia emulation by proportionally linking the time derivative of the grid frequency and frequency deviation to active power references of IE–SC. A comparison of the conventional EIC and FL-EIC is carried out to prove the effectiveness of the proposed FL-EIC. Furthermore, real-time simulations with the help of the OPAL-RT real-time simulator (OP 5700) are presented to validate the advantage of the FL-EIC.
Monitoring and Management of Inland Waters: Insights from the Most Inhabited Italian Region
Authors: Quadroni Silvia , Espa Paolo , Zaccara Serena , Crosa Giuseppe , Bettinetti Roberta , Mastore Maristella , Brivio Maurizio Francesco
Published: February 2022

Monitoring of freshwaters allows the detection of the impacts of multiple anthropic uses and activities on aquatic ecosystems, and an eco-sustainable management of natural resources could limit these impacts. In this work, we highlighted two main issues affecting inland waters, referring to findings from the most inhabited Italian region (Lombardy, approximately 10 M inhabitants): the first issue is lake pollution by old generation pesticides, the second is river development for hydropower. In both cases, some management strategies reducing the anthropic impacts on freshwaters were discussed: organic farming and biocontrol as an alternative to diffuse pollution by agrochemicals; environmental flows and controlled sediment flushing operations to limit the hydropower impact on rivers. Although the two mentioned issues were discussed separately in this paper, the management of water resources should be carried out in a comprehensive way, accounting for the multiple impacts affecting freshwater ecosystems, including those related to the climate changes.
Bibliographic Coupling Links: Alternative Approaches to Carrying Out Systematic Reviews about Renewable and Sustainable Energy
Authors: Martinho Vítor João Pereira Domingues
Published: February 2022

New technologies, specifically the internet, have over the last two decades increased the number of publications in the most diverse fields of science. Subjects related to renewable and sustainable energy are no exception. These frameworks have allowed the main insights produced by the scientific community through literature surveys to be highlighted. Nonetheless, considering the vast quantity of studies, systematic approaches have been proposed by the researchers to better organize and perform the literature review. Considering the subjectivity of some of these methodologies, the main objectives of this research are to conduct a systematic review about renewable and sustainable energy through more objective techniques, based on bibliometric analysis, to provide an alternative or to complement those already available within the literature. For this purpose, a “Biblio4Review” approach was proposed in order to perform systematic reviews about renewable and sustainable energy that may spread into other scientific fields. This methodology is based on bibliographic coupling links from the bibliometric analysis to identify the most relevant studies for the literature review. The results obtained highlight that with this approach it was possible to identify the studies with greater centrality in terms of references shared. In this way, they are among the most relevant documents for these topics. Specifically for the topic considered (renewable and sustainable energy) the main insights were referred to. In any case, the findings obtained show that there is a field for more interdisciplinary approaches.
Above-and-Belowground Carbon Stocks in Two Contrasting Peatlands in the Philippines
Authors: Orella Joel , Africa Diana Riza , Bustillo Catherine Hope , Pascua Noel , Marquez Conrado , Adornado Henry , Aguilos Maricar
Published: February 2022

Although tropical peatlands are huge carbon reservoirs, they are threatened by climate change and anthropogenic disturbances. Here, we assessed two contrasting peatland sites in the Philippines in terms of aboveground biomass and carbon content, soil carbon stock, and CO2 fluxes in the soils. The Caimpugan peatland in Agusan del Sur was considered the ‘undisturbed’ site, while the Bambanin peatland in Mindoro Oriental was the ‘disturbed’ site. The aboveground biomass at the undisturbed site was 35.8 ± 30.0 Mg ha−1) while at the disturbed site, it was 2.0 Mg ha−1 ± 1.9 Mg ha−1. The aboveground C content at the undisturbed site varied from 1.29 Mg C ha−1 to 37.2 Mg C ha−1, while the disturbed site only ranged from 0.1 Mg C ha−1 to 2.1 Mg C ha−1. A trend of increasing soil carbon content as the soil gets deeper was observed in both sites. At the undisturbed site, the average soil carbon content was 750 ± 710 Mg ha−1 and 595 ± 406 Mg ha−1 at the disturbed site. In terms of soil carbon emission, the undisturbed site had 3.6 ± 3.0 g C m−2d−1 and was only one-third the emission rate at the disturbed site (11.2 ± 6.4 g C m−2d−1). Our study highlights the dire condition of a disturbed peatland in terms of vegetation/soil carbon dynamics. We underscored the need to address the pressing issues on peatland drainage, agricultural activities, and human settlement within the peatland sites geared towards effectively managing this important carbon reservoir in the Philippines.
Effects of Climate Change on the Carbon Sequestration Potential of Forest Vegetation in Yunnan Province, Southwest China
Authors: Zhou Ruiwu , Zhang Yiping , Peng Mingchun , Jin Yanqiang , Song Qinghai
Published: February 2022

Ongoing climate changes reportedly affect the potential distribution and carbon sequestration potential (CSP) of forest vegetation. The combined effects of increasing temperature and decreasing precipitation on these features of forest vegetation are poorly understood. In this study, classification and regression tree (CART) models were used to predict the potential distribution and estimate the CSP of forest vegetation in Yunnan Province, Southwest China, under different simulation scenarios. The minimum temperature of the coldest month (TMW) was the main factor limiting the suitable habitat of all forest vegetation types except for warm–temperate coniferous (WTC) forests. When the temperature increased by 1 °C and the precipitation decreased by 20%, the potential distribution area of the 7 forest vegetation types decreased by 12.41% overall. The potential distribution of WTC forests was the least sensitive to temperature increases and precipitation decreases. The CSP of vegetation was higher (1187.69 TgC) under the constant temperature and 10% precipitation decrease scenario than the CSP of vegetation under the 2 °C temperature increase and constant precipitation scenario (647.24 TgC). Specifically, the highest CSP (1337.88 TgC) was observed under the 1 °C temperature increase and 10% precipitation decrease scenario, and the lowest (617.91 TgC) occurred under the constant temperature and 20% precipitation decrease scenario. In summary, the forest vegetation in Yunnan Province has a high CSP under climate change, and the combined effect of increased temperature and decreased precipitation can increase the CSP of forest vegetation in Yunnan Province. This finding is important for improving scientific decision making and policy planning.
Development of a Taxon-Specific Real-Time PCR Method Targeting the Bacillus subtilis Group to Strengthen the Control of Genetically Modified Bacteria in Fermentation Products
Authors: Fraiture Marie-Alice , Gobbo Andrea , Papazova Nina , Roosens Nancy H. C.
Published: February 2022

Most of the bacteria that are used to produce fermentation products, such as enzymes, additives and flavorings, belong to the Bacillus subtilis group. Recently, unexpected contaminations with unauthorized genetically modified (GM) bacteria (viable cells and associated DNA) that were carrying antimicrobial resistance (AMR) genes was noticed in several microbial fermentation products that have been commercialized on the food and feed market. These contaminations consisted of GM Bacillus species belonging to the B. subtilis group. In order to screen for the potential presence of such contaminations, in this study we have developed a new real-time PCR method targeting the B. subtilis group, including B. subtilis, B. licheniformis, B. amyloliquefaciens and B. velezensis. The method’s performance was successfully assessed as specific and sensitive, complying with the Minimum Performance Requirements for Analytical Methods of GMO Testing that is used as a standard by the GMO enforcement laboratories. The method’s applicability was also tested on 25 commercial microbial fermentation products. In addition, this method was developed to be compatible with the PCR-based strategy that was recently developed for the detection of unauthorized GM bacteria. This taxon-specific method allows the strengthening of the set of screening markers that are targeting key sequences that are frequently found in GM bacteria (AMR genes and shuttle vector), reinforcing control over the food and feed chain in order to guarantee its safety and traceability.
Real-Time Forest Fire Detection Framework Based on Artificial Intelligence Using Color Probability Model and Motion Feature Analysis
Authors: Wahyono  , Harjoko Agus , Dharmawan Andi , Adhinata Faisal Dharma , Kosala Gamma , Jo Kang-Hyun
Published: February 2022

As part of the early warning system, forest fire detection has a critical role in detecting fire in a forest area to prevent damage to forest ecosystems. In this case, the speed of the detection process is the most critical factor to support a fast response by the authorities. Thus, this article proposes a new framework for fire detection based on combining color-motion-shape features with machine learning technology. The characteristics of the fire are not only red but also from their irregular shape and movement that tends to be constant at specific locations. These characteristics are represented by color probabilities in the segmentation stage, color histograms in the classification stage, and image moments in the verification stage. A frame-based evaluation and an intersection over union (IoU) ratio was applied to evaluate the proposed framework. Frame-based evaluation measures the performance in detecting fires. In contrast, the IoU ratio measures the performance in localizing the fires. The experiment found that the proposed framework produced 89.97% and 10.03% in the true-positive rate and the false-negative rate, respectively, using the VisiFire dataset. Meanwhile, the proposed method can obtain an average of 21.70 FPS in processing time. These results proved that the proposed method is fast in the detection process and can maintain performance accuracy. Thus, the proposed method is suitable and reliable for integrating into the early warning system.