bluuebunny/crossref_metadata_2025 huggingface dataset:
Hop By-Products: Pharmacological Activities and Potential Application as Cosmetics
Authors: Pereira Olívia R. , Santos Gleiciara , Sousa Maria João
Published: December 2022

Hops (Humulus lupulus L.) are known worldwide as a raw material in beer production due their flavor and preservative values. The beneficial properties of the plant have been mostly associated with the female hop inflorescences (cones), which is also the part used in the brewing industry. However, some studies indicate the presence of compounds associated with health benefits in the vegetative parts of hops or small-caliber cones, which discarded in hop collection. Moreover, large quantities of by-products remain in the forms of spent grains and spent hops/hot trub and are produced by breweries raising environmental and economic sustainability concerns. This review focuses on the phytochemicals and biological and pharmacological activities of hop and their potential use in skin care products and also intends to explore the potential of the hop’ discarded parts and brewery industry by-products for production in the cosmetics industry.
Molecular Structures of the Pyridine-2-olates PhE(pyO)3 (E = Si, Ge, Sn)—[4+3]-Coordination at Si, Ge vs. Heptacoordination at Sn
Authors: Kuß Sarah , Brendler Erica , Wagler Jörg
Published: December 2022

The phenyltetrel pyridine-2-olates PhE(pyO)3 (E = Si, Ge, Sn; pyO = pyridine-2-olate) were synthesized from the respective chlorides PhECl3 and 2-hydroxypyridine (2-pyridone) with the aid of a sacrificial base (triethylamine). Their solid-state structures were determined by single-crystal X-ray diffraction. PhSi(pyO)3 exhibits a three-fold capped tetrahedral Si coordination sphere ([4+3]-coordination, Si···N separations ca. 3.0 Å), in accordance with structures of previously reported silicon pyridine-2-olates. PhGe(pyO)3 adopts a related [4+3]-coordination mode, which differs in terms of the tetrahedral faces capped by the pyridine N atoms. Additionally, shorter Ge···N separations (2.8–2.9 Å) indicate a trend toward tetrel hypercoordination. PhSn(pyO)3 features heptacoordinate tin within a pentagonal bipyramidal Sn coordination sphere (Sn···N separations 2.2–2.4 Å). For the Si and Sn compounds, 29Si and 119Sn NMR spectroscopy indicates retention of their tetrel coordination number in chloroform solution.
Understanding Spatiotemporal Variation in Richness and Rate of Within-Site Turnover for Vegetation Communities in Western Eurasia over the Last 4000 Years
Authors: Goodenough Anne E. , Webb Julia C.
Published: December 2022

Vegetation communities are intricate networks of co-occurring species. Logistical challenges in collecting primary data means research often utilises short-term data from restricted geographical areas. In this study, we examine spatiotemporal change in richness and turnover of vascular plants and bryophytes over the last 4000 years at 23 sites in western Eurasia using high-resolution palaeoecological data. We find support for the Latitudinal Diversity Gradient and Altitudinal Diversity Gradient in both the overall vegetation community (arboreal and non-arboreal species) and the shrub and herb sub-community (non-arboreal species only), as well as a significant temporal increase in the gradient of both relationships. There was a temporal increase in (alpha) richness; the rate of turnover was high but temporally consistent for the overall vegetation community and high but decreasing over time for the shrub and herb sub-community. The rate of change in turnover was affected by latitude (steeper negative relationship at higher latitudes) and altitude (steeper negative relationship at lower altitudes). The Diversity-Stability Hypothesis was supported: vegetation communities changed from “lower richness, higher turnover” historically to “higher richness, lower turnover” more recently. Causal mechanisms for these complex interlinked biogeographical patterns remain ambiguous, but likely include climate change, non-native introductions, increasing homogenisation of generalist taxa, landscape simplification, and anthropogenic disturbance. Further research into drivers of the spatiotemporal patterns revealed here is a research priority, which is especially important in the context of biodiversity decline and climate change.
Comparison of Boraginales Plastomes: Insights into Codon Usage Bias, Adaptive Evolution, and Phylogenetic Relationships
Authors: Li Qiang , Wei Ran
Published: December 2022

The Boraginales (Boraginaceae a.l.) comprise more than 2450 species worldwide. However, little knowledge exists of the characteristics of the complete plastid genome. In this study, three new sequences representing the first pt genome of Heliotropiaceae and Cordiaceae were assembled and compared with other Boraginales species. The pt genome sizes of Cordia dichotoma, Heliotropium arborescens, and Tournefortia montana were 151,990 bp, 156,243 bp, and 155,891 bp, respectively. Multiple optimal codons were identified, which may provide meaningful information for enhancing the gene expression of Boraginales species. Furthermore, codon usage bias analyses revealed that natural selection and other factors may dominate codon usage patterns in the Boraginales species. The boundaries of the IR/LSC and IR/SSC regions were significantly different, and we also found a signal of obvious IR region expansion in the pt genome of Nonea vesicaria and Arnebia euchroma. Genes with high nucleic acid diversity (pi) values were also calculated, which may be used as potential DNA barcodes to investigate the phylogenetic relationships in Boraginales. psaI, rpl33, rpl36, and rps19 were found to be under positive selection, and these genes play an important role in our understanding of the adaptive evolution of the Boraginales species. Phylogenetic analyses implied that Boraginales can be divided into two groups. The existence of two subfamilies (Lithospermeae and Boragineae) in Boraginaceae is also strongly supported. Our study provides valuable information on pt genome evolution and phylogenetic relationships in the Boraginales species.
Computer-Aided Breast Surgery Framework Using a Markerless Augmented Reality Method
Authors: Khang Seungwoo , Park Taeyong , Lee Junwoo , Kim Kyung Won , Song Hyunjoo , Lee Jeongjin
Published: December 2022

This study proposes a markerless Augmented Reality (AR) surgical framework for breast lesion removal using a depth sensor and 3D breast Computed Tomography (CT) images. A patient mesh in the real coordinate system is acquired through a patient 3D scan using a depth sensor for registration. The patient mesh on the virtual coordinate system is obtained by contrast-based skin segmentation in 3D mesh generated from breast CT scans. Then, the nipple area is detected based on the gradient in the segmented skin area. The region of interest (ROI) is set based on the detection result to select the vertices in the virtual coordinate system. The mesh on the real and virtual coordinate systems is first aligned by matching the center of mass, and the Iterative Closest Point (ICP) method is applied to perform more precise registration. Experimental results of 20 patients’ data showed 98.35 ± 0.71% skin segmentation accuracy in terms of Dice Similarity Coefficient (DSC) value, 2.79 ± 1.54 mm nipple detection error, and 4.69 ± 1.95 mm registration error. Experiments using phantom and patient data also confirmed high accuracy in AR visualization. The proposed method in this study showed that the 3D AR visualization of medical data on the patient’s body is possible by using a single depth sensor without having to use markers.
Identification of an Individualized Prognostic Biomarker for Serous Ovarian Cancer: A Qualitative Model
Authors: Luo Fengyuan , Li Na , Zhang Qi , Ma Liyuan , Li Xinqiao , Hu Tao , Zhong Haijian , Li Hongdong , Hong Guini
Published: December 2022

Serous ovarian cancer is the most common type of ovarian epithelial cancer and usually has a poor prognosis. The objective of this study was to construct an individualized prognostic model for predicting overall survival in serous ovarian cancer. Based on the relative expression orderings (Ea > Eb/Ea ≤ Eb) of gene pairs closely associated with serous ovarian prognosis, we tried constructing a potential individualized qualitative biomarker by the greedy algorithm and evaluated the performance in independent validation datasets. We constructed a prognostic biomarker consisting of 20 gene pairs (SOV-P20). The overall survival between high- and low-risk groups stratified by SOV-P20 was statistically significantly different in the training and independent validation datasets from other platforms (p < 0.05, Wilcoxon test). The average area under the curve (AUC) values of the training and three validation datasets were 0.756, 0.590, 0.630, and 0.680, respectively. The distribution of most immune cells between high- and low-risk groups was quite different (p < 0.001, Wilcoxon test). The low-risk patients tended to show significantly better tumor response to chemotherapy than the high-risk patients (p < 0.05, Fisher’s exact test). SOV-P20 achieved the highest mean index of concordance (C-index) (0.624) compared with the other seven existing prognostic signatures (ranging from 0.511 to 0.619). SOV-P20 is a promising prognostic biomarker for serous ovarian cancer, which will be applicable for clinical predictive risk assessment.
Gross Cystic Disease Fluid Protein-15 (GCDFP-15) Expression Characterizes Breast Mucinous Carcinomas in Older Women
Authors: Kinoshita Mayumi , Sawabe Motoji , Soejima Yurie , Mieno Makiko Naka , Arai Tomio , Honma Naoko
Published: December 2022

The predominant histological subtype of breast mucinous carcinoma in older women is type B (hypercellular type), and, in younger women, it is type A (hypocellular type). The characteristics of mucinous carcinomas of the same histological subtype may differ between older and younger women. This study aims to systematically clarify the pathological/immunohistochemical features of mucinous carcinomas. A total of 21 surgical cases of mucinous carcinoma (type A/B: 9/12 cases) in the older group (≥65 years) and 16 cases (type A/B: 14/2 cases) in the younger group (≤55 years) (n = 37) were included. Gross cystic disease fluid protein-15 (GCDFP-15) and eight other markers were used for immunostaining. The GCDFP-15-positive rate in the older group was high regardless of the histological subtype (type A, 77.8%; type B, 91.7%). The GCDFP-15 positivity in the older group was significantly higher than that in the younger group (p < 0.001 for Allred score). Among type A, GCDFP-15 positivity was significantly higher in the older group than in the younger group (p = 0.042 for the Allred score and p = 0.007 for the positivity rate). The present results suggest that GCDFP-15 expression characterizes mucinous carcinomas in older women.
Golden Mean and Proportion in Dental Esthetics after Orthodontic Treatments: An In Vivo Study
Authors: Lucchi Patrizia , Fortini Giulia , Preo Giorgia , Gracco Antonio , De Stefani Alberto , Bruno Giovanni
Published: December 2022

Purpose: The definition of the golden ratio was established around the sixth century BC; Levin and Snow developed specific theories applicable in dentistry, which apply the golden proportion rule with the intention of reproducing a perfect smile. This study analyzed the literature and assessed whether these concepts remain valid and applicable in clinical practice, evaluating the theories with a group of patients followed by an experienced orthodontic team. Methods: This study was retrospectively performed on 400 patients (241 females and 159 males) who underwent orthodontic treatments. The analysis was conducted on intraoral frontal photos, both pre-treatment and post-orthodontic treatment, to observe if there was a statistically significant difference in the tooth display according to the golden mean and golden proportion theories. Results: The canine at the end of the orthodontic treatment had a greater visibility than that proposed by Levin and Snow. Conclusions: This study revealed how these theories could be considered in certain respects, but nowadays are not totally valid and applicable to the clinical reality. Snow’s theory appears to be more consistent with the clinical findings than Levin’s theory.
The Use of Polyetheretherketone (PEEK) as an Alternative Post and Core Material: Five-Year Follow-Up Report
Authors: Kasem Ammar T. , Shams Mahmoud , Tribst João Paulo Mendes
Published: December 2022

This clinical report demonstrated the use of polyetheretherketone (PEEK) for manufacturing of custom-made post and core in weakened endodontically treated central incisors. The PEEK structure was manufactured using computer-aided design/computer-aided manufacturing (CAD/CAM). The optimal fit of this custom-made endodontic post allowed a thinner cement layer; and removed the need to manufacture a core build-up. While supplementary clinical trials and in vitro studies are needed to totally elucidate the advantages and limitations of PEEK as an option for post and core manufacturing, this case report showed that it can be promising for a predictable and simplified treatment with five years of success.
Poetry and Motion: Rhythm, Rhyme and Embodiment as Oral Literacy Pedagogy for Young Additional Language Learners
Authors: Beaumont Natasha Elizabeth
Published: December 2022

Literacy pedagogy that integrates oracy, poetry and embodiment can foster children’s language development in multiple ways: (1) oracy is foundational to children’s emergent literacy as writing extends from oral language, (2) poetry uses rhythm and rhyme to support letter-recognition and the learning of phonemes and morphemes, (3) embodiment and roleplay provide semiotic support and opportunities for expressive and receptive communication. This article shares findings from a phenomenological case study investigating how literacy pedagogy that integrated oracy, poetry and embodiment impacted three additional language students aged 6. A series of weekly literacy classes in a school in Sydney’s multicultural western region were observed and recorded on video. This instrument was able to capture ‘micro-moments’ of learning between peers, depicting how physicalisation and the use of rhythm and rhyme effectively engaged students whose first language was not used in the classroom. Using a hermeneutic phenomenological approach to data analysis, case study findings revealed that embodied explorations of poetry immersed participants socially and imaginatively whilst pushing them beyond their additional language comfort zone. The pedagogy was also shown to increase comprehension and support the acquisition of new vocabulary.
Digital Twin-Based Zero-Touch Management for IoT
Authors: Ma Jiali , Guo Yuanbo , Fang Chen , Zhang Qi
Published: December 2022

The rapid development of the Internet of Things (IoT) requires network automation, to improve management efficiency and reduce manual operations. Zero-touch network is a promising technology for empowering network management automation by creating virtualized networks for software-based solutions. However, the traditional software-defined network (SDN) technology is not suitable for IoT devices, due to its massive, heterogeneous, and distributed characteristics. In this paper, we introduce digital twin technology (DT) into the IoT, and propose a DT modeling method through ontology and knowledge graph technologies, which maps IoT elements in the digital space and provides the advantages of centralized control, device abstraction, and flexible control of management. Then, referring to the conceptual architecture of a zero-touch network, a DT-based zero-touch management framework suitable for IoT is established. Finally, aiming at specific device management and network optimization problems in the IoT, a zero-touch management scheme with digital twin technology as the core and intention as the driver is proposed, and the effectiveness of the proposed method is demonstrated using an example.
Wideband Lorenz Resonance Reconfigurable Metasurface for 5G+ Communications
Authors: Yang Chun , Yang Chuanchuan , Zhang Cheng , Feng Jiqiang , Xu Chen , Li Hongbin
Published: December 2022

Reconfigurable intelligent surfaces (RIS) have been considered as a promising solution to enhance the spectrum and energy efficiency of the 5G+ and future 6G wireless communication systems. The performance of RIS will become the key metric of these communication systems. In this paper, we proposed a wideband Lorenz resonance-based metasurface reconfigurable reflectarray (MSRRA) realization scheme with low energy consumption targeted at the center frequency of 28 GHz. A compact voltage bias network for the varactor diodes is carefully designed to reduce losses in RF current and the influence of the bias circuit on the radiating element effectively. An equivalent circuit model for the MSRRA unit cell is also introduced to predict the properties of the MSRRA system, which can be used to optimize the MSRRA design efficiently. In the experimental tests, the proposed MSRRA system can be optimized to cover a dynamic reflection phase range of over 300° with a bandwidth of 3.83 GHz, which is consistent with the simulation results. The measured single-scattering beam bandwidth is 1.85 GHz at the center frequency of 28 GHz, which can fully cover the whole n257 channel of 5G NR. The proposed continuous tunable MSRRA can support 5G+ and 6G indoor, short-range links, and outdoor point-to-point communications.
A 320 μW Multi-Band Receiver with N-Path Switched-Capacitor Networks
Authors: Lei Lei , Han Fang , Liu Zicheng , Qi Quanwen , Wang Xinghua , Wang Weijiang
Published: December 2022

This paper presents a multi-band ultra-low power (ULP) receiver with N-Path Switched-Capacitor (NPSC) networks in 90 nm CMOS process. The NPSC is integrated into the feedback loop of the low noise amplifier (LNA) to flexibly provide narrowband input matching at multiple sub-GHz Industrial, Scientific, and Medical (ISM) bands by adjusting the switching frequency. Moreover, the LNA with an NPSC network is utilized to suppress the out-of-band signal at the input and output of the LNA, simultaneously. In order to achieve an ultra-low power consumption, a sub-threshold LNA and four passive NPSC mixers are implemented in this receiver. The ULP receiver achieves a measured gain of 40±2 dB in ISM bands (430/860/915/960 MHz). The measured noise figure and out-of-band IIP3 are 10±0.5 dB and −0.3±2 dBm, respectively. The ULP receiver chip consumes 320 μW at 0.4 V power supply and occupies a chip area of 0.31 mm2.
Compact High-Directivity Contra-Directional Coupler
Authors: Chang Won Il , Chung Mahn Jea , Park Chul Soon
Published: December 2022

This paper presents a novel design of a compact contra-directional coupler with high directivity for high-power monitoring in high frequency. Microstrip parallel coupled lines are widely used for directional couplers; however, they show poor directivity inherently. Their directivity has been improved by many works. However, the suggested approaches often result in other limitations, such as a weak structure for high-power monitoring, or a larger size to be integrated with other circuits. The design approach proposed in this study starts from a ring-type four-port network to avoid weak components that are vulnerable to high power, and uses a 60° electrical length of coupled line for a compact size. The design equations for the initial dimensions are derived from the ring-type four-port network model. The weak coupling of the 20 dB coupler was designed and measured. The measurement shows 20 dB directivity from 12.8 GHz to 14.8 GHz, covering the Ku-band satellite uplink communication and peak directivity of about 45 dB. The coupler’s active area is 4 mm by 5.5 mm; this is a compact size compared with other works.
Approach for Designing Real-Time IoT Systems
Authors: Deniziak Stanisław , Płaza Mirosław , Arcab Łukasz
Published: December 2022

Along with the rapid development of Internet of Things (IoT) technology over the past few years, opportunities for its implementation in service areas that require real-time requirements have begun to be recognized. In this regard, one of the most important criteria is to maintain Quality of Service (QoS) parameters at an appropriate and sufficiently high level. The QoS level should ensure the delivery of data packets in the shortest time possible while preventing critical parameters relevant to real-time transmission from being exceeded. This article proposes a new methodology for designing real-time IoT systems. The premise of the proposed approach is to adapt selected solutions used in other types of systems working with real-time requirements. Some analogy to embedded systems with a distributed architecture has been noted and used in this regard. The main differences from the concept of built-in systems can primarily be seen in the communication layer. The methodology proposed in this article is based on the authors’ proposed model of real-time system functional specification and its mapping to the IoT architecture. In addition, the developed methodology makes extensive use of selected IoT architecture elements described in this article, as well as selected task scheduling methods and communication protocols. The proposed methodology for designing RTIoT systems is based on dedicated transmission serialization methods and dedicated routing protocols. These methods ensure that the time constraints for the assumed bandwidth of IoT links are met by appropriately prioritizing transmissions and determining communication routes. The presented approach can be used to design a broad class of RTIoT systems.
A 3D Scene Information Enhancement Method Applied in Augmented Reality
Authors: Li Bo , Wang Xiangfeng , Gao Qiang , Song Zhimei , Zou Cunyu , Liu Siyuan
Published: December 2022

Aiming at the problem that the detection of small planes with unobvious texture is easy to be missed in augmented reality scene, a 3D scene information enhancement method to grab the planes for augmented reality scene is proposed based on a series of images of a real scene taken by a monocular camera. Firstly, we extract the feature points from the images. Secondly, we match the feature points from different images, and build the three-dimensional sparse point cloud data of the scene based on the feature points and the camera internal parameters. Thirdly, we estimate the position and size of the planes based on the sparse point cloud. The planes can be used to provide extra structural information for augmented reality. In this paper, an optimized feature points extraction and matching algorithm based on Scale Invariant Feature Transform (SIFT) is proposed, and a fast spatial planes recognition method based on a RANdom SAmple Consensus (RANSAC) is established. Experiments show that the method can achieve higher accuracy compared to the Oriented Fast and Rotated Brief (ORB), Binary Robust Invariant Scalable Keypoints (BRISK) and Super Point. The proposed method can effectively solve the problem of missing detection of faces in ARCore, and improve the integration effect between virtual objects and real scenes.
System for Semi-Automated Literature Review Based on Machine Learning
Authors: Bacinger Filip , Boticki Ivica , Mlinaric Danijel
Published: December 2022

This paper presents the design and implementation of a system for semi-automating the literature review process based on machine learning. By using machine learning algorithms, the system determines whether scientific papers belong to the topic that is being explored as part of the review process. The system’s user interface allows the process of creating a literature review to be managed through a series of steps: selecting data sources, building queries and topic searches, displaying the scientific papers found, selecting papers that belong to the set of desired papers, running machine learning algorithms for learning and automated classification, and displaying and exporting the final set of papers. Manual literature reviews are compared with automated reviews, and similarities and differences between the two approaches in terms of duration, accuracy, and ease of use are discussed. This study concludes that the best results in terms of sensitivity and accuracy for the automated literature review process are achieved by using a combined machine learning model, which uses multiple unweighted machine learning models. Cross-testing the models on two alternative datasets revealed an overlap in the machine learning hyperparameters. The stable sensitivity and accuracy in the tests indicate the potential for generalized use in automated literature review.
A Study on the Wind Power Forecasting Model Using Transfer Learning Approach
Authors: Oh JeongRim , Park JongJin , Ok ChangSoo , Ha ChungHun , Jun Hong-Bae
Published: December 2022

Recently, wind power plants that generate wind energy with electricity are attracting a lot of attention thanks to their smaller installation area and cheaper power generation costs. In wind power generation, it is important to predict the amount of generated electricity because the power system would be unstable due to uncertainty in supply. However, it is difficult to accurately predict the amount of wind power generation because the power varies due to several causes, such as wind speed, wind direction, temperature, etc. In this study, we deal with a mid-term (one day ahead) wind power forecasting problem with a data-driven approach. In particular, it is intended to solve the problem of a newly completed wind power generator that makes it very difficult to predict the amount of electricity generated due to the lack of data on past power generation. To this end, a deep learning based transfer learning model was proposed and compared with other models, such as a deep learning model without transfer learning and Light Gradient Boosting Machine (LGBM). As per the experimental results, when the proposed transfer learning model was applied to a similar wind power complex in the same region, it was confirmed that the low predictive performance of the newly constructed generator could be supplemented.
Webly Supervised Fine-Grained Image Recognition with Graph Representation and Metric Learning
Authors: Lin Jianman , Lin Jiantao , Gao Yuefang , Yang Zhijing , Chen Tianshui
Published: December 2022

The aim of webly supervised fine-grained image recognition (FGIR) is to distinguish sub-ordinate categories based on data retrieved from the Internet, which can significantly mitigate the dependence of deep learning on manually annotated labels. Most current fine-grained image recognition algorithms use a large-scale data-driven deep learning paradigm, which relies heavily on manually annotated labels. However, there is a large amount of weakly labeled free data on the Internet. To utilize fine-grained web data effectively, this paper proposes a Graph Representation and Metric Learning (GRML) framework to learn discriminative and effective holistic–local features by graph representation for web fine-grained images and to handle noisy labels simultaneously, thus effectively using webly supervised data for training. Specifically, we first design an attention-focused module to locate the most discriminative region with different spatial aspects and sizes. Next, a structured instance graph is constructed to correlate holistic and local features to model the holistic–local information interaction, while a graph prototype that contains both holistic and local information for each category is introduced to learn category-level graph representation to assist in processing the noisy labels. Finally, a graph matching module is further employed to explore the holistic–local information interaction through intra-graph node information propagation as well as to evaluate the similarity score between each instance graph and its corresponding category-level graph prototype through inter-graph node information propagation. Extensive experiments were conducted on three webly supervised FGIR benchmark datasets, Web-Bird, Web-Aircraft and Web-Car, with classification accuracy of 76.62%, 85.79% and 82.99%, respectively. In comparison with Peer-learning, the classification accuracies of the three datasets separately improved 2.47%, 4.72% and 1.59%.
An IoT-Based Framework and Ensemble Optimized Deep Maxout Network Model for Breast Cancer Classification
Authors: Peta Jyothi , Koppu Srinivas
Published: December 2022

Internet of Things (IoT) plays an essential role in the area of the healthcare system. IoT devices provide information about patients in the healthcare monitoring framework. Moreover, patients can examine their health with smart devices and hence IoT is a major factor in all aspects of the health care management system. Breast cancer is a deadly cancer in women and the detection of this disease at the primary stage increases the survival rate. Due to the computational complexity associated with acquiring features, classification results generated from the existing methods are unsatisfactory and hence it is important to design a method using deep learning concepts for classifying cancer disease. An efficient and robust classification model named Student Psychology Whale Optimization-based Deep maxout network with optimization (SPWO-based Deep maxout network) classifies breast cancer disease. The advantage of using a Deep maxout network is that it effectively learns intrinsic features from the data. The weight factor of the deep learning model is updated with respect to iteration based on the fitness measure that in turn results in higher results by acquiring a minimal error value. However, the proposed model obtains outstanding accuracy, sensitivity, and specificity in terms of testing with the values of 0.931, 0.953, and 0.915 with 100 nodes.
Optimal Schedule the Operation Policy of a Pumped Energy Storage Plant Case Study Zimapán, México
Authors: Acuña Gerardo , Domínguez Ramón , Arganis Maritza L. , Fuentes Oscar
Published: December 2022

Pumped-storage hydroelectric plants are an alternative to adapting the energy generation regimen to that of the demand, especially considering that the generation of intermittent clean energy provided by solar and wind power will cause greater differences between these two regimes. In this research, an optimal operation policy is determined through a simulation tool that allows the annual benefits under the energy arbitration service (purchase–sale) to be estimated, considering the variations of the energy price in Mexico. A case study is proposed in the Zimapán hydroelectric facility, where reservoir operation at the hourly level is simulated with records for a period of 3 years, considering historical values. The results establish that this type of pumped storage power plant obtains greater benefits by generating electrical energy during 8 h of high demand and pumping for more than 11 continuous hours in times of low demand. With this configuration, the PHES consumes 82.33 GWh/year more energy than it produces, and the energy generated is 210.83 GWh/year; however, when considering the energy arbitration service, a net income of more than USD 3.25 million per year is identified, which represents a 123.52% increase for the annual energy purchase.
Research on Cyber ISR Visualization Method Based on BGP Archive Data through Hacking Case Analysis of North Korean Cyber-Attack Groups
Authors: Youn Jaepil , Kim Kookjin , Kang Daeyoung , Lee Jaeil , Park Moosung , Shin Dongkyoo
Published: December 2022

North Korean cyber-attack groups such as Kimsuky, Lazarus, Andariel, and Venus 121 continue to attempt spear-phishing APT attacks that exploit social issues, including COVID-19. Thus, along with the worldwide pandemic of COVID-19, related threats also persist in cyberspace. In January 2022, a hacking attack, presumed to be Kimsuky, a North Korean cyber-attack group, intending to steal research data related to COVID-19. The problem is that the activities of cyber-attack groups are continuously increasing, and it is difficult to accurately identify cyber-attack groups and attack origins only with limited analysis information. To solve this problem, it is necessary to expand the scope of data analysis by using BGP archive data. It is necessary to combine infrastructure and network information to draw correlations and to be able to classify infrastructure by attack group very accurately. Network-based infrastructure analysis is required in the fragmentary host area, such as malware or system logs. This paper studied cyber ISR and BGP and a case study of cyber ISR visualization for situational awareness, hacking trends of North Korean cyber-attack groups, and cyber-attack tracking. Through related research, we estimated the origin of the attack by analyzing hacking cases through cyber intelligence-based profiling techniques and correlation analysis using BGP archive data. Based on the analysis results, we propose an implementation of the cyber ISR visualization method based on BGP archive data. Future research will include a connection with research on a cyber command-and-control system, a study on the cyber battlefield area, cyber ISR, and a traceback visualization model for the origin of the attack. The final R&D goal is to develop an AI-based cyber-attack group automatic identification and attack-origin tracking platform by analyzing cyber-attack behavior and infrastructure lifecycle.
Comparison of Two Measurement Methods for the Emission of Radiated Disturbances Generated by LED Drivers
Authors: Kuryło Kazimierz , Sabat Wiesław , Klepacki Dariusz , Kamuda Kazimierz
Published: December 2022

The comparison of the results obtained using two methods for measuring the radio disturbance emissions produced by compact lighting drivers in the frequency range of 30 to 300 MHz has been presented in this paper. Any electrical and electronic equipment used within the EU must comply with Directive 2014/30/EC and harmonised standards. For lighting equipment, the dedicated standard is EN-IEC 55015:2019-11E. In this standard, for tests in the frequency range of 30 to 300 MHz, two equivalent test methods are allowed for lighting drivers, i.e., the traditional method in which disturbance emissions are measured in a semianechoic chamber SAC and the alternative CDNE (Coupling Decoupling Network Emission) method. Each method is characterised by a different measurement technique. For this reason, this paper aims to compare the results obtained by the two methods and to find out whether the CDNE and SAC methods, despite the difference in measurement technique, can be considered equivalent. The theoretical part of this study presents the results of an analysis of the literature on the subject and the technical aspects of measuring disturbance emission using both measurement methods. The practical part describes the construction of measurement stands for selected LED lamps and presents the measurement results and their statistical analysis.
Assessment of Past Decadal Dynamics of Tree Stands in Forest–Tundra Transition Zone on the Polar Ural Mountains Calibrated Using Historical and Modern Field Measurements
Authors: Nizametdinov Nail’ F. , Shalaumova Yulia V. , Mazepa Valery S. , Moiseev Pavel A.
Published: December 2022

Altitudinal forest limits are typically climatically dependent, such that increasing temperatures connected to global warming are causing upslope shifts in treeline ecotones worldwide. However, at the local and regional levels, the degree of such a response is dependent on differences in climate, topography and soil features. In recent decades, attempts have been undertaken to estimate tree stand dynamics with remote sensing methods, but their resolution is still too coarse for a precise assessment of stand structural changes, and requires ground-truthing, which is not possible without historical data collected on a single-tree level. We used aerial photos (1962) and satellite images (2021) in combination with historical inventory data to investigate changes in open forest positions at different spatial scales at the eastern macroslope of the Polar Urals over the past 60 years. Additionally, obtained remote sensing data were validated on a single-slope level using tree crown size estimations. Our investigations showed that since 1960 up to present day, the total crown coverage increased from 6.9 to 22.1% within the test polygon. A highly spatially variable upslope advance in an open forest boundary was identified from 1.7 up to 7.1 m in altitude per decade. We revealed that the rate of tree stand transformations was to a great extent depended on the stand density in the 1960s, soil substrate type, moisture regime, slope aspect and inclination. Our results highlighted the necessity to consider the abovementioned factors when trying to predict climate-induced tree distributional responses in subarctic mountain regions.
Promotion Effects of Taxus chinensis var. mairei on Camptotheca acuminata Seedling Growth in Interplanting Mode
Authors: Zhao Chunjian , Shi Sen , Ahmad Naveed , Gao Yinxiang , Xu Chunguo , Guan Jiajing , Fu Xiaodong , Li Chunying
Published: December 2022

Wild Camptotheca acuminata Decne (C. acuminata) resources are becoming endangered and face poor growth. Preliminary investigation results found that the growth of C. acuminata in an artificial mixed forest of Taxus chinensis var. mairei (Lemee et Levl.), Cheng et L. K. Fu (T. chinensis var. mairei) and C. acuminata was significantly higher than that in pure forests. Understanding the reasons for the above differences can help create a mixed forest of T. chinensis var. mairei and C. acuminata to solve the problem of depleting C. acuminata resources. In this study, the growth and soil indexes under two different modes (C. acuminata/T. chinensis var. mairei interplanted and monocultured C. acuminata seedlings) were compared. The results showed that plant height, basal diameter, photosynthesis rate and chlorophyll content of C. acuminata under the interplanting mode were higher than those under monoculture. The growth rates of plant height and basal diameter that were calculated from interplanted specimens increased by 25% and 40%, respectively, compared with those from specimens that were monocultured. Photosynthetic rates from different light intensities under interplanting were higher than those in seedlings under monoculture. The contents of chlorophylls a and b and total chlorophyll under interplanting were 1.50, 1.59, and 1.47 times higher than those under monoculture, respectively. The numbers of bacteria and fungi in the interplanted culture were higher than those in the monoculture. Furthermore, the differences in microbial diversity under different planting modes were analyzed via the amplicon sequencing method. Soil enzyme activities increased under interplanting compared with that in the monoculture. Taxane allelochemicals were detected in the range of 0.01–0.67 μg/g in the interplanting mode from April to September. T. chinensis var. mairei may increase the establishment and productivity of C. acuminata seedlings under interplanting mode through improvements in enzyme activity, changes in microorganism population structure, and release of allelochemicals.
The Long-Lasting Territories of Forest Apex Predators Sustain Diverse Bird Communities throughout the Year
Authors: Kajtoch Łukasz , Kusal Bartłomiej
Published: December 2022

Apex predators, such as raptors, are used as surrogates to attain conservation objectives; however, their presence in a particular area does not necessarily mean long-term occurrence. Here we used data on long-lasting (20–40 years) territories of two generalist raptors: the diurnal Northern goshawk and the nocturnal Ural owl in deciduous and coniferous forests of southern Poland to assess their role as hotspots of bird diversity. Species richness and abundance of birds were much higher in the long-lasting territories of both apex predators than in random never-occupied sites and this pattern was common for breeding and wintering periods. These differences were more pronounced in deciduous than coniferous stands. Rare bird species (e.g., annexed in the Bird Directive of the European Parliament and of the Council on the conservation of wild birds such as some woodpeckers and flycatchers) were found to be particularly associated with long-lasting territories of raptors. Long-lasting territories were also characterized by greater forest habitat quality (e.g., higher number of old trees and deadwood) with lower management intensity. These results strongly point to the role of long-lasting territories of raptors as surrogates of biodiversity. Such territories, if known in forests, could be excellent for the designation of protected areas or logging there should at least be reduced to allow for the continuous breeding of apex predators and associated bird assemblages.
Microclimate Drives Shelter-Seeking Behaviour in Lambing Ewes
Authors: Atkin-Willoughby Jack , Hollick Sam , Pritchard Charlotte E. , Williams A. Prysor , Davies Peers L. , Jones Dewi , Smith Andrew R.
Published: December 2022

Silvopastoral agroforestry and the strategic placement of trees and hedgerows offers potential to improve livestock welfare and production efficiency through the provision of shelter in livestock farming systems. The aim of this study was to investigate the relationship between shelter-seeking behaviour of ewes during the lambing period and the microclimate influenced by landscape shelter features. Artificial and natural shelter was provided to Aberfield ewes (n = 15) on an upland sheep farm in Wales, UK, which were then continuously monitored for 14 days using global positioning system tracking devices. Modelling of microclimate influenced by topographical shelter features at the test site was used to generate a 1 m resolution wind field for geospatial statistical analysis of localised wind speed. Ewes demonstrated an increased preference for natural (3.4-fold; p < 0.01) and artificial (3.0-fold; p < 0.05) shelter zones five times the height of the shelter, compared to the exposed area of the trial site. Wind-chill and modelled local-scale wind speeds were found to have the greatest influence on shelter-seeking behaviour, with temperature and field-scale wind speed significantly influencing livestock behaviour. Mean wind-chill temperature during the trial was 3.7 °C (min −5.3 °C; max 13.1 °C), which is within the cold stress temperature threshold (−3 and 8 °C) that requires thermoregulatory strategies such as shelter-seeking behaviour. An improved understanding of the relationship between microclimate and shelter-seeking behaviour in sheep, demonstrated through the agent-based model developed in this project, shall better inform the economic incentives (e.g., reduction in lamb mortality and forage requirements) behind silvopastoral practices that benefit farm productivity, livestock welfare and the environment.
Agro-Industrial Wastewaters for Algal Biomass Production, Bio-Based Products, and Biofuels in a Circular Bioeconomy
Authors: de Carvalho Júlio Cesar , Molina-Aulestia Denisse Tatiana , Martinez-Burgos Walter José , Karp Susan Grace , Manzoki Maria Clara , Medeiros Adriane Bianchi Pedroni , Rodrigues Cristine , Scapini Thamarys , Vandenberghe Luciana Porto de Souza , Vieira Sabrina , Woiciechowski Adenise Lorenci , Soccol Vanete Thomaz , Soccol Carlos Ricardo
Published: December 2022

Recycling bioresources is the only way to sustainably meet a growing world population’s food and energy needs. One of the ways to do so is by using agro-industry wastewater to cultivate microalgae. While the industrial production of microalgae requires large volumes of water, existing agro-industry processes generate large volumes of wastewater with eutrophicating nutrients and organic carbon that must be removed before recycling the water back into the environment. Coupling these two processes can benefit the flourishing microalgal industry, which requires water, and the agro-industry, which could gain extra revenue by converting a waste stream into a bioproduct. Microalgal biomass can be used to produce energy, nutritional biomass, and specialty products. However, there are challenges to establishing stable and circular processes, from microalgae selection and adaptation to pretreating and reclaiming energy from residues. This review discusses the potential of agro-industry residues for microalgal production, with a particular interest in the composition and the use of important primary (raw) and secondary (digestate) effluents generated in large volumes: sugarcane vinasse, palm oil mill effluent, cassava processing waster, abattoir wastewater, dairy processing wastewater, and aquaculture wastewater. It also overviews recent examples of microalgae production in residues and aspects of process integration and possible products, avoiding xenobiotics and heavy metal recycling. As virtually all agro-industries have boilers emitting CO2 that microalgae can use, and many industries could benefit from anaerobic digestion to reclaim energy from the effluents before microalgal cultivation, the use of gaseous effluents is also discussed in the text.
Evaluation of the Thermal Processes on Changing the Phenotypic Characteristics of Escherichia coli Strains from Ice Cream Compared to Non-Pasteurized Milk
Authors: Ranjbar Maryam , Nedaeinia Reza , Goli Mohammad , Shahi Sharifeh
Published: December 2022

Escherichia coli (E. coli) is shocked by various temperature processes in milk, which forces the organism to make proteins as a result of changes in the synthesis of enzymes that might give the strain special characteristics. The purpose of this study was to investigate the effects of the heat shock factor on changing the results of biochemical and molecular tests among E. coli strains obtained from ice cream and non-pasteurized milk when compared to a reference strain from the American-type culture collection (ATCC) in order to determine the phenotypic variation caused by the temperature conditions of the manufacturing process. Furthermore, isolates with characteristics similar to E. coli were discovered, but they were not E. coli and caused some ambiguity. To test the E. coli contamination of traditional and industrial ice cream, 82 samples were chosen at random. SDS-PAGE and 16S rDNA sequencing were carried out, as well as phenotypic testing. Isolated strains did not exactly match the reference strain. The results of biochemical testing and protein analysis revealed that the isolates were diverse. Samples E. coli phenons were classified. In the electrophoresis, the ice cream strain had two protein bands in the 20.75 and 23.59 kDa ranges that were distinct from the reference strain. These isolates appear to experience alterations in enzyme characteristics and structural proteins as a result of being exposed to various temperature conditions, such as pasteurization and frigidity. When compared to the reference strain, the calculated similarity percentage of the elicited isolate varied from 60 to 70%. The electrophoretic patterns of E. coli isolated elicited from milk samples differed from E. coli isolated obtained from the ice cream. The distinctions were in the intensity or position of the bands. The results also revealed that when isolates are subjected to thermal stresses, they exhibit a pattern similar to that of ice cream isolates. These considerations are made because a change in protein composition might result in a change in biochemical features, resulting in uncertainty in its identification. Sequences revealed that the sequences were related to E. coli 16S rDNA, despite differences in phenotypic and electrophoretic features between the isolated bacteria and the reference strain E. coli ATCC 25922. Our findings revealed that 16S rDNA could potentially be used to instantly implement an appropriate preventive measure for the purpose of identifying this type of bacteria and avoid some ambiguity.