bluuebunny/crossref_metadata_2025 huggingface dataset:
Effects of Peri-Urbanization on Coastal Sage Scrub Ant Species in Baja California
Authors: Mieles Alejandro E. , Voss Margaret A. , Jiménez-Soto Estelí
Published: August 2023

Increasing urbanization on the Baja California Peninsula threatens ant diversity. Reductions in ant species diminish ecosystem services provided to semiarid coastal scrub areas. Peri-urban areas in particular are at high risk of reductions in ant biodiversity due to development. To document and evaluate ant species diversity and richness in a rapidly developing area, nine sites were sampled within areas of coastal sage scrub (CSS) encircling the urban periphery of Ensenada, Baja California. Forty species and 17 genera of ants were collected, only one of which was non-native. Although the sampled area represents less than 1% of the peninsula and 3% of the State of Baja California, approximately one-third of the total species recorded for the peninsula and state were collected. Environmental variables (compass orientation, slope, and vegetation cover) were not significant determinants of species richness. Sandy soils were associated with the highest species abundance, richness, and functional diversity of feeding guilds. Despite limitations, our results present a historically significant snapshot of ant diversity in the sage scrub areas surrounding Ensenada. Sandy regions of semiarid coastal scrub are prime conservation management areas as they support the greatest functional diversity and have the highest potential to supply environmental services to the surrounding CSS ecosystem.
Systematic Review for Risks of Pressure Injury and Prediction Models Using Machine Learning Algorithms
Authors: Barghouthi Eba’a Dasan , Owda Amani Yousef , Asia Mohammad , Owda Majdi
Published: August 2023

Pressure injuries are increasing worldwide, and there has been no significant improvement in preventing them. This study is aimed at reviewing and evaluating the studies related to the prediction model to identify the risks of pressure injuries in adult hospitalized patients using machine learning algorithms. In addition, it provides evidence that the prediction models identified the risks of pressure injuries earlier. The systematic review has been utilized to review the articles that discussed constructing a prediction model of pressure injuries using machine learning in hospitalized adult patients. The search was conducted in the databases Cumulative Index to Nursing and Allied Health Literature (CINAHIL), PubMed, Science Direct, the Institute of Electrical and Electronics Engineers (IEEE), Cochrane, and Google Scholar. The inclusion criteria included studies constructing a prediction model for adult hospitalized patients. Twenty-seven articles were included in the study. The defects in the current method of identifying risks of pressure injury led health scientists and nursing leaders to look for a new methodology that helps identify all risk factors and predict pressure injury earlier, before the skin changes or harms the patients. The paper critically analyzes the current prediction models and guides future directions and motivations.
Detecting Bone Marrow Edema of the Extremities on Spectral Computed Tomography Using a Three-Material Decomposition
Authors: Schierenbeck Marie , Grözinger Martin , Reichardt Benjamin , Jansen Olav , Kauczor Hans-Ulrich , Campbell Graeme M. , Sedaghat Sam
Published: August 2023

Background: Detecting bone marrow edema (BME) as a sign of acute fractures is challenging on conventional computed tomography (CT). This study evaluated the diagnostic performance of a three-material decomposition (TMD) approach for detecting traumatic BME of the extremities on spectral computed tomography (SCT). Methods: This retrospective diagnostic study included 81 bone compartments with and 80 without BME. A TMD application to visualize BME was developed in collaboration with Philips Healthcare. The following bone compartments were included: distal radius, proximal femur, proximal tibia, distal tibia and fibula, and long bone diaphysis. Two blinded radiologists reviewed each case independently in random order for the presence or absence of BME. Results: The interrater reliability was 0.84 (p < 0.001). The different bone compartments showed sensitivities of 86.7% to 93.8%, specificities of 84.2% to 94.1%, positive predictive values of 82.4% to 94.7%, negative predictive values of 87.5% to 93.3%, and area under the curve (AUC) values of 85.7% to 93.1%. The distal radius showed the highest sensitivity and the proximal femur showed the lowest sensitivity, while the proximal femur presented the highest specificity and the distal tibia presented the lowest specificity. Conclusions: Our TMD approach provides high diagnostic performance for detecting BME of the extremities. Therefore, this approach could be used routinely in the emergency setting.
Ankle Joint MRI—Comparison of Image Quality and Effect of Sports-Related Stress
Authors: Gorzolla Robert A. J. , Rolle Udo , Vogl Thomas J.
Published: August 2023

Objectives: The main aims of the study were the evaluation of stress-related effects (strenuous vs. non-strenuous sport vs. nonathletes) in stimulating or reducing influences on cartilage volume in the ankle joint and the evaluation of the image quality of a magnetic resonance imaging (MRI) device with a field strength of 3.0 Tesla compared to one of 1.5 Tesla. Methods: A total of 15 subjects (6 male, 9 female) aged 19–33 years participated voluntarily in this prospective study. The subjects were divided into three groups: high-performance athletes of the German Football Association (DFB) (football/soccer = strenuous sport), high-performance athletes of the German Swimming Association (DSV) (swimming = non-strenuous sport), and nonathletes. MRI was performed on both ankle joints of all subjects in the 1.5 T and 3.0 T MRI scanners using survey sequences, proton density sequences in the coronal and sagittal planes, and VIBE sequences. Using the images of both feet produced by VIBE sequences, the cartilages of the talus and tibia were manually circumscribed using a computer mouse in every third layer, and the volume was calculated. For qualitative assessment, blinded images were submitted to three radiologists with defined standards. The images were scored using a scale from 1 to 5. Results: Cartilage volume: The investigation and examination of the individual cartilage volumes by analysis of variance (ANOVA) showed no significant differences among the three groups. The effect intensities, as calculated by Cohen’s d, were right tibia (Tiri) = 2.5, left tibia (Tile) = 2.2, right talus (Tari) = 1.9, and left talus (Tale) = 1.6 in the strenuous sport versus nonstrenuous sport groups; Tiri = 0.8, Tile = 1.2, Tari = 0.4, and Tale = 0.5 in the strenuous sport versus nonathlete groups; and Tiri = 0.3, Tile = 0.2, Tari = 0.7, and Tale = 0.5 in the nonstrenuous sport versus nonathlete groups. Device comparison: In the investigation of each evaluated area on the 1.5 T and 3.0 T MR images by the Wilcoxon matched-pair test, significant differences were found for the cartilage–bone border (KKG = 0.002), cancellous bone (Sp = 0.001), medial ligamentous apparatus (mBa = 0.001), lateral ligamentous apparatus (lBa = 0.001), and adipose tissue (Fg = 0.002). Thus, there were significant differences in the assessment of the 1.5 T MRI and the 3.0 T MRI in all five evaluated areas. Conclusion: The study showed no significant difference in the volume of hyaline articular cartilage in the upper ankle joint among the high-performance strenuous DFB athlete, high-performance non-strenuous DSV athlete, and nonathlete groups. The 3.0 Tesla device offers significant advantages in image quality compared to the 1.5 Tesla device.
Stepwise Soft Actor–Critic for UAV Autonomous Flight Control
Authors: Hwang Ha Jun , Jang Jaeyeon , Choi Jongkwan , Bae Jung Ho , Kim Sung Ho , Kim Chang Ouk
Published: August 2023

Despite the growing demand for unmanned aerial vehicles (UAVs), the use of conventional UAVs is limited, as most of them require being remotely operated by a person who is not within the vehicle’s field of view. Recently, many studies have introduced reinforcement learning (RL) to address hurdles for the autonomous flight of UAVs. However, most previous studies have assumed overly simplified environments, and thus, they cannot be applied to real-world UAV operation scenarios. To address the limitations of previous studies, we propose a stepwise soft actor–critic (SeSAC) algorithm for efficient learning in a continuous state and action space environment. SeSAC aims to overcome the inefficiency of learning caused by attempting challenging tasks from the beginning. Instead, it starts with easier missions and gradually increases the difficulty level during training, ultimately achieving the final goal. We also control a learning hyperparameter of the soft actor–critic algorithm and implement a positive buffer mechanism during training to enhance learning effectiveness. Our proposed algorithm was verified in a six-degree-of-freedom (DOF) flight environment with high-dimensional state and action spaces. The experimental results demonstrate that the proposed algorithm successfully completed missions in two challenging scenarios, one for disaster management and another for counter-terrorism missions, while surpassing the performance of other baseline approaches.
Quantum State Assignment Flows
Authors: Schwarz Jonathan , Cassel Jonas , Boll Bastian , Gärttner Martin , Albers Peter , Schnörr Christoph
Published: August 2023

This paper introduces assignment flows for density matrices as state spaces for representation and analysis of data associated with vertices of an underlying weighted graph. Determining an assignment flow by geometric integration of the defining dynamical system causes an interaction of the non-commuting states across the graph, and the assignment of a pure (rank-one) state to each vertex after convergence. Adopting the Riemannian–Bogoliubov–Kubo–Mori metric from information geometry leads to closed-form local expressions that can be computed efficiently and implemented in a fine-grained parallel manner. Restriction to the submanifold of commuting density matrices recovers the assignment flows for categorical probability distributions, which merely assign labels from a finite set to each data point. As shown for these flows in our prior work, the novel class of quantum state assignment flows can also be characterized as Riemannian gradient flows with respect to a non-local, non-convex potential after proper reparameterization and under mild conditions on the underlying weight function. This weight function generates the parameters of the layers of a neural network corresponding to and generated by each step of the geometric integration scheme. Numerical results indicate and illustrate the potential of the novel approach for data representation and analysis, including the representation of correlations of data across the graph by entanglement and tensorization.
An Entropy-Based Approach to Measuring Diet Adherence
Authors: Huffman Curtis , Ortega-Avila Ana G. , Nájera Héctor
Published: August 2023

The aim of this study is to put forward an approach designed to calculate and sum up discrepancies between the actual food acquisition or intake and any standard or norm. Based on secondary analysis of cross-sectional data from the Mexican National Survey of Household Income and Expenditure, our proposed method to produce classes of entropy-based Diet Adherence Indices generates a Food Basket Adherence Index (FBAI) for Mexico City (2129 households). Findings suggest that it is possible to measure and decompose diet adherence using a cross entropy measure. Using food expenditure data and a normative food basket for Mexico City results, we show households’ deviations from the suggested norm for different food groups. The average FBAI was 0.44, far above the minimum score of 0 which would indicate full adherence to the normative food basket. Our measure has a distribution wide enough to detect meaningful changes and distinguish between groups with known differences, providing important new insights on the linkages between home food environments and income distribution, and food insecurity and household distribution.
A Survey of Video Surveillance Systems in Smart City
Authors: Myagmar-Ochir Yanjinlkham , Kim Wooseong
Published: August 2023

Smart cities are being developed worldwide with the use of technology to improve the quality of life of citizens and enhance their safety. Video surveillance is a key component of smart city infrastructure, as it involves the installation of cameras at strategic locations throughout the city for monitoring public spaces and providing real-time surveillance footage to law enforcement and other city representatives. Video surveillance systems have evolved rapidly in recent years, and are now integrated with advanced technologies like deep learning, blockchain, edge computing, and cloud computing. This study provides a comprehensive overview of video surveillance systems in smart cities, as well as the functions and challenges of those systems. The aim of this paper is to highlight the importance of video surveillance systems in smart cities and to provide insights into how they could be used to enhance safety, security, and the overall quality of life for citizens.
Sub-Pixel Convolutional Neural Network for Image Super-Resolution Reconstruction
Authors: Shao Guifang , Sun Qiao , Gao Yunlong , Zhu Qingyuan , Gao Fengqiang , Zhang Junfa
Published: August 2023

Image super-resolution (SR) reconstruction technology can improve the quality of low-resolution (LR) images. There are many available deep learning networks different from traditional machine learning algorithms. However, these networks are usually prone to poor performance on complex computation, vanishing gradients, and loss of useful information. In this work, we propose a sub-pixel convolutional neural network (SPCNN) for image SR reconstruction. First, to reduce the strong correlation, the RGB mode was translated into YCbCr mode, and the Y channel data was chosen as the input LR image. Meanwhile, the LR image was chosen as the network input to reduce computation instead of the interpolation reconstructed image as used in the super-resolution convolutional neural network (SRCNN). Then, two convolution layers were built to obtain more features, and four non-linear mapping layers were used to achieve different level features. Furthermore, the residual network was introduced to transfer the feature information from the lower layer to the higher layer to avoid the gradient explosion or vanishing gradient phenomenon. Finally, the sub-pixel convolution layer based on up-sampling was designed to reduce the reconstruction time. Experiments on three different data sets proved that the proposed SPCNN performs superiorly to the Bicubic, sparsity constraint super-resolution (SCSR), anchored neighborhood regression (ANR), and SRCNN methods on reconstruction precision and time consumption.
An Innovative Electromechanical Joint Approach for Contact Pair Fault Diagnosis of Oil-Immersed On-Load Tap Changer
Authors: Li Shuaibing , Dou Lilong , Li Hongwei , Li Zongying , Kang Yongqiang
Published: August 2023

This paper presents a novel fault diagnosis method for oil-immersed on-load tap changers (OLTC) to address the issue of limited diagnostic accuracy. The proposed method combines the analysis of mechanical vibration signals and high-frequency current signals from the contact pair, aiming to improve the precision of fault diagnosis. To begin with, an experimental platform was used to simulate the OLTC contact, enabling the collection of mechanical vibration signals and high-frequency current signals under different operational states. These signals underwent wavelet packet transform for denoising, followed by correlation analysis to investigate their interrelationships across various states. Features were then extracted and analyzed using ensemble empirical mode decomposition and the Hilbert–Huang transform. Subsequently, a support vector machine (SVM) was employed to analyze both the mechanical vibration signal and high-frequency current signal, facilitating the classification of the OLTC contact state. The results demonstrated that the joint analysis of electrical and mechanical signals provided a comprehensive representation of the actual contact state under different conditions. The SVM classification achieved an error below 10% in predicting the values of the two signal types, validating the efficiency and feasibility of the proposed fault diagnosis method for OLTC contacts. The findings presented in this paper offer valuable insights for on-site fault diagnosis of practical OLTCs.
Polarization Direction of Arrival Estimation Using Dual Algorithms Based on Time-Frequency Cross Terms
Authors: Shao Shuai , Liu Aijun , Wang Xiuhong , Yu Changjun
Published: August 2023

In radar array signal processing, weak nonstationary polarization signal direction of arrival (DOA) estimation is a challenging and significant issue when both strong and weak nonstationary signals coexist. Time-frequency (T-F) analysis is an effective method to deal with nonstationary signals. In the last decade, spatial time-frequency distributions (STFDs) have been proposed for multiple dual-polarization antenna arrays and efficaciously used for nonstationary signal DOA estimation. In this article, we introduced a novelty means for estimating weak nonstationary polarization signal DOA by utilizing spatial polarimetric time-frequency distributions (SPTFDs) of cross terms when there are strong nonstationary polarization interference signals and additive Gaussian white noise. The cross terms’ SPTFDs are considered via a replaceability matrix for data covariance in multiple signal classification (MUSIC) and the estimation of signal parameters using the rotational invariance technique (ESPRIT). Combining the STFDs of cross terms with polarization information about weak nonstationary signals improves signal DOA estimation accuracy. The combined MUSIC and ESPRIT are used in the algorithm to further ensure the success probability and accuracy of DOA estimation. Through simulation analyses, the proposed algorithm is more suitable for the required application scenarios than other algorithms and is superior to other algorithms.
A Novel Compact Gysel Power Divider with Bandpass Filtering Responses
Authors: Wu Zeyu , Chen Zihao , Wang Kaixu
Published: August 2023

This study presents a novel compact design of the Gysel topology and a filtering power divider (FPD) that utilizes a coupling structure. The proposed design replaces the traditional four-quarter wavelength transmission lines of the Gysel power divider with transmission lines and lumped components, resulting in a significantly reduced circuit size. Furthermore, the introduction of this coupling structure ensures the integration of the filtering and power division functions. Two transmission zeros are created near the passband to enhance the frequency selectivity of the responses. Theoretical analysis is carried out, and closed-form equations are derived based on the even–odd-mode method. To validate the theory, a three-port equal Gysel FPD operating at 2 GHz was designed and fabricated. The simulated and measured results demonstrate that this FPD has good power splitting and filtering capability with the size of 0.15 λg × 0.25 λg (λg is the medium wavelength of the central frequency), which is a significant reduction compared to the existing Gysel FPDs. The simulated and measured results are presented to verify the theoretical derivation, demonstrating good features, such as a return loss greater than 15 dB, isolation greater than 15 dB, and an insertion loss of about 4.02 dB (3 + 1.02 dB) in the passband.
An Excess Kurtosis People Counting System Based on 1DCNN-LSTM Using Impulse Radio Ultra-Wide Band Radar Signals
Authors: Zhang Jinlong , Dang Xiaochao , Hao Zhanjun
Published: August 2023

As the Artificial Intelligence of Things (AIOT) and ubiquitous sensing technologies have been leaping forward, numerous scholars have placed a greater focus on the use of Impulse Radio Ultra-Wide Band (IR-UWB) radar signals for Region of Interest (ROI) population estimation. To address the problem concerning the fact that existing algorithms or models cannot accurately detect the number of people counted in ROI from low signal-to-noise ratio (SNR) received signals, an effective 1DCNN-LSTM model was proposed in this study to accurately detect the number of targets even in low-SNR environments with considerable people. First, human-induced excess kurtosis was detected by setting a threshold using the optimized CLEAN algorithm. Next, the preprocessed IR-UWB radar signal pulses were bundled into frames, and the resulting peaks were grouped to develop feature vectors. Subsequently, the sample set was trained based on the 1DCNN-LSTM algorithm neural network structure. In this study, the IR-UWB radar signal data were acquired from different real environments with different numbers of subjects (0–10). As indicated by the experimental results, the average accuracy of the proposed 1DCNN-LSTM model for the recognition of people counting reached 86.66% at ROI. In general, a high-accuracy, low-complexity, and high-robustness solution in IR-UWB radar people counting was presented in this study.
SWIPT Cooperative Protocol for Improving the Communication Quality of Cell-Edge Users in NOMA Network and Its Performance Analysis
Authors: Li Suoping , Jia Tongtong , Yang Hailing , Gao Ruiman , Yang Qian
Published: August 2023

To solve the problems of complex energy supply and poor communication effect of cell-edge users, combining the advantages of simultaneous wireless information and power transfer (SWIPT) and collaborative non-orthogonal multiple access (CNOMA), two novel protocols are proposed. By employing the PS and TS strategies in SWIPT, respectively, two protocols are named: SWIPT-CNOMA-PS and SWIPT-CNOMA-TS. Based on the protocols, a new method for selecting relays is first established by considering two factors—energy state and channel condition. To further improve energy efficiency, the relay harvests the energy of the signal sent by the source and stores it. We establish a one-dimensional Markov chain with the energy state as the system state to analyze the variation of the relay energy. Exploiting the conservation equation, the probability of energy sufficiency of the node and outage probabilities of users are derived. Finally, the impact of the energy threshold and the number of relays on the outage probability of users is revealed. The protocol in this paper shows better performance than the OMA protocol when the transmit signal-to-noise ratio (SNR) is less than 14 dB and the protocol in the literature when the transmit SNR is less than 11 dB.
Study on Heat Transfer Performance and Parameter Improvement of Gravity-Assisted Heat Pipe Heat Transfer Unit for Waste Heat Recovery from Mine Return Air
Authors: Zhai Yu , Zhao Xu , Xue Guanghui , Dong Zhifeng
Published: August 2023

One of the effective methods for energy conservation and emission reduction in coal mines is to utilize waste heat recovery technology to recover mine return air waste heat. The gravity heat pipe is widely used in mine return air waste heat recovery due to its sustainable and economic advantages, but its heat transfer is a complex process influenced by multiple parameters. A single-tube heat transfer resistance model and a heat transfer calculation model based on enthalpy difference were established for the heat exchange tubes. Four typical application cases of a low flow rate and a low number of tube rows were selected, and their heat transfer characteristics were tested onsite and analyzed. It was found that there were problems such as a low overall heat transfer efficiency, a low fresh air outlet temperature, and a risk of icing in the final tube section. The effects of the gravity heat pipe parameters on the heat transfer performance were studied, such as the tube outer diameter, tube spacing, and the finned tube outer diameter. It was found that the air-resistant force of the heat exchanger increased with the increase of the tube spacing and the finned tube outer diameter, the heat transfer resistance increased with the increase of the tube spacing and the decrease of the finned tube outer diameter, and the heat transfer coefficient first increased and then decreased with the increase of the tube outer diameter. A configuration improvement scheme with a high flow rate and a high number of tube rows is proposed here. Taking Case 2 as an example, the temperature distribution of the heat tube before and after improvement is compared and analyzed. The results show that the heat transfer performance of the heat exchange system significantly improved. Without increasing the air resistance of the heat tube, the temperature of the return air outlet after improvement was reduced to 1.1 °C, 4.1 °C lower than that before improvement, further recovering the waste heat of the mine return air. The temperature of the condensate water film was greater than 0.5 °C, avoiding the icing problem of the condensate tube section, the fresh air outlet temperature reached 5.2 °C, an increase of 7.8 °C compared to that before improvement, and the overall heat transfer efficiency increased from 56.7% to 66%.
Co-Simulation of a Cellular Energy System
Authors: Venzke Marcus , Shudrenko Yevhenii , Youssfi Amine , Steffen Tom , Turau Volker , Becker Christian
Published: August 2023

The concept of cellular energy systems of the German Association for Electrical, Electronic & Information Technologies (VDE) proposes sector coupled energy networks for energy transition based on cellular structures. Its decentralized control approach radically differs from that of existing networks. Deeply integrated information and communications technologies (ICT) open opportunities for increased resilience and optimizations. The exploration of this concept requires a comprehensive simulation tool. In this paper, we investigate simulation techniques for cellular energy systems and present a concept based on co-simulation. We combine simulation tools developed for different domains. A classical tool for studying physical aspects of energy systems (Modelica, TransiEnt library) is fused with a state-of-the-art communication networks simulator (OMNeT++) via the standardized functional mock-up interface (FMI). New components, such as cell managers, aggregators, and markets, are integrated via remote procedure calls. A special feature of our concept is that the communication simulator coordinates the co-simulation as a master and integrates other components via a proxy concept. Model consistency across different domains is achieved by a common description of the energy system. Evaluation proves the feasibility of the concept and shows simulation speeds about 20 times faster than real time for a cell with 111 households.
Volatility and Spillover Effects between Central–Eastern European Stock Markets and Energy Markets: An Emphasis on Crisis Periods
Authors: Jude Octavian , Turgeman Avraham , Boțoc Claudiu , Miloș Laura Raisa
Published: August 2023

The objective of this paper is to study the spillover effects between energy markets and stock markets with emphasis on the significant crisis periods of the last 15 years, the period of the financial crisis that officially started in 2008, the pandemic period, generically called COVID-19, and the recent confrontation in Eastern Europe. Understanding the volatility transmission mechanisms between the energy and capital markets and also from the energy markets back and the spillover effects that result is very important. We use multivariate GARCH models to highlight a spillover effect between energy commodities and equities in Central and Eastern Europe. The highest correlations are recorded for CEE stock markets with electricity and Brent, and the lowest for CEE stock markets with gas. The biggest symmetric shocks between energy and CEE stock markets occurred during the COVID-19 pandemic. In contrast, the biggest asymmetric shocks occurred during the financial crisis (for gas) and the Ukrainian invasion (for Brent). We also find that volatility is more sensitive to its lagged values in the marketplace than it is to new information. The impact and contagion of shocks caused by the oil market are greater than those of other energy markets.
Impact of Automation on Enhancing Energy Quality in Grid-Connected Photovoltaic Systems
Authors: Rodríguez Virgilio Alfonso Murillo , Villaseñor Noé Villa , Solís José Manuel Robles , Barbosa Omar Alejandro Guirette
Published: August 2023

Rapid growth in the integration of new consumers into the electricity sector, particularly in the industrial sector, has necessitated better control of the electricity supply and of the users’ op-erating conditions to guarantee an adequate quality of service as well as the unregulated dis-turbances that have been generated in the electrical network that can cause significant failures, breakdowns and interruptions, causing considerable expenses and economic losses. This research examines the characteristics of electrical variations in equipment within a company in the industrial sector, analyzes the impact generated within the electrical system according to the need for operation in manufacturing systems, and proposes a new solution through automation of the regulation elements to maintain an optimal system quality and prevent damage and equipment failures while offering a cost-effective model. The proposed solution is evaluated through a reliable simulation in ETAP (Energy Systems Modeling, Analysis and Optimization) software, which emulates the interaction of control elements and simulates the design of electric flow equipment operation. The results demonstrate an improvement in system performance in the presence of disturbances when two automation schemes are applied as well as the exclusive operation of the capacitor bank, which improves the total system current fluctuations and improves the power factor from 85.83% to 93.42%. Such a scheme also improves the waveform in the main power system; another improvement result is when simultaneously operating the voltage and current filter together with the PV system, further improving the current fluctuations, improving the power factor from 85.83% to 94.81%, achieving better stability and improving the quality of the waveform in the main power grid.
Assessing Water Relations and Carbon Dynamics of Pinus taeda Branches Undergoing Shade-Induced Mortality
Authors: Majekobaje Adelodun R. , Dean Thomas J.
Published: August 2023

Light acts as a complex signal, influencing various plant physiological, phenological and morphogenetic traits. Although previous studies have explored the effects of varying light levels on branch growth and survival, the underlying mechanisms of branch mortality under shade conditions remain poorly understood, hindering our understanding of canopy dynamics. In this study, contrasting shade conditions were imposed on Pinus taeda branches, and the changes in their water relations and carbon dynamics were evaluated. Monthly measurements of the photosynthetic light–response curve (LRC), sap flow and water potential of the branches were conducted. Furthermore, the conditions that led to the deaths of lower branches were investigated, and principal component analysis (PCA) was used to classify branches according to their mortality status. Significant shade treatment effects were observed for all photosynthetic parameters. The assimilation at light saturation (Amax), dark respiration rate (Rd), apparent quantum yield (AQY), light compensation point (LCP) and light saturation point (LSP) all decreased from full light to deepest shade, whereas the opposite was the case for the convexity term (θ). All water relations traits also decreased from full light to deepest shade; however, although significant shade effect was observed in stomatal conductance (gs) and sap flow, the differences in the pre-dawn (Ψpre-dawn) and mid-day (Ψmid-day) water potentials among treatments were not statistically significant. The PCA classification results showed that it could be used as a reliable method to screen for branch mortality as early as four months before mortality becomes evident. Our results shed more light on branch physiology and mortality under shade and have the potential to help improve the prediction of tree crown size, ultimately improving process-based forest growth models.
Comparative Analysis and Characterization of Ten Complete Chloroplast Genomes of Eremurus Species (Asphodelaceae)
Authors: Makhmudjanov Dilmurod , Abdullaev Davlatali , Juramurodov Inom , Tuychiev Shakhzodbek , Yusupov Ziyoviddin , Sun Hang , Tojibaev Komiljon , Deng Tao
Published: August 2023

Eremurus, a perennial rhizomatous mesophytic ornamental plant and one of the largest genera of the family Asphodelaceae, is distributed mainly in southwestern and central Asia. We sequenced the complete chloroplast genomes of ten species corresponding to all sections of the genus and analyzed their basic structure and evolutionary relationships. The cp genomes showed significant similarities in size, gene sequences, gene classes, and inverted repeat regions (IRs). The complete chloroplast genome of Eremurus has a typical tetrad structure, ranging in length from 153,782 bp (E. lactiflorus) to 155,482 bp (E. aitchisonii). The length of the large single-copy region (LSC) ranges from 84,005 bp (E. lactiflorus) to 84,711 bp (E. robustus), that of the small single-copy region (SSC) ranges from 16,727 bp (E. soogdianus) to 17,824 bp (E. suworowii), and that of the inverted repeat regions (IR) ranges from 26,484 bp (E. lactiflorus) to 26,597 bp (E. inderiensis and E. soogdianus). A total of 131 genes were detected, including 85 protein-coding genes, 8 rRNA genes, and 38 tRNA genes. In addition, we found seven common and eight unique SSRs in ten Eremurus species. Among the protein-coding genes, five highly variable genes (ycf1, rps15, rps16, and rpl36) with high Pi values were detected and showed potential as DNA barcodes for the genus. Three genes (rps19, ycf1, and ndhB) had positive Ka/Ks values. Codon usage patterns were very similar across species: 33 codons had relative synonymous codon usage values of more than one, of which three ended with G, and the remaining codons ended with A and U. Phylogenetic analyses using complete cp genomes and 81 protein-coding genes confirmed previous studies with the genus as well as subgenus Eremurus monophyletic and the subgenus Henningia paraphyletic.
Solid-State Fermentation of Green Tea Residues as Substrates for Tannase Production by Aspergillus niger TBG 28A: Optimization of the Culture Conditions
Authors: Peña-Lucio Erick , Chávez-González Mónica , Londoño-Hernandez Liliana , Ruiz Héctor , Martínez-Hernandez José , Govea-Salas Mayela , Nediyaparambil Sukumaran Pradeep , Abdulhameed Sabu , Aguilar Cristóbal
Published: August 2023

Tea (Camellia sinensis) is an evergreen shrub that is recognized worldwide for its functional properties. The current global production of green tea is approximately 5.3 million tons per year. Green tea processing has severely affected the generation of agro-industrial waste. One strategy for reducing waste accumulation is the revalorization of agro-industrial wastes via solid-state fermentation (SSF). The aim of this study was to valorize green tea processing residues to produce tannase under SSF using an endemic strain from Western Ghats, Aspergillus niger TBG 28A. SSF was performed in Erlenmeyer flasks with spent green tea leaves inoculated with spores of A. niger TBG 28A. Bioprocess optimization was carried out by employing the Box–Benkhen experimental design, achieving a high enzymatic yield of 246.82 (U/g). The present study shows the complexity of the degradation of tannins and the different patterns of expression of fungal tannase obtained from A. niger TBG 28 A. The enzyme was further purified to obtain a fold purification of 16.35% and a molecular mass of 150 kDa. Producing tannase with a novel strain of A. niger TBG 28A is an interesting strategy to revalorize green tea waste.
Generative AI in Medicine and Healthcare: Promises, Opportunities and Challenges
Authors: Zhang Peng , Kamel Boulos Maged N.
Published: August 2023

Generative AI (artificial intelligence) refers to algorithms and models, such as OpenAI’s ChatGPT, that can be prompted to generate various types of content. In this narrative review, we present a selection of representative examples of generative AI applications in medicine and healthcare. We then briefly discuss some associated issues, such as trust, veracity, clinical safety and reliability, privacy, copyrights, ownership, and opportunities, e.g., AI-driven conversational user interfaces for friendlier human-computer interaction. We conclude that generative AI will play an increasingly important role in medicine and healthcare as it further evolves and gets better tailored to the unique settings and requirements of the medical domain and as the laws, policies and regulatory frameworks surrounding its use start taking shape.
Recommended Separation Distances for 1.3 Ammunition and Explosives
Authors: Guymon Clint , Liu Ming , Covino Josephine
Published: August 2023

Separation Distances are used throughout the world to protect people and assets from the potential hazardous effects from propellants, explosives, and pyrotechnics. The current separation distances for Hazard Division (HD) 1.3 substances and articles used in the United States, in some cases, may not adequately protect against the effects from heat flux and debris when those substances and articles are ignited in a confined structure. Multiple tests in such a confined scenario with HD 1.3 substances have shown that the heat flux and debris hazards could result in injury at distances beyond the current specified explosives safety separation distance (ESSD). Herein are the recommended ESSDs for confined as well as unconfined HD 1.3 articles and substances based on the analysis of hundreds of tests. Recommended ESSDs include a smaller value for unconfined quantities less than 145 kg and ESSDs that are consistent with NATO distances for confined substances and articles.
Simultaneous Occurrence of Multiple Neoplasms in Children with Cancer Predisposition Syndromes: Collaborating with Abnormal Genes
Authors: Telman Gabriela , Strauss Ewa , Sosnowska-Sienkiewicz Patrycja , Halasz Magdalena , Januszkiewicz-Lewandowska Danuta
Published: August 2023

The identification of cancer predisposition syndromes (CPSs) plays a crucial role in understanding the etiology of pediatric cancers. CPSs are genetic mutations that increase the risk of developing cancer at an earlier age compared to the risk for the general population. This article aims to provide a comprehensive analysis of three unique cases involving pediatric patients with CPS who were diagnosed with multiple simultaneous or metachronous cancers. The first case involves a child with embryonal rhabdomyosarcoma, nephroblastoma, glioma, and subsequent medulloblastoma. Genetic analysis identified two pathogenic variants in the BRCA2 gene. The second case involves a child with alveolar rhabdomyosarcoma, juvenile xanthogranuloma, gliomas, and subsequent JMML/MDS/MPS. A pathogenic variant in the NF1 gene was identified. The third case involves a child with pleuropulmonary blastoma and pediatric cystic nephroma/nephroblastoma, in whom a pathogenic variant in the DICER1 gene was identified. Multiple simultaneous and metachronous cancers in pediatric patients with CPSs are a rare but significant phenomenon. Comprehensive analysis and genetic testing play significant roles in understanding the underlying mechanisms and guiding treatment strategies for these unique cases. Early detection and targeted interventions are important for improving outcomes in these individuals.
Loss of a Premature Stop Codon in the Rice Wall-Associated Kinase 91 (WAK91) Gene Is a Candidate for Improving Leaf Sheath Blight Disease Resistance
Authors: Al-Bader Noor , Meier Austin , Geniza Matthew , Gongora Yamid Sanabria , Oard James , Jaiswal Pankaj
Published: August 2023

Leaf sheath blight disease (SB) of rice caused by the soil-borne fungus Rhizoctonia solani results in 10–30% global yield loss annually and can reach 50% under severe outbreaks. Many disease resistance genes and receptor-like kinases (RLKs) are recruited early on by the host plant to respond to pathogens. Wall-associated receptor kinases (WAKs), a subfamily of receptor-like kinases, have been shown to play a role in fungal defense. The rice gene WAK91 (OsWAK91), co-located in the major SB resistance QTL region on chromosome 9, was identified by us as a candidate in defense against rice sheath blight. An SNP mutation T/C in the WAK91 gene was identified in the susceptible rice variety Cocodrie (CCDR) and the resistant line MCR010277 (MCR). The consequence of the resistant allele C is a stop codon loss, resulting in an open reading frame with extra 62 amino acid carrying a longer protein kinase domain and additional phosphorylation sites. Our genotype and phenotype analysis of the parents CCDR and MCR and the top 20 individuals of the double haploid SB population strongly correlate with the SNP. The susceptible allele T is present in the japonica subspecies and most tropical and temperate japonica lines. Multiple US commercial rice varieties with a japonica background carry the susceptible allele and are known for SB susceptibility. This discovery opens the possibility of introducing resistance alleles into high-yielding commercial varieties to reduce yield losses incurred by the sheath blight disease.
Glutathione Peroxidase gpx1 to gpx8 Genes Expression in Experimental Brain Tumors Reveals Gender-Dependent Patterns
Authors: Cueto-Ureña Cristina , Ramírez-Expósito María Jesús , Mayas María Dolores , Carrera-González María Pilar , Godoy-Hurtado Alicia , Martínez-Martos José Manuel
Published: August 2023

Extensive research efforts in the field of brain tumor studies have led to the reclassification of tumors by the World Health Organization (WHO) and the identification of various molecular subtypes, aimed at enhancing diagnosis and treatment strategies. However, the quest for biomarkers that can provide a deeper understanding of tumor development mechanisms, particularly in the case of gliomas, remains imperative due to their persistently incurable nature. Oxidative stress has been widely recognized as a key mechanism contributing to the formation and progression of malignant tumors, with imbalances in antioxidant defense systems being one of the underlying causes for the excess production of reactive oxygen species (ROS) implicated in tumor initiation. In this study, we investigated the gene expression patterns of the eight known isoforms of glutathione peroxidase (GPx) in brain tissue obtained from male and female control rats, as well as rats with transplacental ethyl nitrosourea (ENU)-induced brain tumors. Employing the delta-delta Ct method for RT-PCR, we observed minimal expression levels of gpx2, gpx5, gpx6, and gpx7 in the brain tissue from the healthy control animals, while gpx3 and gpx8 exhibited moderate expression levels. Notably, gpx1 and gpx4 displayed the highest expression levels. Gender differences were not observed in the expression profiles of these isoforms in the control animals. Conversely, the tumor tissue exhibited elevated relative expression levels in all isoforms, except for gpx4, which remained unchanged, and gpx5, which exhibited alterations solely in female animals. Moreover, except for gpx1, which displayed no gender differences, the relative expression values of gpx2, gpx3, gpx6, gpx7, and gpx8 were significantly higher in the male animals compared to their female counterparts. Hence, the analysis of glutathione peroxidase isoforms may serve as a valuable approach for discerning the behavior of brain tumors in clinical settings.
Structured-Light Scanning and Metrological Analysis for Archaeology: Quality Assessment of Artec 3D Solutions for Cuneiform Tablets
Authors: Diara Filippo
Published: August 2023

This paper deals with a metrological and qualitative evaluation of the Artec 3D structured-light scanners: Micro and Space Spider. As part of a larger European project called ITSERR, these scanners are tested to reconstruct small archaeological artefacts, in particular cuneiform tablets with different dimensions. For this reason, Micro and Space Spider are compared in terms of the entire workflow, from preparatory work to post-processing. In this context, three cuneiform replica tablets will serve as examples on which the Artec scanners will have to prove their worth. Metric analyses based on distance maps, RMSe calculations and density analyses will be carried out to understand metrological differences between these tools. The creation of 3D models of cuneiform tablets is the first step in developing a virtual environment suitable for sharing the archaeological collection with collaborators and other users. The inclusion of semantic information through specific ontologies will be the next step in this important project.
Genetically Modified Plants Based on Bacillus Genes and Commercial Bacillus-Based Biopesticides for Sustainable Agriculture
Authors: Ortiz Aurelio , Sansinenea Estibaliz
Published: August 2023

Due to the increase in the global population, there is an urgent call to enhance the crop production through sustainable agriculture. Biological control is a possible solution. There are many examples of biological control agents applied to different crops that have improved their yield or quality, including vegetable and fruit crops and ornamental plants. The Bacillus species have been used as powerful tools since they suppress plant pathogens and promote plant growth as well. During the last five decades, B. thuringiensis has been used as biopesticide in several crops. However, it has some disadvantages such as its instability under field conditions due to sunlight; therefore, frequent applications are necessary, making its use more expensive. To solve this problem, genetically modified crops have been employed to allow the plant to express the toxin in the whole plant. Genetic engineering is a method used to make changes in the genetic material of an organism using scientific techniques. Therefore, genetic engineering opens up opportunities for creating genetically modified plants to increase crop yields and avoid pests. Genetically modified (GM) crops have been cultivated during the last three decades. Transgenic plant technology can be used to address global food scarcity, particularly in developing countries. Genetically modified organisms are a controversial topic that needs to be considered more carefully. Many toxicology studies have confirmed that Bt microbial formulations are safe for consumption. In this review, we will revise the application of Bacillus genes and Bacillus formulations to crops and their safety for human health to provide a more comprehensive understanding of this topic.
Stability of the TiO2 Nanuclusters Supported on Fe2O3-Hematite for Application in Electrocatalytic Water Splitting—An Insight from DFT Simulations
Authors: Dymkowski Tomasz , Żuczkowski Wiktor , Kołodziejczyk Wojciech , Hill Glake , Szyja Bartłomiej M.
Published: August 2023

We present the analysis of the stability of the (TiO2)n nanoclusters, where n = 2–4, supported on the Fe3O3-hematite (100) surface. The analysis is focused on the size and geometry of the nanocluster, which defines the contact with the supporting hematite surface. The aim of the work is to explore the role of the interaction within the nanocluster as well as between the nanocluster and the surface in the structure of the composite system. We have used an in-house developed variant of the solids docking procedure to determine the most stable initial configurations of the nanoclusters with respect to the surface. Subsequently, we have carried out molecular dynamics simulations to enable finding a more stable configurations by the systems. The results show the three possible binding modes for the (TiO2)2 systems, but many more such modes for the larger clusters. Additionally, we have found that the partial dissociation of the nanocluster takes place upon the contact with the surface.