bluuebunny/crossref_metadata_2025 huggingface dataset:
Study on the Deposition Characteristics of Molybdenum Thin Films Deposited by the Thermal Atomic Layer Deposition Method Using MoO2Cl2 as a Precursor
Authors: Lee Baek-Ju , Lee Kyu-Beom , Cheon Min-Ho , Seo Dong-Won , Choi Jae-Wook
Published: June 2023

In this study, we conducted research on manufacturing molybdenum (Mo) thin films by a thermal atomic layer deposition method using solid MoO2Cl2 as a precursor. Mo thin films are widely used as gate electrodes and electrodes in metal-oxide semiconductor field-effect transistors. Tungsten (W) has primarily been used as a conventional gate electrode, but it suffers from reduced resistivity due to the residual fluorine component generated from the deposition process. Thus, herein, we developed a Mo thin film with low resistivity that can substitute W. The MoO2Cl2 precursor used to deposit the Mo thin film exists in a solid state. For solid precursors, the vapor pressure does not remain constant compared to that of liquid precursors, thereby making it difficult to set process conditions. Furthermore, the use of solid precursors at temperatures 600 °C and above has many limitations. Herein, H2 was used as the reactive gas for the deposition of Mo thin films, and the deposition temperature was increased to 650 °C, which was the maximum processing temperature of the aluminum nitride heater. Additionally, deposition rate, resistivity change, and surface morphology characteristics were compared. While resistivity decreased to 12.9 μΩ∙cm with the increase of deposition temperature from 600 °C to 650 °C, surface roughness (Rq) was increased to 0.560 nm with step coverage of 97%. X-ray diffraction analysis confirmed the crystallization change in the Mo thin film with increasing process temperature, and a certain thickness of the seed layer was required for nucleation on the initial wafer of the Mo thin film. Thus, the molybdenum nitride thin film was deposited after the 4 nm deposition of Mo thin film. This study confirmed that crystallinity of Mo thin films must be increased to reduce their resistivity and that a seed layer for initial nucleation is required.
Luminescent Properties of Polycarbonate Methacrylates Containing Organic Fluorescent Dyad
Authors: Matveeva Irina A. , Shashkova Valentina T. , Lyubimov Alexander V. , Lyubimova Galina V. , Koltsova Liubov S. , Shienok Andrey I. , Zaichenko Natalia L. , Levin Peter P.
Published: June 2023

The luminescent properties of photocured aliphatic and aromatic network polycarbonate methacrylates, containing organic fluorescent dyad, have been studied. The dyad molecule includes two photosensitive fragments—tetraarylimidazole with a hydroxyl group and azomethinocoumarin—in each of which excited state intramolecular proton transfer (ESIPT) occurs, leading to the appearance of two emissions: blue (450 nm) and green (535 nm). It was established that the ratio of the intensities of these emissions depends very significantly on the excitation wavelength, as well as on the length, flexibility and polarity of the matrix oligomeric bridges.
Optical Characterization of Al Island Films: A Round Robin Test
Authors: Sancho-Parramon Jordi , Amochkina Tatiana , Wilbrandt Steffen , Kamble Hrishikesh , Janicki Vesna , Salamon Krešimir , Stenzel Olaf , Trubetskov Michael
Published: June 2023

The determination of the effective optical constants of metal island films is an essential step towards the practical incorporation of this kind of films in optical coatings. In this work, the optical properties of aluminium island films deposited by electron beam evaporation on quartz substrates are investigated using different approaches employed by three research groups. The effective optical constants of the island films are inferred from optical measurements (spectrophotometry and spectroscopic ellipsometry) using: (i) a parameter-free dispersion model, (ii) a multiple oscillator model based on Gaussian line-shapes and (iii) the β distributed oscillator model. All the used approaches provide similar physical insights, i.e., an increase in the effective thickness of the metal island film, a red-shift and broadening of the plasmon resonance and an enhancement of the infrared absorption as the amount of deposited material increases. However, the optimal values of the effective optical constants and thickness significantly depend on the employed model and the experimental data used for data fitting.
Raman Studies of Two-Dimensional Group-VI Transition Metal Dichalcogenides under Extreme Conditions
Authors: Yang Yang , Han Yongping , Li Renfei
Published: June 2023

In the past decade, two-dimensional (2D) transition metal dichalcogenides (TMDs) have attracted increasing attention because of their striking physical properties and extensive applicability. Meanwhile, Raman spectroscopy has been demonstrated to be a feasible tool and is extensively employed in research on 2D TMDs. In recent years, the deployment of Raman spectroscopy under extreme conditions has elucidated the physical properties of TMDs. In this review, we focus on the extreme-condition Raman spectroscopy of typical group-VI TMDs, which are classified and discussed under the three extreme conditions of low temperature, high pressure and high magnetic field. The conclusion presents the most pressing challenges and attractive future opportunities in this rapidly developing research field.
Phase Composition and Temperature Effect on the Dynamic Young’s Modulus, Shear Modulus, Internal Friction, and Dilatometric Changes in AISI 4130 Steel
Authors: Matlakhova Lioudmila , Pessanha Emanuel , Alves Henrique , Palii Natalia , Monteiro Sergio
Published: June 2023

Elastic properties of materials and their changes with temperature are important for their applications in engineering. In the present study the influence of phase composition and temperature of AISI 4130 alloy on Young’s modulus (Ed), shear modulus (Gd), and damping (Q−1) was carried out by the impulse excitation technique (IET). The material characterization was performed using confocal microscopy, XRD, SEM, HV, and dilatometry. A stable structure, composed of ferrite (BCC) and pearlite (α-Fe + Fe3C), was obtained by annealing. Metastable structure of martensite (BCT) was obtained by quenching. The Ed, Gd, and Q−1 were measured by varying the temperature from RT to 900 °C. The values of Ed and Gd, at RT, were determined as 201.5 and 79.2 GPa (annealed) and 190.13 and 76.5 GPa (quenched), respectively. In the annealed steel, the values Ed and Gd decrease linearly on heating up to 650 °C, with thermal expansion. In the quenched steel, weak changes occurred in the dilatometric curve, Ed, Gd, and Q−1, in the range of 350–450 °C, which indicated decompositions of the martensitic phase. A sharp decrease in the moduli and high peak of Q−1 were observed for both samples around 650–900 °C, revealing low lattice elastic stability of the phases during transformations α(BCC) + Fe3Cγ(FCC).
Phononic Band Structure by Calculating Effective Parameters of One-Dimensional Metamaterials
Authors: Flores Méndez Javier , Heredia Jiménez Aurelio H. , Minquiz Gustavo M. , Morales-Sánchez A. , Moreno Mario , Luna López José Alberto , Severiano Francisco , Piñón Reyes A. C.
Published: June 2023

Using a theory of homogenization that consists in the discretization of the inclusion of a binary phononic crystal in small volumes, in which the material parameters can be expanded in Fourier series, we have determined the dependence of the effective elastic parameters as a function of the frequency. In particular, the frequency dependence of all the elements that constitute the effective tensors of stiffness (moduli of elasticity) and density was analyzed for a 1D phononic crystal conformed of materials whose main characteristic is the high contrast between their elastic properties. In this dynamic case of homogenization, it was found that the effective parameters can reproduce the exact dispersion relations for the acoustic modes that propagate along the periodicity direction of the crystal. Particularly, in the second pass band (high-frequency branch) corresponding to the transverse vibrational modes, the homogenized elastic phononic crystal exhibits a metamaterial behavior because the effective C44-component (shear modulus) and dynamic mass density were found to be both negative. It is noteworthy that the study derived from this homogenization technique can lead to design of double negative metamaterial systems for potential applications.
Crystal Structure, Raman Spectroscopy and Optical Property Study of Mg-Doped SnO2 Compounds for Optoelectronic Devices
Authors: Singha K. K. , Singh P. P. , Narzary R. , Mondal A. , Gupta M. , Sathe V. G. , Kumar D. , Srivastava S. K.
Published: June 2023

Researchers have been consistently looking for new materials that can be integrated in optoelectronic and spintronic devices. In this research, we investigated the crystalline structure, Raman, and optical characteristics of Mg-doped SnO2 compounds. The solid-state reaction technique was utilized to produce polycrystalline samples of Sn1−xMgxO2 (0 ≤ x ≤ 0.10) for their potential use in optoelectronics devices. It was discovered that all the compounds were synthesized into a tetragonal rutile-type structure of SnO2. The analysis of these samples using Raman spectroscopy provided more evidence, supporting the creation of the tetragonal rutile phase of SnO2 and the successful integration of Mg ions in SnO2. The measurements of the optical properties, such as absorbance and transmittance, carried out with a UV-Vis spectrophotometer demonstrated that the optical band gap widened with the increase in the magnesium doping concentration in SnO2. In addition, it was noticed that increasing the quantity of magnesium doping concentration led to an increase in the transmittance value from 83% to 91%.
Whole-Genome Sequence-Based Characterization of Pre-XDR M. tuberculosis Clinical Isolates Collected in Kazakhstan
Authors: Daniyarov Asset , Akhmetova Ainur , Rakhimova Saule , Abilova Zhannur , Yerezhepov Dauren , Chingissova Lyailya , Bismilda Venera , Takenov Nurlan , Akilzhanova Ainur , Kairov Ulykbek , Kozhamkulov Ulan
Published: June 2023

Background: Kazakhstan has a high burden of multidrug-resistant tuberculosis in the Central Asian region. This study aimed to perform genomic characterization of Mycobacterium tuberculosis strains obtained from Kazakhstani patients with pre-extensively drug-resistant tuberculosis diagnosed in Kazakhstan. Methods: Whole-genome sequencing was performed on 10 pre-extensively drug-resistant M. tuberculosis strains from different regions of Kazakhstan. All strains had high-confidence resistance mutations according to the resistance grading system previously established by the World Health Organization. The genome analysis was performed using TB-Profiler, Mykrobe, CASTB, and ResFinder. Results: Valuable information for understanding the genetic diversity of tuberculosis in Kazakhstan can also be obtained from whole-genome sequencing. The results from the Phenotypic Drug Susceptibility Testing (DST) of bacterial strains were found to be consistent with the drug resistance information obtained from genomic data that characterized all isolates as pre-XDR. This information can help in developing targeted prevention and control strategies based on the local epidemiology of tuberculosis. Furthermore, the data obtained from whole-genome sequencing can help in tracing the transmission pathways of tuberculosis and facilitating early detection of outbreaks. Conclusions: The results from whole-genome sequencing of tuberculosis clinical samples in Kazakhstan provide important insights into the drug resistance patterns and genetic diversity of tuberculosis in the country. These results can contribute to the improvement of tuberculosis control and management programs in Kazakhstan.
Application of Spectral Algorithm Applied to Spatially Registered Bi-Parametric MRI to Predict Prostate Tumor Aggressiveness: A Pilot Study
Authors: Mayer Rulon , Turkbey Baris , Choyke Peter L. , Simone Charles B.
Published: June 2023

Background: Current prostate cancer evaluation can be inaccurate and burdensome. Quantitative evaluation of Magnetic Resonance Imaging (MRI) sequences non-invasively helps prostate tumor assessment. However, including Dynamic Contrast Enhancement (DCE) in the examined MRI sequence set can add complications, inducing possible side effects from the IV placement or injected contrast material and prolonging scanning time. More accurate quantitative MRI without DCE and artificial intelligence approaches are needed. Purpose: Predict the risk of developing Clinically Significant (Insignificant) prostate cancer CsPCa (CiPCa) and correlate with the International Society of Urologic Pathology (ISUP) grade using processed Signal to Clutter Ratio (SCR) derived from spatially registered bi-parametric MRI (SRBP-MRI) and thereby enhance non-invasive management of prostate cancer. Methods: This pilot study retrospectively analyzed 42 consecutive prostate cancer patients from the PI-CAI data collection. BP-MRI (Apparent Diffusion Coefficient, High B-value, T2) were resized, translated, cropped, and stitched to form spatially registered SRBP-MRI. Efficacy of noise reduction was tested by regularizing, eliminating principal components (PC), and minimizing elliptical volume from the covariance matrix to optimize the SCR. MRI guided biopsy (MRBx), Systematic Biopsy (SysBx), combination (MRBx + SysBx), or radical prostatectomy determined the ISUP grade for each patient. ISUP grade ≥ 2 (<2) was judged as CsPCa (CiPCa). Linear and logistic regression were fitted to ISUP grade and CsPCa/CiPCa SCR. Correlation Coefficients (R) and Area Under the Curves (AUC) for Receiver Operator Curves (ROC) evaluated the performance. Results: High correlation coefficients (R) (>0.55) and high AUC (=1.0) for linear and/or logistic fit from processed SCR and z-score for SRBP-MRI greatly exceed fits using prostate serum antigen, prostate volume, and patient age (R ~ 0.17). Patients assessed with combined MRBx + SysBx and from individual MRI scanners achieved higher R (DR = 0.207+/−0.118) than all patients used in the fits. Conclusions: In the first study, to date, spectral approaches for assessing tumor aggressiveness on SRBP-MRI have been applied and tested and achieved high values of R and exceptional AUC to fit the ISUP grade and CsPCA/CiPCA, respectively.
Emerging Role of Quantitative Ultrasound-Based Imaging Techniques for Characterizing Rotator Cuff Tears: A Scoping Review
Authors: Nasr Andrew , Pierson Chris , Tzen Yi-Ting , Khazzam Michael , Jain Nitin , Lin Yen-Sheng
Published: June 2023

Rotator cuff myosteatosis following cuff tears is very common and one of the most important prognostic factors in clinical management. Quantitative ultrasound-based imaging techniques (QUBIT) are frequently used along with magnetic resonance imaging (MRI) to evaluate rotator cuff fatty degeneration. However, the examination of rotator cuff tissue integrity by QUBIT is lacking a standardized imaging protocol and procedural methodologies. In this scoping review, we synthesized the current state of QUBIT against the reference imaging modalities in patients with rotator cuff tears. The literature search was extracted from 963 studies, with 22 studies included in the final review in accordance with the preferred reporting items for systematic reviews and meta-analyses extensions for scoping reviews. The selected studies included human participants and focused on measuring at least one prognostic or diagnostic factor using ultrasonography-based imaging with reference to MRI. The findings suggest both conventional B-mode ultrasound and shear wave elastography imaging were comparable to MRI-based imaging techniques for the evaluation of fatty infiltration and rotator cuff tear characterization. This review establishes guidelines for reporting shoulder-specific QUBIT aimed at developing a standardized imaging protocol. The objective was to enhance the diagnostic and prognostic capabilities of QUBIT in the clinical setting.
Expanded PCR Panel Testing for Identification of Respiratory Pathogens and Coinfections in Influenza-like Illness
Authors: Upadhyay Pallavi , Reddy Jairus , Proctor Teddie , Sorel Oceane , Veereshlingam Harita , Gandhi Manoj , Wang Xuemei , Singh Vijay
Published: June 2023

While COVID-19 has dominated Influenza-like illness (ILI) over the past few years, there are many other pathogens responsible for ILI. It is not uncommon to have coinfections with multiple pathogens in patients with ILI. The goal of this study was to identify the different organisms in symptomatic patients presenting with ILI using two different high throughput multiplex real time PCR platforms. Specimens were collected from 381 subjects presenting with ILI symptoms. All samples (nasal and nasopharyngeal swabs) were simultaneously tested on two expanded panel PCR platforms: Applied Biosystems™ TrueMark™ Respiratory Panel 2.0, OpenArray™ plate (OA) (32 viral and bacterial targets); and Applied Biosystems™ TrueMark™ Respiratory Panel 2.0, TaqMan™ Array card (TAC) (41 viral, fungal, and bacterial targets). Results were analyzed for concordance between the platforms and for identification of organisms responsible for the clinical presentation including possible coinfections. Very good agreement was observed between the two PCR platforms with 100% agreement for 12 viral and 3 bacterial pathogens. Of 381 specimens, approximately 58% of the samples showed the presence of at least one organism with an important incidence of co-infections (~36–40% of positive samples tested positive for two and more organisms). S. aureus was the most prevalent detected pathogen (~30%) followed by SARS-CoV-2 (~25%), Rhinovirus (~15%) and HHV6 (~10%). Co-infections between viruses and bacteria were the most common (~69%), followed by viral-viral (~23%) and bacterial-bacterial (~7%) co-infections. These results showed that coinfections are common in RTIs suggesting that syndromic panel based multiplex PCR tests could enable the identification of pathogens contributing to coinfections, help guide patient management thereby improving clinical outcomes and supporting antimicrobial stewardship.
Intrathymic Localization of Melanoma: A Brief Report of Two Cases and a Review of the Literature
Authors: Cannone Giorgio , Verzeletti Vincenzo , Fortarezza Francesco , Pezzuto Federica , Polverosi Roberta , Faccioli Eleonora , Comacchio Giovanni Maria , Dell’Amore Andrea , Rea Federico , Schiavon Marco , Calabrese Fiorella
Published: June 2023

Intrathymic localizations of melanoma represent a very rare entity, with fewer than ten cases of intrathymic melanoma described in the literature. Herein, we describe two cases of patients who underwent surgical removal of a thymic mass at our thoracic surgery department between 2015 and 2022. The final pathological examination revealed a malignant melanoma in both cases; we therefore carried out a literature review to identify such rare and similar cases. In the first case, the intrathymic localization of melanoma was the first manifestation of the disease, posing a dilemma regarding the metastatic and primitive nature of the neoplasm. The second case described a thymic metastasis from a known previous cutaneous melanoma, for which the patient had successfully been treated six years earlier. After carefully reviewing the literature, we identified only six cases of verified primary intrathymic melanomas and one case of intrathymic metastasis resulting from melanoma previously described. Pathologists should be aware of the occurrence of this rare entity and mindful of the differential diagnoses. Several tools, including immunostaining of melanocytic markers and molecular investigations, are mandatory for final pathological diagnosis.
Empowering Adaptive Geolocation-Based Routing for UAV Networks with Reinforcement Learning
Authors: Park Changmin , Lee Sangmin , Joo Hyeontae , Kim Hwangnam
Published: June 2023

Since unmanned aerial vehicles (UAVs), such as drones, are used in various fields due to their high utilization and agile mobility, technologies to deal with multiple UAVs are becoming more important. There are many advantages to using multiple drones in a swarm, but, at the same time, each drone requires a strong connection to some or all of the other drones. This paper presents a superior approach for the UAV network’s routing system without wasting memory and computing power. We design a routing system called the geolocation ad hoc network (GLAN) using geolocation information, and we build an adaptive GLAN (AGLAN) system that applies reinforcement learning to adapt to the changing environment. Furthermore, we increase the learning speed by applying a pseudo-attention function to the existing reinforcement learning. We evaluate the proposed system against traditional routing algorithms.
Neighbors Matter: An Investigation into Intergroup Interactions Affecting the Social Networks of Adjacent Chimpanzee Groups
Authors: Gil-Dolz Jose , Riba David , Crailsheim Dietmar
Published: June 2023

Wild chimpanzees live in large and complex social communities, but their complexity is determined by the number of potential social partners as well as the frequent changes in group composition due to fission–fusion dynamics. Alternatively, captive housed chimpanzee groups are usually much smaller and less complex. However, studies have shown that groups can be housed in adjacent habitats, potentially increasing the number of social partners, i.e., granting additional relationship opportunities and enhanced social complexity. While most social network studies analyze social groups as closed systems, this study assessed the impact of social interactions between two neighboring groups of chimpanzees, based on two social network indices (Vertex strength centrality and Deviation from edge weight disparity). Furthermore, Linear Mixed Models (LMMs) were employed to assess whether gender, age, and intra-/intergroup directionality influenced these indices. We recorded occurrences of social behaviors, social proximity and whether chimpanzees observed individuals in the other group as a measure of interest. Most social behaviors were directed towards group members; however, 13% were directed towards the neighboring group. Although enclosure barriers constrained the chimpanzee’s capacity to physically interact, it does not necessarily impede social interactions with the outside world. Hence, the presence of neighboring chimpanzees potentially provides additional relationship opportunities, increasing social stimulation and complexity leading to an enriching social environment.
Dealing with Diverse Cultures and Needs: How Have Higher Education Institutions in Portugal Responded to COVID-19?
Authors: Lyrio Bianca , Nada Cosmin , França Thais
Published: June 2023

This article seeks to provide a comprehensive analysis of the strategies implemented by Portuguese higher education institutions in addressing cultural diversity and meeting the demands of international students, particularly in the context of the COVID-19 pandemic outbreak. In methodological terms, this is a qualitative study in which more than 40 in-depth interviews were conducted with degree mobility students from Brazil, Portuguese-speaking African Countries, China and Syria, who were already in Portugal when the pandemic was declared in the country in March 2020. Through the lens of multiculturalism, which understands that higher education should be inclusive and equal for all, we found that higher education institutions in Portugal did not provide adequate support to its international student body at a time of so many challenges and uncertainties. Our data indicate that higher education institutions in Portugal need to make more efforts towards fostering a diverse and inclusive environment, whilst taking into account the complex needs of international students.
Pupil Localization Algorithm Based on Improved U-Net Network
Authors: Chen Gongzheng , Dong Zhenghong , Wang Jue , Xia Lurui
Published: June 2023

Accurately localizing the pupil is an essential requirement of some new human–computer interaction methods. In the past, a lot of work has been done to solve the pupil localization problem based on the appearance characteristics of the eye, but these methods are often specific to the scenario. In this paper, we propose an improved U-net network to solve the pupil location problem. This network uses the attention mechanism to automatically select the contribution of coded and uncoded features in the model during the skip connection stage of the U-net network in the channel and spatial axis. It can make full use of the two features of the model in the decoding stage, which is beneficial for improving the performance of the model. By comparing the sequential channel attention module and spatial attention module, average pooling and maximum pooling operations, and different attention mechanisms, the model was finally determined and validated on two public data sets, which proves the validity of the proposed model.
Spatial-Temporal Self-Attention Transformer Networks for Battery State of Charge Estimation
Authors: Shi Dapai , Zhao Jingyuan , Wang Zhenghong , Zhao Heng , Wang Junbin , Lian Yubo , Burke Andrew F.
Published: June 2023

Over the past ten years, breakthroughs in battery technology have dramatically propelled the evolution of electric vehicle (EV) technologies. For EV applications, accurately estimating the state-of-charge (SOC) is critical for ensuring safe operation and prolonging the lifespan of batteries, particularly under complex loading scenarios. Despite progress in this area, modeling and forecasting the evaluation of multiphysics and multiscale electrochemical systems under realistic conditions using first-principles and atomistic calculations remains challenging. This study proposes a solution by designing a specialized Transformer-based network architecture, called Bidirectional Encoder Representations from Transformers for Batteries (BERTtery), which only uses time-resolved battery data (i.e., current, voltage, and temperature) as an input to estimate SOC. To enhance the Transformer model’s generalization, it was trained and tested under a wide range of working conditions, including diverse aging conditions (ranging from 100% to 80% of the nominal capacity) and varying temperature windows (from 35 °C to −5 °C). To ensure the model’s effectiveness, a rigorous test of its performance was conducted at the pack level, which allows for the translation of cell-level predictions into real-life problems with hundreds of cells in-series conditions possible. The best models achieve a root mean square error (RMSE) of less than 0.5 test error and approximately 0.1% average percentage error (APE), with maximum absolute errors (MAE) of 2% on the test dataset, accurately estimating SOC under dynamic operating and aging conditions with widely varying operational profiles. These results demonstrate the power of the self-attention Transformer-based model to predict the behavior of complex multiphysics and multiscale battery systems.
A State-of-the-Art Review of Task Scheduling for Edge Computing: A Delay-Sensitive Application Perspective
Authors: Avan Amin , Azim Akramul , Mahmoud Qusay H.
Published: June 2023

The edge computing paradigm enables mobile devices with limited memory and processing power to execute delay-sensitive, compute-intensive, and bandwidth-intensive applications on the network by bringing the computational power and storage capacity closer to end users. Edge computing comprises heterogeneous computing platforms with resource constraints that are geographically distributed all over the network. As users are mobile and applications change over time, identifying an optimal task scheduling method is a complex multi-objective optimization problem that is NP-hard, meaning the exhaustive search with a time complexity that grows exponentially can solve the problem. Therefore, various approaches are utilized to discover a good solution for scheduling the tasks within a reasonable time complexity, while achieving the most optimal solution takes exponential time. This study reviews task scheduling algorithms based on centralized and distributed methods in a three-layer computing architecture to identify their strengths and limitations in scheduling tasks to edge service nodes.
A Linearly and Circularly Polarization-Reconfigurable Leaky Wave Antenna Based on SSPPs-HSIW
Authors: Wei Dujuan , Zhang Pengquan
Published: June 2023

In this manuscript, a reconfigurable leaky wave antenna is proposed with linearly polarized and circularly polarized properties, which is composed of two layers with feeding waveguide and radiation elements. The bottom layer is a half-mode substrate integrated waveguide etched with a spoof surface plasmon polaritons structure as a high-dispersion feeding waveguide to excite 8 circular patches as radiation elements in the top layer. In a unit element, the horizontal linear polarization (HLP) and right-hand circular polarization (RHCP) radiation are switched using a p-i-n diode crossing a slot of a circular metal patch. HLP performance is achieved as the p-i-n diode is switched off, and RHCP is achieved as the p-i-n diode is switched on. The measured results verify the design theory and the simulated results. Over the working band of 10.4~12.8 GHz, the proposed antenna can radiate scanning beams covering about a 73° region, including the broadside direction with HLP and RHCP.
Digital Twin Haptic Robotic Arms: Towards Handshakes in the Metaverse
Authors: Faisal Mohd , Laamarti Fedwa , El Saddik Abdulmotaleb
Published: June 2023

More daily interactions are happening in the digital world of the metaverse. Providing individuals with means to perform a handshake during these interactions can enhance the overall user experience. In this paper, we put forward the design and implementation of two right-handed underactuated Digital Twin robotic arms to mediate the physical handshake interaction between two individuals. This allows them to perform a handshake while they are in separate locations. The experimental findings are very promising as our evaluation shows that the participants were highly interested in using our system to shake hands with their loved ones when they are physically separated. With this Digital Twin robotic arms system, we also found a correlation between the handshake characteristics and personality traits of the participants from the handshake data collected during the experiment.
Low-Profile Wideband Dual-Polarized Patch Antenna Based on Differential-Paired Multi-Mode Arms
Authors: Li Yuanchun , Wei Lijuan , Wang Kaixu , Cai Hanzhen , Chen Zihao
Published: June 2023

This paper presents a low-profile wideband, dual-polarized patch antenna using differential-paired, multi-mode arms. By employing the arrow-shaped, differential-paired arms, three modes of them are excited simultaneously, leading to a broad bandwidth. The shorting pins are uniquely inserted at the wings of the arms to obtain stable radiation patterns. Then, two pairs of arms are structured like the dipoles and a dual-polarized antenna is designed. In addition, by employing coplanar coupling feeding structures, a good wideband impedance matching is also achieved without increasing the height. For demonstration, a wideband dual-polarized patch antenna is designed and measured. Benefitting from the advantages of the multi-mode patch and symmetrical structure as a dipole antenna, the proposed dual-polarized antenna operates between 2.10–3.95 GHz, possessing a 10-dB impedance bandwidth of 61%, a profile of 0.1λ0, an average gain of 7.31 dBi, and stable radiation patterns.
Leveraging State-of-the-Art Topic Modeling for News Impact Analysis on Financial Markets: A Comparative Study
Authors: Chen Weisi , Rabhi Fethi , Liao Wenqi , Al-Qudah Islam
Published: June 2023

News impact analysis has become a common task conducted by finance researchers, which involves reading and selecting news articles based on themes and sentiments, pairing news events and relevant stocks, and measuring the impact of selected news on stock prices. To facilitate more efficient news selection, topic modeling can be applied to generate topics out of a large number of news documents. However, there is very limited existing literature comparing topic models in the context of finance-related news impact analysis. In this paper, we compare three state-of-the-art topic models, namely Latent Dirichlet allocation (LDA), Top2Vec, and BERTopic, in a defined scenario of news impact analysis on financial markets, where 38,240 news articles with an average length of 590 words are analyzed. A service-oriented framework for news impact analysis called “News Impact Analysis” (NIA) is advocated to leverage multiple topic models and provide an automated and seamless news impact analysis process for finance researchers. Experimental results have shown that BERTopic performed best in this scenario, with minimal data preprocessing, the highest coherence score, the best interpretability, and reasonable computing time. In addition, a finance researcher was able to conduct the entire news impact analysis process, which validated the feasibility and usability of the NIA framework.
Blood Group Interpretation Algorithm Based on Improved AlexNet
Authors: Shen Ranxin , Wen Jiayi , Zhu Peiyi
Published: June 2023

Traditional blood group interpretation technology has poor detection efficiency and interpretation accuracy in the face of complex conditions in clinical environments. In order to improve the interpretation accuracy of the automatic blood group interpretation system, the important role of deep learning in the blood group interpretation system was studied. Based on the AlexNet network model, this paper proposes an improved scheme because of its advantages in terms of speeding up the convergence training speed and enhancing the model’s generalizability. However, it still needs improvement in terms of blood group interpretation accuracy. The improved AlexNet network model proposed in this paper added an attention mechanism to the network structure, optimized the loss function in the training algorithm, and adjusted the learning rate attenuation function. The experiments showed that compared with the accuracy of the AlexNet model, its training effect was remarkable, with an accuracy of 96.9%—an increase of 3%. Moreover, the improved network model paid more attention to fine-grained classification, minimized the loss rate, and improved the accuracy of system interpretation.
Impact of Parameter Mismatch on Three-Phase Dual-Active-Bridge Converters
Authors: Nguyen Duy-Dinh , Pham The-Tiep , Le Tat-Thang , Do Ton Duc , Goto Takuya , Yukita Kazuto
Published: June 2023

Three-phase dual active bridge converters (DAB3) are a widely used topology in battery charging applications thanks to their numerous advantages, such as bidirectional power flow, galvanic isolation, low output current ripple, and inherent soft-switching. In such applications, three single-phase transformers are commonly employed as the AC-link to simplify manufacturing and reduce costs. These transformers’ leakage inductance can be utilized instead of the external leakage inductance to achieve high power density. However, the assumption of uniformity in these inductances is not always accurate as they can vary significantly during fabrication. This study presents a comprehensive analysis of the impact of transformer leakage inductance variation, which can deviate by up to 24% from the desired value. The effects of this variation are investigated from different perspectives, including power transfer, soft-switching range, root-mean-square (RMS) current, and the temperature rise of the transformer winding. Although the power transfer and total copper loss of transformers are changed insignificantly even under highly mismatched leakage inductance, the currents and thermal distribution among phases are considerably impacted. Based on statistical probability, a maximum leakage inductance variation threshold of 10–15% compared to the desired value is recommended to ensure the maximum acceptable temperature rise among phases. Experimental results are presented to validate the analysis.
Container Allocation in Cloud Environment Using Multi-Agent Deep Reinforcement Learning
Authors: Danino Tom , Ben-Shimol Yehuda , Greenberg Shlomo
Published: June 2023

Nowadays, many computation tasks are carried out using cloud computing services and virtualization technology. The intensive resource requirements of virtual machines have led to the adoption of a lighter solution based on containers. Containers isolate packaged applications and their dependencies, and they can also operate as part of distributed applications. Containers can be distributed over a cluster of computers with available resources, such as the CPU, memory, and communication bandwidth. Any container distribution mechanism should consider resource availability and their impact on overall performance. This work suggests a new approach to assigning containers to servers in the cloud, while meeting computing and communication resource requirements and minimizing the overall task completion time. We introduce a multi-agent environment using a deep reinforcement learning-based decision mechanism. The high action space complexity is tackled by decentralizing the allocation decisions among multiple agents. Considering the interactions among the agents, we introduce a new cooperative mechanism for a state and reward design, resulting in efficient container assignments. The performances of both long short term memory (LSTM) and memory augmented-based agents are examined, for solving the challenging container assignment problem. Experimental results demonstrated an improvement of up to 28% in the execution runtime compared to existing bin-packing heuristics and the common Kubernetes industrial tool.
Impacts of Climate Change on Rural Communities: Vulnerability and Adaptation in the Global South
Authors: Atkinson Christopher L. , Atkinson Allison M.
Published: June 2023

Climate change has resulted in negative impacts upon rural communities, notably in the Global South; these impacts expose vulnerabilities that exist on individual and societal levels, necessitating consideration of adaptive capacity given the climate change threat, as well as the role of government in responding to hazards, and encouraging resilience and sustainability.
Select or Not? Comparing the Impact of Selective and Schematic Thinning on Scots Pine Tree Growth and Stand Structure
Authors: Segtowich Amanda Castro , Huuskonen Saija , Fahlvik Nils , Holmström Emma
Published: June 2023

The first commercial thinning usually entails a high cost in harvest operations and a low resulting income. From a practical forestry perspective, a schematic spatial selection might be more efficient than a selective approach. Therefore, this study aimed to compare basal area, total and standing volumes, and periodic annual increment (PAI), as well as stand structure, between different thinning designs (selective and schematic thinning) and strategies (thinning once or more than once) over a long-term monitoring period of Scots pine (Pinus sylvestris) plantations in Sweden. We also evaluated the relevancy of distance-dependent competition indices (CIs) in individual tree growth models by comparing growth model predictions with the use of distance-dependent and distance-independent CIs. Despite higher heterogeneity in schematically thinned stands, there were no significant differences in standing and total volumes (m3·ha−1) among treatments in the short or long term. Although the inclusion of a distance-dependent CI improved the model slightly, distance-independent models predicted diameter growth just as effectively. Schematic thinning could be a viable option for a first commercial thinning or one-time thinning if, at least, one more thinning is included in the management plan, or if the motivating interest is mainly volume.
The Use of Compost Tea in a Containerized Urban Tree Nursery Shows No Evident Benefits to Tree Growth or Mycorrhizal Colonization
Authors: Du Dan , Livesley Stephen J. , Arndt Stefan K. , Truong Camille , Miller Rebecca E.
Published: June 2023

Compost tea is a liquid organic amendment that has been reported to benefit plant growth and performance through positive effects on microbial communities and plant nutrition. However, few studies have demonstrated this for containerized plants produced in tree nurseries. Five common urban tree species (Acer negundo, Corymbia maculata, Ficus platypoda, Hymenosporum flavum, Jacaranda mimosifolia) were grown in a containerized experiment to investigate the effects of compost tea application on tree growth and root mycorrhizal colonization over six months. The microbial composition of compost tea was also determined with 16S (bacteria) and ITS1 (fungi) metabarcoding. No significant positive effect of compost tea on plant growth or root mycorrhizal colonization was observed. Roots of all tree species were colonized by one type of mycorrhizal fungi, ectomycorrhizae (ECM), or vesicular–arbuscular mycorrhizae (VAM). However, no relationship between the mycorrhizal colonization percentage and plant growth was detected. Thus, there was no evidence that a once-off application of compost tea had benefits for mycorrhizal colonization and growth of containerized trees in a nursery setting. Further research is needed to investigate whether any benefit from compost tea is evident once containerized trees are planted into urban landscapes where growth conditions may be more challenging.
Multi-Omics Techniques in Genetic Studies and Breeding of Forest Plants
Authors: Wang Mingcheng , Li Rui , Zhao Qi
Published: June 2023

In recent years, the ecological and economic values of forest plants have been gradually recognized worldwide. However, the growing global demand for new forest plant varieties with higher wood production capacity and better stress tolerance cannot be satisfied by conventional phenotype-based breeding, marker-assisted selection, and genomic selection. In the recent past, diverse omics technologies, including genomics, transcriptomics, epigenomics, proteomics, and metabolomics, have been developed rapidly, providing powerful tools for the precision genetic breeding of forest plants. Genomics lays a solid foundation for understanding complex biological regulatory networks, while other omics technologies provide different perspectives at different levels. Multi-omics integration combines the different omics technologies, becoming a powerful tool for genome-wide functional element identification in forest plant breeding. This review summarizes the recent progress of omics technologies and their applications in the genetic studies on forest plants. It will provide forest plant breeders with an elementary knowledge of multi-omics techniques for future breeding programs.
Zoning Prediction and Mapping of Three-Dimensional Forest Soil Organic Carbon: A Case Study of Subtropical Forests in Southern China
Authors: Li Yingying , Zhang Zhongrui , Zhao Zhengyong , Sun Dongxiao , Zhu Hangyong , Zhang Geng , Zhu Xianliang , Ding Xiaogang
Published: June 2023

Accurate soil organic carbon (SOC) maps are helpful for guiding forestry production and management. Different ecological landscape areas within a large region may have different soil–landscape relationships, so models specifically for these areas may capture these relationships more accurately than the global model for the entire study area. The aim of this study was to investigate the role of zonal modelling in predicting forest SOC and to produce highly accurate forest SOC distribution maps. The prediction objects were SOC at five soil depths (0–20, 20–40, 40–60, 60–80, and 80–100 cm). First, the forest type map and soil texture class map were used to divide the relative homogeneous regions in Shaoguan City, Guangdong Province, China. Second, seven terrain variables derived from a 12.5-m digital elevation model (DEM) and five vegetation variables generated from 10-m Sentinel-2 remote sensing images were used as predictors to develop regional artificial neural network (ANN) models for each homogeneous region, as well as a global ANN model for the entire study area (1000 sample points). Finally, 10-fold cross-validation was used to assess the ANN prediction model performance, and independent validation was used to evaluate the produced forest SOC prediction maps (194 additional samples). The cross-validation results showed that the accuracies of the regional models were better than that of the global model. Independent validation results also showed that the precision (R2) of 0- to 100-cm forest SOC maps generated by forest type modelling had an improvement of 0.05–0.15, and that by soil texture class modelling had an improvement of 0.07–0.13 compared to the map generated by the global model. In conclusion, delineating relatively homogeneous regions via simple methods can improve prediction accuracy when undertaking soil predictions over large areas, especially with complex forest landscapes. In addition, SOC in the study area is generally more abundant in broadleaf forest and clay areas, with overall levels decreasing with soil depth. Accurate SOC distribution information can provide references for fertilization and planting. Plants with particularly high soil fertility requirements may perhaps be planted in broadleaf forests or clay areas, and plants with particularly developed roots may require furrow application of a small amount of SOC.
Analysis of the Effects of Windthrows on the Microbiological Properties of the Forest Soils and Their Natural Regeneration
Authors: Sicoe Silviu Ioan , Crainic Ghiță Cristian , Samuel Alina Dora , Bodog Marinela Florica , Iovan Călin Ioan , Curilă Sorin , Hâruța Ioan Ovidiu , Șerban Eugenia , Dorog Lucian Sorin , Sabău Nicu Cornel
Published: June 2023

Windthrows in the forestry fund, which have become more frequent due to the increase in extreme weather events, have had, and continue to have, mostly negative economic and ecological effects, making them a pressing issue in forestry research. The main objectives of this study are to evaluate the effects of windthrows on some microbiological properties of forest soils and to monitor the evolution of the degraded tree regeneration, four years after the event, for three tree species: Norway spruce (Picea abies L.), sessile oak (Quercus petraea), and European beech (Fagus sylvatica L.). The experimental plot used is arranged in dispersed blocks and subdivided plots, with three repetitions, and is bifactorial, with factor A representing the tree species and factor B the windthrows. There are two possibilities: affected by windthrows (AW) and unaffected by windthrows (WW). For each tree species, dehydrogenase activity (DA) and the number of fungi (NF) in the organic horizon at the soil surface were studied. Correlations were highlighted between the differences in AW and WW of Current Dehydrogenase Activity (CDA), Potential Dehydrogenase Activity (PDA), and NF with the number of naturally regenerated seedlings (NRS) and the type of soil. Stimulating NRS in AW forests and increasing the volume of terrestrial organic carbon (TOC) biomass is directly dependent on soil fertility, primarily determined by Soil Organic Carbon (SOC), which accumulates in the soil as a result of organic matter, deposited on the surface. Sustainable forest management of AW plots should stimulate the accumulation of SOC, including the partial or total preservation of dead trees, provided that the attack of specific diseases and pests is avoided.