bluuebunny/crossref_metadata_2025 huggingface dataset:
RS Transformer: A Two-Stage Region Proposal Using Swin Transformer for Few-Shot Pest Detection in Automated Agricultural Monitoring Systems
Authors: Wu Tengyue , Shi Liantao , Zhang Lei , Wen Xingkai , Lu Jianjun , Li Zhengguo
Published: November 2023

Agriculture is pivotal in national economies, with pest classification significantly influencing food quality and quantity. In recent years, pest classification methods based on deep learning have made progress. However, there are two problems with these methods. One is that there are few multi-scale pest detection algorithms, and they often lack effective global information integration and discriminative feature representation. The other is the lack of high-quality agricultural pest datasets, leading to insufficient training samples. To overcome these two limitations, we propose two methods called RS Transformer (a two-stage region proposal using Swin Transformer) and the Randomly Generated Stable Diffusion Dataset (RGSDD). Firstly, we found that the diffusion model can generate high-resolution images, so we developed a training strategy called the RGSDD, which was used to generate agricultural pest images and was mixed with real datasets for training. Secondly, RS Transformer uses Swin Transformer as the backbone to enhance the ability to extract global features, while reducing the computational burden of the previous Transformer. Finally, we added a region proposal network and ROI Align to form a two-stage training mode. The experimental results on the datasets show that RS Transformer has a better performance than the other models do. The RGSDD helps to improve the training accuracy of the model. Compared with methods of the same type, RS Transformer achieves up to 4.62% of improvement.
Application of Bonded-Block Models to Rock Failure Analysis
Authors: Lemos José V.
Published: November 2023

Discrete element models are being increasingly applied to model rock failure processes. Bonded-particle models, based on circular or spherical particle systems, have been successfully used for two decades. More recently, bonded-block models, using polygonal or polyhedral elements, have proven to be a powerful alternative. This paper describes the basis of the application of these models in the numerical simulation of failure in rock materials. The critical governing parameters are identified, and their influence is discussed. The model calibration procedure based on the analysis of laboratory tests is discussed. An application example of an underground excavation problem is presented using a simple bonded-block model employing rigid blocks and a bilinear softening contact model. The results show the capability of this approach to reproduce observed failure modes involving block fractures.
Investigating the Nonlinear Effect of Built Environment Factors on Metro Station-Level Ridership under Optimal Pedestrian Catchment Areas via the Machine Learning Method
Authors: Wang Zhenbao , Li Shihao , Li Yongjin , Liu Dong , Liu Shuyue , Chen Ning
Published: November 2023

Exploring the built environment factor’s impact on metro ridership can help develop metro station area planning strategies. This is in order to compensate for the shortcomings of previous studies, which mostly used all uniform pedestrian catchment areas (PCA) around metro stations. Beijing was divided into two zones and 12 built environment explanatory variables were selected as independent variables based on the “7D” dimension of the built environment. The boarding ridership during the morning peak hours was used as the dependent variable. Nineteen PCA radii from 200 to 2000 m were assumed. The optimal PCA of metro stations for each zone was determined by using the eXtreme Gradient Boosting (XGBoost) model with the objective of minimizing the Mean Absolute Percentage Error (MAPE). The nonlinear impact of the built environment factor of each zone on metro ridership is analyzed under the optimal PCA of metro stations. The study results show that (1) the optimal PCAs of metro stations inside the 4th Ring Road and outside the 4th Ring Road are the circular buffer zones with a radius of 800 m and 1300 m, respectively. (2) There is a nonlinear influence of the built environment factor on metro ridership, with strong threshold effects and spatial heterogeneity. The PCA results can be used for the built environment’s zoning of metro stations. The XGBoost model and the nonlinear impact results provide significant implications for the practice of station-level ridership forecasting and integrating TOD development and built environment renewal.
Application of Performance Test Method in Korea for LED Optical Medical Device Samples
Authors: Lee Jae-Young , Kwon Yi-Suk , Park Sang-Geon
Published: November 2023

This study obtained key performance items related to phototherapy and the standards of light-emitting diode (LED) phototherapy devices through the published literature to secure LED phototherapy device safety in South Korea. Based on these items and IEC 62471-1 for the photobiological safety of lamps and lamp systems, a performance test method and wavelength parameters, which are the main performance indicators of the LED phototherapy device, were derived. We conducted a performance test derived from this study using samples with the same performance as the sample that is being developed. The samples comprised a laser and IR LED, red LED, and blue LED. All samples were within ±5%, of the standard threshold. The 455 nm blue LED and 625 nm red LED were close to the set value with a difference of 1 to 2 nm; their wavelengths’ accuracy was within ±0.32%, ±0%, and ±0.219%, depending on the samples’ wavelengths, which was the same or similar to the error range of ±0%. As for laser and IR LED, the difference from the set value was as large as 2 to 7 nm, and their error ranges were close to ±1%, as shown by ±0.615%, ±0.828%, or ±0.591%, which were larger than the values for red and blue LEDs.
Stock Market Prediction Using Deep Reinforcement Learning
Authors: Awad Alamir Labib , Elkaffas Saleh Mesbah , Fakhr Mohammed Waleed
Published: November 2023

Stock value prediction and trading, a captivating and complex research domain, continues to draw heightened attention. Ensuring profitable returns in stock market investments demands precise and timely decision-making. The evolution of technology has introduced advanced predictive algorithms, reshaping investment strategies. Essential to this transformation is the profound reliance on historical data analysis, driving the automation of decisions, particularly in individual stock contexts. Recent strides in deep reinforcement learning algorithms have emerged as a focal point for researchers, offering promising avenues in stock market predictions. In contrast to prevailing models rooted in artificial neural network (ANN) and long short-term memory (LSTM) algorithms, this study introduces a pioneering approach. By integrating ANN, LSTM, and natural language processing (NLP) techniques with the deep Q network (DQN), this research crafts a novel architecture tailored specifically for stock market prediction. At its core, this innovative framework harnesses the wealth of historical stock data, with a keen focus on gold stocks. Augmented by the insightful analysis of social media data, including platforms such as S&P, Yahoo, NASDAQ, and various gold market-related channels, this study gains depth and comprehensiveness. The predictive prowess of the developed model is exemplified in its ability to forecast the opening stock value for the subsequent day, a feat validated across exhaustive datasets. Through rigorous comparative analysis against benchmark algorithms, the research spotlights the unparalleled accuracy and efficacy of the proposed combined algorithmic architecture. This study not only presents a compelling demonstration of predictive analytics but also engages in critical analysis, illuminating the intricate dynamics of the stock market. Ultimately, this research contributes valuable insights and sets new horizons in the realm of stock market predictions.
Bi-Continuous Si/C Anode Materials Derived from Silica Aerogels for Lithium-Ion Batteries
Authors: Shan Yunpeng , Wang Junzhang , Xu Zhou , Bai Shengchi , Zhu Yingting , Wang Xiaoqi , Guo Xingzhong
Published: November 2023

Poor cycling performance caused by massive volume expansion of silicon (Si) has always hindered the widespread application of silicon-based anode materials. Herein, bi-continuous silicon/carbon (Si/C) anode materials are prepared via magnesiothermic reduction of silica aerogels followed by pitch impregnation and carbonization. To fabricate the expected bi-continuous structure, mesoporous silica aerogel is selected as the raw material for magnesiothermic reduction. It is successfully reduced to mesoporous Si under the protection of NaCl. The as-obtained mesoporous Si is then injected with molten pitch via vacuuming, and the pitch is subsequently converted into carbon at a high temperature. The innovative point of this strategy is the construction of a bi-continuous structure, which features both Si and carbon with a cross-linked structure, which provides an area to accommodate the colossal volume change of Si. The pitch-derived carbon facilitates fast lithium ion transfer, thereby increasing the conductivity of the Si/C anode. It can also diminish direct contact between Si and the electrolyte, minimizing side reactions between them. The obtained bi-continuous Si/C anodes exhibit excellent electrochemical performance with a high initial discharge capacity of 1481.7 mAh g−1 at a current density of 300 mA g−1 and retaining as 813.5 mAh g−1 after 200 cycles and an improved initial Coulombic efficiency of 82%. The as-prepared bi-continuous Si/C anode may have great potential applications in high-performance lithium-ion batteries.
Vascular Growth Factor Inhibition with Bevacizumab Improves Cardiac Electrical Alterations and Fibrosis in Experimental Acute Chagas Disease
Authors: Nisimura Lindice Mitie , Ferreira Roberto Rodrigues , Coelho Laura Lacerda , de Oliveira Gabriel Melo , Gonzaga Beatriz Matheus , Meuser-Batista Marcelo , Lannes-Vieira Joseli , Araujo-Jorge Tania , Garzoni Luciana Ribeiro
Published: November 2023

Chagas disease (CD) caused by Trypanosoma cruzi is a neglected illness and a major reason for cardiomyopathy in endemic areas. The existing therapy generally involves trypanocidal agents and therapies that control cardiac alterations. However, there is no treatment for the progressive cardiac remodeling that is characterized by inflammation, microvasculopathy and extensive fibrosis. Thus, the search for new therapeutic strategies aiming to inhibit the progression of cardiac injury and failure is necessary. Vascular Endothelial Growth Factor A (VEGF-A) is the most potent regulator of vasculogenesis and angiogenesis and has been implicated in inducing exacerbated angiogenesis and fibrosis in chronic inflammatory diseases. Since cardiac microvasculopathy in CD is also characterized by exacerbated angiogenesis, we investigated the effect of inhibition of the VEGF signaling pathway using a monoclonal antibody (bevacizumab) on cardiac remodeling and function. Swiss Webster mice were infected with Y strain, and cardiac morphological and molecular analyses were performed. We found that bevacizumab significantly increased survival, reduced inflammation, improved cardiac electrical function, diminished angiogenesis, decreased myofibroblasts in cardiac tissue and restored collagen levels. This work shows that VEGF is involved in cardiac microvasculopathy and fibrosis in CD and the inhibition of this factor could be a potential therapeutic strategy for CD.
PGPR-Soil Microbial Communities’ Interactions and Their Influence on Wheat Growth Promotion and Resistance Induction against Mycosphaerella graminicola
Authors: Samain Erika , Duclercq Jérôme , Ait Barka Essaïd , Eickermann Michael , Ernenwein Cédric , Mazoyon Candice , Sarazin Vivien , Dubois Frédéric , Aussenac Thierry , Selim Sameh
Published: November 2023

The efficiency of plant-growth-promoting rhizobacteria (PGPR) may not be consistently maintained under field conditions due to the influence of soil microbial communities. The present study aims to investigate their impact on three PGPR-based biofertilizers in wheat. We used the PGPR Paenibacillus sp. strain B2 (PB2), PB2 in co-inoculation with Arthrobacter agilis 4042 (Mix 2), or with Arthrobacter sp. SSM-004 and Microbacterium sp. SSM-001 (Mix 3). Inoculation of PB2, Mix 2, and Mix 3 into non-sterile field soil had a positive effect on root and aboveground dry biomass, depending on the wheat cultivar. The efficiency of the PGPR was further confirmed by the protection they provided against Mycosphaerella graminicola, the causal agent of Septoria leaf blotch disease. PB2 exhibited protection of ≥37.8%, while Mix 2 showed ≥47.9% protection in the four cultivars tested. These results suggest that the interactions between PGPR and native soil microbial communities are crucial for promoting wheat growth and protection. Additionally, high-throughput sequencing of microbial communities conducted 7 days after PGPR inoculations revealed no negative effects of PB2, Mix 2, and Mix 3 on the soil microbial community structure. Interestingly, the presence of Arthrobacter spp. appeared to mitigate the potential negative effect of PB2 on bacterial community and foster root colonization by other beneficial bacterial strains.
The Ultraviolet Irradiation of Keratinocytes Induces Ectopic Expression of LINE-1 Retrotransposon Machinery and Leads to Cellular Senescence
Authors: Touma Fadi , Lambert Marine , Martínez Villarreal Amelia , Gantchev Jennifer , Ramchatesingh Brandon , Litvinov Ivan V.
Published: November 2023

Retrotransposons have played an important role in evolution through their transposable activity. The largest and the only currently active human group of mobile DNAs are the LINE-1 retrotransposons. The ectopic expression of LINE-1 has been correlated with genomic instability. Narrow-band ultraviolet B (NB-UVB) and broad-band ultraviolet B (BB-UVB) phototherapy is commonly used for the treatment of dermatological diseases. UVB exposure is carcinogenic and can lead, in keratinocytes, to genomic instability. We hypothesize that LINE-1 reactivation occurs at a high rate in response to UVB exposure on the skin, which significantly contributes to genomic instability and DNA damage leading to cellular senescence and photoaging. Immortalized N/TERT1 and HaCaT human keratinocyte cell lines were irradiated in vitro with either NB-UVB or BB-UVB. Using immunofluorescence and Western blotting, we confirmed UVB-induced protein expression of LINE-1. Using RT-qPCR, we measured the mRNA expression of LINE-1 and senescence markers that were upregulated after several NB-UVB exposures. Selected miRNAs that are known to bind LINE-1 mRNA were measured using RT-qPCR, and the expression of miR-16 was downregulated with UVB exposure. Our findings demonstrate that UVB irradiation induces LINE-1 reactivation and DNA damage in normal keratinocytes along with the associated upregulation of cellular senescence markers and change in miR-16 expression.
ADMET and Solubility Analysis of New 5-Nitroisatine-Based Inhibitors of CDK2 Enzymes
Authors: Czeleń Przemysław , Jeliński Tomasz , Skotnicka Agnieszka , Szefler Beata , Szupryczyński Kamil
Published: November 2023

The development of new substances with the ability to interact with a biological target is only the first stage in the process of the creation of new drugs. The 5-nitroisatin derivatives considered in this study are new inhibitors of cyclin-dependent kinase 2 (CDK2) intended for anticancer therapy. The research, carried out based on the ADMET (absorption, distribution, metabolism, excretion, toxicity) methods, allowed a basic assessment of the physicochemical parameters of the tested drugs to be made. The collected data clearly showed the good oral absorption, membrane permeability, and bioavailability of the tested substances. The analysis of the metabolite activity and toxicity of the tested drugs did not show any critical hazards in terms of the toxicity of the tested substances. The substances’ low solubility in water meant that extended studies tested compounds were required, which helped to select solvents with a high dissolving capacity of the examined substances, such as DMSO or NMP. The use of aqueous binary mixtures based on these two solvents allowed a relatively high solubility with significantly reduced toxicity and environmental index compared to pure solvents to be maintained, which is important in the context of the search for green solvents for pharmaceutical use.
The Evolution of Robin Sequence Treatment Based on the Biomimetic Interdisciplinary Approach: A Historical Review
Authors: Čverha Martin , Varga Ivan , Trenčanská Tereza , Šufliarsky Barbora , Thurzo Andrej
Published: November 2023

The Robin sequence is a congenital anomaly characterized by a triad of features: micrognathia, glossoptosis, and airway obstruction. This comprehensive historical review maps the evolution of approaches and appliances for its treatment from the past to the current modern possibilities of an interdisciplinary combination of modern engineering, medicine, materials, and computer science combined approach with emphasis on designing appliances inspired by nature and individual human anatomy. Current biomimetic designs are clinically applied, resulting in appliances that are more efficient, comfortable, sustainable, and safer than legacy traditional designs. This review maps the treatment modalities that have been used for patients with a Robin sequence over the years. Early management of the Robin sequence focused primarily on airway maintenance and feeding support, while current management strategies involve both nonsurgical and surgical interventions and biomimetic biocompatible personalized appliances. The goal of this paper was to provide a review of the evolution of management strategies for patients with the Robin sequence that led to the current interdisciplinary biomimetic approaches impacting the future of Robin Sequence treatment with biomimetics at the forefront.
Investigation on the Energy-Absorbing Properties of Bionic Spider Web Structure
Authors: Xie Baocheng , Wu Xilong , Ji Xuhui
Published: November 2023

In recent years, spider webs have received significant attention due to their exceptional mechanical properties, including strength, toughness, elasticity, and robustness. Among these spider webs, the orb web is a prevalent type. An orb web’s main framework consists of radial and spiral threads, with elastic and sticky threads used to capture prey. This paper proposes a bionic orb web model to investigate the energy-absorbing properties of a bionic spider web structure. The model considers structural parameters such as radial line length, radial line cross-sectional diameter, number of spiral lines, spiral spacing, and spiral cross-sectional diameter. These parameters are evaluated to assess the energy absorption capability of the bionic spider web structure. Simulation results reveal that the impact of the radial line length and spiral cross-sectional diameter on the energy absorption of the spider web is more significant compared to the radial line cross-sectional diameter, the number of spiral lines, and spiral spacing. Specifically, within a radial line length range of 60–80 mm, the total absorbed energy of a spider web is inversely proportional to the radial line length of the web. Moreover, the number of spiral lines and spiral spacing of the spider web, when within the range of 6–10 turns and 4–5.5 mm, respectively, are proportional to the total energy absorbed. A regression equation is derived to predict the optimal combination of structural parameters for maximum energy absorption. The optimal parameters are determined as follows: radial line length of 63.48 mm, radial line cross-sectional diameter of 0.46 mm, ten spiral lines, spiral spacing of 5.39 mm, and spiral cross-sectional diameter of 0.48 mm.
Ultrafast Electrochemical Self-Doping of Anodic Titanium Dioxide Nanotubes for Enhanced Electroanalytical and Photocatalytic Performance
Authors: Spanu Davide , Dhahri Aicha , Binda Gilberto , Monticelli Damiano , Pinna Marco , Recchia Sandro
Published: November 2023

This study explores an ultrarapid electrochemical self-doping procedure applied to anodic titanium dioxide (TiO2) nanotube arrays in an alkaline solution to boost their performance for electroanalytical and photocatalytic applications. The electrochemical self-doping process (i.e., the creation of surface Ti3+ states by applying a negative potential) is recently emerging as a simpler and cleaner way to improve the electronic properties of TiO2 compared to traditional chemical and high-temperature doping strategies. Here, self-doping was carried out through varying voltages and treatment times to identify the most performing materials without compromising their structural stability. Interestingly, cyclic voltammetry characterization revealed that undoped TiO2 shows negligible activity, whereas all self-doped materials demonstrate their suitability as electrode materials: an outstandingly short 10 s self-doping treatment leads to the highest electrochemical activity. The electrochemical detection of hydrogen peroxide was assessed as well, demonstrating a good sensitivity and a linear detection range of 3–200 µM. Additionally, the self-doped TiO2 nanotubes exhibited an enhanced photocatalytic activity compared to the untreated substrate: the degradation potential of methylene blue under UV light exposure increased by 25% in comparison to undoped materials. Overall, this study highlights the potential of ultrafast electrochemical self-doping to unleash and improve TiO2 nanotubes performances for electroanalytical and photocatalytic applications.
Psychometric Performance of Generic Childhood Multi-Attribute Utility Instruments in Preterm and Low Birthweight Populations: A Systematic Review
Authors: Kwon Joseph , Bolbocean Corneliu , Onyimadu Olu , Roberts Nia , Petrou Stavros
Published: November 2023

Background: Individuals born preterm (gestational age < 37 weeks) and/or at low birthweight (<2500 g) are at increased risk of health impairments from birth to adulthood. This review aimed to evaluate the psychometric performance of generic childhood-specific or childhood-compatible multi-attribute utility instruments (MAUIs) in preterm and/or low birthweight (PLB) populations. Methods: Searches covered seven databases, including studies that targeted childhood (aged < 18 years) and/or adult (≥18 years) PLB populations; provided psychometric evidence for generic childhood-specific or compatible MAUI(s) (any language version); and published in English. Eighteen psychometric properties were evaluated using a four-part criteria rating system. Data syntheses identified psychometric evidence gaps and summarised the psychometric assessment methods/results. Results: A total of 42 studies were included, generating 178 criteria rating outputs across four MAUIs: 17D, CHSCS-PS, HUI2, and HUI3. Moreover, 64.0% of outputs concerned the HUI3 MAUI, and 38.2% related to known-group validity. There was no evidence for five psychometric properties. Only 6.7% of outputs concerned reliability and proxy–child agreement. No MAUI outperformed others across all properties. The frequently applied HUI2 and HUI3 lacked content validity evidence. Conclusions: This psychometric evidence catalogue should inform the selection of MAUI(s) suited to the specific aims of applications targeting PLB populations. Further psychometric research is warranted to address the gaps in psychometric evidence.
Nerve Growth Factor and Autoimmune Diseases
Authors: Terracina Sergio , Ferraguti Giampiero , Tarani Luigi , Fanfarillo Francesca , Tirassa Paola , Ralli Massimo , Iannella Giannicola , Polimeni Antonella , Lucarelli Marco , Greco Antonio , Fiore Marco
Published: November 2023

NGF plays a crucial immunomodulatory role and increased levels are found in numerous tissues during autoimmune states. NGF directly modulates innate and adaptive immune responses of B and T cells and causes the release of neuropeptides and neurotransmitters controlling the immune system activation in inflamed tissues. Evidence suggests that NGF is involved in the pathogenesis of numerous immune diseases including autoimmune thyroiditis, chronic arthritis, multiple sclerosis, systemic lupus erythematosus, mastocytosis, and chronic granulomatous disease. Furthermore, as NGF levels have been linked to disease severity, it could be considered an optimal early biomarker to identify therapeutic approach efficacy. In conclusion, by gaining insights into how these molecules function and which cells they interact with, future studies can devise targeted therapies to address various neurological, immunological, and other disorders more effectively. This knowledge may pave the way for innovative treatments based on NGF manipulation aimed at improving the quality of life for individuals affected by diseases involving neurotrophins.
Biosynthesis Effect of Egg White on Formation and Characteristics of NiO/NiCo2O4 Nanocomposites
Authors: Al-Senani Ghadah M. , Al-Fawzan Foziah F. , Alshabanat Mashael , Abd-Elkader Omar H. , Nasrallah Mai , Nasrallah Mohamed
Published: November 2023

For the successful production of NiO/NiCo2O4 nanocomposites, the environmentally friendly method of egg white supplementation has been used. Several analytical techniques were employed to characterize the morphology, purity, and crystal structure of the as-prepared nanocomposites. These techniques included transmission electron microscopy (TEM), Fourier-transform infrared spectroscopy (FTIR), scanning electron microscopy (SEM), and X-ray diffraction (XRD). The physical adsorption and magnetic properties of the investigated composite were determined using the Brunauer–Emmett–Teller (BET) method and a vibrating-sample magnetometer (VSM), respectively. The results have shown that the as-prepared composite particles had diameters of about 10–25 nm, with uniform distribution. The XRD analysis showed that the as-synthesized composites consisted entirely of cubic structures of both NiO and spinel NiCo2O4 nanoparticles, with a space group of Fd3m. The FTIR analysis showed characteristic vibration modes related to metal oxides, confirming the formation of composites containing NiO and NiCo2O4 crystallites. The investigated composites’ saturation magnetization (MS) and coercivity (HC) were easily controllable because of the ingredients’ ferromagnetic (NiCo2O4) and antiferromagnetic (NiO) characteristics. The excellent combination of the NiO/NiCo2O4 nanocomposites’ properties is anticipated to make this system suitable for a wide range of applications.
Attention TurkerNeXt: Investigations into Bipolar Disorder Detection Using OCT Images
Authors: Arslan Sermal , Kaya Mehmet Kaan , Tasci Burak , Kaya Suheda , Tasci Gulay , Ozsoy Filiz , Dogan Sengul , Tuncer Turker
Published: November 2023

Background and Aim: In the era of deep learning, numerous models have emerged in the literature and various application domains. Transformer architectures, particularly, have gained popularity in deep learning, with diverse transformer-based computer vision algorithms. Attention convolutional neural networks (CNNs) have been introduced to enhance image classification capabilities. In this context, we propose a novel attention convolutional model with the primary objective of detecting bipolar disorder using optical coherence tomography (OCT) images. Materials and Methods: To facilitate our study, we curated a unique OCT image dataset, initially comprising two distinct cases. For the development of an automated OCT image detection system, we introduce a new attention convolutional neural network named “TurkerNeXt”. This proposed Attention TurkerNeXt encompasses four key modules: (i) the patchify stem block, (ii) the Attention TurkerNeXt block, (iii) the patchify downsampling block, and (iv) the output block. In line with the swin transformer, we employed a patchify operation in this study. The design of the attention block, Attention TurkerNeXt, draws inspiration from ConvNeXt, with an added shortcut operation to mitigate the vanishing gradient problem. The overall architecture is influenced by ResNet18. Results: The dataset comprises two distinctive cases: (i) top to bottom and (ii) left to right. Each case contains 987 training and 328 test images. Our newly proposed Attention TurkerNeXt achieved 100% test and validation accuracies for both cases. Conclusions: We curated a novel OCT dataset and introduced a new CNN, named TurkerNeXt in this research. Based on the research findings and classification results, our proposed TurkerNeXt model demonstrated excellent classification performance. This investigation distinctly underscores the potential of OCT images as a biomarker for bipolar disorder.
Are Allergy-Induced Implant Failures Actually Hypersensitivity Reactions to Titanium? A Literature Review
Authors: Watanabe Megumi , Liu Lipei , Ichikawa Tetsuo
Published: November 2023

Purpose: This literature review was performed to assess whether implant failures are associated with titanium allergy. Materials and Methods: An electronic search of the MEDLINE/PubMed, Cochrane Library, and Scopus databases up to April 2021 was conducted, and the obtained articles were independently assessed by two reviewers. Articles describing cases of implant failure in which the cause of implant failure was only identified as allergy were included. Results: Twelve studies were included. Eight studies identified Ti allergy by clinical examinations, of which four used patch tests, three used the lymphocyte transformation test (LTT)/memory lymphocyte immunostimulation assay (MELISA), and one used both tests. Nine studies reported cases of titanium hypersensitivity in combination with other systemic allergy-related disorders, with eight cases also showing positive results for Ni, Hg, Cr, and Co hypersensitivity. Ten papers reported the improvement of symptoms after the removal of the Ti implants and their replacement with zirconia implants, and two of these papers showed good results. Conclusion: Cases of probable titanium allergy included those with true titanium allergies and those with a potentially different cause. However, the differentiation of these cases is difficult. Since no definitive method has been established for diagnosing titanium allergy, a comprehensive diagnosis based on the clinical course and clinical examination using a patch test/LTT/MELISA is necessary. Implant treatment should be performed with caution in patients with any preoperative allergies.
Robust Global Trends during Pandemics: Analysing the Interplay of Biological and Social Processes
Authors: Mitrović Dankulov Marija , Tadić Bosiljka , Melnik Roderick
Published: November 2023

The essence of the stochastic processes behind the empirical data on infection and fatality during pandemics is the complex interdependence between biological and social factors. Their balance can be checked on the data of new virus outbreaks, where the population is unprepared to fight the viral biology and social measures and healthcare systems adjust with a delay. Using a complex systems perspective, we combine network mapping with K-means clustering and multifractal detrended fluctuations analysis to identify typical trends in fatality rate data. We analyse global data of (normalised) fatality time series recorded during the first two years of the recent pandemic caused by the severe acute respiratory syndrome coronavirus 2 as an appropriate example. Our results reveal six clusters with robust patterns of mortality progression that represent specific adaptations to prevailing biological factors. They make up two significant groups that coincide with the topological communities of the correlation network, with stabilising (group g1) and continuously increasing rates (group g2). Strong cyclic trends and multifractal small-scale fluctuations around them characterise these patterns. The rigorous analysis and the proposed methodology shed more light on the complex nonlinear shapes of the pandemic’s main characteristic curves, which have been discussed extensively in the literature regarding the global infectious diseases that have affected humanity throughout its history. In addition to better pandemic preparedness in the future, the presented methodology can also help to differentiate and predict other trends in pandemics, such as fatality rates, caused simultaneously by different viruses in particular geographic locations.
Design and Implementation of a Low-Complexity Multi-h CPM Receiver with Linear Phase Approximation Synchronization Algorithm
Authors: Wang Le , Wen Huan , Wu Xucen , Song Qingping
Published: November 2023

Multi-h continuous phase modulation (CPM), with extremely high spectral efficiency, involves the plague of high demodulation complexity with a large number of matched filters and a complex trellis. In this paper, an efficient all-digital demodulator for multi-h continuous phase modulation (CPM) is proposed based on a low-complexity decision-directed synchronization algorithm. Based on the maximum-likelihood estimation of the carrier phase and timing errors, we propose a reduced-complexity timing error detector with linear phase approximation (LPA) to the phase of the multi-h CPM. Compared with the traditional synchronization methods, it avoids derivative matched filtering and reduces about 2/3 of matched filters. The estimated accuracy and bit error rate (BER) performance of the LPA-based synchronization algorithm have no loss, as shown by the numerical simulation. Its stability is verified by the derived S-curve. Then, the receivers with the LPA-based synchronization for the three kinds of promising multi-h CPM are implemented on a Xilinx Kintex-7 FPGA platform. The experimental results show that the onboard tested BER of the proposed design has an ignorable loss in the numerical simulation. The implementation overhead on FPGA is significantly reduced by about 27% slices, 64% DSPs, and 70% block RAMs compared with the conventional method.
Exergoeconomic Analysis of a Mechanical Compression Refrigeration Unit Run by an ORC
Authors: Taban Daniel , Apostol Valentin , Grosu Lavinia , Balan Mugur C. , Pop Horatiu , Dobre Catalina , Dobrovicescu Alexandru
Published: November 2023

To improve the efficiency of a diesel internal combustion engine (ICE), the waste heat carried out by the combustion gases can be recovered with an organic Rankine cycle (ORC) that further drives a vapor compression refrigeration cycle (VCRC). This work offers an exergoeconomic optimization methodology of the VCRC-ORC group. The exergetic analysis highlights the changes that can be made to the system structure to reduce the exergy destruction associated with internal irreversibilities. Thus, the preheating of the ORC fluid with the help of an internal heat exchanger leads to a decrease in the share of exergy destruction in the ORC boiler by 4.19% and, finally, to an increase in the global exergetic yield by 2.03% and, implicitly, in the COP of the ORC-VCRC installation. Exergoeconomic correlations are built for each individual piece of equipment. The mathematical model for calculating the monetary costs for each flow of substance and energy in the system is presented. Following the evolution of the exergoeconomic performance parameters, the optimization strategy is developed to reduce the exergy consumption in the system by choosing larger or higher-performance equipment. When reducing the temperature differences in the system heat exchangers (ORC boiler, condenser, and VCRC evaporator), the unitary cost of the refrigeration drops by 44%. The increase in the isentropic efficiency of the ORC expander and VCRC compressor further reduces the unitary cost of refrigeration by another 15%. Following the optimization procedure, the cost of the cooling unit drops by half. The cost of diesel fuel has a major influence on the unit cost of cooling. A doubling of the cost of diesel fuel leads to an 80% increase in the cost of the cold unit. The original merit of the work is to present a detailed and comprehensive model of optimization based on exergoeconomic principles that can serve as an example for any thermal system optimization.
How to Increase Students’ Involvement in Extracurricular Activities: A Structural Equation Model
Authors: Assante Gabriela Monica , Lișman Carmen Gabriela
Published: November 2023

Participation in extracurricular activities (ECAs) represents an effective strategy for students to become better competitors in the labor market. Their benefits extend the academic area to professional and personal domains. Therefore, this paper examines the predictive relationship between autonomous motivation, cognitive engagement, and ECA participation. We assumed that individual attributes such as cognitive emotional self-regulation, autonomous motivation, and cognitive engagement will have an impact on students’ involvement in ECAs. The results of the structural equation model results show the positive impact of positive refocus and positive reappraisal on ECA participation. Further, emotional self-regulation positively impacts autonomous motivation and cognitive engagement, which, in turn, have a positive impact on students’ involvement in ECAs. The implications and limitations of the study are further discussed.
The Perth Empathy Scale: Psychometric Properties of the Polish Version and Its Mental Health Correlates
Authors: Larionow Paweł , Preece David A.
Published: November 2023

The Perth Empathy Scale (PES) is a 20-item self-report questionnaire that assesses people’s ability to recognize emotions in others (i.e., cognitive empathy) and vicariously experience other’s emotions (i.e., affective empathy), across positive and negative emotions. Originally developed in English, the aim of our study was to introduce the first Polish version of the PES and test its psychometric performance. Our sample was 318 people (184 females, 134 males) with ages ranging from 18 to 77. The factor structure was verified with confirmatory factor analysis. Reliability was tested in terms of internal consistency and test–retest reliability. To explore convergent, divergent, and discriminant validity, we examined relationships between the PES and measures of depression, anxiety, and emotional intelligence. It was shown that the scale was characterized by the intended four-factor solution, thus supporting factorial validity. The internal consistency reliability was also good and test–retest reliability was moderate. The convergent, divergent, and discriminant validity were strong. The clinical importance of assessing affective empathy across both positive and negative emotions was supported. Overall, our results therefore suggest that the Polish version of the PES has strong psychometric performance and clinical relevance as a measure of the multidimensional empathy construct.
DFANet: Denoising Frequency Attention Network for Building Footprint Extraction in Very-High-Resolution Remote Sensing Images
Authors: Lu Lei , Liu Tongfei , Jiang Fenlong , Han Bei , Zhao Peng , Wang Guoqiang
Published: November 2023

With the rapid development of very-high-resolution (VHR) remote-sensing technology, automatic identification and extraction of building footprints are significant for tracking urban development and evolution. Nevertheless, while VHR can more accurately characterize the details of buildings, it also inevitably enhances the background interference and noise information, which degrades the fine-grained detection of building footprints. In order to tackle the above issues, the attention mechanism is intensively exploited to provide a feasible solution. The attention mechanism is a computational intelligence technique inspired by the biological vision system capable of rapidly and automatically catching critical information. On the basis of the a priori frequency difference of different ground objects, we propose the denoising frequency attention network (DFANet) for building footprint extraction in VHR images. Specifically, we design the denoising frequency attention module and pyramid pooling module, which are embedded into the encoder–decoder network architecture. The denoising frequency attention module enables efficient filtering of high-frequency noises in the feature maps and enhancement of the frequency information related to buildings. In addition, the pyramid pooling module is leveraged to strengthen the adaptability and robustness of buildings at different scales. Experimental results of two commonly used real datasets demonstrate the effectiveness and superiority of the proposed method; the visualization and analysis also prove the critical role of the proposal.
High-Resistance Connection Diagnosis of Doubly Fed Induction Generators
Authors: Ding Wei , Jin Yulong , Wu Xijin , Yang Yufeng , Jiang Yongjiang
Published: November 2023

The high resistance connection fault of the stator is a common fault in doubly fed induction generators, which causes a three-phase imbalance in the stator circuit. Since the stator winding is directly connected to the power grid, interference from the asymmetric power grid must be eliminated in order to achieve the accurate diagnosis of stator resistance imbalance faults. Therefore, a new diagnosis method based on filter shunt capacitor banks is proposed in this paper. By introducing shunt capacitor banks, an artificial neutral point is constructed to replace the neutral point of the power grid. Then, the neutral point voltage of the stator winding relative to the artificial neutral point is selected as a fault characteristic signal. In this paper, the change in three-phase stator currents after a high-resistance connection fault is analyzed in detail, and by comparing the fault characteristic signal with three-phase stator currents, the fault phase location and fault severity of high-resistance connection can be accurately obtained. Finally, simulations are carried out via the field-circuit coupling method to validate the effectiveness of the proposed method.
Enhancing Islanded Power Systems: Microgrid Modeling and Evaluating System Benefits of Ocean Renewable Energy Integration
Authors: Vicente Miguel , Imperadore Alessandra , Correia da Fonseca Francisco X. , Vieira Mário , Cândido José
Published: November 2023

The energy transition hinges on the effective integration of renewable energy sources into the power grid. Islands can provide invaluable insights into the challenges and opportunities of integrating variable renewable energy into the grid due to their relatively small power systems, isolated grids, and diverse availability of renewable energy resources. This paper presents a study on the system benefits and challenges of marine energy integration in insular power systems, focusing on the Orkney Islands as a case study. A microgrid modeling approach that optimizes the mix of renewable sources and energy storage systems for future scenarios considering strategic time horizons (2030, 2040, and 2050) was employed. Results suggest that integrating ocean energies, namely, wave and tidal energy, yields notable benefits compared to traditional renewable energy sources exclusively. These benefits encompass reduced installed capacity, minimized energy storage requirements, lower excess generation, and overall cost-saving.
Hydrogen-Rich Syngas Production via Dry and Steam Reforming of Methane in Simulated Producer Gas over ZSM-5-Supported Trimetallic Catalysts
Authors: Iminabo John Tamunosaki , Iminabo Misel , Yip Alex C. K. , Pang Shusheng
Published: November 2023

This study investigated the production of hydrogen-rich syngas from renewable sources using durable and efficient catalysts. Specifically, the research focused on steam methane reforming (SRM) and dry methane reforming (DRM) of simulated producer gas from biomass steam gasification in a fluidized bed reactor. The catalysts tested are ZSM-5-supported nickel-iron-cobalt-based trimetallic catalysts in different ratios, which were prepared via the wet impregnation method. Synthesized catalysts were characterized using XRD, BET, H2-TPR, and SEM techniques. The results of the SRM with the simulated producer gas showed that the 20%Ni-20%Fe-10%Co/ZSM-5 trimetallic catalyst, at a gas hourly space velocity (GHSV) of 12 L·h−1·g−1 and reaction temperature of 800 °C, achieved the highest CH4 conversion (74.8%) and highest H2 yield (65.59%) with CO2 conversion (36.05%). Comparing the performance of the SRM and DRM of the simulated producer gas with the 20%Ni-20%Fe-10%Co/ZSM5 at a GHSV of 36 L·h−1·g−1 and 800 °C, they achieved a CH4 conversion of 67.18% and 64.43%, a CO2 conversion of 43.01% and 52.1%, and a H2 yield of 55.49% and 42.02%, respectively. This trimetallic catalyst demonstrated effective inhibition of carbon formation and sintering, with only 2.6 wt.% carbon deposition observed from the thermo-gravimetric analysis of the used catalyst from the SRM of the simulated producer gas, thus promoting the potential of the ZSM-5-supported trimetallic catalysts in methane reforming.
Monitoring β-Fructofuranosidase Activity through Kluyveromyces marxianus in Bioreactor Using a Lab-Made Sequential Analysis System
Authors: Barbosa-Hernández Edwin J. , Pliego-Sandoval Jorge E. , Gschaedler-Mathis Anne , Arrizon-Gaviño Javier , Arana-Sánchez Alejandro , Femat Ricardo , Herrera-López Enrique J.
Published: November 2023

The yeast Kluyveromyces marxianus has shown the potential to produce β-fructofuranosidases, which are enzymes capable of hydrolyzing β-fructofuranosides links of fructans to obtain fructooligosaccharides. The thriving market for fructose syrup and the quality standards imposed by food and pharmaceutical industries have generated an increased search for improved, monitored, and controlled production processes. Monitoring β-fructofuranosidase activity in a bioprocess requires the use of adequate sensors and the processing of information using efficient software algorithms; nevertheless, currently, such a sensor does not exist for this purpose. In this contribution, a sequential injection analysis system (SIA) developed in our laboratory was adapted to monitor at-line β-fructofuranosidase activity produced by the yeast K. marxianus. Samples were taken out automatically from the bioreactor and analyzed using 3,5-dinitrosalicylic (DNS). An algorithm was designed to operate the overall components of the lab-made SIA system. The enzymatic activity error obtained with the automatic SIA compared to the off-line laboratory determinations varied from 0.07% at high enzyme concentrations to 20.39% at low β-fructofuranosidase activity. Further development is required to improve the performance of the lab-made SIA system; nevertheless, such a device must be considered as a potential method for monitoring β-fructofuranosidase activity in real time.