bluuebunny/crossref_metadata_2025 huggingface dataset:
Proteomic Analysis of Maize Cultivars Tolerant to Drought Stress
Authors: Pinto Mariana Cabral , de Oliveira Odair Honorato , de Oliveira Maria Beatriz Araújo , da Silva Cleiton Ribeiro , de Figueiredo Marcela Portela Santos , de Luna Rômulo Gil , Souza Anielson dos Santos , Souto Lauter Silva , de Oliveira Godim Ancélio Ricardo , de Almeida Lacerda Rodolfo Rodrigo , Porto Andréa Chaves Fiuza , Gomes-Silva Frank , Vasconcelos Josimar Mendes de , Moreira Guilherme Rocha , Costa Maria Lindomárcia Leonardo da , Pereira de Figueiredo Mércia Regina , Silva Fabiana Aparecida Cavalcante , Alvino Francisco Cássio Gomes , Silva Amaro Epifânio Pereira , Alves Leonardo de Sousa , Neder Diogo Gonçalves , Araújo Bianca Galúcio Pereira , Freitas Lucas Carvalho de , Calsa Junior Tercilio , Dutra Filho João de Andrade
Published: August 2023

Maize is a crop of significant economic importance. In the northeast region of Brazil, it serves as the foundation of family support for the majority of farmers. However, achieving high levels of productivity requires an adequate water supply throughout its growth cycle. The northeast semi-arid region experiences low rainfall and high potential evapotranspiration, directly affecting maize development and leading to severe declines in productivity. In this study, genetic selection and proteomic analysis are proposed as a strategy to identify the tolerance of maize cultivars against water stress. The experiments were conducted under two water regimes using randomized block designs with three replicates. Development and productivity traits were evaluated, and genetic parameters were estimated using mixed linear models. Selection for water stress tolerance was based on the harmonic mean of the relative performance of genotypic values. Total protein extraction from maize leaves followed the protocol established by the phenol method, and peptides were analyzed through mass spectrometry. The AG8677P cultivar demonstrated remarkable productivity under drought stress conditions, and proteins related to various fundamentally important biological processes for the tolerance mechanism were identified. The combination of genetic selection with proteomic analysis proves to be an efficient strategy, even in the face of limited resources and a small number of treatments.
Surgery Scheduling and Perioperative Care: Smoothing and Visualizing Elective Surgery and Recovery Patient Flow
Authors: Lyons John S. F. , Begen Mehmet A. , Bell Peter C.
Published: August 2023

This paper addresses the practical problem of scheduling operating room (OR) elective surgeries to minimize the likelihood of surgical delays caused by the unavailability of capacity for patient recovery in a central post-anesthesia care unit (PACU). We segregate patients according to their patterns of flow through a multi-stage perioperative system and use characteristics of surgery type and surgeon booking times to predict time intervals for patient procedures and subsequent recoveries. Working with a hospital in which 50+ procedures are performed in 15+ ORs most weekdays, we develop a constraint programming (CP) model that takes the hospital’s elective surgery pre-schedule as input and produces a recommended alternate schedule designed to minimize the expected peak number of patients in the PACU over the course of the day. Our model was developed from the hospital’s data and evaluated through its application to daily schedules during a testing period. Schedules generated by our model indicated the potential to reduce the peak PACU load substantially, 20-30% during most days in our study period, or alternatively reduce average patient flow time by up to 15% given the same PACU peak load. We also developed tools for schedule visualization that can be used to aid management both before and after surgery day; plan PACU resources; propose critical schedule changes; identify the timing, location, and root causes of delay; and to discern the differences in surgical specialty case mixes and their potential impacts on the system. This work is especially timely given high surgical wait times in Ontario which even got worse due to the COVID-19 pandemic.
Oak Acorn Poisoning in Cattle during Autumn 2022: A Case Series and Review of the Current Knowledge
Authors: Eppe Justine , Bayrou Calixte , Casalta Hélène , Cassart Dominique , Gille Linde , Stipulanti Margot , Versyp Jérôme , Sartelet Arnaud
Published: August 2023

Oak poisoning is a known intoxication in grazing animals, but is slightly described in the literature. This case report describes 7 cattle from 3 different farms admitted to the clinic for ruminants of the University of Liège for suspected acorn poisoning in the autumn of 2022. The clinical signs were, anorexia, apathy with polyuria with low density. Further investigations led to the diagnosis of renal failure (blood urea 162 ± 88 mg/dL; blood creatinine 12 ± 4 mg/L). Supportive treatment, based on infusions (NaCl 0.9%) and electrolyte rebalancing, was administered and renal values were assessed every 24–48 h. Of these animals, 5/7 were euthanized. At necropsy, digestive erosions and ulcerations, oedema and renal hemorrhages, between the pyloric/caliceal cavity and the medulla were observed. Histopathological examination revealed necrosis of the renal tubules. The renal values of the two remaining animals were reduced, their general condition improved, and they were discharged. Acorn poisoning is a serious disease with no specific antidote or characteristic symptoms. Animals are identified as sick too late, when renal failure is already established. Farmers should be made more aware in order to prevent exposure, especially in years when acorns are abundant. Furthermore, there is no antidote for this intoxication.
Antimicrobial Resistance of Erysipelothrix rhusiopathiae Strains Isolated from Geese to Antimicrobials Widely Used in Veterinary Medicine
Authors: Bobrek Kamila , Gaweł Andrzej
Published: August 2023

The aim of this study was to determine the antibiotic resistance of E. rhusiopathiae when isolated from clinical outbreaks of erysipelas in geese to antimicrobials commonly used in poultry production. All isolates were susceptible to amoxicillin alone or with clavulanic acid, with MIC values ranging from 0.016 to 0.125 μg/mL. Ninety-six percent of isolates were fully sensitive to penicillin G (MIC 0.125–0.5 μg/mL). All isolates were fully or moderately sensitive to erythromycin (MIC 0.125–0.5 μg/mL). Most E. rhusiopathiae isolates proved resistant to fluoroquinolones (76.6% of isolates were resistant to enrofloxacin, with MIC values ranging from 0.064 to 32 μg/mL, and 68% were resistant to norfloxacin, with MIC values ranging from 0.094 to 96 μg/mL), and tetracyclines (61.7% of isolates were resistant to doxycycline, with MIC values ranging from 0.25 to 64 μg/mL, and 63.8% were resistant to tetracycline, with MIC values ranging from 0.38 to 256 μg/mL). Point mutations in the gyrA gene (responsible for fluoroquinolone resistance) and the presence of the tetM gene (responsible for tetracycline resistance) were noted in most of the resistant isolates. Multidrug resistance, defined as resistance to at least one substance in three or more antimicrobial classes, was not observed.
Hospital Pharmacists’ Viewpoint on Quality Use of Antibiotics and Resistance: A Qualitative Exploration from a Tertiary Care Hospital of Quetta City, Pakistan
Authors: Farooqui Maryam , Iqbal Zaffar , Sadiq Abdul , Raziq Abdul , Alshammari Mohammed Salem , Iqbal Qaiser , Haider Sajjad , Saleem Fahad
Published: August 2023

Suboptimal antibiotics use and the development of antibiotic resistance is a universal calamity. The theoretical model of therapeutic efficacy correlates quality use of antibiotics with healthcare practitioners’ understanding of antibiotic use and resistance. Keeping this phenomenon in mind, we aimed to evaluate hospital pharmacists’ understanding of antibiotic use and resistance at a public healthcare institute in Quetta city, Pakistan. This was a qualitative study that employed a semi-structured interview guide for data extraction. The phenomenology-based approach commissioned in-depth, face-to-face interviews with hospital pharmacists stationed at the surgical unit of Sandeman Provincial Hospital, Quetta. The interviews were audio taped followed by transcribed verbatim and were then analyzed for thematic contents by the standard content analysis framework. Although the saturation was reached after the 10th interview, we conducted two additional interviews for definite validation. Content analysis revealed five major themes: (1) Defining antibiotics, quality use of antibiotics and resistance, (2) antibiotic use: awareness and concern, (3) antimicrobial resistance: awareness and concern, (4) responding to antibiotic use and resistance, and (5) barriers to quality use of antibiotics and prevention of antibiotic resistance. The knowledge of quality use of antibiotics and resistance was promising, and the respondents were eager to address the drastic situation. The respondents were aware of the critical situation and provided valuable insights that can offer valued input while promoting the quality use of antibiotics in a developing country. The current study managed to identify an adequate understanding of antibiotic use and resistance among hospital pharmacists. Additionally, prospective concerns and possible predictors of antibiotic resistance were also highlighted. The current findings must be disseminated to the policymakers and prescribers to take prompt restorative actions to address antibiotic use and the development of antibiotic resistance in a developing country like Pakistan.
Individualised Exercise Training Enhances Antioxidant Buffering Capacity in Idiopathic Pulmonary Fibrosis
Authors: Wallis Tim J. M. , Minnion Magdalena , Freeman Anna , Bates Andrew , Otto James M. , Wootton Stephen A. , Fletcher Sophie V. , Grocott Michael P. W. , Feelisch Martin , Jones Mark G. , Jack Sandy
Published: August 2023

Exercise training is recommended for patients with idiopathic pulmonary fibrosis (IPF); however, the mechanism(s) underlying its physiological benefits remain unclear. We investigated the effects of an individualised aerobic interval training programme on exercise capacity and redox status in IPF patients. IPF patients were recruited prospectively to an 8-week, twice-weekly cardiopulmonary exercise test (CPET)-derived structured responsive exercise training programme (SRETP). Systemic redox status was assessed pre- and post-CPET at baseline and following SRETP completion. An age- and sex-matched non-IPF control cohort was recruited for baseline comparison only. At baseline, IPF patients (n = 15) had evidence of increased oxidative stress compared with the controls as judged by; the plasma reduced/oxidised glutathione ratio (median, control 1856 vs. IPF 736 p = 0.046). Eleven IPF patients completed the SRETP (median adherence 88%). Following SRETP completion, there was a significant improvement in exercise capacity assessed via the constant work-rate endurance time (+82%, p = 0.003). This was accompanied by an improvement in post-exercise redox status (in favour of antioxidants) assessed via serum total free thiols (median increase, +0.26 μmol/g protein p = 0.005) and total glutathione concentration (+0.73 μM p = 0.03), as well as a decrease in post-exercise lipid peroxidation products (−1.20 μM p = 0.02). Following SRETP completion, post-exercise circulating nitrite concentrations were significantly lower compared with baseline (−0.39 μM p = 0.04), suggestive of exercise-induced nitrite utilisation. The SRETP increased both endurance time and systemic antioxidant capacity in IPF patients. The observed reduction in nitrite concentrations provides a mechanistic rationale to investigate nitrite/nitrate supplementation in IPF patients.
Near-Optimal Active Learning for Multilingual Grapheme-to-Phoneme Conversion
Authors: Cao Dezhi , Zhao Yue , Wu Licheng
Published: August 2023

The construction of pronunciation dictionaries relies on high-quality and extensive training data in data-driven way. However, the manual annotation of corpus for this purpose is both costly and time consuming, especially for low-resource languages that lack sufficient data and resources. A multilingual pronunciation dictionary includes some common phonemes or phonetic units, which means that these phonemes or units have similarities in the pronunciation of different languages and can be used in the construction process of pronunciation dictionaries for low-resource languages. By using a multilingual pronunciation dictionary, knowledge can be shared among different languages, thus improving the quality and accuracy of pronunciation dictionaries for low-resource languages. In this paper, we propose using shared articulatory features among multiple languages to construct a universal phoneme set, which is then used to label words for multiple languages. To achieve this, we first developed a grapheme−phoneme (G2P) model based on an encoder−decoder deep neural network. We then adopted a near-optimal active learning method in the process of building the pronunciation dictionary to select informative samples from a large, unlabeled corpus and had them labeled by experts. Our experiments demonstrate that this method selected about 1/5 of the unlabeled data and achieved an even higher conversion accuracy than the results of the large data training method. By selectively labeling samples with a high uncertainty in the model, while avoiding labeling samples that were accurately predicted by the current model, our method greatly enhances the efficiency of pronunciation dictionary construction.
M2GF: Multi-Scale and Multi-Directional Gabor Filters for Image Edge Detection
Authors: Li Yunhong , Bi Yuandong , Zhang Weichuan , Ren Jie , Chen Jinni
Published: August 2023

An image edge detection algorithm using multi-directional and multi-scale Gabor filters is proposed in this paper. The main merit of this method is that high edge detection accuracy can be obtained while maintaining noise robustness. The approach proposed in this paper consists of three procedures: firstly, the transformation to the CIE L*a*b* color space, which has a wide shading area and uniform distribution; secondly, under different scales, the edge feature information of the image is extracted from several different directions by Gabor filters, and a new edge strength map is obtained by feature fusion; thirdly, the new fused edge strength map is enhanced with local features, and a noise-resistant image edge detector is obtained under a novel hysteresis threshold calculation. The experiments illustrate that, compared to the methods involved, the designed edge detector outperforms by about 2% to 4%, and also shows competitive performance regarding the ability to handle noise.
Photocatalytic Activity of TiNbC-Modified TiO2 during Hydrogen Evolution and CO2 Reduction
Authors: Syuy Alexander V. , Shtarev Dmitry S. , Kozlova Ekaterina A. , Kurenkova Anna Yu. , Zhurenok Angelina V. , Shtareva Anna V. , Gurin Mikhail S. , Tselikov Gleb I. , Tikhonowski Gleb V. , Arsenin Aleksey , Volkov Valentyn
Published: August 2023

Photocatalytic CO2 reduction and the production of hydrogen are urgent tasks of green energy. One of the most studied semiconductor photocatalysts for this purpose is titanium dioxide. However, it has a number of fundamental limitations that do not allow its application for such tasks on an industrial scale. Another class of promising materials, which is being investigated very actively, are two-dimensional materials based on MXenes. In this work, we present the first results on photocatalytic hydrogen evolution and CO2 reduction using TiNbC/TiO2 heterostructures with TiNbC contents of 1, 5, and 10%. The approach to the creation of heterostructures proposed in this work may become a significant breakthrough in the search for new highly efficient systems for carbon dioxide reduction and hydrogen production.
Examining the Influence of Self-Esteem and Digital Literacy on Professional Competence Factors in Dental Education: A Cross-Sectional Study
Authors: Ceylan Gulsum , Eken Melike Ozlem , Yuruk Selen , Emir Faruk
Published: August 2023

This study aims to investigate the effects of digital literacy and self-esteem on dental students’ perceptions of professional competence and to provide recommendations for improving educational programs in dental schools. A mixed-methods, descriptive, and relational scanning design was employed, using a questionnaire comprising demographic information, the Rosenberg Self-Esteem Scale (RSES), the Digital Literacy Scale (DLS), and the Professional Competence Scale (PCS). The sample included 427 dental students in Istanbul, Turkey. Statistical analyses included Cronbach Alpha, Confirmatory Factor Analysis, Mann–Whitney U, Kruskal–Wallis, Spearman’s rho correlation, and the Generalized Linear Model (Logit Model). The majority of participants were female (65.6%), aged 21 or older (85.2%), and in their 4th grade of study (35.2%). There were no significant differences in PCS scores concerning gender, age, grade, type of residence, and residence location (p > 0.05). However, PCS scores were significantly higher among those who listed dentistry among their top five preferences, expressed high satisfaction with education, and demonstrated high professional interest (p < 0.05). A significant, positive correlation was observed between PCS and RSES (r = 0.398; p < 0.01), DLS (r = 0.404; p < 0.01), preference (r = 0.120; p < 0.05), education satisfaction (r = 0.298; p < 0.01), and occupational interest (r = 0.502; p < 0.05). Furthermore, the Logit Model analysis revealed that RSES (B = 0.290; p < 0.01), DLS (B = 0.258; p < 0.01), education satisfaction (B = 0.806; p < 0.05), and occupational interest (B = 3.825; p < 0.01) significantly influenced PCS. The findings underscore self-esteem and digital literacy’s integral role in shaping dental students’ perceptions of their professional abilities. Digital literacy is a substantial pillar supporting students’ professional competency. Coupled with a genuine interest in the field and bolstered self-confidence, digital literacy proves instrumental in enhancing students’ academic success in dentistry. By emphasizing and expanding upon digital literacy content within the curriculum, universities can further propel advancements in the dental domain. As such, it is pivotal for dental institutions to weave strategies into their educational fabric to elevate students’ self-esteem and digital proficiency.
Design of Liquid–Air Hybrid Cooling Garment and Its Effect on Local Thermal Comfort
Authors: Wang Wanwan , Zhao Mengmeng
Published: August 2023

Personal cooling garments were reported effective in improving thermal comfort in hot environments. In this study, three liquid–air hybrid cooling garments and one control garment were designed and made: aluminum-tube fan cooling (AAL), silicone-tube fan cooling (SAL), silicone-tube fan cooling with inner yarn fabric (YAL), and a control garment (CON) without the cooling sources. Subject trials were performed by eight female subjects in a climate chamber to simulate a summer indoor working environment at 32 °C and 50% relative humidity. The results showed that the liquid–air hybrid cooling garment provided effective convective and conductive heat dissipation compared with the no-cooling (CON) stat, chest, belly, shoulder, back, hand, thigh, and calf. The horizontal e, resulting in a decrease in local body skin temperature. Compared with the CON, the liquid–air cooling garment resulted in a maximum reduction of 1 °C for the mean torso skin temperature and 1.5 °C for the localized shoulder skin temperature. The AAL had a better cooling effect on the torso skin temperature compared with the SAL, and the cooling of the AAL was 0.5 °C lower than that of the SAL for the shoulder skin temperature. The presented liquid–air hybrid cooling garments were effective in cooling the body and improving thermal comfort. They were portable, accessible, and sustainable in hot indoor environments compared with air conditioners. Therefore, they could save energy.
Ac-Susceptibility Studies of the Energy Barrier to Magnetization Reversal in Frozen Magnetic Nanofluids of Different Concentrations
Authors: Botez Cristian E. , Price Alex D.
Published: August 2023

We used ac-susceptibility to measure the blocking temperature, TB, and energy barrier to the magnetization reversal, EB, of nanomagnetic fluids of different concentrations, c. We collected data on five samples synthesized by dispersing Fe3O4 nanoparticles of average diameter ⟨D⟩ = 8 nm in different volumes of carrier fluid (hexane). We found that TB increases with the increase in c, a behavior predicted by the Dormann–Bessais–Fiorani (DBF) theory. In addition, our observed TB vs. c dependence is excellently described by a power law TB = A∙cγ, with A = 64 K and γ = 0.056. Our data also show that a Néel–Brown activation law τT=τ0exp⁡EBkBT describes the superspin dynamics in the most diluted sample, whereas an additional energy barrier term, Ead, is needed at higher concentrations, according to the DBF model: τT=τrexp⁡EB+EadkBT.  We found EB/kB = 366 K and additional energy barriers Ead/kB that increase linearly with the common logarithm of the volume concentration, from 138 K at c = 8.3 × 10−4% to 745 K at c = 4 × 10−2%. These results add to our understanding of the contributions by different factors to the superspin dynamics. In addition, the quantitative relations that we established between the TB, Ead, and c support the current efforts towards the rational design of functional nanomaterials.
LPS-Net: Lightweight Parallel Strategy Network for Underwater Image Enhancement
Authors: Jiang Jingxia , Huang Peiyun , Tong Lihan , Yin Junjie , Chen Erkang
Published: August 2023

Underwater images are frequently subject to color distortion and loss of details. However, previous enhancement methods did not tackle these mixed degradations by dividing them into sub-problems that could be effectively addressed. Moreover, the parameters and computations required for these methods are usually costly for underwater equipment, which has limited power supply, processing capabilities, and memory capacity. To address these challenges, this work proposes a Lightweight Parallel Strategy Network (LPS-Net). Firstly, a Dual-Attention Enhancement Block and a Mirror Large Receptiveness Block are introduced to, respectively, enhance the color and restore details in degraded images. Secondly, we employed these blocks on parallel branches at each stage of LPS-Net, with the goal of achieving effective image color and detail rendering simultaneously. Thirdly, a Gated Fusion Unit is proposed to merge features from different branches at each stage. Finally, the network utilizes four stages of parallel enhancement, achieving a balanced trade-off between performance and parameters. Extensive experiments demonstrated that LPS-Net achieves optimal color enhancement and superior detail restoration in terms of visual quality. Furthermore, it attains state-of-the-art underwater image enhancement performance on the evaluation metrics, while using only 80.12 k parameters.
Dynamic Analysis and Safety Assessment of Ships and Cables during Salvage Operations
Authors: Zou Han , Chen Shengtao , Sun Gang , Gong Yongjun
Published: August 2023

The International Maritime Organization (IMO) emphasizes that shipwreck accidents frequently occur at sea and advocates for the safe recovery of shipwrecks. This paper examines the case of the Korean “Sewol” ferry salvage, where two lifting barges were symmetrically utilized to retrieve a substantial shipwreck. The dynamic analysis of the salvage operation is based on the computational fluid dynamics (CFD) approach. The main investigation covers two fundamental physical parameters: the motion response of the lifting barges and shipwreck and the tension response of the lifting cables. Using the parameters of the maximum absolute value (MA), root mean square (RMS), and coefficient of variation (CV), a unified criterion is established to quantitatively evaluate the safety of the salvage operation under different working conditions. The study demonstrates that by carefully considering the enhancement of safety and stability for the three vessels involved in the salvage process and by optimizing the safety performance of the lifting cables, suitable operating windows are determined at wave intervals of (115°, 155°) and (205°, 245°). Under most working conditions, curves illustrating the maximum tensions of lifting cables No. 1–15 and No. 16–30 show a distribution with a “middle part drooping” shape. The placement of connecting cables on the water’s surface at 1.1–1.2 times the salvage spacing between the two lifting barges or the arrangement of inclined lifting cables underwater proves advantageous in constraining the motion response of the three vessels. Reinforcing the lifting cables at the bow and stern ends is recommended. This study presents a methodology for salvaging a shipwreck using two lifting barges, which can be used as a reference for designing related salvage approaches.
Maneuver Decision-Making through Automatic Curriculum Reinforcement Learning without Handcrafted Reward Functions
Authors: Wei Yujie , Zhang Hongpeng , Wang Yuan , Huang Changqiang
Published: August 2023

Maneuver decision-making is essential for autonomous air combat. However, previous methods usually make decisions to aim at the target instead of hitting the target and use discrete action spaces instead of continuous action spaces. While these simplifications make maneuver decision-making easier, they also make maneuver decision-making more unrealistic. Meanwhile, previous studies usually rely on handcrafted reward functions, which are troublesome to design. Therefore, to solve these problems, we propose an automatic curriculum reinforcement learning method that enables agents to maneuver effectively in air combat from scratch. On the basis of curriculum reinforcement learning, maneuver decision-making is divided into a series of sub-tasks from easy to difficult. Thus, agents can gradually learn how to complete a series of sub-tasks, from easy to difficult without handcrafted reward functions. The ablation studies show that automatic curriculum learning is essential for reinforcement learning; namely, agents cannot make effective decisions without curriculum learning. Simulations show that, after training, agents are able to make effective decisions given different states, including tracking, attacking, and escaping, which are both rational and interpretable.
Synthesis and Biological Activity of Novel Complexes with Anthranilic Acid and Its Analogues
Authors: Marinova Petja , Hristov Mariyan
Published: August 2023

Anthranilic acid analogues and their derivatives hold significant therapeutic potential for crafting designed compounds aimed at regulating cancer-causing pathways and addressing metabolic challenges linked to diabetes, antiviral agents [...]
Development of the Gravel Pressure and Voice Synchronous Observation System and Application in Bedload Transport Measurement
Authors: Tian Mi , Yang Shengfa , Zhang Peng , Guo Qi
Published: August 2023

Bedload sediment transport is critical in the natural river environmental and ecological system. It is quite challenging to measure the bedload sediment transport rate in rivers with any degree of accuracy. In this study, the authors developed the Gravel Pressure and Voice Synchronous observation system (GPVS) to estimate the bedload sediment transport rate in rivers. The core of the GPVS includes an underwater high-fidelity audio recorder and pressure sensor. The audio recorder is intended to monitor the low bedload sediment transport rate, whereas the pressure sensor is utilized to detect relatively substantial bedload sediment transport. The GPVS is tested by running flume experiments with natural gravel to evaluate the system’s reliability and feasibility. Results reveal that the GPVS has a very high sensitivity for detecting bedload transport. When the bedload sediment transport rate is relatively low, the audio recorder can measure it quantitatively, showing that the system is not impacted by ambient noise.
Evaluating the Impact of Seismic Activity on the Slope Stability of the Western Coast of Lefkada Island Using Remote Sensing Techniques, Geographical Information Systems, and Field Data
Authors: Nikolakopoulos Konstantinos G. , Koukouvelas Ioannis K. , Kyriou Aggeliki , Apostolopoulos Dionysios , Pappas George
Published: August 2023

The current research aims to examine the long-term evolution of the western cliffs of Lefkada Island following the occurrence of the last two strong earthquakes, on 14 August 2003 and 17 November 2015, respectively. Medium resolution satellite data (Landsat) and very high-resolution data (Ikonos, Pleiades, and airphotos) were processed in Google Earth Engine and Erdas imagine software, respectively. The study area covers a 20 km-long region of the western cliffs of Lefkada Island, extending from Egremni beach to the South to Komilio beach to the North. Relief, vegetation, and inclination changes were detected in the ArcGis environment. The results were associated with in situ data provided through the installation of a sediment trap. The analysis of the results proved that seismicity is the main factor that formed the western coastline of Lefkada Island, affecting the integrity of the cliffs. Specifically, large earthquakes cause immediate vegetation and topographic (inclination changes, mass movements) modifications in the western cliffs of the island. Meanwhile, small earthquakes (magnitudes < 4.1) contribute to the cliff’s evolution during the inter-seismic era. The intensity of these aforementioned changes was closely related to the seismic activity that occurred in the vicinity of the study area. In addition, it was found that precipitation and wind do not exert a similar influence on the cliff’s evolution.
Clinical and Kinematic Outcomes Based on Bone Graft Utilization for Salvage First Metatarsophalangeal Arthrodesis: A Systematic Review
Authors: Talaski Grayson M. , Baumann Anthony N. , Anastasio Albert T. , Walley Kempland C. , de Cesar Netto Cesar
Published: August 2023

Motion-preserving options for the treatment of first metatarsophalangeal (MTP) osteoarthritis are appealing, but the conversion to arthrodesis in failed cases comes with additional challenges. Loss of first ray length may not only lower arthrodesis success rates but can also cause aberrancies in the biomechanics of the foot and ankle. Selection of the proper graft for the restoration of length is crucial in order to minimize the chance of post-operative complications. The primary objective of this systematic review was to determine the optimal graft type for MTP salvage arthrodesis in terms of clinical outcomes, kinematic outcomes, and bony integration to improve patient care. A systematic review was performed using PubMed, SPORTDiscus, Cumulated Index to Nursing and Allied Health Literature (CINAHL), MEDLINE, and Web of Science from database inception until 20 June 2023. Inclusion criteria were articles that examined clinical outcomes, examined different types of bone grafts, discussed impact of bone graft on lengthening, and articles related to first MTP arthrodesis salvage procedures. Data extraction relating to clinical metrics and kinematic metrics was performed and analyzed. Subgroup analysis was performed to compare graft types, such as (1) foot and ankle autograft, (2) non-foot and ankle autograft, and (3) allograft. A total of ten articles met eligibility criteria from 180 articles initially retrieved. Included patients (n = 164) had a frequency-weighted mean age of 55.2 ± 4.6 years with a frequency-weighted mean time from primary to salvage procedure of 36.6 ± 21.9 months and a frequency-weighted mean follow-up time of 42.7 ± 17.4 months. The non-foot and ankle autograft group had a mean length restoration of 4.4 ± 0.1 mm (n = 33, 73.3% reported) whereas the allograft group had a mean length restoration of 7.6 ± 3.5 mm (n = 49, 100% reported). The foot and ankle autograft group (n = 12 procedures) had an overall complication rate of 25.0%, the non-foot and ankle autograft group (n = 45 procedures) had an overall complication rate of 53.3%, and the allograft group (n = 49 procedures) had an overall complication rate of 10.2%. Preoperative AOFAS scores were lower but improved postoperatively, with the allograft group showing the highest postoperative scores, shorter time to union, and varying graft lengths among different autograft subgroups. The allograft group for salvage MTP arthrodesis has promise, as this group had the greatest mean length restoration and the lowest complication rate. This is the first systematic review examining different bone graft utilization for salvage MTP arthrodesis. More high-quality research is needed before solid recommendations can be made on this topic.
Vector Decomposition of Elastic Seismic Wavefields Using Self-Attention Deep Convolutional Generative Adversarial Networks
Authors: Liu Wei , Cao Junxing , You Jiachun , Wang Haibo
Published: August 2023

Vector decomposition of P- and S-wave modes from elastic seismic wavefields is a key step in elastic reverse-time migration (ERTM) to effectively improve the multi-wave imaging accuracy. Most previously developed methods based on the apparent velocities or the polarization characteristics of different wave modes are unable to accurately achieve the vector decomposition of P- and S-wave modes. To effectively overcome the shortcomings of conventional methods, we develop a vector decomposition method of P- and S-wave modes using self-attention deep convolutional generative adversarial networks (SADCGANs) to effectively separate the horizontal and vertical components of P- and S-wave modes from elastic seismic wavefields and accurately preserve their amplitude and phase characteristics for isotropic elastic media. For an elastic model, we use many time slices for a given source position to train the neural network, and use other time slices not in this training dataset to test the neural network. Numerical examples of different models demonstrate the effectiveness and feasibility of our developed method and indicate that it provides an effective intelligent data-driven vector decomposition method of P- and S-wave modes.
Performance Analysis of Multiple Steel Corrugated Pipe Arch Culvert under Construction and Periodic Vehicle Load
Authors: Bao Xiaohua , Wu Xianlong , Shen Jun , Wu Shidong , Chen Xiangsheng , Cui Hongzhi
Published: August 2023

The arrangement of multiple culverts has gradually increased in road engineering. However, the arrangement will face a series of risks in both the construction and operation stages. A numerical model was established to analyze the construction and operation safety of multiple steel corrugated pipe arch culverts by using a fully fluid–solid coupling two-dimensional (2D) model of a highway project. The sensitivity of factors affecting the settlement of the composite foundation such as modulus and depth of ground reinforcement was discussed. Based on the results of the 2D model, a fully fluid–solid coupling three-dimensional (3D) model was established to study the influence of dynamic cyclic vehicle load on the mechanical properties of multiple steel corrugated pipe arch culverts. The ground deformation, soil stress and pore pressure, structure stress, and deformation were analyzed. The results show that the maximum settlement of the soil in the arch culvert area is at the junction of the two different arch culverts after construction. The maximum vertical deformation of the structure appears at the vault, and the arch waist is prone to stress concentration. Under cyclic vehicle dynamic load, the ground deformation, structural stress, and arch culvert subgrade deformation showed a rapid growth stage, and then tended to be stable. The weak points in the structure during the construction and operation stages were revealed, which can provide a useful reference for the design and construction of multiple steel corrugated pipe arch culverts.
The Vibration Isolation Design of a Re-Entrant Negative Poisson’s Ratio Metamaterial
Authors: Gao Xu , Wei Jiyuan , Huo Jiajing , Wan Zhishuai , Li Ying
Published: August 2023

An improved re-entrant negative Poisson’s ratio metamaterial based on a combination of 3D printing and machining is proposed. The improved metamaterial exhibits a superior load-carrying and vibration isolation capacity compared to its traditional counterpart. The bandgap of the proposed metamaterial can be easily tailored through various assemblies. Additionally, particle damping is introduced to enhance the diversity of bandgap design, improve structural damping performance, and achieve better vibration isolation at low and medium frequencies. An experiment and simulation were conducted to assess the static and vibration performances of the metamaterial, and consistent results were obtained. The results indicate a 300% increase in the bearing capacity of the novel structure compared to traditional structural metamaterials. Furthermore, by increasing the density of metal assemblies, a vibration-suppressing bandgap with a lower frequency and wider bandwidth can be achieved. The introduction of particle damping significantly enhanced the vibration suppression capability of the metamaterial in the middle- and low-frequency range, effectively suppressing resonance peaks. This paper establishes a vibration design method for re-entrant metamaterials, which is experimentally validated and provides a foundation for the vibration suppression design of metamaterials.
Marketing Insights from Reviews Using Topic Modeling with BERTopic and Deep Clustering Network
Authors: An Yusung , Oh Hayoung , Lee Joosik
Published: August 2023

The feedback shared by consumers on e-commerce platforms holds immense value in marketing, as it offers insights into their opinions and preferences, which are readily accessible. However, analyzing a large volume of reviews manually is impractical. Therefore, automating the extraction of essential insights from these data can provide more comprehensive and efficient information. This research focuses on leveraging clustering algorithms to automate the extraction of consumer intentions, related products, and the pros and cons of products from review data. To achieve this, a review dataset was created by performing web crawling on the Naver Shopping platform. The findings are expected to contribute to a more precise understanding of consumer sentiments, enabling marketers to make informed decisions across a wide range of products and services.
HIPPP: Health Information Portal for Patients and Public
Authors: Brandon Colm , Doherty Adam J. , Kelly Dervla , Leddin Desmond , Margaria Tiziana
Published: August 2023

Cancer misinformation is becoming an increasingly complex issue. When a person or a loved one receives a diagnosis of possible cancer, that person, family and friends will try to better inform themselves in this area of healthcare. Like most people, they will turn to their clinician for guidance and the internet to better verse themselves on the topic. But can they trust the information provided online? Are there ways to provide a quick evaluation of such information in order to prevent low-quality information and potentially dangerous consequences of trusting it? In the context of the UL Cancer Research Network (ULCan), this interdisciplinary project aims to develop the Health Information Portal for Patients and Public (HIPPP), a web-based application co-designed with healthcare domain experts that helps to improve people navigate the health information space online. HIPPP will be used by patients and the general public to evaluate user-provided web-based health information (WBHI) sources with respect to the QUEST framework and return a quality score for the information sources. As a web application, HIPPP is developed with modern extreme model-driven development (XMDD) technologies in order to make it easily adaptable and evolvable. To facilitate the automated evaluation of WBHI, HIPPP embeds an artificial intelligence (AI) pipeline developed following model-driven engineering principles. Through co-design with health domain experts and following model-driven engineering principles, we have extended the Domain Integrated Modelling Environment (DIME) to include a graphical domain-specific language (GDSL) for developing websites for evaluating WBHI. This GDSL allows for greater participation from stakeholders in the development process of both the user-facing website and the AI-driven evaluation pipeline through encoding concepts familiar to those stakeholders within the modelling language. The time efficiency study conducted as part of this research found that the HIPPP evaluation pipeline evaluates a sample of WBHI with respect to the QUEST framework up to 98.79% faster when compared to the time taken by a human expert evaluator.
Biometric-Based Human Identification Using Ensemble-Based Technique and ECG Signals
Authors: Aleidan Anfal Ahmed , Abbas Qaisar , Daadaa Yassine , Qureshi Imran , Perumal Ganeshkumar , Ibrahim Mostafa E. A. , Ahmed Alaa E. S.
Published: August 2023

User authentication has become necessary in different life domains. Traditional authentication methods like personal information numbers (PINs), password ID cards, and tokens are vulnerable to attacks. For secure authentication, methods like biometrics have been developed in the past. Biometric information is hard to lose, forget, duplicate, or share because it is a part of the human body. Many authentication methods focused on electrocardiogram (ECG) signals have achieved great success. In this paper, we have developed cardiac biometrics for human identification using a deep learning (DL) approach. Cardiac biometric systems rely on cardiac signals that are captured using the electrocardiogram (ECG), photoplethysmogram (PPG), and phonocardiogram (PCG). This study utilizes the ECG as a biometric modality because ECG signals are a superior choice for accurate, secure, and reliable biometric-based human identification systems, setting them apart from PPG and PCG approaches. To get better performance in terms of accuracy and computational time, we have developed an ensemble approach based on VGG16 pre-trained transfer learning (TL) and Long Short-Term Memory (LSTM) architectures to optimize features. To develop this authentication system, we have fine-tuned this ensemble network. In the first phase, we preprocessed the ECG biosignal to remove noise. In the second phase, we converted the 1-D ECG signals into a 2-D spectrogram image using a transformation phase. Next, the feature extraction step is performed on spectrogram images using the proposed ensemble DL technique, and finally, those features are identified by the boosting machine learning classifier to recognize humans. Several experiments were performed on the selected dataset, and on average, the proposed system achieved 98.7% accuracy, 98.01% precision, 97.1% recall, and 0.98 AUC. In this paper, we have compared the developed approach with state-of-the-art biometric authentication systems. The experimental results demonstrate that our proposed system outperformed the human recognition competition.
Safety Evaluation of Crossing Tunnel Engineering: A Case Study
Authors: Xianyao Dai , Guobin Wang , Ming Ye , Yongquan Zhang
Published: August 2023

With the growing demand for transportation, there has been a significant increase in road-related projects, leading to potential risks in the safety of existing structures. This paper presents a study on the influence of new tunnel construction on the stability of an adjacent existing tunnel and provides valuable insights for the safety technology evaluation of similar tunnel crossing projects. In order to evaluate the influence of tunnel excavation on adjacent tunnels, the excavation process of a new tunnel near the original tunnel is simulated using the finite element software Midas GTS. This analysis includes the evaluation of static and dynamic responses. The results indicate that the horizontal and vertical displacements caused by the excavation of the railway tunnel are minimal. Furthermore, during the blasting excavation of the railway tunnel, the vibration velocity experienced by the highway tunnel remains below the safe allowable limit. These findings demonstrate that in this project, the influence of blasting excavation for the railway tunnel on the highway tunnel is both safe and manageable.
A Systematic Review of the Biomechanical Studies on Shoulder Kinematics in Overhead Sporting Motions: Types of Analysis and Approaches
Authors: Ramasamy Yuvaraj , Usman Juliana , Razman Rizal , Wei Yeap Ming , Towler Harley , King Mark
Published: August 2023

The shoulder is a unique and complex joint in the human body with three bones and four joints, which makes it the most unstable joint in the body due to the amount of motion. To improve approaches toward understanding the performance of overhead throwing movements, this systematic review summarizes the type of analysis related to shoulder biomechanics involving overhead sporting motions. A search of seven databases identified 33 eligible studies, which were subsequently scored using the Modified Coleman Methodology Score scale. A total of nine articles from badminton, seven from baseball, five from volleyball, five from tennis, three from cricket, and one from softball were reviewed. All 33 studies evaluated shoulder kinematics and 12 of them also investigated the forces and torques (kinetics). The most common methods used were 3D motion analysis (76%), digital video cameras (15%), electromagnetic tracking system (6%), and finally 3% used IMU sensors. Overall, shoulder external rotation during the back swing, internal rotation, and elbow extension during the forward acceleration phase were the strongest predictors of high velocity overhead throwing movement. The findings provide some useful insights and guidance to researchers in their future contribution to the existing body of literature on shoulder overhead throwing movement biomechanics.
Spatial Oxygen Distribution of the Direct Metal Deposition Process for Different Powder Nozzles
Authors: Keller Dominik , Monney Axel , Schudeleit Timo , Wegener Konrad
Published: August 2023

Additive manufacturing processes are among the most innovative manufacturing processes of this century. Powder-based direct metal deposition (DMD) is one of these processes. In the DMD process, local shielding takes place via the powder nozzle. The process is therefore critical for oxidation, especially for materials with an affinity for oxidation such as titanium, aluminum and their alloys. In order to study the oxidation behavior in more detail, the present gas dynamics must be further understood. Wirth and Wegener have made a first approach with their gas flow simulation. In this study, a measurement method for spatial oxygen concentration determination is presented. It can be shown that the spatial oxygen concentration follows the nozzle geometry. Furthermore, the coaxial nozzle is superior to the three-jet nozzle with respect to a low oxygen concentration from a carrier gas to shielding gas volume flow ratio of equal to or greater than 0.4. Finally, it can be shown that the use of a shielding gas chamber eliminates the optimization of the gas flow settings.
Special Issue on New Frontiers in Wine Sciences
Authors: Antalick Guillaume , Butinar Lorena , Lemut Melita Sternad , Philipp Christian
Published: August 2023

Wine is a mark of cultural heritage, is an ancient and celebrated beverage, and is a global industry that is today valued at approximately USD 450 billion [...]