bluuebunny/crossref_metadata_2025_split huggingface dataset:
Effect of gold nanoparticles distribution radius on photothermal therapy efficacy
Authors: Kim Donghyuk , Paik Jeeyong , Kim Hyunjung 
Published: July 2023

AbstractLasers are used in various fields, however, in the medical field, they are mainly used for incision or chemotherapy. Photothermal therapy (PTT) is an anti-cancer treatment technique that uses lasers and the photothermal effect to increase the temperature of tumor tissue and induce its death. In this study, the therapeutic effect of PTT using gold nanoparticles as a photothermal converter was analyzed numerically for the occurrence of squamous cell carcinoma inside a skin section consisting four layers. Numerical modeling was implemented to calculate the temperature distribution inside the biological tissue while varying the distribution radius of gold nanoparticles in the tumor tissue, the number of injections, and the intensity of the irradiating laser. For the given situation, the optimal treatment effect was observed when the distribution radius ratio of the injected gold nanoparticles (GNPs) was 1, the number of injections was 7, and the intensity of the irradiated laser was 52 mW. Three apoptotic variables were used to quantitively evaluate the effect of PTT in each case and thus suggest the optimal treatment effect. However, although the temperature range at which apoptosis occurs is known, the maintenance of that temperature range is still under research and the temporal influence of apoptosis remains to be determined.
Social-networks use as adaptive or maladaptive strategy for coping with stress
Authors: Wegmann Elisa , Schiebener Johannes , Brand Matthias 
Published: July 2023

AbstractSocial networks are frequently used to distract, procrastinate, or cope with stress. We aimed to investigate how (problematic) social-networks use affect stress perception in interaction with different stress recovery conditions. A total of 104 participants were randomly assigned to one of four groups. Three groups underwent a stress induction with subsequent stress recovery via (1) using Facebook, (2) reading magazines, or (3) waiting. Another group (4) waited without stress induction. Stress perception was repeatedly assessed with the State-Trait-Anxiety-Inventory. Facebook use and reading magazines decreased acute stress indicating adaptive coping strategies. Stress-recovery conditions and symptom severity showed significant interactions. Facebook use was not effective for individuals with high symptom severity in contrast to non-digital strategies or for individuals with low symptom severity. The usage of social networks may be an adaptive strategy for coping with stress for some people, it is maladaptive for individuals having a problematic usage.
Pregnancy outcomes after vaginal probiotic supplementation before frozen embryo transfer: a randomized controlled study
Authors: Thanaboonyawat Isarin , Pothisan Sootthinan , Petyim Somsin , Laokirkkiat Pitak 
Published: July 2023

AbstractIn women receiving assisted reproductive treatment, intrauterine lactobacilli dominance has been associated with higher rates of pregnancy achievement. This randomized controlled trial conducted in the fertility clinic of the university hospital from 7 August 2019 to May 2021, aimed to compare the clinical outcome of embryo transfer in frozen-thaw cycles with Lactobacillus supplementation prior to embryo transfer and the standard treatment. A total of 340 infertile women underwent randomization. The biochemical and clinical pregnancy rates were comparable between the groups (39.9 and 34.2% in the study group vs. 41.8 and 31.7% in the control group); however, the miscarriage rate was significantly decreased in the study group (9.5 vs. 19.1%, respectively, p = 0.02), [OR = 0.44, 95% CI (0.23, 0.86)]. Among 49 women diagnosed with bacterial vaginosis, the live birth rate in the study group was higher than the control group (42.31 vs. 26.09%, p = 0.23), [OR = 2.08, 95% CI (0.62, 6.99)]. In the blastocyst transfer group (n = 206), the live birth rate was significantly higher in the study group than in the control group (35.71 vs. 22.22%, p = 0.03) [OR = 1.9, 95% CI (1.05, 3.59)]. Therefore, intravaginal lactobacilli supplementation before embryo transfer in the frozen-thaw cycle did not improve the biochemical and clinical pregnancy rate in the general population but significantly reduced the miscarriage rate.Trial Registration: TCTR20190429001 (29/04/2019) @ www.thaiclinicaltrials.org.
Novel method for predicting nonvisible symptoms using machine learning in cancer palliative care
Authors: Shimada Kazuki , Tsuneto Satoru 
Published: July 2023

AbstractEnd-of-life patients with cancer may find expressing their symptoms difficult if they can no longer communicate verbally because of deteriorating health. In this study, we assessed these symptoms using machine learning, which has excellent predictive capabilities and has recently been applied in healthcare. We performed a retrospective clinical survey involving 213 patients with cancer from August 2015 to August 2016. We divided the reported symptoms into two groups—visible and nonvisible symptoms. We used decision tree analysis, an analytical machine learning method that organizes and analyzes information in the form of a tree diagram to visually represent the information structure. Our machine learning model used patient background data and visible symptoms to predict nonvisible symptoms: pain, dyspnea, fatigue, drowsiness, anxiety, delirium, inadequate informed consent, and spiritual issues. The highest and/or lowest values for prediction accuracy, sensitivity, and specificity were 88.0%/55.5%, 84.9%/3.3%, and 96.7%/24.1%, respectively. This work will facilitate better assessment and management of symptoms in patients with cancer. This study was the first to predict nonvisible symptoms using decision tree analyses for patients with cancer receiving palliative care. Notably, applications based on our results may assess symptoms to the same extent as healthcare professionals.
The potential use of glycosyl-transferase inhibitors for targeted reduction of S. mutans biofilms in dental materials
Authors: Scaffa Polliana Mendes Candia , Kendall Alexander , Icimoto Marcelo Yudi , Fugolin Ana Paula Piovezan , Logan Matthew G. , DeVito-Moraes Andre G. , Lewis Steven H. , Zhang Hua , Wu Hui , Pfeifer Carmem S. 
Published: July 2023

AbstractStreptococcus mutans is the primary oral caries-forming bacteria, adept at producing “sticky” biofilms via the synthesis of insoluble extracellular polysaccharides (EPS), catalyzed by glucosyltransferases (GTFs). To circumvent the use of broad-spectrum antibiotics to combat these bacteria, this study sought to modify existing EPS-targeting small molecules with the ultimate goal of producing anti-biofilm polymer surfaces specifically targeting S. mutans. To achieve this, a known GTF inhibitor (G43) was modified with methoxy or tetraethyleneglycol substitutions in different positions (nine derivatives, tested at 50-µM) to pinpoint potential sites for future methacrylate functionalization, and then assessed against single-species S. mutans biofilms. As expected, the compounds did not diminish the bacterial viability. In general, the compounds with methoxy substitution were not effective in reducing EPS formation, whereas the tetraethyleneglycol substitution (G43-C3-TEG) led to a decrease in the concentration of insoluble EPS, although the effect is less pronounced than for the parent G43. This aligns with the reduced GTF-C activity observed at different concentrations of G43-C3-TEG, as well as the consequent decrease in EPS formation, and notable structural changes. In summary, this study determined that G43-C3-TEG is non-bactericidal and can selectively reduce the biofilm formation, by decreasing the production of EPS. This molecule will serve to functionalize surfaces of materials to be tested in future research.
The promise of zero-shot learning for alcohol image detection: comparison with a task-specific deep learning algorithm
Authors: Bonela Abraham Albert , Nibali Aiden , He Zhen , Riordan Benjamin , Anderson-Luxford Dan , Kuntsche Emmanuel 
Published: July 2023

AbstractExposure to alcohol content in media increases alcohol consumption and related harm. With exponential growth of media content, it is important to use algorithms to automatically detect and quantify alcohol exposure. Foundation models such as Contrastive Language-Image Pretraining (CLIP) can detect alcohol exposure through Zero-Shot Learning (ZSL) without any additional training. In this paper, we evaluated the ZSL performance of CLIP against a supervised algorithm called Alcoholic Beverage Identification Deep Learning Algorithm Version-2 (ABIDLA2), which is specifically trained to recognise alcoholic beverages in images, across three tasks. We found ZSL achieved similar performance compared to ABIDLA2 in two out of three tasks. However, ABIDLA2 outperformed ZSL in a fine-grained classification task in which determining subtle differences among alcoholic beverages (including containers) are essential. We also found that phrase engineering is essential for improving the performance of ZSL. To conclude, like ABIDLA2, ZSL with little phrase engineering can achieve promising performance in identifying alcohol exposure in images. This makes it easier for researchers, with little or no programming background, to implement ZSL effectively to obtain insightful analytics from digital media. Such analytics can assist researchers and policy makers to propose regulations that can prevent alcohol exposure and eventually prevent alcohol consumption.
N-eicosapentaenoyl-ethanolamine decreases the proliferation of psoriatic keratinocytes in a reconstructed psoriatic skin model
Authors: Simard Mélissa , Tremblay Andréa , Morin Sophie , Rioux Geneviève , Flamand Nicolas , Pouliot Roxane 
Published: July 2023

AbstractPsoriasis is an inflammatory skin disease that is characterized by keratinocyte hyperproliferation, abnormal epidermal differentiation and dysregulated lipid metabolism. Some lipid mediators of the N-acylethanolamines (NAEs) and monoacylglycerols (MAGs) can bind to cannabinoid (CB) receptors and are referred to as part of the endocannabinoidome. Their implication in psoriasis remains unknown. The aim of the present study was to characterize the endocannabinoid system and evaluate the effects of n-3-derived NAEs, namely N-eicosapentaenoyl-ethanolamine (EPEA), in psoriatic keratinocytes using a psoriatic skin model produced by tissue engineering, following the self-assembly method. Psoriatic skin substitutes had lower FAAH2 expression and higher MAGL, ABHD6 and ABHD12 expression compared with healthy skin substitutes. Treatments with alpha-linolenic acid (ALA) increased the levels of EPEA and 1/2-docosapentaenoyl-glycerol, showing that levels of n-3 polyunsaturated fatty acids modulate related NAE and MAG levels. Treatments of the psoriatic substitutes with 10 μM of EPEA for 7 days resulted in decreased epidermal thickness and number of Ki67 positive keratinocytes, both indicating decreased proliferation of psoriatic keratinocytes. EPEA effects on keratinocyte proliferation were inhibited by the CB1 receptor antagonist rimonabant. Exogenous EPEA also diminished some inflammatory features of psoriasis. In summary, n-3-derived NAEs can reduce the psoriatic phenotype of a reconstructed psoriatic skin model.
Usefulness of intraoperative optical coherence tomography to minimize the intraocular lens tilt during the intrascleral fixation: a clinical and experimental evaluation
Authors: Sotani Yasuyuki , Imai Hisanori , Iwane Yukako , Yamada Hiroko , Matsumiya Wataru , Miki Akiko , Kusuhara Sentaro , Nakamura Makoto 
Published: July 2023

AbstractTo report the usefulness of intraoperative real-time adjustment of intraocular lens (IOL) tilt during the intrascleral fixation with intraoperative optical coherence tomography (iOCT) as a clinical evaluation and investigate the factors contributing to IOL tilt using iOCT as an experimental evaluation. Retrospective cohort study and experimental research. As a clinical evaluation, the medical records of 43 eyes of 41 patients who underwent intrascleral IOL fixation combined with real-time iOCT observation were retrospectively reviewed. As an experimental evaluation, in order to investigate the factors contributing to IOL tilt, the four experiments were performed using iOCT. The mean IOL tilt angle (°) at the end of surgery and 3 months after surgery were 1.81 ± 1.15 and 2.10 ± 1.66, respectively (p = 0.46). No apparent intra- or postoperative complications occurred during the follow-up period. The experimental evaluation indicated that the IOL tilt was influenced by the insertion angle of the haptic in the vertical direction. The mean IOL tilt angle (°) was 1.94 ± 0.09, 4.67 ± 0.11, 8.90 ± 0.11, and 15.78 ± 0.85 when the insertion angle of the haptic was 0°, 10°, 27.5°, and 45° in the vertical direction, respectively (p < 0.01). Clinical and experimental IOL tilt assessment using iOCT is interactively useful for better quality surgery and better postoperative outcome.
Optimizing efficiency in the creation of patient-specific plates through field-driven generative design in maxillofacial surgery
Authors: Tel Alessandro , Kornfellner Erik , Moscato Francesco , Vinayahalingam Shankeeth , Xi Tong , Arboit Lorenzo , Robiony Massimo 
Published: July 2023

AbstractField driven design is a novel approach that allows to define through equations geometrical entities known as implicit bodies. This technology does not rely upon conventional geometry subunits, such as polygons or edges, rather it represents spatial shapes through mathematical functions within a geometrical field. The advantages in terms of computational speed and automation are conspicuous, and well acknowledged in engineering, especially for lattice structures. Moreover, field-driven design amplifies the possibilities for generative design, facilitating the creation of shapes generated by the software on the basis of user-defined constraints. Given such potential, this paper suggests the possibility to use the software nTopology, which is currently the only software for field-driven generative design, in the context of patient-specific implant creation for maxillofacial surgery. Clinical scenarios of applicability, including trauma and orthognathic surgery, are discussed, as well as the integration of this new technology with current workflows of virtual surgical planning. This paper represents the first application of field-driven design in maxillofacial surgery and, although its results are very preliminary as it is limited in considering only the distance field elaborated from specific points of reconstructed anatomy, it introduces the importance of this new technology for the future of personalized implant design in surgery.
SALA-LSTM: a novel high-precision maritime radar target detection method based on deep learning
Authors: Wang Jingang , Li Songbin 
Published: July 2023

AbstractRadar detection of maritime targets plays an important role in marine environment monitoring. For civil maritime detection in the areas of inshore coastal, pulse-compression radar is universally used owing to its low cost. The complex sea clutter in the practical application will greatly affect the received radar echoes. Due to the inability to accurately describe the differences in characteristics between sea clutter and maritime targets, the detection performance of methods based on mathematical derivation is not satisfactory in actual deployment. Recently, neural-based methods have made strides in many pattern recognition tasks, such as computer vision and natural language processing. The sophisticated deep neural models can be applied to different downstream tasks due to their powerful learning ability. Inspired by this idea, we propose a maritime radar target detection method in sea clutter based on deep learning. To better model the sequence correlation of radar echoes, we propose a Self-Adaption Local Augmented Long Short-Term Memory (SALA-LSTM) structure. The proposed SALA-LSTM integrates adaptive convolution into vanilla LSTM cells, which not only maintains the inherent overall sequence modeling ability of vanilla LSTM, but also strengthens its ability to perceive the correlation on a small scale in the local scope. Based on SALA-LSTM and other neural structures, we propose a radar target detection network. A measured dataset containing different typical scenarios is utilized to evaluate the detection probability and false alarm rate. The detection performance of our proposed network is superior to that of the existing methods.
Nanohybrids of atomically precise metal nanoclusters
Authors: Sahoo Koustav , Gazi Tapu Raihan , Roy Soumyadip , Chakraborty Indranath 
Published: July 2023

AbstractAtomically precise metal nanoclusters (NCs) with molecule-like structures are emerging nanomaterials with fascinating chemical and physical properties. Photoluminescence (PL), catalysis, sensing, etc., are some of the most intriguing and promising properties of NCs, making the metal NCs potentially beneficial in different applications. However, long-term instability under ambient conditions is often considered the primary barrier to translational research in the relevant application fields. Creating nanohybrids between such atomically precise NCs and other stable nanomaterials (0, 1, 2, or 3D) can help expand their applicability. Many such recently reported nanohybrids have gained promising attention as a new class of materials in the application field, exhibiting better stability and exciting properties of interest. This perspective highlights such nanohybrids and briefly explains their exciting properties. These hybrids are categorized based on the interactions between the NCs and other materials, such as metal-ligand covalent interactions, hydrogen-bonding, host-guest, hydrophobic, and electrostatic interactions during the formation of nanohybrids. This perspective will also capture some of the new possibilities with such nanohybrids.
Bilingual Adolescents' Complex Syntax Production in Both Languages Across Conversational and Expository Contexts
Authors: Rioux Eve Julie , Thordardottir Elin 
Published: July 2023

Purpose:
Bilingual development has been shown to be highly dependent on language-specific exposure. This study extended the study of bilingual development to adolescence and to the production of complex syntax in two contexts: conversation and expository discourse.

Method:

English–French bilinguals (EFbil;
n
= 27) and French L1 speakers (
n
= 14) aged 12 to 17 years produced French and English conversational and expository samples. Measures of mean length of T-units and clausal density were used, as well as a measure of detailed subordinate clause diversity developed in this study.

Results:
Both groups produced more complex syntax in expository discourse compared to conversation and performed very similarly overall. Significant group differences were found in French subordinate clause diversity but not in sentence length or clause density. For EFbil, differences between languages were unexpectedly greater in conversation. Previous language exposure impacted both languages of the EFbil and in both contexts.

Conclusions:
This study is the first to report on the spontaneous syntactic use of bilingual adolescents in both their languages. Subtle but significant differences were found in the syntactic skills of the two groups. Expository and conversational contexts each provided unique information on aspects of complex syntactic development, calling into question the idea that the ability to produce a more complex context guarantees conversational abilities. Finally, for the EFbil, previous language exposure impacted both languages, particularly in conversation.

Supplemental Material:

https://doi.org/10.23641/asha.23713152
Novel circulator design using substrate integrated coaxial line
Authors: Ho Min‐Hua , Hong Jing‐Jie , Hsu Chung I. G. , Hong Wanchu 
Published: July 2023

AbstractThe contribution of this work is to propose a novel circulator design using the substrate‐integrated coaxial line (SICL) structure. Conventionally, the circulator is composed of three‐dimensional waveguide components, and, in contrast, the proposed SICL circulator allows the 3‐D waveguide circulator to be built in a planar form using the printed circuit board (PCB) technology. The proposed SICL circulator is composed of three substrates with two parallel signal strips embedded in the central SICL tunnel. For better impedance matching, a widened section is inserted in each uniform feedline, and the Y‐junction joint on the bottom surface of the middle substrate is connected with three stubs and is loaded with a circular disk on the top surface of the middle substrate. A bandpass filter (BPF) can be embedded in each circulator's branch to improve signal selectivity and the out‐of‐band isolation. Experiments are conducted to verify the circuit design. Agreements are observed between the measured and simulated data.
A high‐performance and lightweight framework for real‐time facial expression recognition
Authors: Xu Xuebin , Liu Chenguang , Cao Shuxin , Lu Longbin 
Published: July 2023

AbstractFacial expression recognition technology has become a powerful tool for conveying human emotions and intentions and is widely used in areas such as assisted driving and intelligent medical care. Due to the limited computing power of current hardware devices and the real‐time requirements of application scenarios, this paper proposes a high‐performance and lightweight framework for real‐time facial expression recognition framework to solve the problem of real‐time completion of expression recognition tasks under low hardware costs. To address these issues, this paper first designs a RepVGG and mobileNetV2 dual‐channel structure in the feature extraction. It is then input into the MobileViT Block for global feature modelling. Finally, the position vector of the capsule network is used to replace the output of the global pooling, preserving the spatial relationship of the salient features and enhancing the classification effect. Compared with the mainstream facial expression recognition algorithm that cannot get good classification results under low complexity conditions, the model has a significant accuracy improvement while ensuring lightweight. With only 294.60M FLOPS and 0.95M parameters, it achieved an accuracy of 97.53% on the KDEF dataset and 85.56% on the RAF‐DB, demonstrating the advanced nature of the algorithm.
CMLocate: A cross‐modal automatic visual geo‐localization framework for a natural environment without GNSS information
Authors: Liu Zhuoqun , Guo Fan , Liu Heng , Xiao Xiaoyue , Tang Jin 
Published: July 2023

AbstractIn this paper, a new approach to visual geo‐localization for natural environments is proposed. The digital elevation model (DEM) data in virtual space is rendered and construct a panoramic skyline database is constructed. By combining the skyline database with real‐world image data (used as the “queries” to be localized), visual geo‐localization is treated as a cross‐modal image retrieval problem for panoramic skyline images, creating a unique new visual geo‐localization benchmark for the natural environment. Specifically, the semantic segmentation model named LineNet is proposed, for skyline extractions from query images, which has proven to be robust to a variety of complex natural environments. On the aforementioned benchmarks, the fully automatic method is elaborated for large‐scale cross‐modal localization using panoramic skyline images. Finally, the compound index is delicately designed to reduce the storage space of the positioning global descriptors and improve the retrieval efficiency. Moreover, the proposed method is proven to outperform most state‐of‐the‐art methods.