bluuebunny/crossref_metadata_2025 huggingface dataset:
Predicting the effect of headphones on the time to localize a target in an auditory-guided visual search task
Authors: Lladó Pedro , Barumerli Roberto , Baumgartner Robert , Majdak Piotr
Published: June 2024

In augmented reality scenarios, headphones obstruct the direct path of the sound to the ears, affecting the users’ abilities to localize surrounding sound sources and compromising the immersive experience. Unfortunately, the assessment of the perceptual implications of wearing headphones on localization in ecologically valid scenarios is costly and time-consuming. Here, we propose a model-based tool for automatic assessment of the dynamic localization degradation (DLD) introduced by headphones describing the time required to find a target in an auditory-guided visual search task. First, we introduce the DLD score obtained for twelve headphones and the search times with actual listeners. Then, we describe the predictions of the headphone-induced DLD score obtained by an auditory model designed to simulate the listener’s search time. Our results indicate that our tool can predict the degradation score of unseen headphones. Thus, our tool can be applied to automatically assess the impact of headphones on listener experience in augmented reality applications.
Rapid multi-band space-based optical timing: revolutionizing accretion physics
Authors: Smith Krista Lynne
Published: June 2024

Optical timing with rapid, seconds-to-minutes cadences with high photometric precision and gap-free long baselines is necessary for an unambiguous physical picture of accretion phenomena, and is only possible from space. Exoplanet-hunting missions like Kepler and TESS have offered an outstanding new window into detailed jet and accretion physics, but have been severely hampered by incomplete calibration and systematics treatments and, most especially, a monochromatic single wide bandpass. Advances made using Kepler and TESS survey data, when considered alongside detailed, expensive multi-color experiments done from the ground, reveal the enormous potential of a space-based multi-color optical timing mission with a high energy focus.
Consumer behavior and healthy food consumption: quasi-natural experimental evidence from Chinese household participation in long-term care insurance
Authors: Chen Wenting , Ma Guangcheng , Jia Zhe
Published: June 2024

Introduction

There is a strong link between consumer behavior and healthy food consumption. However, how to narrow the gap between consumption intentions and actual healthy food consumption is still under discussion.

Methods

This study takes Chinese families as the research object, based on the family participation in long-term care insurance (LTCI) policy, and constructs an analytical framework including healthy eating behavior, food consumption, and insurance system to discuss how to narrow the gap between consumption intention and actual healthy food consumption. In addition, the intermediary role played by the risk prevention mechanism is also analyzed. Based on data from the China Health and Nutrition Survey (CHNS), this study uses a difference-in-differences analysis framework to empirically examine the impact of changes in consumption behavior on healthy food consumption after households participate in the LTCI pilot.

Results and discussion

The research results show that implementing LTCI can increase the frequency of healthy meal preparation methods by 0.045 units and the frequency of not including processed foods in the meals of households participating in the policy by 0.033 units compared with households that do not participate. The daily meal quantity is increased by 0.198 (converted to 1.219 grams), and 0.198 units increase the healthy food consumption structure. This conclusion holds under a series of robustness tests. Mechanism test shows that LTCI affects healthy food consumption through risk prevention mechanisms. The impact of the LTCI policy will also not be affected by similar competitive policies. The heterogeneity test further proves that LTCI policies are more likely to increase healthy food consumption among urban households, larger households, and households employed in private enterprises. Based on these findings, it is recommended that families participate in LTCI to reduce the financial stress faced by families due to illness and care needs while increasing the demand for and consumption of healthy foods. The findings also provide a valuable reference for current policy formulation on improving family dietary quality in China.
Combined replantation of the posterior arch of the atlas and bilateral axial lamina in the treatment of intradural schwannoma: a case report
Authors: Leng Ao , Li Jiacheng , Meng Lingzhi , Wang Qi
Published: June 2024

Background

Laminotomy and laminar replantation have emerged as novel treatment modalities for intraspinal tumors, aiming to minimize postoperative complications and retain spinal mobility. However, existing research predominantly emphasizes their application in the thoracolumbar spine. The unique anatomy of the atlantoaxial segments necessitates surgical techniques that differ from those used in other spinal regions, and the clinical effect of such procedure remains unknown.

Case presentation

A 61-year-old male patient with intradural schwannoma at the atlantoaxial level was operated on. The patient underwent posterior laminectomy, as well as a combined replantation of the posterior arch of the atlas and bilateral axial laminae. Postoperatively, the patient experienced significant neurological improvement, with no deformities or instability on the radiological assessments during the follow-up.

Conclusion

Laminotomy with combined replantation of the posterior arch of the atlas and bilateral axial lamina emerges as an effective approach for managing intraspinal tumors at the atlantoaxial level. This technique not only offers ample operating space but also restores the stability of the spinal canal. Moreover, it preserves the mobility of the atlantoaxial segment, minimizes impact on adjacent segments, and mitigates the formation of postoperative fibrosis.
Deep learning models for interpretation of point of care ultrasound in military working dogs
Authors: Hernandez Torres Sofia I. , Holland Lawrence , Edwards Thomas H. , Venn Emilee C. , Snider Eric J.
Published: June 2024

Introduction

Military working dogs (MWDs) are essential for military operations in a wide range of missions. With this pivotal role, MWDs can become casualties requiring specialized veterinary care that may not always be available far forward on the battlefield. Some injuries such as pneumothorax, hemothorax, or abdominal hemorrhage can be diagnosed using point of care ultrasound (POCUS) such as the Global FAST® exam. This presents a unique opportunity for artificial intelligence (AI) to aid in the interpretation of ultrasound images. In this article, deep learning classification neural networks were developed for POCUS assessment in MWDs.

Methods

Images were collected in five MWDs under general anesthesia or deep sedation for all scan points in the Global FAST® exam. For representative injuries, a cadaver model was used from which positive and negative injury images were captured. A total of 327 ultrasound clips were captured and split across scan points for training three different AI network architectures: MobileNetV2, DarkNet-19, and ShrapML. Gradient class activation mapping (GradCAM) overlays were generated for representative images to better explain AI predictions.

Results

Performance of AI models reached over 82% accuracy for all scan points. The model with the highest performance was trained with the MobileNetV2 network for the cystocolic scan point achieving 99.8% accuracy. Across all trained networks the diaphragmatic hepatorenal scan point had the best overall performance. However, GradCAM overlays showed that the models with highest accuracy, like MobileNetV2, were not always identifying relevant features. Conversely, the GradCAM heatmaps for ShrapML show general agreement with regions most indicative of fluid accumulation.

Discussion

Overall, the AI models developed can automate POCUS predictions in MWDs. Preliminarily, ShrapML had the strongest performance and prediction rate paired with accurately tracking fluid accumulation sites, making it the most suitable option for eventual real-time deployment with ultrasound systems. Further integration of this technology with imaging technologies will expand use of POCUS-based triage of MWDs.
Updates on antifungal pharmacotherapy in elasmobranchs: pharmacokinetics of 4 mg/kg voriconazole after IM and IV administration in undulate skates (Raja undulata) maintained under human care
Authors: Cañizares-Cooz Daniela , Rojo-Solís Carlos , Rubio-Langre Sonia , García-Párraga Daniel , Encinas Teresa , Morón-Elorza Pablo
Published: June 2024

Introduction

Fungal diseases are frequently associated with elevated mortality rates in elasmobranchs. Currently, there is a notable absence of scientifically validated therapeutic medications that can ensure both effectiveness and safety when administered to this group of animals. The empirical prescription of azole antifungal agents, particularly voriconazole, has been posited as a potentially efficacious treatment approach for addressing most common mycoses in sharks and rays. However, there are still no published pharmacokinetic studies supporting its use in elasmobranchs and there is a lack of scientific base for its utilization in elasmobranchs.

Methods

For this study, voriconazole was administered intravenously (IV) and intramuscularly (IM), at a single dose of 4 mg/kg to six adult undulate skates (Raja undulata). A washout period of 8 weeks was left between each route of administration. Blood samples were collected both before and at ten predetermined intervals after each dosing (0.25, 0.5, 1, 1.5, 2, 4, 8, 12, 24, and 36 h after drug administration). Plasma concentrations were quantified using a validated high-performance liquid chromatography method, and pharmacokinetic (PK) data was analyzed through non-compartmental methods.

Results

The mean extrapolated concentration at 0 h (C0) after IV administration was 27.19 ± 7.15 μg/mL and the mean peak plasma concentrations (Cmax) ± SEM after IM administration resulted 2.98 ± 0.28 μg/mL at a mean time to maximum concentration (T max) of 1.33 ± 0.17 h. Terminal half-lives were calculated and resulted 11.18 ± 1.32 h for IV injections and 9.59 ± 1.38 h for IM injections. The area under the curve extrapolated to infinity was determined as 58.14 ± 2.79 h·μg/ml following IV injections and 37.60 ± 6.67 h·μg/ml following IM injections. The IM-administered voriconazole exhibited a mean absolute bioavailability of 64.67 ± 11.47%.

Discussion

These discoveries provide backing for the possible application of voriconazole through the intramuscular route in undulate skates and support using lower dosage regimens compared to those required for oral administration, emphasizing the importance of conducting further pharmacokinetic studies with antifungals in elasmobranchs.
ChatGPT in veterinary medicine: a practical guidance of generative artificial intelligence in clinics, education, and research
Authors: Chu Candice P.
Published: June 2024

ChatGPT, the most accessible generative artificial intelligence (AI) tool, offers considerable potential for veterinary medicine, yet a dedicated review of its specific applications is lacking. This review concisely synthesizes the latest research and practical applications of ChatGPT within the clinical, educational, and research domains of veterinary medicine. It intends to provide specific guidance and actionable examples of how generative AI can be directly utilized by veterinary professionals without a programming background. For practitioners, ChatGPT can extract patient data, generate progress notes, and potentially assist in diagnosing complex cases. Veterinary educators can create custom GPTs for student support, while students can utilize ChatGPT for exam preparation. ChatGPT can aid in academic writing tasks in research, but veterinary publishers have set specific requirements for authors to follow. Despite its transformative potential, careful use is essential to avoid pitfalls like hallucination. This review addresses ethical considerations, provides learning resources, and offers tangible examples to guide responsible implementation. A table of key takeaways was provided to summarize this review. By highlighting potential benefits and limitations, this review equips veterinarians, educators, and researchers to harness the power of ChatGPT effectively.
Insertion trauma of a novel inner ear catheter for intracochlear drug delivery
Authors: Gerlitz Matthias , Yildiz Erdem , Gadenstaetter Anselm J. , Niisuke Katrin , Kandathil Sam A. , Nieratschker Michael , Landegger Lukas D. , Honeder Clemens , Arnoldner Christoph
Published: June 2024

Introduction

Even with recent research advances, effective delivery of a compound to its target cells inside the inner ear remains a challenging endeavor due to anatomical and physiological barriers. Direct intracochlear drug administration with an inner ear catheter (IEC) aims to overcome this obstacle and strives to provide a safe and efficient way for inner ear pharmacotherapy. The goal of this study was to histologically and audiologically evaluate the traumatic properties of a novel IEC for intracochlear drug delivery in a large animal model.

Methods

Seven inner ears of piglets that had undergone intracochlear fluorescein isothiocyanate dextran application via an IEC (n = 4) or round window membrane (RWM) puncture with a needle (n = 3) followed by sequential apical perilymph sampling were histologically analyzed. Additionally, obtained objective auditory compound action potential and cochlear microphonic measurements were compared. Cochlear cryosections were stained using hematoxylin and eosin, and preservation of inner ear structures was investigated. Moreover, one cochlea was methylmethacrylate-embedded and analyzed with the IEC in situ.

Results

Histological evaluation revealed an atraumatic insertion and subsequent compound application in a majority of IEC-inserted inner ears. Click cochlear compound action potential (CAP) shifts in the IEC groups reached a maximum of 5 dB (1.25 ± 2.5 dB) post administration and prior to perilymph sampling. In comparison, application by RWM puncture generated a maximum click CAP hearing threshold shift of 50 dB (23.3 ± 23.1 dB) coinciding with coagulated blood in the basal cochlear turn in one specimen of the latter group. Furthermore, in situ histology showed an atraumatic insertion of the IEC demonstrating preserved intracochlear structures.

Conclusion

The IEC appears to be a promising and efficient way for inner ear drug delivery. The similarities between the porcine and human inner ear enhance the clinical translation of our findings and increase confidence regarding the safe applicability of the IEC in human subjects.
Molecular characterization of Cryptosporidium spp. in Bactrian camels (Camelus bactrianus) from Yili Kazak Autonomous Prefecture of Xinjiang, China
Authors: Mi Rongsheng , Silayi Amanguli , Wang Yongsheng , Xia Chenyang , Tang Wenqiang , Gong Haiyan , Huang Yan , Zhang Yan , Yan Genqiang , Chen Zhaoguo
Published: June 2024

Introduction

Cryptosporidium spp. is a significant zoonotic parasite. The prevalence and infection characteristics of Cryptosporidium spp. in Bactrian camels in Yili Kazak Autonomous Prefecture have yet to be fully understood. Thus, the molecular epidemiology of cryptosporidiosis in camels was investigated in this region.

Methods

A total of 1,455 fecal samples were collected from 6 counties in three regions (Altay, Tacheng, and Yili) in Yili Prefecture. Nested PCR targeting the small subunit ribosomal RNA (ssu rRNA) gene was used to identify the species or genotypes of Cryptosporidium infection in camels. For C. parvum positive samples, the subtypes were identified using the 60-kDa glycoprotein (gp60) gene.

Results and discussion

The overall infection rate was 8.7% (126/1,455), ranging from 5.6% to 11.7% in different regions, and 4.2% to 15.8% in different counties. A significant difference was observed amongst the counties (p < 0.001). Three species were detected, namely C. andersoni (65.1%, 82/126), C. parvum (34.1%, 43/126), and C. occultus (0.8%, 1/126). Three C. parvum subtypes, If-like-A15G2 (n = 29), IIdA15G1 (n = 4), and IIdA19G1(n = 1) were detected, with If-like-A15G2 being the most prevalent subtype. Camels aged 3-12 months exhibited the highest infection rate (11.4%, 44/387), with no significant difference among age groups (p > 0.05). C. parvum was predominant in camels under 3 months, while C. andersoni prevailed in camels over 3 months. There was an extremely significant difference observed among seasons (p < 0.001), summer had the highest infection rates (16.9%, 61/360). This study collected nearly 1,500 samples and, for the first time, investigated Cryptosporidium spp. infection in camels based on different age groups and seasons. All three Cryptosporidiumspecies identified were zoonotic, posing a potential threat to human health and requiring close attention.
Rapid lateral flow immunoassay for fluorescence detection of canine distemper virus (CDV)
Authors: Cao Zhigang , Yi Li , Liu Xiangnan , Shang Jinyuan , Cheng Yuening , Feng Erkai , Liu Xingyu , Fan Yuping , Hu Xiaoliang , Cai Wenlong , Cong Feng , Cheng Shipeng
Published: June 2024

Canine distemper virus (CDV) is a highly contagious and potentially lethal virus that affects dogs and other members of the Canidae family, including wolves, foxes, and coyotes. Here, we present a fluorescent lateral flow immunoassay (FLFA) platform for the detection of CDV, which utilizes fluorescent microspheres - fusion protein monoclonal antibody (mAb)-labeled monoclonal antibody. The assay detected CDV within 5 min, with a detection limit threshold of 3 × 102 TCID50/mL. Notably, the assay demonstrated no cross-reactivity with canine parvovirus, canine coronavirus, canine adenovirus, feline calicivirus, feline herpesvirus, or feline parvovirus. Field and clinical applicability of the assay was evaluated using 63 field samples, including 30 canine fecal samples, 18 swab samples, and 15 blood samples. The coincidence rate between the detection results of clinical samples obtained through FLFA and reverse transcription polymerase chain reaction (RT-PCR) was 96.83%. Thus, this assay offers a significant advancement for the rapid diagnosis of CDV at the point of care.
Investigating the effect of prescribing status and patient characteristics on the therapeutic outcomes in patients with diabetes using a leftover drug adjustment protocol
Authors: Hirai Toshiyuki , Hanaoka Shunsuke , Terakado Yuusuke , Seki Toshiichi , Watanabe Fumiyuki
Published: June 2024

Treatment for diabetes includes anti-diabetic medication in addition to lifestyle improvements through diet and exercise. In Japan, protocol-based pharmacotherapy management allows drug treatment to be provided through cooperation between physicians and pharmacists, based on a protocol that is prepared and agreed upon in advance. However, there are no studies to clarify the relationship between patient characteristics and therapeutic effects after pharmacist intervention in protocol-based pharmacotherapy management for patients with diabetes. Therefore, this study aimed to use protocol-based reports from pharmacies to understand the status of outpatient diabetes medication compliance. We classified patients with diabetes on the basis of patient characteristics that can be collected in pharmacies and investigated the characteristics that impacted diabetes treatment. Patients were prescribed oral anti-diabetic drugs at outpatient clinics of Hitachinaka General Hospital, Hitachi, Ltd., from April 2016 to March 2021. Survey items included patient characteristics (sex, age, number of drugs used, observed number of years of anti-diabetic drug prescription, number of anti-diabetic drug prescription days, and presence or absence of leftover anti-diabetic drugs) and HbA1c levels. Graphical analyses indicated the relationship between each categorised patient characteristic using multiple correspondence analyses. Subsequently, the patients were clustered using K-means cluster analysis based on the coordinates obtained for each patient. Patient characteristics and HbA1c values were compared between the groups for each cluster. A total of 1,910 patients were included and classified into three clusters, with clusters 1, 2, and 3 containing 625, 703, and 582 patients, respectively. Patient characteristics strongly associated with Cluster 1 were ages between 65 and 74 years, use of three or more anti-diabetic drugs, use of 3 years or more of anti-diabetic drugs, and leftover anti-diabetic drugs. Furthermore, Cluster 1 had the highest number of patients with worsening HbA1c levels compared with other clusters. Using the leftover drug adjustment protocol, we clarified the patient characteristics that affected the treatment course. We anticipate that through targeted interventions in patients exhibiting these characteristics, we can identify those who are irresponsibly continuing with drug treatment, are not responding well to therapy, or both. This could substantially improve the efficacy of their anti-diabetic care.
On the Variability in the Temporal Stability Pattern of Soil Moisture Under Mediterranean Conditions
Authors: González-Zamora Ángel , Benito-Verdugo Pilar , Martínez-Fernández José
Published: June 2024

In recent decades, there has been increasing interest in studying the variability in soil water properties and, specifically, the spatiotemporal variability in the soil water content. This is motivated by the notable theoretical and applied research interests in soil moisture dynamics and their implications for many natural processes. This study aimed to study whether there are variations in the spatial pattern of the temporal stability of soil moisture over time and to analyze the possible influences of certain hydroclimatic (soil water content, precipitation, and evapotranspiration) and soil factors (texture, bulk density, and organic matter content) on these variations. This study was conducted within the Soil Moisture Measurement Stations Network of the University of Salamanca (REMEDHUS, Spain) under Mediterranean conditions, with daily surface moisture data (0–5 cm depth) obtained from 20 stations for the 2006-2023 period. The results showed differences between the average pattern obtained with the 18-year data series and that obtained with the data series for each year. In more than half of the years studied, the representative station differed from that derived from the average pattern. The mean annual precipitation and summer precipitation characteristics seem to be the main factors influencing the variability in the spatial pattern of the temporal stability of soil moisture.
Disturbance Observer and Adaptive Control for Disturbance Rejection of Quadrotor: A Survey
Authors: Wang Ruiying , Shen Jun
Published: June 2024

Quadrotors are widely applied in many fields, but they often face various external disturbances in actual operation. This makes it necessary to design a controller that can handle disturbances. Disturbance observer and adaptive control techniques are commonly used disturbance rejection techniques, the core idea of which is to estimate the disturbances in real time and incorporate the estimated values into the controller to suppress the disturbances. In this paper, various disturbance observers and adaptive control techniques, including nonlinear disturbance observers, extended state observers, neural networks, and fuzzy logic systems, are introduced, along with their variants or different structures. These techniques improve the adaptability and robustness of quadrotors to complex environments. Finally, future research directions for the disturbance rejection of quadrotors are also presented.
Analysis of the Dihedral Corner Reflector’s RCS Features in Multi-Resource SAR
Authors: Liu Jie , Li Tao , Ma Sijie , Wen Yangmao , Xu Yanhao , Nie Guigen
Published: June 2024

Artificial corner reflectors are widely used in the vegetated landslide for time series InSAR monitoring due to their permanent scattering features. This paper investigated the RCS features of a novel dihedral CR under multi-resource SAR datasets. An RCS reduction model for the novel dihedral corner reflector has been proposed to evaluate the energy loss caused by the deviation between the SAR incident angle and the CR’s axis. On the Huangtupo slope, Badong county, Hubei province, tens of dihedral CRs had been installed and the TSX–spotlight and Sentinel-TOPS data had been collected. Based on the observation results of CRs with more than ten deviation angles, the proposed reduction model was tested with preferable consistency under a real dataset, while 2 dBsm of systematic bias was verified in those datasets. The maximum incident angle deviation in the Sentinel data overlapping area is over 12°, which leads to a 2.4 dBsm RCS decrease for horizontally placed dihedral CRs estimated by the proposed model, which has also been testified by the observed results. The testing results from the Sentinel data show that in high, vegetation-covered mountain areas like the Huangtupo slope, the dihedral CRs with a 0.4 m slide length can be achieve 1 mm precision accuracy, while a side length of 0.2 m can achieve the same accuracy under TSX–spotlight data.
A Novel Stacking Ensemble Learning Approach for Predicting PM2.5 Levels in Dense Urban Environments Using Meteorological Variables: A Case Study in Macau
Authors: Tian Haoting , Kong Hoiio , Wong Chanseng
Published: June 2024

Air pollution, particularly particulate matter such as PM2.5 and PM10, has become a focal point of global concern due to its significant impact on air quality and human health. Macau, as one of the most densely populated cities in the world, faces severe air quality challenges. We leveraged daily pollution data from 2015 to 2023 and hourly meteorological pollution monitoring data from 2020 to 2022 in Macau to conduct an in-depth analysis of the temporal trends of and seasonal variations in PM2.5 and PM10, as well as their relationships with meteorological factors. The findings reveal that PM10 concentrations peak during dawn and early morning, whereas PM2.5 distributions are comparatively uniform. PM concentrations significantly increase in winter and decrease in summer, with relative humidity, temperature, and sea-level atmospheric pressure identified as key meteorological determinants. To enhance prediction accuracy, a Stacking-based ensemble learning model was developed, employing LSTM and XGBoost as base learners and LightGBM as the meta-learner for predicting PM2.5 concentrations. This model outperforms traditional methods such as LSTM, CNN, RF, and XGB across multiple performance metrics.
Educational Data Clustering in Secondary School Sensor-Based Engineering Courses Using Active Learning Approaches
Authors: Panskyi Taras , Korzeniewska Ewa , Firych-Nowacka Anna
Published: June 2024

The authors investigated the impact of active learning STEM and STEAM approaches on secondary school students’ general engineering knowledge, intrinsic relevance, and creativity. Three out-of-school sensor-based courses were held successively. Every sensor-based course involved the final project development. A structured questionnaire was administered to 379 students and consisted of two critical factors: creativity and intrinsic relevance. The third factor was dedicated to the students’ engineering learning outcomes. Two factors were addressed to secondary school students, while the third factor was addressed to the tutors’ observations of the students’ general sensor-based knowledge. Clustering validation analysis quantified the obtained results and justified the significant differences in all estimated factors for different educational modes. Moreover, the study showcases the value of the arts in sensor-based learning-by-doing courses when tackling complex issues like engineering topics. The authors suggest that broader research be undertaken, involving a larger sample, a greater scale, and a diversity of factors.
Harmonic Detection Method Based on Parameter Optimization VMD-IWT Combined Noise Reduction
Authors: Xu Jiechuan , Ma Hongyan , He Wei
Published: June 2024

Aiming at the problem that the existing harmonic detection methods are susceptible to noise interference in the actual working environment, which leads to the reduction of detection accuracy, this paper introduces a novel harmonic detection technique utilizing a RIME optimization algorithm (RIME) to enhance variational mode decomposition (VMD) combined with an improved wavelet threshold (IWT) approach. Initially, RIME optimization refines VMD for the decomposition of harmonic current signals, yielding several modal components. Subsequently, a correlation coefficient method distinguishes between effective and ineffective modal components, discarding the latter. The effective components undergo noise reduction through an enhanced wavelet thresholding technique, and these denoised components are then reconstructed to produce the final noise-reduced signal. Finally, the Hilbert transform is applied to the denoised signal to extract harmonic parameters. Verification through both simulated and actual signal measurements demonstrates that the proposed method not only surpasses other noise reduction algorithms in signal-to-noise ratio and root-mean-square error, but also shows superior accuracy and robustness compared to alternative detection techniques. This method effectively filters out signal noise under noise interference, minimizes detection errors, and achieves precise harmonic signal detection with improved accuracy.
A Reinforcement Learning-Based Multi-Objective Bat Algorithm Applied to Edge Computing Task-Offloading Decision Making
Authors: Tseng Chwan-Lu , Cheng Che-Shen , Shen Yu-Hsuan
Published: June 2024

Amid the escalating complexity of networks, wireless intelligent devices, constrained by energy and resources, bear the increasing burden of managing various tasks. The decision of whether to allocate tasks to edge servers or handle them locally on devices now significantly impacts network performance. This study focuses on optimizing task-offloading decisions to balance network latency and energy consumption. An advanced learning-based multi-objective bat algorithm, MOBA-CV-SARSA, tailored to the constraints of wireless devices, presents a promising solution for edge computing task offloading. Developed in C++, MOBA-CV-SARSA demonstrates significant improvements over NSGA-RL-CV and QLPSO-CV, enhancing hypervolume and diversity-metric indicators by 0.9%, 15.07%, 4.72%, and 0.1%, respectively. Remarkably, MOBA-CV-SARSA effectively reduces network energy consumption within acceptable latency thresholds. Moreover, integrating an automatic switching mechanism enables MOBA-CV-SARSA to accelerate convergence speed while conserving 150.825 W of energy, resulting in a substantial 20.24% reduction in overall network energy consumption.
Description of the Early Larval Development in Freshwater Shrimp Atya lanipes Holthuis, 1963 (Decapoda: Caridea: Atyidae) from Puerto Rico
Authors: Cruz-Rosa Stefani , Estruche-Santos Ángel S. , Pérez-Reyes Omar
Published: June 2024

The family Atyidae is composed of species whose existence has been known since the seventeenth century. Widely found in the Caribbean, Atya lanipes is a freshwater scraper/filter feeder shrimp with an amphidromous complex life cycle. Hunte (1975) described the first larval (zoeal) stage of the species. However, no scientific study has described the early larval development of this species after the first stage. This study aimed to document the early larval development of Atya lanipes under laboratory conditions and compare its larval development with other previously described species of the Atyidae family. Larval development was recorded by taking daily photos and videos of larval (zoeal) growth using a stereo microscope. Larvae were also preserved in ethanol for further morphological analysis. The results revealed that the best conditions for Atya lanipes development were 30 ppm water salinity, constant gentle aeration, and 27 °C water temperature. Nine stages were identified for the description of the early larval development of Atya lanipes. Early larval stages differ primarily in interstage larval size, the appearance and development of the telson, appendage appearance, growth of antennae and antennules, and pigmentation. The present contribution represents the first study that describes the larval development of the Caribbean shrimp Atya lanipes.
Missense and Non-Missense Lamin A/C Gene Mutations Are Similarly Associated with Major Arrhythmic Cardiac Events: A 20-Year Single-Centre Experience
Authors: Forleo Cinzia , Carella Maria Cristina , Basile Paolo , Carulli Eugenio , Dadamo Michele Luca , Amati Francesca , Loizzi Francesco , Sorrentino Sandro , Dentamaro Ilaria , Dicorato Marco Maria , Ricci Stefano , Bagnulo Rosanna , Iacoviello Matteo , Santobuono Vincenzo Ezio , Caiati Carlo , Pepe Martino , Desaphy Jean-Francois , Ciccone Marco Matteo , Resta Nicoletta , Guaricci Andrea Igoren
Published: June 2024

Arrhythmic risk stratification in patients with Lamin A/C gene (LMNA)-related cardiomyopathy influences clinical decisions. An implantable cardioverter defibrillator (ICD) should be considered in patients with an estimated 5-year risk of malignant ventricular arrhythmia (MVA) of ≥10%. The risk prediction score for MVA includes non-missense LMNA mutations, despite their role as an established risk factor for sudden cardiac death (SCD) has been questioned in several studies. The purpose of this study is to investigate cardiac features and find gene–phenotype correlations that would contribute to the evidence on the prognostic implications of non-missense vs. missense mutations in a cohort of LMNA mutant patients. An observational, prospective study was conducted in which 54 patients positive for a Lamin A/C mutation were enrolled, and 20 probands (37%) were included. The median age at first clinical manifestation was 41 (IQR 19) years. The median follow-up was 8 years (IQR 8). The type of LMNA gene mutation was distributed as follows: missense in 26 patients (48%), non-frameshift insertions in 16 (30%), frameshift deletions in 5 (9%), and nonsense in 7 (13%). Among the missense mutation carriers, two (8%) died and four (15%) were admitted onto the heart transplant list or underwent transplantation, with a major adverse cardiovascular event (MACE) rate of 35%. No statistically significant differences in MACE prevalence were identified according to the missense and non-missense mutation groups (p value = 0.847). Our data shift the spotlight on this considerable topic and could suggest that some missense mutations may deserve attention regarding SCD risk stratification in real-world clinical settings.
The Role of Zinc in the Development of Vascular Dementia and Parkinson’s Disease and the Potential of Carnosine as Their Therapeutic Agent
Authors: Mizuno Dai , Kawahara Masahiro , Konoha-Mizuno Keiko , Hama Ryoji , Ogawara Terumasa
Published: June 2024

Synaptic zinc ions (Zn2+) play an important role in the development of vascular dementia (VD) and Parkinson’s disease (PD). In this article, we reviewed the current comprehension of the Zn2+-induced neurotoxicity that leads to the pathogenesis of these neuronal diseases. Zn2+-induced neurotoxicity was investigated by using immortalised hypothalamic neurons (GT1-7 cells). This cell line is useful for the development of a rapid and convenient screening system for investigating Zn2+-induced neurotoxicity. GT1-7 cells were also used to search for substances that prevent Zn2+-induced neurotoxicity. Among the tested substances was a protective substance in the extract of Japanese eel (Anguilla japonica), and we determined its structure to be like carnosine (β-alanylhistidine). Carnosine may be a therapeutic drug for VD and PD. Furthermore, we reviewed the molecular mechanisms that involve the role of carnosine as an endogenous protector and its protective effect against Zn2+-induced cytotoxicity and discussed the prospects for the future therapeutic applications of this dipeptide for neurodegenerative diseases and dementia.
Effects of Mineral Elements and Annealing on the Physicochemical Properties of Native Potato Starch
Authors: Thomann Johanna A. , Polhuis Michael , Lasorsa Alessia , Heeres Hero J. , Heeres André
Published: June 2024

Native potato starch is an excellent carrier of minerals due to its inherent ion exchange capacity. Mineral enrichment not only changes the nutritional value but also influences starch pasting and swelling properties. Hydrothermal treatments like annealing constitute a straightforward and green way to tune functional properties. Here, novel combinations of mineral enrichment and annealing were studied. Ion exchange was readily achieved by suspending starch in a salt solution at room temperature over 3 h and confirmed by ICP-OES. Annealing at 50 °C for 24 h using demineralized water or salt solutions strongly affected pasting, thermal, and swelling properties. The obtained XRD and DSC results support a more ordered structure with relative crystallinity increasing from initially 41.7% to 44.4% and gelatinization onset temperature increasing from 60.39 to 65.94 J/g. Solid-state NMR spectroscopy revealed no detectable changes after annealing. Total digestible starch content decreased after annealing from 8.89 to 7.86 g/100 g. During both ion exchange at room temperature and annealing, monovalent cations promoted swelling and peak viscosity, and divalent cations suppressed peak viscosity through ionic crosslinking. The presented combination allows fine-tuning of pasting behavior, potentially enabling requirements of respective food applications to be met while offering an alternative to chemically modified starches.
Optimizing Sensor-Controlled Systems with Minimal Intervention: A Fuzzy Relational Calculus Approach
Authors: Zahariev Zlatko
Published: June 2024

This article describes an approach for optimizing sensor-controlled systems through minimal intervention, utilizing fuzzy linear systems of equations (FLSEs). Starting with a generalized model of the system behavior, we incorporate an array of control units, environmental sensors, and an expert knowledge base. The described problems of detecting the level of intervention needed to change the system state to another is handled with the help of developed methods for solving the inverse problem faced by FLSEs. By achieving minimal intervention, we ensure that the system adjustments are effective, economically optimal, and non-intrusive. A MATLAB-based implementation is presented.
Benthic Diatoms on Macrophytes of the Israeli Mediterranean Coast
Authors: Barinova Sophia , Ryabushko Larisa , Balycheva Daria , Blaginina Anastasiia , Chiernyavsky Elena , Shiroyan Armine
Published: June 2024

Benthic diatoms have been studied in different areas of the Mediterranean Sea, but no data have been available for Israeli coastal waters until the present time. In this work, the composition, ecology, and phytogeography of diatoms of the macrophytes epiphyton are presented for the first time. Altogether, 85 diatom taxa were found among the epiphyton of 25 species of green, brown, and red macroalgae from the Israeli coast between March and May of 2021. These diatoms represent three classes, 17 orders, 26 families, and 41 genera. The taxonomic composition, ecology, and phytogeography of species are discussed. The distribution of diatoms are compared to that of other macrophytes and anthropogenic loads across the shoreline. The dominant species are given. Ecological characteristics and abundance in communities of revealed species are represented and statistically analyzed. The index of saprobity S varies between 1.69–2.71. Sites that stressed aquatic communities are indicated. The influence of the anthropogenic loads on the coastal territories is defined as a major factor that stimulated diatom species richness. Sites with anthropogenic stress for aquatic communities are indicated. Based on the composition of bioindicators, it is concluded that the section of the Israeli coast studied is oligo-mesotrophic compared to the eutrophic Gulf of Tartus.
Reproductive Response of Platynothrus peltifer (C.L. Koch, 1839) to Continuous Nitrogen Deposition
Authors: Petersdorf Marie-Charlott , Bruggink Joren , de Nijs Evy A. , Siepel Henk
Published: June 2024

Continuous nitrogen deposition threatens ecosystems by acidifying soils, causing a stoichiometric imbalance in the vegetation and ultimately, the disappearance of plant and animal species. There is a gap in knowledge of how decomposers such as oribatid mites cope with the effects of nitrogen deposition. Therefore, we conducted feeding experiments with the herbivorous mite Platynothrus peltifer (C.L. Koch, 1839) to assess its fitness as a measure of its reproductive response towards different nitrogen levels in its diet. Mites were collected from the field, starved, and allowed to lay eggs. We recorded the number of eggs during 60 days of experimental trial. The fecundity of mites varied with different elemental compositions, whereby phosphorus seemed to be a limiting factor. With ongoing nitrogen deposition in the future and concomitant phosphorus limitation, we expect a negative impact on the population dynamics of herbivorous decomposers such as Platynothrus peltifer.
Frequency of Oral Lesions, Olfactory, and Gustatory Disorders and Xerostomia in Patients with COVID-19
Authors: Castilho Natália Lopes , Martelli Daniella R. Barbosa , Machado Renato Assis , Cunha Zêus Araujo , dos Reis Claudiojanes , Queiroz Priscila Regina , de Sá Silva Dayane , Oliveira Eduardo Araujo , Coletta Ricardo D. , Martelli-Júnior Hercílio
Published: June 2024

COVID-19, a respiratory illness with a global impact on millions, has recently been linked to manifestations affecting various bodily systems, including the oral cavity. Studies highlight oral issues, like ulcers, blisters, and white patches, alongside olfactory and gustatory dysfunction, influencing an individual’s quality of life. In this context, our study aimed to assess the frequency of oral lesions, olfactory and gustatory disorders, and xerostomia resulting from COVID-19. An observational study was conducted with 414 patients to evaluate the frequency of oral symptoms resulting from COVID-19. Patients were diagnosed with mild symptoms and evaluated through clinical examination of the oral cavity and a questionnaire to assess functional alterations. The findings showed that 139 out of 414 patients presented clinical manifestations, with oral lesions being the most prevalent (19.1%), followed by gustatory disorders (18.1%), xerostomia (14.2%), and olfactory dysfunction (14%). The most prevalent oral lesions were ulcerations (n = 51), candidiasis (n = 8), and erythema or red plaques (n = 7). Unfortunately, 50 (12.1%) patients died during this study. Therefore, oral lesions, olfactory and gustatory dysfunctions, and xerostomia are common symptoms associated with COVID-19.
Predicting the Direction of NEPSE Index Movement with News Headlines Using Machine Learning
Authors: Dahal Keshab Raj , Gupta Ankrit , Pokhrel Nawa Raj
Published: June 2024

Predicting stock market movement direction is a challenging task due to its fuzzy, chaotic, volatile, nonlinear, and complex nature. However, with advancements in artificial intelligence, abundant data availability, and improved computational capabilities, creating robust models capable of accurately predicting stock market movement is now feasible. This study aims to construct a predictive model using news headlines to predict stock market movement direction. It conducts a comparative analysis of five supervised classification machine learning algorithms—logistic regression (LR), support vector machine (SVM), random forest (RF), extreme gradient boosting (XGBoost), and artificial neural network (ANN)—to predict the next day’s movement direction of the close price of the Nepal Stock Exchange (NEPSE) index. Sentiment scores from news headlines are computed using the Valence Aware Dictionary for Sentiment Reasoning (VADER) and TextBlob sentiment analyzer. The models’ performance is evaluated based on sensitivity, specificity, accuracy, and the area under the receiver operating characteristic (ROC) curve (AUC). Experimental results reveal that all five models perform equally well when using sentiment scores from the TextBlob analyzer. Similarly, all models exhibit almost identical performance when using sentiment scores from the VADER analyzer, except for minor variations in AUC in SVM vs. LR and SVM vs. ANN. Moreover, models perform relatively better when using sentiment scores from the TextBlob analyzer compared to the VADER analyzer. These findings are further validated through statistical tests.
Hierarchical Inverse Distance Transformer for Enhanced Localization in Dense Crowds
Authors: Qiu Xiangfeng , Ye Jin , Chen Siyu , Su Jinhe
Published: June 2024

Achieving precise individual localization within densely crowded scenes poses a significant challenge due to the intricate interplay of occlusions and varying density patterns. Traditional methods for crowd localization often rely on convolutional neural networks (CNNs) to generate density maps. However, these approaches are prone to inaccuracies stemming from the extensive overlaps inherent in dense populations. To overcome this challenge, our study introduces the Hierarchical Inverse Distance Transformer (HIDT), a novel framework that harnesses the multi-scale global receptive fields of Pyramid Vision Transformers. By adapting to the multi-scale characteristics of crowds, HIDT significantly enhances the accuracy of individual localization. Incorporating Focal Inverse Distance techniques, HIDT adeptly addresses issues related to scale variation and dense overlaps, prioritizing local small-scale features within the broader contextual understanding of the scene. Rigorous evaluation on standardized benchmarks has unequivocally validated the superiority of our approach. HIDT exhibits outstanding performance across various datasets. Notably, on the JHU-Crowd++ dataset, our method demonstrates significant improvements over the baseline, with MAE and MSE metrics decreasing from 66.6 and 253.6 to 59.1 and 243.5, respectively. Similarly, on the UCF-QNRF dataset, performance metrics increase from 89.0 and 153.5 to 83.6 and 138.7, highlighting the effectiveness and versatility of our approach.
Optimizing Mixed-Model Synchronous Assembly Lines with Bipartite Sequence-Dependent Setup Times in Advanced Manufacturing
Authors: Varyani Asieh , Salehi Mohsen , Heydari Gharahcheshmeh Meysam
Published: June 2024

In advanced manufacturing, optimizing mixed-model synchronous assembly lines (MMALs) is crucial for enhancing productivity and adhering to sustainability principles, particularly in terms of energy consumption and energy-efficient sequencing. This paper introduces a novel approach by categorizing sequence-dependent setup times into bipartite categories: workpiece-independent and workpiece-dependent. This strategic division streamlines assembly processes, reduces idle times, and decreases energy consumption through more efficient machine usage. A new mathematical model is proposed to minimize the intervals at which workpieces are launched on an MMAL, aiming to reduce operational downtime that typically leads to excessive energy use. Given the Non-deterministic Polynomial-time hard (NP-hard) nature of this problem, a genetic algorithm (GA) is developed to efficiently find solutions, with performance compared against the traditional branch and bound technique (B&B). This method enhances the responsiveness of MMALs to variable production demands and contributes to energy conservation by optimizing the sequence of operations to align with energy-saving objectives. Computational experiments conducted on small and large-sized problems demonstrate that the proposed GA outperforms the conventional B&B method regarding solution quality, diversity level, and computational time, leading to energy reductions and enhanced cost-effectiveness in manufacturing settings.