bluuebunny/crossref_metadata_2025 huggingface dataset:
Trehalose: Neuroprotective Effects and Mechanisms—An Updated Review
Authors: Sevriev Borislav , Dimitrova Simeonka , Kehayova Gabriela , Dragomanova Stela
Published: October 2024

Trehalose is a naturally occurring disaccharide that has recently gained significant attention for its neuroprotective properties in various models of neurodegeneration. This review provides an overview of available experimental data on the beneficial properties of trehalose for central nervous system pathological conditions. Trehalose’s impact on neuronal cell survival and function was also examined. As a result, we identified that trehalose’s neuroprotection includes autophagy modulation as well as its capability to stabilize proteins and inhibit the formation of misfolded ones. Moreover, trehalose mitigates oxidative stress-induced neuronal damage by stabilizing cellular membranes and modulating mitochondrial function. Furthermore, trehalose attenuates excitotoxicity-induced neuroinflammation by suppressing pro-inflammatory cytokine release and inhibiting inflammasome activation. A possible connection of trehalose with the gut–brain axis was also examined. These findings highlight the potential therapeutic effects of trehalose in neurodegenerative diseases. According to the conclusions drawn from this study, trehalose is a promising neuroprotective agent as a result of its distinct mechanism of action, which makes this compound a candidate for further research and the development of therapeutic strategies to combat neuronal damage and promote neuroprotection in various neurological diseases.
Perception of University Nursing Students and Faculty Members Regarding Simulated Practices: A Mixed Methods Study
Authors: Núñez Rosalbina Castillo , Bermeo Rosa Nury Zambrano , Casierra Nancy Francisca Bonilla , Tusconi Massimo , Curcio Felice , Gonzalez Cesar Ivan Aviles
Published: October 2024

Introduction: Clinical simulation has been used as a teaching strategy for students in health programmes, fostering greater preparedness and confidence in performing procedures. Objective: This study aimed to analyse the perception of fourth-semester nursing students and teachers regarding the simulated practice methodology implemented in a private university in Cali, Colombia. Method: A robust mixed-methods approach was used, incorporating quantitative surveys and qualitative interviews with 41 students and 5 teaching nursing faculty members. Data triangulation was applied to ensure the robustness of the results. Results: Both students and teachers reported a positive perception of simulated practice, which contributes to knowledge acquisition and contextual learning. Students emphasised that simulation improved their prior knowledge and motivated them to explore new topics. Lecturers emphasised the importance of well-trained instructors in simulation environments. However, participants identified challenges affecting performance, including simulation duration, group size, realism, and resource constraints. Conclusions: Students and teachers recommend strategic changes to the curriculum to optimise simulation practices.
Paediatric Emergency Nurses’ Perception of Medication Errors: A Qualitative Study
Authors: Collado-González Blanca , Fernández-López Ignacio , Urtubia-Herrera Valentina , Palmar-Santos Ana María , García-Perea Eva , Navarta-Sánchez María Victoria
Published: October 2024

Patient safety is fundamental to healthcare. Adverse events, particularly medication errors, cause harm to patients, especially the paediatric population in the emergency department. Aim: To explore paediatric emergency nurses’ perceptions of medication administration errors. Method: A qualitative, ethnomethodological, descriptive study. The participants were nurses working in the paediatric emergency department. Data were collected through in-depth individual interviews with paediatric emergency nurses. The study excluded nurses employed for less than six months. Ten individual interviews were carried out. All interviews were face-to-face and audio-recorded with the participant’s consent. Interviews took between 52 min and 1 h 25 min. A questions guide was followed during the interviews. The analysis of the data was carried out according to the scheme proposed by Taylor and Bogdan. Results: The participants’ discourse revealed three main categories: Safety culture, transmitted by supervisors and safety groups. Teamwork, with good communication and a positive relationship. Error management, the lack of formal support and negative feelings despite an understanding of the multifactorial nature of errors. The study identifies several challenges in the healthcare system. Emphasis was placed on the perception of errors in terms of patient harm, while near misses or dose delays or omissions are not treated as errors. Conclusions: Although institutions have implemented safety culture strategies, nurses have not fully embraced them. There is a need to promote a positive safety culture and a safe working environment that encourages communication within the team. The hospital should provide training in safe management and patient safety and develop effective protocols. This study was not registered.
Vertical Shear, Diapycnal Shear and the Gradient Richardson Number
Authors: Pelegrí Josep L. , Claret Mariona , Sangrà Pablo
Published: October 2024

In Cartesian coordinates x,y,z, the gradient Richardson number Ri is the ratio between the square of the buoyancy frequency N and the square of the vertical shear S, Ri=N2/S2, where N2=−g/ρ ∂ρ/∂z and S2=∂u/∂z2+∂v/∂z2, with ρ potential density, u,v the horizontal velocity components and g gravity acceleration. In isopycnic coordinates x,y,ρ, Ri is expressed as the ratio between M2≡N−2 and the squared diapycnal shear Sρ2=ρ/g2∂u/∂ρ2+∂v/∂ρ2, Ri=M2/Sρ2. This could suggest that a decrease (increase) in stratification brings a decrease (increase) in dynamic stability in Cartesian coordinates, but a stability increase (decrease) in isopycnic coordinates. The apparently different role of stratification arises because S and Sρ are related through the stratification itself, Sρ=S/N2. In terms of characteristic times, this is equivalent to τ≡Sρ=to2/td, which is interpreted as a critical dynamic time τ that equals the buoyancy period to≡N−1 normalized by the ratio td/to, where td=S−1 is the deformation time. Here we follow simple arguments and use field data from three different regions (island shelf break, Gulf Stream and Mediterranean outflow) to endorse the usefulness of the isopycnal approach. In particular, we define the reduced squared diapycnal shear σρ2=Sρ2−M2 and compare it with the reduced squared vertical σ2=S2−N2, both being positive (negative) for unstable (stable) conditions. While both Ri and σ2 remain highly variable for all stratification conditions, the mean σρ2 values approach Sρ2 with increasing stratification. Further, the field data follow the relation σρ2=1−Ri/N2Ri, with a subcritical Ri=0.22 for both the island shelf break and the Mediterranean outflow. We propose σρ2 and Sρ2 to be good indexes for the occurrence of effective mixing under highly stratified conditions.
Multilayer Metamaterials with Vertical Cavities for High-Efficiency Transmittance with Metallic Components in the Visible Spectrum
Authors: Li Huiyu , Zhao Lin , Chen Guangwei , Hu Guoqing , Zhou Zhehai
Published: October 2024

Metasurfaces are opening promising flexibilities to reshape the wavefront of electromagnetic waves. Notable optical phenomena are observed with the tailored surface plasmon, which is excited by metallic components in the visible spectrum. However, metamaterial or metasurface devices utilizing metallic materials encounter the challenge of low transmission efficiency, particularly within the visible spectrum. This study proposes a multilayer design strategy to enhance their transmission efficiency. By incorporating additional metal layers for improvements in the transmission efficiency and dielectric layers as spacers, cavities are formed along the propagation direction, enabling the modulation of transmittance and reflection through a process mimicking destructive interference. An analytical model simplified with the assumption of deep-subwavelength-thick metal layers is proposed to predict the structural parameters with optimized transmittance. Numerical studies employing the rigorous coupled wave analysis method confirmed that the additional metal layers significantly improve the transmittance. The introduction of the extra metal and dielectric layers enhances the transmission efficiency in specific spectral regions, maintaining a controllable passband and transmittance. The results indicate that the precise control over the layers’ thicknesses facilitates the modulation of peak-to-valley ratios and the creation of comb-like filters, which can be further refined through controlled random variation in the thickness. Furthermore, when the thickness of the silver layer followed an arithmetic sequence, a multilayer structure with a transmittance of approximately 80% covering the entire visible spectrum could be achieved. Significantly, the polarization extinction ratio and the phase delay of the incident beams could still be modulated by adjusting the geometrical structure and parameters of the multilayer metamaterial for diversified functionalities.
Enhancing the Cooling of a Rotating Mirror in a Laguerre–Gaussian Cavity Optorotational System via Nonlinear Cross-Kerr Interaction
Authors: Cao Xinyue , Huang Sumei , Deng Li , Chen Aixi
Published: October 2024

The cooling of a macroscopic mechanical oscillator to its quantum ground state is an important step for achieving coherent control over mechanical quantum states. Here, we theoretically study the cooling of a rotating mirror in a Laguerre–Gaussian (L-G) cavity optorotational system with a nonlinear cross-Kerr (CK) interaction. We discuss the effects of the nonlinear CK coupling strength, the cavity detuning, the power of the input Gaussian beam, the topological charge (TC) of the L-G cavity mode, the mass of the rotating mirror, and the cavity length on the cooling of the rotating mirror. We find that it is only possible to realize the improvement in the cooling of the rotating mirror by the nonlinear CK interaction when the cavity detuning is less than the mechanical frequency. Compared to the case without the nonlinear CK interaction, we find that the cooling of the rotating mirror can be improved by the nonlinear CK interaction at lower laser powers, smaller TCs of the L-G cavity mode, larger masses of a rotating mirror, and longer optorotational cavities. We show that the cooling of the rotating mirror can be enhanced by the nonlinear CK interaction by a factor of about 23.3 compared to that without the nonlinear CK interaction.
Performance Exploration of Optical Wireless Video Communication Based on Adaptive Block Sampling Compressive Sensing
Authors: Li Jinwang , Yao Haifeng , Dong Keyan , Song Yansong , Liu Tianci , Cao Zhongyu , Wang Weihao , Zhang Yixiang , Jiang Kunpeng , Liu Zhi
Published: October 2024

Optical wireless video transmission technology combines the advantages of high data rates, enhanced security, large bandwidth capacity, and strong anti-interference capabilities inherent in optical communication, establishing it as a pivotal technology in contemporary data transmission networks. However, video data comprises a large volume of image information, resulting in substantial data flow with significant redundant bits. To address this, we propose an adaptive block sampling compressive sensing algorithm that overcomes the limitations of sampling inflexibility in traditional compressive sensing, which often leads to either redundant or insufficient local sampling. This method significantly reduces the presence of redundant bits in video images. First, the sampling mechanism of the block-based compressive sensing algorithm was optimized. Subsequently, a wireless optical video transmission experimental system was developed using a Field-Programmable Gate Array chip. Finally, experiments were conducted to evaluate the transmission of video optical signals. The results demonstrate that the proposed algorithm improves the peak signal-to-noise ratio by over 3 dB compared to other algorithms, with an enhancement exceeding 1.5 dB even in field tests, thereby significantly optimizing video transmission quality. This research contributes essential technical insights for the enhancement of wireless optical video transmission performance.
Polymer-Based Optical Guided-Wave Biomedical Sensing: From Principles to Applications
Authors: Nagar Malhar A. , Janner Davide
Published: October 2024

Polymer-based optical sensors represent a transformative advancement in biomedical diagnostics and monitoring due to their unique properties of flexibility, biocompatibility, and selective responsiveness. This review provides a comprehensive overview of polymer-based optical sensors, covering the fundamental operational principles, key insights of various polymer-based optical sensors, and the considerable impact of polymer integration on their functional capabilities. Primary attention is given to all-polymer optical fibers and polymer-coated optical fibers, emphasizing their significant role in “enabling” biomedical sensing applications. Unlike existing reviews focused on specific polymer types and optical sensor methods for biomedical use, this review highlights the substantial impact of polymers as functional materials and transducers in enhancing the performance and applicability of various biomedical optical sensing technologies. Various sensor configurations based on waveguides, luminescence, surface plasmon resonance, and diverse types of polymer optical fibers have been discussed, along with pertinent examples, in biomedical applications. This review highlights the use of biocompatible, hydrophilic, stimuli-responsive polymers and other such functional polymers that impart selectivity, sensitivity, and stability, improving interactions with biological parameters. Various fabrication techniques for polymer coatings are also explored, highlighting their advantages and disadvantages. Special emphasis is given to polymer-coated optical fiber sensors for biomedical catheters and guidewires. By synthesizing the latest research, this review aims to provide insights into polymer-based optical sensors’ current capabilities and future potential in improving diagnostic and therapeutic outcomes in the biomedical field.
Cyclic Isothiocyanate Goitrin Impairs Lotus japonicus Nodulation, Affects the Proteomes of Nodules and Free Mesorhizobium loti, and Induces the Formation of Caffeic Acid Derivatives in Bacterial Cultures
Authors: Jeong Seungwoo , Schütz Vadim , Demir Fatih , Preusche Matthias , Huesgen Pitter , Bigler Laurent , Kovacic Filip , Gutbrod Katharina , Dörmann Peter , Schulz Margot
Published: October 2024

The continuous release of glucosinolates into the soil by Brassicaceae root exudation is a prerequisite to maintaining toxic levels of breakdown products such as isothiocyanates (ITCs). ITCs influence plant and microbial diversity in ecosystems, while fungi and Rhizobiaceae are particularly injured. Studies explaining the molecular mechanisms of the negative effects are presently limited. Therefore, we investigated the early effects of cyclic ITC goitrin on proteomes of the host and symbiotic Mesorhizobium loti in the nodules of Lotus japonicus and of free-living bacteria. In the nodules, many host proteins had a higher abundance, among them, peroxidases and pathogenesis-related PR-10 proteins functioning in the abscisic-acid-activated signaling pathway. In the microsymbiont, transporter proteins as a prominent group are enhanced; some proteins involved in N-fixation decreased. The proteomes give a report about the loss of immunity suppression resulting in the termination of symbiosis, which initiates nodule senescence. Free-living M. loti are severely damaged, indicated, i.a., by a decrease in transporter proteins, the assumed candidates for goitrin protein complex formation, and high proteolysis. The production of chicoric acid by the accompanying bacteria is inhibitory for M. loti but connected to goitrin elimination, as confirmed by mass spectrometric (MS) analysis. In summary, the nodulation process is severely affected by goitrin, causing nodule dysfunction and failed nodule development. N deficiency conditions leads to yellowish leaves and leaf abscission.
Chemical Composition and Biological Activity of Hypericum Species—H. hirsutum, H. barbatum, H. rochelii
Authors: Baljak Jovan , Bogavac Mirjana , Karaman Maja , Srđenović Čonić Branislava , Vučković Biljana , Anačkov Goran , Kladar Nebojša
Published: October 2024

St. John’s wort (Hypericum perforatum, Hypericaceae) is the most well-known species in the genus Hypericum, which comprises several hundred species. This study investigates the biological and phytochemical potential of the under-researched Hypericum species, H. hirsutum, H. barbatum, and H. rochelii. A high level of similarity between the chemical profiles of H. hirsutum and H. barbatum and the official source of the herbal drug (H. perforatum) was shown, but a higher content of quercetin and rutin was also found in all three evaluated species (116–230 µg/g dry herb). The highest amount of phenolics (195 mg GAE/g) was recorded in H. hirsutum extract, while the highest amount of flavonoids (47 mg QE/g) was recorded in H. barbatum extract. The evaluated species were excellent scavengers of DPPH, OH, and NO radicals, as well as strong ferric ion reducers in the FRAP test. Prominent monoamine oxidase A and α-glucosidase inhibition was observed, compared to modest inhibition of monoamine oxidase B, α-amylase, and acetylcholinesterase. High activity against Gram-positive MRSA S. aureus was demonstrated for the tested species, with MIC/MBC values recorded at 12.5 µg/mL. Antifungal activity against Candida strains was not observed. The obtained results emphasize the need for further investigation of species of the genus Hypericum to discover potentially new sources of biologically active compounds.
Ascophyllum nodosum Extract Improves Olive Performance Under Water Deficit Through the Modulation of Molecular and Physiological Processes
Authors: Dias Maria Celeste , Figueiras Rui , Sousa Marta , Araújo Márcia , de Oliveira José Miguel P. Ferreira , Pinto Diana C. G. A. , Silva Artur M. S. , Santos Conceição
Published: October 2024

The olive tree is well adapted to the Mediterranean climate, but how orchards based on intensive practices will respond to increasing drought is unknown. This study aimed to determine if the application of a commercial biostimulant improves olive tolerance to drought. Potted plants (cultivars Arbequina and Galega) were pre-treated with an extract of Ascophyllum nodosum (four applications, 200 mL of 0.50 g/L extract per plant), and were then well irrigated (100% field capacity) or exposed to water deficit (50% field capacity) for 69 days. Plant height, photosynthesis, water status, pigments, lipophilic compounds, and the expression of stress protective genes (OeDHN1—protective proteins’ dehydrin; OePIP1.1—aquaporin; and OeHSP18.3—heat shock proteins) were analyzed. Water deficit negatively affected olive physiology, but the biostimulant mitigated these damages through the modulation of molecular and physiological processes according to the cultivar and irrigation. A. nodosum benefits were more expressive under water deficit, particularly in Galega, promoting height (increase of 15%) and photosynthesis (increase of 34%), modulating the stomatal aperture through the regulation of OePIP1.1 expression, and keeping OeDHN1 and OeHSP18.3 upregulated to strengthen stress protection. In both cultivars, biostimulant promoted carbohydrate accumulation and intrinsic water-use efficiency (iWUE). Under good irrigation, biostimulant increased energy availability and iWUE in Galega. These data highlight the potential of this biostimulant to improve olive performance, providing higher tolerance to overcome climate change scenarios. The use of this biostimulant can improve the establishment of younger olive trees in the field, strengthen the plant’s capacity to withstand field stresses, and lead to higher growth and crop productivity.
Formation of Fine Structures in Incompressible Hall Magnetohydrodynamic Turbulence Simulations
Authors: Miura Hideaki
Published: October 2024

Hall magnetohydrodynamic simulations are often carried out to study the subjects of instabilities and turbulence of space and nuclear fusion plasmas in which sub-ion-scale effects are important. Hall effects on a structure formation at a small scale in homogeneous and isotropic turbulence are reviewed together with a simple comparison to a (non-Hall) MHD turbulence simulation. A comparison between MHD and Hall MHD simulations highlights a fine structure in Hall MHD turbulence. This enhancement of the fine structures by the Hall term can be understood in relation to the whistler waves at the sub-ion scale. The generation and enhancement of fine-scale sheet, filamentary, or tubular structures do not necessarily contradict one another.
A Review of the Homogenized Lattice Boltzmann Method for Particulate Flow Simulations: From Fundamentals to Applications
Authors: Marquardt Jan E. , Krause Mathias J.
Published: October 2024

The homogenized lattice Boltzmann method (HLBM) has emerged as a flexible computational framework for studying particulate flows, providing a monolithic approach to modeling pure fluid flows and flows through porous media, including moving solid and porous particles, within a unified framework. This paper presents a thorough review of HLBM, elucidating its underlying principles and highlighting its diverse applications to particle-laden flows in various fields as reported in literature. These include studies leading to new fundamental knowledge on the settling of single arbitrarily shaped particles as well as application-oriented research on wall-flow filters, hindered settling, and evaluation of the damage potential during particle transport. Among the strengths of HLBM are its monolithic approach, which allows seamless simulation of different fluid-solid interactions, and its ability to handle arbitrary particle shapes, including irregular and concave geometries, while resolving surface interactions to capture local forces. In addition, its parallel scheme based on the lattice Boltzmann method (LBM) results in high computational efficiency, making it suitable for large-scale simulations, even though LBM requires small time steps. Important future development needs are identified, including the addition of a lubrication force correction model, performance enhancements, such as support for hybrid parallelization and GPU, and the extension of compatible contact models to accommodate concave shapes. These advances promise expanded capabilities for HLBM and broader applicability for solving complex real-world problems.
Research on Adaptive Edge Detection Method of Part Images Using Selective Processing
Authors: Li Yaohe , Jin Long , Liu Min , Mo Youtang , Zheng Weiguang , Ge Dongyuan , Bai Yindi
Published: October 2024

Visual quality inspection of part surfaces is a crucial step in industrial production. Image edge detection is a common technique for assessing the surface conditions of parts. However, current methods have limitations, including poor noise filtering, low adaptability, and inadequate accuracy of edge detection. To overcome these challenges, this study proposes an adaptive edge detection method for part images using selective processing. Firstly, this method divides the input image into noise, edge, and noise-free blocks, followed by selective mixed filtering to remove noise while preserving original image details. Secondly, a four-parameter adaptive selective edge detection algorithm model is constructed, which adaptively adjusts parameter values based on image characteristics to address issues of missing edges and false detections, thereby enhancing the adaptability and accuracy of the method. Moreover, by comparing and adjusting the four parameter values, different edge information can be selectively detected, enabling rapid acquisition of desired edge detection results and improving detection efficiency and flexibility. Experimental results demonstrated that the proposed method outperformed existing classical techniques in both subjective and objective evaluations, maintaining stable detection under varying noise conditions. Thus, this method was validated for its effectiveness and stability, enhancing production efficiency in manufacturing processes of parts.
Child and Adolescent Mental Health in a Period of Fewer COVID-19-Related Restrictions in an Urban Population in Germany
Authors: Konopka Anna , Führer Amand , Binder Mascha , Diexer Sophie , Frese Thomas , Gekle Michael , Girndt Matthias , Gottschick Cornelia , Hoell Jessica , Klee Bianca , Kreilinger Katharina , Moor Irene , Rosendahl Jonas , Sedding Daniel , Klusmann Jan-Henning , Mikolajczyk Rafael , Raberger Katja
Published: October 2024

The aim of this study was to assess the mental health situation of children and adolescents during a period of less strict COVID-19-pandemic-related measures after the first pandemic wave. This cross-sectional study was conducted in July 2021 by carrying out an online survey among children and adolescents (aged 10–18 years) from Halle (Saale), Germany (n = 233). The questionnaire measured important aspects of mental health among young people, namely health-related quality of life (HRQoL, using the self-report version of the KIDSCREEN-10), mental health problems in general (using the SDQ), depressive symptoms (using the CES-DC), and psychosomatic complaints (using the HBSC symptom checklist). In addition, other important health issues such as sleep behavior and related difficulties, disordered eating, and any positive consequences of the pandemic were addressed. The results were analyzed using descriptive statistics. A total of 223 children participated in the survey. About 69.7% of the participating children and adolescents had a high HRQoL, while 10.5% displayed abnormal results on the SDQ. There were indications of emotional problems in 16.5% of the participants based on the SDQ subscales. Almost 44% of the participants were screened as positive for depressive symptoms on the CES-DC, with girls and older adolescents being more likely to be affected. This also applied for psychosomatic complaints. Here, irritability was experienced at least once a week or more frequently by 58.9% of the children and adolescents. Although we had a small sample size, this study showed a high prevalence of mental health problems regarding the SDQ and HRQoL. However, our study population showed a better mental health than comparable studies conducted earlier in the pandemic. Depressive symptoms were still substantially higher than those in pre-pandemic data. We hypothesize that this might reflect the fact that there were a few COVID-19-related restrictions at the time when our survey took place. Based on these findings, we assume that the mental health of children and adolescents differed between different phases in the pandemic.
IL-11 Expression in Systemic Sclerosis Is Dependent on Caspase-1 Activity but Does Not Increase Collagen Deposition
Authors: McFalls Caya M. , Connolly Lianne M. , Fustakgi Alfred G. , Artlett Carol M.
Published: October 2024

Background: Interleukin-11 (IL-11) is increased in patients with systemic sclerosis (SSc) and is thought to play a role in fibrosis. Many studies have reported decreased fibrosis when IL-11 is blocked, but few have examined factors that induce IL-11 expression. Because fibrosis has been linked to activated inflammasomes driving caspase-1 maturation and the secretion of IL-1β, we set out to determine if IL-11 expression was dependent on caspase-1 activity. Methods: Primary lung fibroblast cell lines derived from patients with SSc, IPF (fibrotic control), and healthy individuals were cultured at low passage. Gene expression for IL-11 and the IL-11 receptor (IL-11Rα1) was analyzed using qPCR and normalized to the control, and collagen production was measured using Sirius Red. Results: SSc and IPF fibroblasts expressed significantly more IL-11 transcripts than normal cells (3.35-fold and 9.97-fold more, p = 0.0396 and p = 0.0023, respectively). IL-11Rα1 was expressed 2.32-fold and 2.27-fold more in SSc and IPF (p = 0.0004 and p = 0.0032, respectively) than in normal cells. In SSc fibroblasts, inhibition of caspase-1 with YVAD decreased IL-11 expression by 49.59% (p = 0.0016) but did not affect IL-11Rα1 expression (p > 0.05). IL-11 expression was increased 2.97-fold with TGF-β1 (p = 0.0030) and 22.24-fold with IL-1β (p < 0.0001), while the expression of IL-11Rα1 was not induced with these two cytokines. LPS increased IL-11 expression in normal fibroblasts 1.52-fold (p = 0.0042), which was abolished with YVAD (p < 0.0001). IL-11Rα1 gene transcripts were also increased with LPS 1.50-fold (p = 0.0132), but YVAD did not inhibit this expression. In these studies, we were unable to detect IL-11 protein nor were we able to induce COL1A1 expression or increase the total amount of collagen secreted by fibroblasts with human recombinant IL-11. Conclusions: IL-11 and its receptor, IL-11Rα1, are both elevated in fibrosis. IL-11 expression is dependent on inflammasome activation of caspase-1 and the downstream cytokines TGF-β1 and IL-1β, while IL-11Rα1 was only dependent on NF-kB.
Assessment of the Intra- and Inter-Observer Reliability of Beef Cattle Mobility Scoring Performed by UK Veterinarians and Beef Farmers
Authors: Fitzsimmonds Hannah May , Tunstall Jay , Fishwick John , Mahendran Sophie Anne
Published: October 2024

Background: Lameness in cattle negatively affects welfare and productivity. Early identification of lameness allows for prompt treatment, and mobility scoring allows for herd-level prevalence data to be monitored. The reliability of a four-point mobility scoring system was investigated when used by beef farmers and veterinary surgeons. Methods: An online questionnaire that contained forty video clips of beef cattle was created for mobility scoring performed by farmers and vets. Results: The Fleiss kappa coefficient for inter-observer agreement across all 81 respondents and all videos was 0.34, which showed fair agreement. Beef farmers generally had lower agreement than vets (0.29 vs. 0.38). Vets had significantly higher inter-observer reliability compared to beef farmers (p = 0.035). Overall, Cohen’s kappa coefficient for intra-observer agreement across all respondents varied from 0.085 (slight agreement) to 0.871 (almost perfect agreement). Limitations: The survey was only available online, which may have limited distribution and engagement. The recruitment of participants was not specific to differing levels of previous experience in mobility scoring. The mobility scoring was not performed in person, which could be more reflective of clinical application. Conclusions: The application of a four-point mobility scoring system for beef cattle had fair inter-observer reliability and a wide range of intra-observer reliability, but this is poorer than previously reported. This presents a challenge for the identification of lame beef cattle at both the individual and herd levels.
Vaccination Timing Does Not Affect Growth Performance but Enhances Antibody Titers in Previously Vaccinated Calves
Authors: DeHaan Erin R. , Rusche Warren C. , Smith Zachary K.
Published: October 2024

The objective of this study was to evaluate the health, growth performance, and antibody titers of previously vaccinated newly weaned calves administered a respiratory and clostridial vaccine compared to no vaccination upon arrival. Single-sourced, newly weaned beef steers [n = 70; initial body weight (BW) = 254 ± 5.9 kg] were allotted to 10 pens (n = 5 pens/treatment; 7 steers/pen). Steers were blocked by BW in a randomized complete block design and assigned to one of two treatments: VAC (vaccinated for respiratory and clostridial species upon arrival) or NOVAC (not vaccinated upon arrival). Steers were individually weighed on d 0 (arrival), 1, 21, and 42 for growth performance measures. Whole blood samples were collected (n = 3 steers/pen) on d 1, 21, and 42 via jugular venipuncture for antibody titer responses. Depression scores (DS) of 0 (normal) to 4 (moribund) were recorded daily for each individual steer for 21 d. Dry matter intake as a percentage of BW tended (p = 0.07) to increase for the NOVAC group compared to the VAC group. No treatment × day interactions (p ≥ 0.50) were observed for DS or antibody titers. Growth performance was unaffected by vaccination but vaccinated calves had greater antibody titer responses throughout the 42 d study.
Advances in Portable Optical Microscopy Using Cloud Technologies and Artificial Intelligence for Medical Applications
Authors: Molani Alessandro , Pennati Francesca , Ravazzani Samuele , Scarpellini Andrea , Storti Federica Maria , Vegetali Gabriele , Paganelli Chiara , Aliverti Andrea
Published: October 2024

The need for faster and more accessible alternatives to laboratory microscopy is driving many innovations throughout the image and data acquisition chain in the biomedical field. Benchtop microscopes are bulky, lack communications capabilities, and require trained personnel for analysis. New technologies, such as compact 3D-printed devices integrated with the Internet of Things (IoT) for data sharing and cloud computing, as well as automated image processing using deep learning algorithms, can address these limitations and enhance the conventional imaging workflow. This review reports on recent advancements in microscope miniaturization, with a focus on emerging technologies such as photoacoustic microscopy and more established approaches like smartphone-based microscopy. The potential applications of IoT in microscopy are examined in detail. Furthermore, this review discusses the evolution of image processing in microscopy, transitioning from traditional to deep learning methods that facilitate image enhancement and data interpretation. Despite numerous advancements in the field, there is a noticeable lack of studies that holistically address the entire microscopy acquisition chain. This review aims to highlight the potential of IoT and artificial intelligence (AI) in combination with portable microscopy, emphasizing the importance of a comprehensive approach to the microscopy acquisition chain, from portability to image analysis.
Explosion Detection Using Smartphones: Ensemble Learning with the Smartphone High-Explosive Audio Recordings Dataset and the ESC-50 Dataset
Authors: Takazawa Samuel K. , Popenhagen Sarah K. , Ocampo Giraldo Luis A. , Hix Jay D. , Thompson Scott J. , Chichester David L. , Zeiler Cleat P. , Garcés Milton A.
Published: October 2024

Explosion monitoring is performed by infrasound and seismoacoustic sensor networks that are distributed globally, regionally, and locally. However, these networks are unevenly and sparsely distributed, especially at the local scale, as maintaining and deploying networks is costly. With increasing interest in smaller-yield explosions, the need for more dense networks has increased. To address this issue, we propose using smartphone sensors for explosion detection as they are cost-effective and easy to deploy. Although there are studies using smartphone sensors for explosion detection, the field is still in its infancy and new technologies need to be developed. We applied a machine learning model for explosion detection using smartphone microphones. The data used were from the Smartphone High-explosive Audio Recordings Dataset (SHAReD), a collection of 326 waveforms from 70 high-explosive (HE) events recorded on smartphones, and the ESC-50 dataset, a benchmarking dataset commonly used for environmental sound classification. Two machine learning models were trained and combined into an ensemble model for explosion detection. The resulting ensemble model classified audio signals as either “explosion”, “ambient”, or “other” with true positive rates (recall) greater than 96% for all three categories.
ViTDroid: Vision Transformers for Efficient, Explainable Attention to Malicious Behavior in Android Binaries
Authors: Syed Toqeer Ali , Nauman Mohammad , Khan Sohail , Jan Salman , Zuhairi Megat F.
Published: October 2024

Smartphones are intricately connected to the modern society. The two widely used mobile phone operating systems, iOS and Android, profoundly affect the lives of millions of people. Android presently holds a market share of close to 71% among these two. As a result, if personal information is not securely protected, it is at tremendous risk. On the other hand, mobile malware has seen a year-on-year increase of more than 42% globally in 2022 mid-year. Any group of human professionals would have a very tough time detecting and removing all of this malware. For this reason, deep learning in particular has been used recently to overcome this problem. Deep learning models, however, were primarily created for picture analysis. Despite the fact that these models have shown promising findings in the field of vision, it has been challenging to fully comprehend what the characteristics recovered by deep learning models are in the area of malware. Furthermore, the actual potential of deep learning for malware analysis has not yet been fully realized due to the translation invariance trait of well-known models based on CNN. In this paper, we present ViTDroid, a novel model based on vision transformers for the deep learning-based analysis of opcode sequences of Android malware samples from large real-world datasets. We have been able to achieve a false positive rate of 0.0019 as compared to the previous best of 0.0021. However, this incremental improvement is not the major contribution of our work. Our model aims to make explainable predictions, i.e., it not only performs the classification of malware with high accuracy, but it also provides insights into the reasons for this classification. The model is able to pinpoint the malicious behavior-causing instructions in the malware samples. This means that our model can actually aid in the field of malware analysis itself by providing insights to human experts, thus leading to further improvements in this field.
Setting the Social Media Stage, a Narrative Review: The Role of Theory and Research in Understanding Adolescent Online Sexual Health Information-Seeking
Authors: Allsop Yvonne
Published: October 2024

This narrative review offers a deep dive into the theoretical and empirical literature on adolescent online health information-seeking behavior, specifically in relation to sexual health. It presents ways in which motivational influences impact adolescent social media use to seek sexual health information and offers insight into how Longo’s comprehensive and integrated model for understanding health information, communication, and information-seeking and self-determination theory may be used as frameworks for improved understanding in adolescent use of social media for seeking information related to sexual health. The main objectives of this article are, first, to examine the existing literature pertaining to social media, namely its main characteristics and uses by adolescents, its use as an educational tool, and its relation to health information; second, to explore information-seeking and learning through online platforms, particularly social media; and third, to provide a framework utilizing self-determination theory to better understand adolescent motivation in health-seeking behavior. This manuscript advances current knowledge and practices in supporting adolescent skill-development surrounding information-seeking and evaluation behaviors. Such practices will only become more beneficial as young people seek information in various settings (e.g., online, social media platforms, and artificial intelligence systems), particularly sensitive information such as that related to sexual health.
The Being and the Ought to Be of Citizenship in European Social Innovation Discourse
Authors: Talón Villacañas Alba
Published: October 2024

Social Innovation is defined as both a concept and a tool for social change that, in recent decades, has formed the backbone of numerous policies implemented by the European Commission. However, part of the academic literature identifies several limitations in the discursive potentialities presented within the institutional framework. Accordingly, the aim of this article is to examine how European social policies on Social Innovation conceptualise the ‘being’ and ‘ought to be’ of citizenship, or the subject, from a critical Foucauldian perspective, with a view to problematising its implications for the analysis of the social reality represented in these policies. To this end, a qualitative strategy employing discourse analysis and the ‘logics of critical explanation’ approach is utilised, analysing 26 institutional documents from the European Commission issued between 2010 and 2024. The findings indicate that this discursive institutional framework construes citizenship as embodying a rational, active, capable, and conscious subject, committed to solving social problems. This conception of the ‘being’ of a citizen implies a significant transformation in the ‘ought to be’ of that citizen. If citizens are deemed capable of understanding and transforming their environment, they are thereby responsible for ensuring their own well-being and equipping themselves with the necessary skills to adapt to economic change, transforming them into “neoliberal subjects” within a Foucauldian framework. This new normativity appears to naturalise the functioning of social and economic structures and their dynamics, resulting in an undialectical analysis of social realities.
EU Environmental Protection in Regard to Sustainable Development: Myth or Reality?
Authors: Špelić Ivana , Mihelić-Bogdanić Alka
Published: October 2024

According to conclusions agreed to in the 1995 Report of the World Summit for Social Development and the 2015 Sustainable Development Summit, seventeen sustainable development goals (SDGs) have been ratified and published as the 2030 Agenda for Sustainable Development. In 2022, the 8th Environment Action Programme was legally agreed upon, following the six European Green Deal priorities. These SDGs serve as a constant reminder of the importance of globally coordinated actions in compliance with the theory of sustainable development. However, more than a constant reminder, this international agreement should become the foundation for necessary change. On 22 July 2024, the daily global average temperature reached a new record high. The EU treaties signed between 1951 and 2007 laid the foundation for the creation of EU environmental policy. However, those EU treaties, along with environmental policy, form merely a non-binding and minimum set of priorities without any sanctions imposed for illegal practices. In 2021, EU member countries adopted the European Climate Law as the first legally binding document seeking to achieve goals set by the Paris Agreement and the European Green Deal. Any further EU sustainable development policies are dependent on global cooperation as a key element of survival. With the EU’s dependent on the rest of the world for its energy, the forcing of any obligatory change will be hard to achieve. This proves the importance of the 17th SDG, agreed in 2015. Only global partnership for sustainable development can prevent further damage to our ecosystem and achieve priorities set by the EU and UN agendas. The review aims to present the connection between sustainable development (SD) goals defined by the European Commission, for which the most important aspects are the need to meet the environmental requirements to protect future needs in the long run, and to confront the shortcomings of European law-making practices, in which most crucial reforms are presented as non-binding legal acts. Finally, in 2024 members of the European Parliament established an extended list of environmental crimes to be regarded as punishable offences and replaced the Environmental Crime Directive, making criminal activities and offences potentially legally punishable; however, it is yet to be seen how this initiative will be incorporated within the national legislations of each EU member country and to what extent.
A Bayesian Hierarchical Model for 2-by-2 Tables with Structural Zeros
Authors: Stamey James , Stamey Will
Published: October 2024

Correlated binary data in 2 × 2 tables have been analyzed from both the frequentist and Bayesian perspectives, but a fully Bayesian hierarchical model has not yet been proposed. This is a commonly used model for correlated proportions when considering, for example, a diagnostic test performance where subjects with negative results are tested a second time. We consider a new hierarchical Bayesian model for the parameters resulting from a 2 × 2 table with a structural zero. We investigate the performance of the hierarchical model via simulation. We then illustrate the usefulness of the model by showing how a set of historical studies can be used to build a predictive distribution for a new study that can be used as a prior distribution for both the risk ratio and marginal probability of a positive test. We then show how the prior based on historical 2 × 2 tables can be used to power a future study that accounts for pre-experimental uncertainty. High-quality prior information can lead to better decision-making by improving precision in estimation and by providing realistic numbers to power studies.
Forecasting Mortality Trends: Advanced Techniques and the Impact of COVID-19
Authors: Nalmpatian Asmik , Heumann Christian , Pilz Stefan
Published: October 2024

The objective of this research is to evaluate four distinct models for multi-population mortality projection in order to ascertain the most effective approach for forecasting the impact of the COVID-19 pandemic on mortality. Utilizing data from the Human Mortality Database for five countries—Finland, Germany, Italy, the Netherlands, and the United States—the study identifies the generalized additive model (GAM) within the age–period–cohort (APC) analytical framework as the most promising for precise mortality forecasts. Consequently, this model serves as the basis for projecting the impact of the COVID-19 pandemic on future mortality rates. By examining various pandemic scenarios, ranging from mild to severe, the study concludes that projections assuming a diminishing impact of the pandemic over time are most consistent, especially for middle-aged and elderly populations. Projections derived from the superior GAM-APC model offer guidance for strategic planning and decision-making within sectors facing the challenges posed by extreme historical mortality events and uncertain future mortality trajectories.
Levels of Confidence and Utility for Binary Classifiers
Authors: Zhang Zhiyi
Published: October 2024

Two performance measures for binary tree classifiers are introduced: the level of confidence and the level of utility. Both measures are probabilities of desirable events in the construction process of a classifier and hence are easily and intuitively interpretable. The statistical estimation of these measures is discussed. The usual maximum likelihood estimators are shown to have upward biases, and an entropy-based bias-reducing methodology is proposed. Along the way, the basic question of appropriate sample sizes at tree nodes is considered.