bluuebunny/crossref_metadata_2025 huggingface dataset:
Microbiological Characteristics of Beef Sausage Enriched With Roselle (Hibiscus sabdariffa L.) Sepal Extract
Authors: Ghorbani Sharif , Jafarian Sara , Soltani Mahdi Sharifi , Nasiraie Leila Roozbeh
Published: November 2024

Adding plant extracts to sausage and other meat products is very important to improve their quality, safety, and durability. The aim of this study was to evaluate the microbiological properties of beef sausage enriched with roselle (Hibiscus sabdariffa L.) sepal extract. The total content of phenolic and flavonoid compounds in hydroalcoholic extract of Roselle sepals was measured by Folin‐Ciocalteu test and aluminum chloride colorimetric method, and antioxidant activity was measured by DPPH method. Pectin was used to encapsulate the extract. The characteristics of capsules, including particle size, zeta potential, and capsule efficiency were measured. Minimum Inhibitory Concentration (MIC) and Minimum Bactericidal Concentration (MBC) of extracts were performed by tube dilution method. Microbial tests were performed on sausage treatment samples. Analysis of the obtained data was done using SPSS and Excel software. The study revealed that the total phenolic and flavonoid compounds in the extract were 174.6 mg of gallic acid per gram and 16.8368 mg of quercetin, respectively. The extract displayed the highest antioxidant activity at elevated concentrations. Particle size ranged from 16.833 to 640.534 μm. The zeta potential and capsule efficiency were found to be satisfactory. Compared to the encapsulated extract, the free roselle extract better inhibited Staphylococcus aureus (s. aureus), Salmonella typhimurium (S. typhimurium), and Escherichia coli (E.coli). During storage until day 20, these bacteria did not grow in the free or encapsulated extract groups. However, S. aureus appeared in the free extract group from day 25 and the encapsulated extract group from day 20. Roselle extract has antimicrobial properties that can improve the quality and safety of beef sausage during storage.
A Site‐Wise Reliability Analysis of the ABCD Diffusion Fractional Anisotropy and Cortical Thickness: Impact of Scanner Platforms
Authors: Pan Yezhi , Hong L. Elliot , Acheson Ashley , Thompson Paul M. , Jahanshad Neda , Zhu Alyssa H. , Yu Jiaao , Chen Chixiang , Ma Tianzhou , Liu Ho‐Ling , Veraart Jelle , Fieremans Els , Karcher Nicole R. , Kochunov Peter , Chen Shuo
Published: November 2024

The Adolescent Brain and Cognitive Development (ABCD) project is the largest study of adolescent brain development. ABCD longitudinally tracks 11,868 participants aged 9–10 years from 21 sites using standardized protocols for multi‐site MRI data collection and analysis. While the multi‐site and multi‐scanner study design enhances the robustness and generalizability of analysis results, it may also introduce nonbiological variances including scanner‐related variations, subject motion, and deviations from protocols. ABCD imaging data were collected biennially within a period of ongoing maturation in cortical thickness and integrity of cerebral white matter. These changes can bias the classical test–retest methodologies, such as intraclass correlation coefficients (ICC). We developed a site‐wise adaptive ICC (AICC) to evaluate the reliability of imaging‐derived phenotypes while accounting for ongoing brain development. AICC iteratively estimates the population‐level age‐related brain development trajectory using a weighted mixed model and updates age‐corrected site‐wise reliability until convergence. We evaluated the test–retest reliability of regional fractional anisotropy (FA) measures from diffusion tensor imaging and cortical thickness (CT) from structural MRI data for each site. The mean AICC for 20 FA tracts across sites was 0.61 ± 0.19, lower than the mean AICC for CT in 34 regions across sites, 0.76 ± 0.12. Remarkably, sites using Siemens scanners consistently showed significantly higher AICC values compared with those using GE/Philips scanners for both FA (AICC = 0.71 ± 0.12 vs. 0.46 ± 0.17, p < 0.001) and CT (AICC = 0.80 ± 0.10 vs. 0.69 ± 0.11, p < 0.001). These findings demonstrate site‐and‐scanner related variations in data quality and underscore the necessity for meticulous data curation in subsequent association analyses.
Self‐Attention Mechanisms‐Based Laryngoscopy Image Classification Technique for Laryngeal Cancer Detection
Authors: Kang Yi‐Fan , Yang Lie , Hu Yi‐Fan , Xu Kai , Cai Lan‐Jun , Hu Bin‐Bin , Lu Xiang
Published: November 2024

Background

The early diagnosis of laryngeal cancer (LCA) is crucial for prognosis, driving our search for an accurate, precise, and sensitive deep learning model to assist in LCA detection.

Methods

We collected 5768 laryngoscopic images from 1462 patients and created the intelligent laryngeal cancer detection system (ILCDS) based on Swin‐Transformer. Following training and validation, we assessed the ILCDS performance on the internal and external test sets and compared it with previous convolutional neural network (CNN) models and three professional laryngologists.

Results

The ILCDS outperformed the six CNNs, with the highest accuracy of 92.78% and an area under the curve (AUC) of 0.9732. Despite a slight drop in performance on external sets, the ILCDS maintained the best superiority, with 85.79% accuracy and an AUC of 0.9550. Surpassing professional laryngologists, the ILCDS achieved 92.00% accuracy.

Conclusions

The ILCDS offers high accuracy and stability for LCA detection, reducing the burden on laryngologists.
Depression detection in dementia: A diagnostic accuracy systematic review and meta analysis update
Authors: Atchison Kayla , Nazir Alaia , Wu Pauline , Seitz Dallas , Watt Jennifer A. , Goodarzi Zahra
Published: November 2024

Background

Depression is common in persons with dementia and is often under‐detected and under‐treated. It is critical to understand which available tools accurately detect depression in the context of dementia.

Methods

We updated our systematic review completed in 2015. The search strategy of our original review was replicated in Medline, Embase, and PsycINFO. Studies describing the use of a tool to identify depression in persons with dementia, compared to a criterion standard, and reporting diagnostic accuracy outcomes were included in the review update. Pooled prevalence estimates of major depression and pooled estimates of diagnostic accuracy outcomes (i.e., sensitivity [SN], specificity [SP]) for tools were calculated.

Results

Three studies were included of the 8980 returned from the database search and were added to the prior 20 articles from the 2015 review. The Cornell Scale for Depression in Dementia (CSDD), Geriatric Depression Scale (GDS)−15 item, Neuropsychiatric Inventory‐Depression items (NPI‐D), and Depression in Old Age Scale (DIA‐S) were evaluated in the three studies. Two new studies were added to the existing pooled prevalence estimate of major depression (29%, 95% confidence interval [CI] = 21.6%–36.5%, n = 17) and pooled diagnostic accuracy estimate for the CSDD at the best cut‐off (SN = 0.83, 95% CI = 0.74–0.90; SP = 0.81, 95% CI = 0.69–0.89). New pooled diagnostic accuracy estimates were completed for the CSDD (cut‐off ≥12) (SN = 0.61, 95% CI = 0.42–0.77; SP = 0.83, 95% CI = 0.76–0.88), GDS‐15 (best cut‐off) (SN = 0.65, 95% CI = 0.40–0.83; SP = 0.72, 95% CI = 0.55–0.85), and Montgomery Asberg Depression Rating Scale (MADRS) (best cut‐off) (SN = 0.77, 95% CI = 0.67–0.85; SP = 0.68, 95% CI = 0.60‐0.75).

Conclusions

The CSDD continues to have the most evidence for depression case finding in persons living with dementia. The CSDD and Hamilton Depression Rating Scale have the highest sensitivities and may be recommended for use over other common tools like the GDS‐15 and MADRS. Newly identified tools like the NPI‐D and DIA‐S require further study before they can be recommended for use in practice.
Modeling of Heat Transfer and Airflow Inside Evacuated Tube Collector With Heat Storage Media: Experimental Validation Powered by Artificial Neural Network
Authors: Elbrashy Amr , Elgohr Abdelrahman , Elshennawy Abdullah , Rashad Maher , El‐fakharany Magda
Published: November 2024

Solar air heater (SAH) is a widely employed technology for harnessing solar thermal energy in numerous applications. Contemporary research optimizes designs within identical spatial constraints to maximize energy output. However, there is a recognized need to conduct analytical validation to stimulate the experimental setup and formulate an artificial neural network (ANN) model to govern and predict the operation system. This investigation involved developing and assessing an evacuated tube solar air heater (ETSAH) integrated with annulus‐filled heat storage media. Furthermore, this study introduced an ANN model and analytical solution to predict performance parameters, representing a noteworthy contribution. The proposed ANN model achieved its optimal validation performance with a mean square error of 5.4018 × 10−6 after 11 epochs within 31 of training. Also, correlation findings show that the optimal architecture of a feed‐forward backpropagation is achieved when the 5‐40‐40‐40‐2 model architecture is used. In this case, there are five neural nodes in the input layer that represent timing, temperature, radiation, and airflow rate. The power output of the ETSAH device shows a strong correlation with the flow rate, reaching its peak at 0.05 kg/s with a value of 2261 W and dropping to 368 W at 0.006 kg/s. Correspondingly, the greatest energy efficiency was measured at airflow rates of 0.05, 0.01, and 0.006 kg/s, accounting for 48.38%, 27.32%, and 19.65%, respectively.
Comparative Analysis of Heat Exchanger Models for Phase Change Material Melting Process: Experimental and Numerical Investigation
Authors: Saleh Hussein Hatem , Mussa Munther Abdullah
Published: November 2024

Thermal energy storage systems using PCM offer promising solutions for efficient thermal applications. This study aims to provide valuable insights into the PCM melting process and compare the thermal performance of different heat exchanger models. The experimental rig is carefully designed to simulate a shell and tube heat exchanger with five longitudinal copper fins at specific conditions. Three distinct models of the heat exchanger, labeled Models A, B, and C, were examined for their heat transfer efficiency during the melting process. Numerical simulations were conducted for the three models and compared with experimental results. Model A represented the benchmark model. It had uniform fin length, location, and angle. Model B was the modified design aimed at enhancing melting progress. These modifications included a longer lower fin, a shorter side fin compared to the reference, and a lower fin angle to optimize heat transfer performance. Model C incorporates further design modifications, with a longer lower fin, a shorter top fin, and different lower fin location. Numerical simulations and experimental observations revealed significant differences in heat transfer performance among the three models. The average heat transfer rates, measured up to the critical decline point, are crucial parameters for practical applications. A comparison among the three models showed that Model B surpassed the average heat transfer rate up to the critical point of Models A and C by 10% and 4%, respectively, demonstrating its superior practical applicability.
Optimization of Thermal Performance by Enhancing Natural Convection of Diverse Configurations of Fin Heat Sink Filled With Nano‐Enhanced Phase Change Materials: A Numerical Study
Authors: Omi Mallik Nadim Arman
Published: November 2024

Electronic components require faster propagation of heat to prevent overheating as well as to maintain a stable operating condition. Incorporating phase change materials (PCMs) in fin heat sinks (FHSs) can be a viable solution to enhance natural convection. In the present work, an extensive investigation has been carried out on three types (square, circular, and triangular) of FHSs filled with PCMs to find the best combinations for the thermal cooling of a heat sink. To increase the thermal conductivity of the PCMs, Cu–water nanofluid is added. The effects of three types (paraffin wax, stearic acid, and polyethylene glycol) of PCMs have been studied. Nondimensional equations have been solved numerically by using Galerkin's finite element method. A parametric investigation has been conducted by varying the Rayleigh number within the range of 103–106 to calculate the Nusselt number. Results reveal that a heat sink with PCMs can reduce the temperature rise by 6.41% and increase the Nusselt number by 4.6% compared to a heat sink without PCMs. As the height of the fins increases from 10 to 16 mm, thermal efficiency increases. Moreover, square FHSs show the best thermal performance by reducing the temperature rise by as much as 13.41% compared to circular and triangular FHSs. Therefore, this comparative study shows that the dimensional configurations of FHSs with varying PCMs have a great impact on thermal performance and thus provide one the opportunity to obtain an effective arrangement of heat sinks.
Submarine Groundwater Discharge at a Mega‐Tidal Beach
Authors: Craddock Raymond D. , Mohammed Aaron A. , Tamborski Joseph J. , Kurylyk Barret L.
Published: November 2024

Tidally influenced groundwater systems in coastal environments represent important mixing zones of fresh groundwater and circulating seawater, manifesting as submarine groundwater discharge (SGD). Water circulation induced by tidal pumping enhances the exchange of chemicals between aquifers and coastal waters and thereby influences the biogeochemistry of coastal zones. Here, we report the results of an SGD field study conducted at a steep, mega‐tidal sand and gravel beach along the Canadian coast of the Bay of Fundy, a region with the world's highest tides (semi‐diurnal tidal ranges exceeding 10 m). Several physical and geochemical measurement techniques were employed to document the spatiotemporal SGD variability. SGD was directly sampled from seepage meters installed over multiple tidal cycles and two summer campaigns. SGD rates were estimated from tracer mass balances for radon (August 2020) and radium isotopes (July 2021) over multiple tidal cycles. Tidally averaged SGD estimates from seepage meters ranged from 12 to 87 cm d−1, with an average of 42 cm d−1, while radon tracing yielded a tidally averaged rate of 86 cm d−1. SGD estimates from radium tracing ranged from 23 to 43 cm d−1 along the shoreline and 6 to 71 cm d−1 offshore, depending on the estimated residence times. Radionuclide analyses of seepage meter waters suggest that the residence time of seawater circulation through the aquifer is less than 1 day. SGD measurements in mega‐tidal settings are rare, and the results suggest that the combination of the steep slopes, highly permeable sediments and high tidal range drive very high seepage rates for diffusive SGD. Salinity gradients in the intertidal zone demonstrate that SGD is primarily comprised of circulated seawater with negligible fresh groundwater. Although the freshwater proportion of SGD is relatively low, the large volumetric rates of total SGD can still contribute large amounts of terrestrially derived and remineralized nutrients to coastal waters.
Antimony Flux and Transport Dynamics in a Mining‐Impacted River Is Linked to Catchment Hydrodynamics and Climate Oscillations
Authors: Wichman Gretchen , Johnston Scott G. , Maher Damien T.
Published: November 2024

We investigate how seasonal flow variations and a climatic regime that is dominated by the El Niño–Southern Oscillation (ENSO) influence Sb flux dynamics in an Australian river impacted by mining. Sampling (n = 496) spans a hydrologically complex 7‐year period of drought, bushfires and floods from 2016 to 2023, during which 17% of samples exceeded the Sb drinking water guideline concentration (3 μg L−1). Aqueous Sb (SbAq) concentration–discharge (C–Q) relationships are non‐continuous/non‐linear across the flow range, with chemodynamic behaviour at moderate flows reflecting hydrological connection to the primary Sb‐source area combined with variable dilution. In contrast chemostatic behaviour occurred at extreme low and high flows, reflecting hydrological disconnection from the source area and persistent dilution, respectively. SbAq was significantly positively correlated (p < 0.01, Spearman's ρ = 0.58) with a Q index representing the proportional contribution of sub‐catchment flow from the mineral‐field area, suggesting sufficient localised rainfall in the Sb mining‐impacted sub‐catchment contributes to downstream peaks in SbAq concentrations. Aqueous and particulate Sb (SbP) annual loads (La) during the study period spanned 24–5174 and 1.2–2820 kg, respectively and were strongly flow dependant with extreme interannual variability reflecting dry and wet years. We extrapolate daily load‐daily discharge (Ld–Qd) relationships for SbAq and SbP to estimate Ld over a 53‐year period (1970–2023) of continuous Q data (mean total Sb La = 1865 kg ± [SE] 247). Positive correlations between the annual Southern Oscillation Index and both Sb La (p < 0.05) and proportional SbP La over 53 years suggests ENSO fluctuations influence annual Sb transport dynamics. Upstream SbP load estimates correspond with downstream estimates of coastal floodplain sedimentary Sb mass, with approximately 10%–45% of the estimated SbP exported downstream since approximately 1880 accumulated on the Macleay coastal floodplain. Data suggest at current rates of export, complete flushing‐leaching of mine tailings‐derived Sb from the upper Macleay catchment may take in the order approximately 600–1000 years.
Subsurface Sediment Transport in the Shallow Vadose Zone of Fine‐Textured Soils With Heterogenous Preferential Flows
Authors: Ford William , Williams Mark , Mumbi Rose
Published: November 2024

Subsurface sediment transport in tile‐drained landscapes occurs through macropores; however, little is known regarding how heterogeneous preferential flows influence fluxes. We performed laboratory rainfall simulations on 10 intact core lysimeters from a tile‐drained field in Indiana, USA to study the impacts of surface and subsurface erosion on sediment leachate in heterogeneous preferential flow paths. Seven rainfall simulations were conducted to assess the impact of rainfall intensity on the leachate of surface eroded sediments (three events), and the impact of antecedent conditions on subsurface eroded sediments (four events). Cumulative sediment yield, linear mixed effects modelling, and hysteresis analyses were performed for all events. Results were presented in a series of four case studies. Results showed that surface sediment leachate concentration and yield were tightly linked to the filtration capacity of lysimeters, with more than 2/3rd of sediment originating from a single lysimeter, despite similar flow leachate volumes from each. Rainfall intensity significantly impacted the transport of surface eroded sediment at the highest intensity. Subsurface sediment erosion from undisturbed macropores was low compared to surface soils, but we found contrasting controls on sediment concentrations at low and high antecedent moistures that were equally important to sediment leachate yields. Disturbed macropores produced comparable sediment yields to surface erosion and behaved similarly to soil pipes in terms of erosion mechanics. Hysteresis results generally highlighted contrasting results for surface and subsurface sources but suggest that the prominence of slow flow, low‐concentration leachate sources can alter the interpretation of results in field‐scale applications. Our findings underscore an array of processes and pathways for sediment transport in the shallow vadose zone, and results will be useful for evaluating new model formulations.
YOLOv7‐XAI: Multi‐Class Skin Lesion Diagnosis Using Explainable AI With Fair Decision Making
Authors: Veeramani Nirmala , Jayaraman Premaladha
Published: November 2024

Skin cancer, a prevalent and potentially life‐threatening condition, demands accurate and timely detection for effective intervention. It is an uncontrolled growth of abnormal cells in the human body. Studies are underway to determine if a skin lesion is benign (non‐cancerous) or malignant (cancerous), but the biggest challenge for a doctor is determining the type of skin cancer. As a result, determining the type of tumour is crucial for the right course of treatment. In this study, we introduce a groundbreaking approach to multi‐class skin cancer detection by harnessing the power of Explainable Artificial Intelligence (XAI) in conjunction with a customised You Only Look Once (YOLOv7) architecture. Our research focuses on enhancing the YOLOv7 framework to accurately discern 8 different skin cancer classes, including melanoma, basal cell carcinoma, and squamous cell carcinoma. The YOLOv7 model is the robust backbone, enriched with features tailored for precise multi‐class classification. Concurrently, integrating XAI elements, Local Interpretable Modal‐agnostic Explanations (LIME) and Shapley Additive Explanations (SHAP) ensures transparent decision‐making processes, enabling healthcare professionals to interpret and trust the model's predictions. This innovative synergy between YOLOv7 and XAI heralds a new era in interpretability, resulting in high‐performance skin cancer diagnostics. The obtained results are 96.8%, 94.2%, 95.6%, and 95.8%, evaluated with popular quantitative metrics such as accuracy, precision, recall, and F1 score, respectively.
Artificial intelligence in the diagnosis of cerebrovascular diseases using magnetic resonance imaging: A scoping review
Authors: Wang Yituo , Zhang Zeru , Peng Ying , Chen Silu , Zhou Shuai , Liu Jiqiang , Gao Song , Zhu Guangming , Han Cong , Wu Bing
Published: November 2024

The field of radiology is currently undergoing revolutionary changes owing to the increasing application of artificial intelligence (AI). This scoping review identifies and summarizes the technical methods and clinical applications of AI applied to magnetic resonance imaging of cerebrovascular diseases (CVDs). Preferred Reporting Items for Systematic reviews and Meta‐Analyses extension for Scoping Reviews was adopted and articles listed in PubMed and Cochrane databases from January 1, 2018 to December 31, 2023, were assessed. In total, 67 articles met the eligibility criteria. We obtained a general overview of the field, including lesion types, sample sizes, data sources, and databases and found that nearly half of the studies used multisequence magnetic resonance as the input. Both classical machine learning and deep learning were widely used. The evaluation metrics varied according to the five main algorithm tasks of classification, detection, segmentation, estimation, and generation. Cross‐validation was primarily used with only one third of the included studies using external validation. We also illustrate the key questions of the CVD research studies and grade the clinical utility of their AI solutions. Although most attention is devoted to improving the performance of AI models, this scoping review provides information on the availability of algorithms, reliability of external validations, and consistency of evaluation metrics and may facilitate improved clinical applicability and acceptance.
Bonferroni‐Type Tests for Return Predictability With Possibly Trending Predictors
Authors: Astill Sam , Harvey David I. , Leybourne Stephen J. , Taylor A. M. Robert
Published: November 2024

The Bonferroni
test is widely used in empirical studies investigating predictability in asset returns by strongly persistent and endogenous predictors. Its formulation, however, only allows for a constant mean in the predictor, seemingly at odds with many of the predictors used in practice. We establish the asymptotic size and local power properties of the
test, and the corresponding Bonferroni
‐test, under a local‐to‐zero specification for a linear trend in the predictor, revealing that size and power depend on the magnitude of the trend for both. To rectify this, we develop with‐trend variants of the operational Bonferroni
and
tests. However, where a trend is not present in the predictor, we show that these tests lose (both finite sample and asymptotic local) power relative to the extant constant‐only versions of the tests. In practice, uncertainty will necessarily exist over whether a linear trend is genuinely present in the predictor or not. To deal with this, we also develop hybrid tests based on union‐of‐rejections and switching mechanisms to capitalise on the relative power advantages of the constant‐only tests when a trend is absent (or very weak) and the with‐trend tests otherwise. A further extension allows the use of a conventional
‐test where the predictor appears to be weakly persistent. We show that, overall, our recommended hybrid test can offer excellent size and power properties regardless of whether or not a linear trend is present in the predictor, or the predictor's degrees of persistence and endogeneity. An empirical application illustrates the practical relevance of our new approach.

JEL Classifications: C22, C12, G14
Synergistic Effect of Salinomycin With Budesonide on TNBC Regression via EMT Reversal and Autophagy Induction
Authors: Sarkar Shilpi , Ghosh Siddhartha Sankar
Published: November 2024

Triple‐negative breast cancer (TNBC) poses a significant clinical challenge due to its aggressive nature, lack of specific therapeutic targets, and drug resistance. Chemotherapy resistance in TNBC is largely driven by the abnormal activation of epithelial‐to‐mesenchymal transition (EMT) and the associated cancer stem cell‐like characteristics. The combination of multiple chemotherapeutic drugs has shown promise as a treatment approach for TNBC. This study evaluates the efficacy of a novel combination therapy involving the anti‐inflammatory drug Budesonide and Salinomycin, which targets cancer stem cells. Co‐administration of Budesonide and Salinomycin demonstrated a synergistic effect in inhibiting TNBC cell growth by activating the intrinsic apoptosis pathway. It induced a 2‐ to 3‐fold increase in intracellular reactive oxygen species (ROS) generation and a 25%–30% rise in mitochondrial membrane depolarization. Additionally, extensive signaling studies revealed that the co‐treatment specifically targeted multiple signaling nodes, limiting downstream crosstalk. The combination also enhanced autophagic activity by inhibiting the AKT/mTOR pathway and reduced cell migration and stemness by suppressing the EMT process. Therefore, the combination of Budesonide and Salinomycin offers a novel therapeutic approach for TNBC.
Lactoperoxidase Inhibition of Celecoxib Derivatives Containing the Pyrazole Linked‐Sulfonamide Moiety: Antioxidant Capacity, Antimicrobial Activity, and Molecular Docking Studies
Authors: Bayrak Songül , Gerni Serpil , Öztürk Cansu , Almaz Züleyha , Bayrak Çetin , Kılınç Namık , Özdemir Hasan
Published: November 2024

Celecoxib derivatives that contain the pyrazole‐linked sulfonamide moiety were synthesized, and the in vitro inhibitory impacts of the aforesaid compounds against the lactoperoxidase (LPO) enzyme were researched. To this end, LPO was purified using the affinity chromatography technique with a yield of 12.63% (319.23‐fold). The results showed that the aromatic pyrazole compound (compound 1) containing 2,3‐dimethoxyphenyl functional groups was the most effective LPO inhibitor with a Ki value of 3.2 ± 0.7 nM and noncompetitive inhibition type. The second section of the study tested the previously synthesized compounds to reveal their antioxidant and antimicrobial properties. The above‐mentioned compound also displayed high activity levels compared to standard antibiotics and antifungals, while all other compounds also showed antibacterial activity. In the three antioxidant methods we used, the compound with 2,5‐dimethoxy phenyl groups obtained from the reaction of the aromatic pyrazole compound with propionic anhydride in the presence of NEt3 displayed the highest activity. Furthermore, molecular docking and molecular mechanics studies were conducted to complement and validate the experimental findings. The results obtained from these computational analyses are highly consistent with the experimental data.
Inside‐out tibial tunnel drilling technique is a reliable approach for all‐inside ACL reconstruction: A longitudinal MRI assessment
Authors: Oliveira João Pedro , d'Almeida Otília C. , Sampaio Ricardo , Noronha José Carlos
Published: November 2024

Purpose

To longitudinally evaluate sockets localization, tunnel morphological changes and graft maturation after the inside‐out tibial tunnel drilling technique for all‐inside Anterior Cruciate Ligament Reconstruction (ACLR). We hypothesized that due the necessary angle for the inside‐out reaming procedure, the described technique could input changes in the tibial socket.

Methods

Fourteen knees treated with the same all‐inside ACLR technique were randomly assigned for a magnetic resonance evaluation. All patients were operated by the same surgeon and performed the same follow‐up rehabilitation protocol. Socket's localization, shape and widening, as well as graft maturation and integration, were evaluated intraoperatively at 6 months and 4 years after surgery.

Results

Both femoral and tibial tunnels had an expected increase at 6 months follow‐up. The widening was larger in the tibial tunnel (12.6 ± 10.0% vs. 9.1 ± 8.5%), yet this difference was not statistically different. Tibial tunnel was well centred in the tibial plateau and the integration of the graft was higher in the tibial socket. Four years after surgery, there was a general reduction of diameter in both tunnels. The tunnel occlusion rate was 33.3% for tibia and 16.7% for femur.

Conclusions

Overall, our results show that within a 4‐year follow‐up period, the inside‐out tibial tunnel drilling technique for all‐inside ACLR represents a safe technique that did not influence the tibial socket position nor tunnel widening or graft maturation in the long term.

Level of Evidence

Level IV.
Diagnostic performance of deep learning for leg length measurements on radiographs in leg length discrepancy: A systematic review
Authors: Lezak Bradley A. , Pruneski James A. , Oeding Jacob F. , Kunze Kyle N. , Williams Riley J. , Alaia Michael J. , Pearle Andrew D. , Dines Joshua S. , Samuelsson Kristian , Pareek Ayoosh
Published: November 2024

Purpose

To systematically review the literature regarding machine learning in leg length discrepancy (LLD) and to provide insight into the most relevant manuscripts on this topic in order to highlight the importance and future clinical implications of machine learning in the diagnosis and treatment of LLD.

Methods

A systematic electronic search was conducted using PubMed, OVID/Medline and Cochrane libraries in accordance with Preferred Reporting Items for Systematic Review and Meta‐Analysis guidelines. Two observers independently screened the abstracts and titles of potential articles.

Results

A total of six studies were identified in the search. All measurements were calculated using standardized anterior‐posterior long‐leg radiographs. Five (83.3%) of the studies used measurements of the femoral length, tibial length and leg length to assess LLD, whereas one (16.6%) study used the iliac crest height difference to quantify LLD. The deep learning models showed excellent reliability in predicting all length measurements with intraclass correlation coefficients ranging from 0.98 to 1.0 and mean absolute error (MAE) values ranging from 0.11 to 0.45 cm. Three studies reported measurements of LLD, and the convolutional neural network model showed the lowest MAE of 0.13 cm in predicting LLD.

Conclusions

Machine learning models are effective and efficient in determining LLD. Implementation of these models may reduce cost, improve efficiency and lead to better overall patient outcomes.

Clinical Relevance

This review highlights the potential of deep learning (DL) algorithms for accurate and reliable measurement of lower limb length and leg length discrepancy (LLD) on long‐leg radiographs. The reported mean absolute error and intraclass correlation coefficient values indicate that the performance of the DL models was comparable to that of radiologists, suggesting that DL‐based assessments could potentially be used to automate the measurement of lower limb length and LLD in clinical practice.

Level of Evidence

Level IV.
Leveraging digital twins for improved orthopaedic evaluation and treatment
Authors: Dean Michael C. , Oeding Jacob F. , Diniz Pedro , Seil Romain , Samuelsson Kristian ,   ESSKA Artificial Intelligence Working Group
Published: November 2024

Purpose

The purpose of this article is to explore the potential of digital twin technologies in orthopaedics and to evaluate how their integration with artificial intelligence (AI) and deep learning (DL) can improve orthopaedic evaluation and treatment. This review addresses key applications of digital twins, including surgical planning, patient‐specific outcome prediction, augmented reality‐assisted surgery and simulation‐based surgical training.

Methods

Existing studies on digital twins in various domains, including engineering, biomedical and orthopaedics are reviewed. We also reviewed advancements in AI and DL relevant to digital twins. We focused on identifying key benefits, challenges and future directions for the implementation of digital twins in orthopaedic practice.

Results

The review highlights that digital twins offer significant potential to revolutionise orthopaedic care by enabling precise surgical planning, real‐time outcome prediction and enhanced training. Digital twins can model patient‐specific anatomy using advanced imaging techniques and dynamically update with real‐time data, providing valuable insights during surgery and postoperative care. However, challenges such as the need for large‐scale data sets, technological limitations and integration issues must be addressed to fully realise these benefits.

Conclusion

Digital twins represent a promising frontier in orthopaedic research and practice, with the potential to improve patient outcomes and enhance surgical precision. To enable widespread adoption, future research must focus on overcoming current challenges and further refining the integration of digital twins with AI and DL technologies.

Level of Evidence

Level V.
Older Amphibian Larvae Are More Sensitive to Ultraviolet Radiation and Experience More Sublethal Carryover Effects Post‐Metamorphosis
Authors: Lundsgaard Niclas U. , Franklin Craig E. , Cramp Rebecca L.
Published: November 2024

Elevated ultraviolet radiation (UVR) is postulated as one of multiple, interrelated environmental stressors driving amphibian population declines globally. However, key knowledge gaps remain in elucidating the link between elevated UVR and amphibian declines in a changing climate, including whether timing and irradiance of UVR exposure in early life dictates the onset of detrimental carryover effects post‐metamorphosis. In this study, striped marsh frog larvae (Limnodynastes peronii) were exposed to UVR at one of two different irradiances for up to 7 days, either as hatchlings (Gosner stage 23) or as older larvae (Gosner stage 25−28). These animals were then reared to metamorphosis in the absence of UVR to examine independent and interactive carryover effects throughout development. Older larvae were more sensitive to UVR than hatchlings, with 53.1% and 15.6% mortality in larvae exposed to high and low irradiance respectively, compared with no mortality of hatchlings in either irradiance treatment. Irradiance and timing of UVR exposure had interactive effects on larval body length, causing stunted growth patterns and a lack of compensatory growth following UVR exposure, particularly in animals exposed to high irradiance UVR later in development. Timing of UVR exposure also determined the severity of carryover effects into metamorphosis, including delayed metamorphosis and the first published account (to our knowledge) of latent UVR‐induced depigmentation in an amphibian. These findings highlight how acute changes to the larval UVR exposure regime can impact on amphibian health later in life, with implications for our understanding of the effects of climate change on UVR‐related amphibian declines.
Explicit Commutativity for Lamé Linear Time‐Varying Differential Systems
Authors: Ibrahim Salisu , Boulaaras Salah , Rababah Abedallah , Iqbal Mujahid
Published: November 2024

This article studies the commutativity and sensitivity of the Lamé linear time‐varying systems (LTVSs), and investigates the effects of disturbances on such systems. The commutative pair for the Lamé LTVS of order is found, that is, a new Lamé LTVS of order is derived using the explicit commutative theories for zero initial conditions (ICs). For the case of nonzero ICs, the commutativity between the connected input–output of Lamé systems and is studied. New and simple explicit commutative theories and conditions for second‐order LTVSs are derived, simplifying the use of commutativity for practical and industrial scenarios. These findings enable us to analyse the commutativity, sensitivity, robustness and stability of Lamé systems, and to determine the effects of disturbances. The explicit results presented in this article are supported by simulations and verified by examples and constitute a significant contribution to science and engineering applications.
Inkjet printing of mixed layers comprising multinary semiconductor quantum dots and charge transport materials for light‐emitting diode displays
Authors: Motomura Genichi , Ohisa Satoru , Uematsu Taro , Kuwabata Susumu , Kameyama Tatsuya , Torimoto Tsukasa , Fujisaki Yoshihide
Published: November 2024

Quantum dots (QDs) are important luminescent structures with applications in wide‐color‐gamut displays requiring exceptional color reproducibility. Multinary semiconductor QDs are expected to serve as eco‐friendly materials to replace conventional QDs owing to the narrow spectral widths and tunable bandgaps of these QDs. However, the application of multinary QDs, which tend to exhibit defect‐related emissions, to QD light‐emitting diode (QLED) displays will require electroluminescence to be obtained from QLEDs incorporating inkjet‐printed emitting layers. The present work examines QLEDs exhibiting vibrant color emissions based on blue‐emitting Zn–Se–Te QDs, green‐emitting Ag–In–Ga–S QDs, and red‐emitting Ag–Cu–In–Ga–S QDs. Each such QLED contains QD emitting layers comprising a mixture of charge transport materials. The spectra obtained from these RGB QLEDs fabricated by spin‐coating show very high color purity. Passive matrix QLED displays incorporating these QDs are also fabricated by inkjet printing to demonstrate the high color purity that can be obtained from multinary QDs in displays. In conjunction with passive matrix driving, these displays produce clear moving images with vibrant electroluminescence originating from the multinary QDs. The present results indicate that these QDs have significant potential for utilization in wide‐color‐gamut displays.
Methodology Used in Studies Aimed at Measuring Fetal Soft Tissues by 2D Ultrasound for the Screening of Large for Gestational Age Fetuses
Authors: Lerma‐Puertas Diego , Aguerri Ana , Pardina Gema , Paules Cristina , Lerma‐Irureta David , Oros Daniel , Ruiz‐Martínez Sara
Published: November 2024

Management of suspected large for gestational age (LGA) fetuses remains unclear because ultrasound‐estimated fetal weight (EFW) is not accurate. This was a systematic review of observational studies on fetal soft tissues measurements used alone or in combination to create a new EFW formula, to improve the screening for LGA fetuses. Studies were scored using a predefined set of independently agreed methodological criteria and an overall quality score was assigned for study design, statistical analysis, and reporting methods. There is a need to standardize methodologies for soft fetal tissue measurements. We propose a set of suggestions for this purpose.
Near‐Infrared Dual‐Band Frequency Comb Generation from a Silicon Resonator
Authors: Zhong Keyi , Zhang Yaojing , Zhang Shuangyou , Zhang Yuanfei , Li Yuan , Qin Yue , Wang Yi , Boggio Jose M. Chavez , Sun Xiankai , Shu Chester , Del'Haye Pascal , Tsang Hon Ki
Published: November 2024

Benefitting from the mature, cost‐effective, and scalable manufacturing capabilities of complementary metal‐oxide‐semiconductor (CMOS) technology, silicon photonics has facilitated the seamless and monolithic integration of diverse functionalities, including optical sources, modulators, and photodetectors. Microresonators can generate multiple coherent optical frequency comb lines and serve as optical sources. However, at the telecom band, silicon suffers from two‐photon absorption and free‐carrier absorption, which severely hampers the realization of microcombs from a single silicon chip at telecom wavelengths until now. In this paper, a novel approach is presented and demonstrated with near‐infrared dual‐band frequency combs from a multimode silicon resonator. With a single pumping configuration, dual‐band combs are generated from the interaction between the pump and Raman Stokes fields by involving two different optical mode families but with similar group velocities. It is observed that the pump power required to generate dual‐band combs is as low as 0.7 mW. The work in bringing telecom microcombs to the silicon platform will advance silicon photonics for the next generation of monolithically integrated technology based on a single silicon chip, enabling new possibilities for further exploring silicon photonics‐based applications in optical telecommunications, sensing, and quantum metrology in the telecom band using a monolithic single silicon chip.
Preparation of Diisooctyl Phosphate‐Modified Ultra‐Small Zinc Oxide Nanoparticle and Investigation of Its Tribological Properties as Additive in Alkylnaphthalene
Authors: Li Zhenghao , Fan Shuguang , Song Ningning , Yang Guangbin , Zhang Chunli , Yu Laigui , Zhang Yujuan , Zhang Shengmao
Published: November 2024

ZnO nanoparticle surface‐modified by diisooctyl phosphate (P204) was prepared by liquid‐phase in situ surface modification technique with zinc acetate as the raw material, P204 as the modifier and anhydrous ethanol as the solvent. The morphology and microstructure of the P204‐ZnO nanoparticle were characterised by transmission electron microscopy, X‐ray diffraction and Fourier transform infrared spectrometry. Its thermal stability was evaluated by thermogravimetric analysis; and its tribological properties as the additive in alkylnaphthalene were evaluated with an SRV‐5 friction and wear tester in reciprocal sliding mode. The results show that the as‐prepared P204‐ZnO nanoparticle has an average particle size of about 4 nm and a P204 content of about 42% (mass fraction); and the surface modifier is grafted onto the surface of ZnO nanoparticle by physical adsorption. With a mass fraction of 0.5% in alkylnaphthalene base oil, P204‐ZnO nano‐additive can mildly reduce the friction coefficient and drastically reduce the wear rate of the steel–steel sliding pair. This is due to the formation of the composite tribofilm via the adsorption and deposition of the nano‐additive on rubbed steel surfaces as well as the tribochemical reactions of the modifier P204 yielding phosphate and of steel substrate yielding iron oxides. The as‐formed composite tribofilm with a thickness of about 20 nm, consisting of phosphate and iron oxides as the binder as well as deposited ZnO nanoparticle as the filling phase, is responsible for the excellent friction‐reducing and antiwear abilities of P204‐ZnO nano‐additive for the steel sliding contact.
On collection schemes and Gaifman's splitting theorem
Authors: Kurahashi Taishi , Minami Yoshiaki
Published: November 2024

We study model theoretic characterizations of various collection schemes over from the viewpoint of Gaifman's splitting theorem. Among other things, we prove that for any and , the following are equivalent:

satisfies the collection scheme for formulas.

For any , if , and , then and .

For any , if , then .

Here, is the unique satisfying . We also investigate strong collection schemes and parameter‐free collection schemes from the similar perspective.
Realization of finite groups as isometry groups and problems of minimality
Authors: Chocano Pedro J.
Published: November 2024

A finite group is said to be realized by a finite subset of a Euclidean space if the isometry group of is isomorphic to . We prove that every finite group can be realized by a finite subset consisting of points, where is a generating system for . We define as the minimum number of points required to realize in for some . We establish that provides a sharp upper bound for when considering minimal generating sets. Finally, we explore the relationship between and the isometry dimension of , that is, defined as the least dimension of the Euclidean space in which can be realized.
Reducing the Distance Between Anode and Cathode to Make Handheld Nerve Stimulators More Selective in Nerve Fascicle Selection: Report of Two Cases
Authors: Marina Lucas , Sanz Elisa , Cristobal Lara , Maldonado Andres A.
Published: November 2024

Precise nerve fascicle identification is important in certain peripheral nerve procedures. Although we believe bipolar nerve stimulation with intraoperative neuromonitoring is a superior method, many rely on clinical response evoked by handheld monopolar nerve stimulators. We present a modification in the use of the latter for a more precise fascicle stimulation. A 55‐year‐old man with a right high brachial plexus injury and a 47‐year‐old woman with a left median nerve schwannoma were scheduled for exploration and ulnar‐to‐musculocutaneous nerve transfer, and for surgical excision respectively. Intraoperatively, we used a disposable handheld monopolar nerve stimulator in an unorthodox way, placing the anode right next to the cathode (both touching the same nerve fascicle). In the first case, a fascicle that showed flexor carpi ulnaris (FCU) and intrinsic hand muscle contraction with standard stimulation (anode placed on patient's skin), showed only FCU activation with our modified method, and was chosen as donor. A BMC grade M4 elbow flexion was achieved 9 months after surgery. In the second case, safe schwannoma excision was performed after our modified stimulation technique caused thenar muscle activation in a single, unaffected fascicle, while standard monopolar stimulation showed activation in several fascicles. No unexpected motor/sensory deficits were noted during follow‐up. This report shows an easy modification in the use of handheld nerve stimulators that improves selectiveness when looking for nerve fascicles.
Stabilization for degenerate equations with drift and small singular term
Authors: Fragnelli Genni , Mugnai Dimitri , Sbai Amine
Published: November 2024

We consider a degenerate/singular wave equation in lone dimension, with drift and in presence of a leading operator that is not in divergence form. We impose a homogeneous Dirichlet boundary condition where the degeneracy occurs and a boundary damping at the other endpoint. We provide some conditions for the uniform exponential decay of solutions for the associated Cauchy problem.