bluuebunny/crossref_metadata_2025 huggingface dataset:
Ethnicity data resource in population-wide health records: completeness, coverage and granularity of diversity
Authors: Pineda-Moncusí Marta , Allery Freya , Delmestri Antonella , Bolton Thomas , Nolan John , Thygesen Johan H. , Handy Alex , Banerjee Amitava , Denaxas Spiros , Tomlinson Christopher , Denniston Alastair K. , Sudlow Cathie , Akbari Ashley , Wood Angela , Collins Gary S. , Petersen Irene , Coates Laura C. , Khunti Kamlesh , Prieto-sAlhambra Daniel , Khalid Sara ,   on behalf of the CVD-COVID-UK/COVID-IMPACT Consortium
Published: February 2024

Intersectional social determinants including ethnicity are vital in health research. We curated a population-wide data resource of self-identified ethnicity data from over 60 million individuals in England primary care, linking it to hospital records. We assessed ethnicity data in terms of completeness, consistency, and granularity and found one in ten individuals do not have ethnicity information recorded in primary care. By linking to hospital records, ethnicity data were completed for 94% of individuals. By reconciling SNOMED-CT concepts and census-level categories into a consistent hierarchy, we organised more than 250 ethnicity sub-groups including and beyond “White”, “Black”, “Asian”, “Mixed” and “Other, and found them to be distributed in proportions similar to the general population. This large observational dataset presents an algorithmic hierarchy to represent self-identified ethnicity data collected across heterogeneous healthcare settings. Accurate and easily accessible ethnicity data can lead to a better understanding of population diversity, which is important to address disparities and influence policy recommendations that can translate into better, fairer health for all.
Exploring the effects of competition and predation on the success of biological invasion through mathematical modeling
Authors: Rivera-Estay Viviana , Córdova-Lepe Fernando , Moreno-Gómez Felipe N. , Benitez Hugo , Gutiérrez Rodrigo
Published: February 2024

Biological invasions are a major cause of species extinction and biodiversity loss. Exotic predators are the type of introduced species that have the greatest negative impact, causing the extinction of hundreds of native species. Despite this, they continue to be intentionally introduced by humans. Understanding the causes that determine the success of these invasions is a challenge within the field of invasion biology. Mathematical models play a crucial role in understanding and predicting the behavior of exotic species in different ecosystems. This study examines the effect of predation and competition on the invasion success of an exotic generalist predator in a native predator-prey system. Considering that the exotic predator both consumes the native prey and competes with the native predator, it is necessary to study the interplay between predation and competition, as one of these interspecific interactions may either counteract or contribute to the impact of the other on the success of a biological invasion. Through a mathematical model, represented by a system of ordinary differential equations, it is possible to describe four different scenarios upon the arrival of the exotic predator in a native predator-prey system. The conditions for each of these scenarios are described analytically and numerically. The numerical simulations are performed considering the American mink (Mustela vison), an invasive generalist predator. The results highlight the importance of considering the interplay between interspecific interactions for understanding biological invasion success.
Effect of post-weld heat-treatment and solid-state thermomechanical treatment on the properties of the AA6082 MIG welded joints
Authors: El-Fahhar Hossam Hemdan , Gadallah Elshafey Ahmed , Habba Mohamed I. A. , Seleman Mohamed M. El-Sayed , Ahmed Mohamed M. Z. , Mohamed Abdelkarim Yousif , Fouad Ramy A.
Published: February 2024

Post-weld heat treatment (PWHT) and solid-state thermomechanical treatment (TMT) via friction stir processing (FSP) have been shown to enhance the mechanical properties of aluminum alloys. The current work investigates the effects of PWHT and TMT on the microstructure and mechanical performance of AA6082-T6 welded butt joints welded using the MIG process. The 5 mm thick AA 6082-T6 plates were joined in butt configuration using MIG welding with ER 5356 filler wire, 120 A current, 0.3 mm/s weld speed, and argon shielding gas at 15 L/min flow rate. PWHT was performed on the MIG welds per the T6 temper procedure. TMT was implemented via FSP using a pinless tool rotating at 800 rpm and traversing speed at 200 mm/min with a 3° tilt angle. Microstructural analysis, hardness mapping, tensile testing, and fracture surface evaluation were utilized to characterize the as-welded, PWHT, and TMT samples. The results demonstrate that both PWHT and TMT significantly refine and homogenize the microstructures of the welded joints. However, the TMT samples displayed superior hardness and tensile strength compared to the as-welded and PWHT conditions. The TMT-processed welds achieved approximately 99% joint efficiency versus only 69% and 85% for the as-welded and PWHT samples. In summary, PWHT and especially TMT via FSP are effective at enhancing the mechanical properties of MIG welded AA6082-T6.
Determinants of low birth weight among newborns delivered at Mettu Karl comprehensive specialized hospital, southwest Ethiopia: a case–control study
Authors: Ejeta Chibsa Samuel , Adem Hussen Mustafa , Bayisa Kenbon , Tefera Kefeni Bilisumamulifna
Published: February 2024

Low birth weight is a newborn delivered with birth weight of less than 2500 g regardless of gestational age is called. It is a significant issue affecting over 30 million infants worldwide. Thus, the study determine factors associated with low birth weight among newborns delivered at Mettu Karl Comprehensive Specialized Hospital, Southwest Ethiopia. A facility-based case–control study was conducted with 336 newborns (112 cases and 224 controls) from September 12 to December 23, 2022. The study population was newborns with birth weights of 2500 g to 4000 g as controls and newborns with birth weights < 2500 g were cases. Simple random sampling techniques were used to recruit study participants with a ratio of 1 to 3 cases to controls, respectively. Data was collected by interviews and a checklist. Data were entered and analysed using SPSS version 23. Binary and multivariate logistic regression analyses were computed to identify factors associated with low birth weight, a p-value less than 0.05 was used to declare the strength of statistical significance. A total of 327 newborns were contacted, yielding a 97% response rate. MUAC < 23 cm (AOR = 2.72, 95% CI 1.24 to 6.19), inadequate diet diversification (AOR = 4.19, 95% CI 2.04 to 8.60), lack of iron and folic acid supplementation (AOR = 2.94, 95% CI 1.25 to 6.88), history of hypertension (AOR = 2.55, 95% CI 1.09 to 6.00), and lack of nutritional counselling (AOR = 4.63, 95% CI 2.22 to 9.64) were determinants of low birth weight. Low birth weight is linked to residence, maternal MUAC, hypertension history, and ANC visit. Lifestyle modifications, early detection, management, and nutrition information can reduce risk.
Dynamic educational recommender system based on Improved LSTM neural network
Authors: Ahmadian Yazdi Hadis , Seyyed Mahdavi Seyyed Javad , Ahmadian Yazdi Hooman
Published: February 2024

Nowadays, virtual learning environments have become widespread to avoid time and space constraints and share high-quality learning resources. As a result of human–computer interaction, student behaviors are recorded instantly. This work aims to design an educational recommendation system according to the individual's interests in educational resources. This system is evaluated based on clicking or downloading the source with the help of the user so that the appropriate resources can be suggested to users. In online tutorials, in addition to the problem of choosing the right source, we face the challenge of being aware of diversity in users' preferences and tastes, especially their short-term interests in the near future, at the beginning of a session. We assume that the user's interests consist of two parts: (1) the user's long-term interests, which include the user's constant interests based on the history of the user's dynamic activities, and (2) the user's short-term interests, which indicate the user's current interests. Due to the use of Bilstm networks and their gradual learning feature, the proposed model supports learners' behavioral changes. An average accuracy of 0.9978 and a Loss of 0.0051 offer more appropriate recommendations than similar works.
An adaptive adjacency matrix-based graph convolutional recurrent network for air quality prediction
Authors: Chen Quanchao , Ding Ruyan , Mo Xinyue , Li Huan , Xie Linxuan , Yang Jiayu
Published: February 2024

In recent years, air pollution has become increasingly serious and poses a great threat to human health. Timely and accurate air quality prediction is crucial for air pollution early warning and control. Although data-driven air quality prediction methods are promising, there are still challenges in studying spatial–temporal correlations of air pollutants to design effective predictors. To address this issue, a novel model called adaptive adjacency matrix-based graph convolutional recurrent network (AAMGCRN) is proposed in this study. The model inputs Point of Interest (POI) data and meteorological data into a fully connected neural network to learn the weights of the adjacency matrix thereby constructing the self-ringing adjacency matrix and passes the pollutant data with this matrix as input to the Graph Convolutional Network (GCN) unit. Then, the GCN unit is embedded into LSTM units to learn spatio-temporal dependencies. Furthermore, temporal features are extracted using Long Short-Term Memory network (LSTM). Finally, the outputs of these two components are merged and air quality predictions are generated through a hidden layer. To evaluate the performance of the model, we conducted multi-step predictions for the hourly concentration of PM2.5, PM10 and O3 at Fangshan, Tiantan and Dongsi monitoring stations in Beijing. The experimental results show that our method achieves better predicted effects compared with other baseline models based on deep learning. In general, we designed a novel air quality prediction method and effectively addressed the shortcomings of existing studies in learning the spatio-temporal correlations of air pollutants. This method can provide more accurate air quality predictions and is expected to provide support for public health protection and government environmental decision-making.
Deep learning segmentation of fibrous cap in intravascular optical coherence tomography images
Authors: Lee Juhwan , Kim Justin N. , Dallan Luis A. P. , Zimin Vladislav N. , Hoori Ammar , Hassani Neda S. , Makhlouf Mohamed H. E. , Guagliumi Giulio , Bezerra Hiram G. , Wilson David L.
Published: February 2024

Thin-cap fibroatheroma (TCFA) is a prominent risk factor for plaque rupture. Intravascular optical coherence tomography (IVOCT) enables identification of fibrous cap (FC), measurement of FC thicknesses, and assessment of plaque vulnerability. We developed a fully-automated deep learning method for FC segmentation. This study included 32,531 images across 227 pullbacks from two registries (TRANSFORM-OCT and UHCMC). Images were semi-automatically labeled using our OCTOPUS with expert editing using established guidelines. We employed preprocessing including guidewire shadow detection, lumen segmentation, pixel-shifting, and Gaussian filtering on raw IVOCT (r,θ) images. Data were augmented in a natural way by changing θ in spiral acquisitions and by changing intensity and noise values. We used a modified SegResNet and comparison networks to segment FCs. We employed transfer learning from our existing much larger, fully-labeled calcification IVOCT dataset to reduce deep-learning training. Postprocessing with a morphological operation enhanced segmentation performance. Overall, our method consistently delivered better FC segmentation results (Dice: 0.837 ± 0.012) than other deep-learning methods. Transfer learning reduced training time by 84% and reduced the need for more training samples. Our method showed a high level of generalizability, evidenced by highly-consistent segmentations across five-fold cross-validation (sensitivity: 85.0 ± 0.3%, Dice: 0.846 ± 0.011) and the held-out test (sensitivity: 84.9%, Dice: 0.816) sets. In addition, we found excellent agreement of FC thickness with ground truth (2.95 ± 20.73 µm), giving clinically insignificant bias. There was excellent reproducibility in pre- and post-stenting pullbacks (average FC angle: 200.9 ± 128.0°/202.0 ± 121.1°). Our fully automated, deep-learning FC segmentation method demonstrated excellent performance, generalizability, and reproducibility on multi-center datasets. It will be useful for multiple research purposes and potentially for planning stent deployments that avoid placing a stent edge over an FC.
Machine learning using clinical data at baseline predicts the medium-term efficacy of ustekinumab in patients with ulcerative colitis
Authors: Morikubo Hiromu , Tojima Ryuta , Maeda Tsubasa , Matsuoka Katsuyoshi , Matsuura Minoru , Miyoshi Jun , Tamura Satoshi , Hisamatsu Tadakazu
Published: February 2024

Predicting the therapeutic response to biologics before administration is a key clinical challenge in ulcerative colitis (UC). We previously reported a model for predicting the efficacy of vedolizumab (VDZ) for UC using a machine-learning approach. Ustekinumab (UST) is now available for treating UC, but no model for predicting its efficacy has been developed. When applied to patients with UC treated with UST, our VDZ prediction model showed positive predictive value (PPV) of 56.3% and negative predictive value (NPV) of 62.5%. Given this limited predictive ability, we aimed to develop a UST-specific prediction model with clinical features at baseline including background factors, clinical and endoscopic activity, and blood test results, as we did for the VDZ prediction model. The top 10 features (Alb, monocytes, height, MCV, TP, Lichtiger index, white blood cell count, MCHC, partial Mayo score, and CRP) associated with steroid-free clinical remission at 6 months after starting UST were selected using random forest. The predictive ability of a model using these predictors was evaluated by fivefold cross-validation. Validation of the prediction model with an external cohort showed PPV of 68.8% and NPV of 71.4%. Our study suggested the importance of establishing a drug-specific prediction model.
Sequencing of cerebrospinal fluid cell-free DNA facilitated early differential diagnosis of intramedullary spinal cord tumors
Authors: Chai Ruichao , An Songyuan , Lin Han , Pang Bo , Yan Hao , Liu Yun , Wu Yilin , Wang Long , Liu Xing , Chen Huiyuan , Yang Xueyu , Chang Qing , Jia Wenqing , Wang Yongzhi
Published: February 2024

Pre-surgery differential diagnosis is valuable for personalized treatment planning in intramedullary spinal cord tumors. This study assessed the performance of sequencing cell-free DNA (cfDNA) in cerebrospinal fluid (CSF) for differential diagnosis of these tumors. Prospectively enrolling 45 patients with intramedullary spinal cord lesions, including diffuse midline glioma (DMG), H3K27-altered (14/45), glioblastoma (1/45), H3-wildtype-astrocytoma (10/45), ependymoma (11/45), and other lesions (9/45), CSF samples were collected via lumbar puncture (41/45), intraoperative extraction (3/45), and Ommaya reservoir (1/45). Then, these samples underwent targeted sequencing along with paired tissue DNA. DMG, H3K27-altered patients exhibited a higher ctDNA positivity (85.7%, 12/14) compared to patients with H3-wildtype-astrocytoma (0/8, P = 0.0003), ependymoma (2/10, P = 0.003), and glioneuronal tumor (0/3, P = 0.009). The histological-grade-IV (P = 0.0027), Ki-67 index ≥10% (P = 0.014), and tumor reaching spinal cord surface (P = 0.012) are also associated with higher ctDNA positivity. Interestingly, for patients with TERT promoter mutant tumors, TERT mutation was detectable in the CSF cfDNA of one DMG case, but not other five cases with histological-grade-II tumors. Shared copy number variants were exclusively observed in DMG, H3K27-altered, and showed a strong correlation (Correlation = 0.95) between CSF and tissue. Finally, H3K27M mutations in CSF exhibited high diagnostic efficiency for DMG, H3K27-altered (Sensitivity = 85.7%, Specificity = 100.0%, AUC = 0.929). Notably, H3K27M was detectable in CSF from patients with recurrent tumors, making it easily applicable for postoperative monitoring. In conclusion, the molecular profile from ctDNA released into CSF of malignant tumors was more frequently detected compared to relatively benign ones. Sequencing of ctDNA in CSF exhibited high efficiency for the differential diagnosis of DMG, H3K27-altered.
Negative linear compressibility exhibited by the hybrid perovskite [(NH2)3C]Er(HCO2)2(C2O4)
Authors: Hitchings Thomas J. , Scatena Rebecca , Allan David R. , Cairns Andrew B. , Saines Paul J.
Published: February 2024

Two hybrid perovskites under pressure exhibit drastically different mechanical behaviour, with one expanding in one direction whilst the other compresses conventionally.
“Clickable” graphene nanoribbons for biosensor interfaces
Authors: Hasler Roger , Fenoy Gonzalo E. , Götz Alicia , Montes-García Verónica , Valentini Cataldo , Qiu Zijie , Kleber Christoph , Samorì Paolo , Müllen Klaus , Knoll Wolfgang
Published: February 2024

We demonstrate the synthesis and application of “clickable” graphene nanoribbons (GNRs) as a versatile interface for electrochemical biosensors.
A stimuli-responsive l-DOPA-based supramolecular gel for the detection of fluoride ion
Authors: Mandal Subhra Kanti , Seth Piya , Kar Tanmoy
Published: February 2024

The present work highlights visual detection of fluoride ion by gel to sol transition of an l-DOPA-based LMW gelator.
Active nanoparticle targeting of MUC5AC ameliorates therapeutic outcome in experimental colitis
Authors: Riemann Bernadette , Antoine Thomas , Béduneau Arnaud , Pellequer Yann , Lamprecht Alf , Moulari Brice
Published: February 2024

We report anti-MUC5AC-conjugated PLGA nanoparticles with betametasone for active targeted treatment of mice TNBS-induced colitis.
Correction: Regulating the spherulitic evolution of 3-nitro-1,2,4-triazol-5-one via controlled supersaturation in cooling crystallization: growth mechanism and morphological consequences
Authors: Miao Shuyue , Jiao Fangbao , Wang Ying , Zhang Qi , Jing Suming , Li Hongzhen , Zhou Xin
Published: February 2024

Correction for ‘Regulating the spherulitic evolution of 3-nitro-1,2,4-triazol-5-one via controlled supersaturation in cooling crystallization: growth mechanism and morphological consequences’ by Shuyue Miao et al., CrystEngComm, 2024, https://doi.org/10.1039/d3ce00963g.
Correction: Exploiting Locusta migratoria as a source of bioactive peptides with anti-fibrosis properties using an in silico approach
Authors: Teixeira Carla S. S. , Biltes Rita , Villa Caterina , Sousa Sérgio F. , Costa Joana , Ferreira Isabel M. P. L. V. O. , Mafra Isabel
Published: February 2024

Correction for ‘Exploiting Locusta migratoria as a source of bioactive peptides with anti-fibrosis properties using an in silico approach’ by Carla S. S. Teixeira et al., Food Funct., 2024, 15, 493–502, https://doi.org/10.1039/D3FO04246D.
Facile one-step synthesis of a novel Bi2S3/BiOCl0.1Br0.9 S-scheme heterojunction photocatalyst with enhanced photocatalytic performance: function of interfacial electric field
Authors: Gao Yanhua , Zhang Dongfeng , Liu Hongya , Chen Ying , Liang Yuning , Bi Mingchun , Ren Juan , Wang Zhihua
Published: February 2024

Based on the anion exchange strategy, a novel Bi2S3/BiOCl0.1Br0.9 S-scheme heterojunction was prepared via a facile one-step low-temperature water bath method for the first time.
Correction: Solvent-free synthesis of stable heterostructured-CsPb2Br5/CsPbBr3 assisted by SiO2 for white light-emitting diodes
Authors: Yao Jisong , Yao Tianliang , Zhang Kaishuai , Fan Wenxuan , Yang Zhi , Xu Leimeng , Wang Shalong , Song Jizhong
Published: February 2024

Correction for ‘Solvent-free synthesis of stable heterostructured-CsPb2Br5/CsPbBr3 assisted by SiO2 for white light-emitting diodes’ by Jisong Yao et al., Mater. Chem. Front., 2024, https://doi.org/10.1039/D3QM01233F.
Photo-induced catalyst-free formal carbon insertion of acylsilanes into B–B and B–Si bonds
Authors: Lu Xiongxiong , Zhao Qingbin , Zhang Hao , Xu Pan , Chen Xuenian , Liu Zhenxing
Published: February 2024

A formal carbon insertion of acylsilanes into B–B and B–Si bonds has been developed. The in situ formed siloxycarbene under blue LED irradiation worked as the intermediate for the reaction. When 2-furyl and 2-thiophenyl acylsilanes were used, the B(pin) ring was enlarged to a six-membered ring.
Toward Generalizable Machine Learning Models in Speech, Language, and Hearing Sciences: Estimating Sample Size and Reducing Overfitting
Authors: Ghasemzadeh Hamzeh , Hillman Robert E. , Mehta Daryush D.
Published: February 2024

Purpose:

Many studies using machine learning (ML) in speech, language, and hearing sciences rely upon cross-validations with single data splitting. This study's first purpose is to provide quantitative evidence that would incentivize researchers to instead use the more robust data splitting method of nested
k
-fold cross-validation. The second purpose is to present methods and MATLAB code to perform power analysis for ML-based analysis during the design of a study.

Method:

First, the significant impact of different cross-validations on ML outcomes was demonstrated using real-world clinical data. Then, Monte Carlo simulations were used to quantify the interactions among the employed cross-validation method, the discriminative power of features, the dimensionality of the feature space, the dimensionality of the model, and the sample size. Four different cross-validation methods (single holdout, 10-fold, train–validation–test, and nested 10-fold) were compared based on the statistical power and confidence of the resulting ML models. Distributions of the null and alternative hypotheses were used to determine the minimum required sample size for obtaining a statistically significant outcome (5% significance) with 80% power. Statistical confidence of the model was defined as the probability of correct features being selected for inclusion in the final model.

Results:

ML models generated based on the single holdout method had very low statistical power and confidence, leading to overestimation of classification accuracy. Conversely, the nested 10-fold cross-validation method resulted in the highest statistical confidence and power while also providing an unbiased estimate of accuracy. The required sample size using the single holdout method could be 50% higher than what would be needed if nested
k
-fold cross-validation were used. Statistical confidence in the model based on nested
k
-fold cross-validation was as much as four times higher than the confidence obtained with the single holdout–based model. A computational model, MATLAB code, and lookup tables are provided to assist researchers with estimating the minimum sample size needed during study design.

Conclusion:

The adoption of nested
k
-fold cross-validation is critical for unbiased and robust ML studies in the speech, language, and hearing sciences.

Supplemental Material:

https://doi.org/10.23641/asha.25237045
Vegetation composition analysis for sequestration potential evaluation in the Republic of Tatarstan
Authors: Kozhevnikova Maria , Prokhorov Vadim , Usmanov Bulat , Gafurov Artur , Ivanov Maxim
Published: February 2024

To assess the carbon sequestration potential of terrestrial ecosystems of the Republic of Tatarstan, vegetation classification was carried out at the class level using the Braun-Blanquet system. 17,000 relevés from the "Flora" database were used as source materials. The classification was carried out using the EuroVeg Checklist expert system in the Juice 7.0 software. A total of 34 classes of vegetation were identified. The 14 largest classes have been selected for vegetation cover modelling.
Preservation of β-Cells as a Therapeutic Strategy for
Diabetes
Authors: Taneera Jalal , Saber-Ayad Maha M.
Published: February 2024

The preservation of pancreatic islet β-cells is crucial in diabetes mellitus,
encompassing both type 1 and type 2 diabetes. β-cell dysfunction, reduced mass,
and apoptosis are central to insufficient insulin secretion in both types.
Research is focused on understanding β-cell characteristics and the factors
regulating their function to develop novel therapeutic approaches. In type 1
diabetes (T1D), β-cell destruction by the immune system calls for exploring
immunosuppressive therapies, non-steroidal anti-inflammatory drugs, and
leukotriene antagonists. Islet transplantation, stem cell therapy, and
xenogeneic transplantation offer promising strategies for type 1 diabetes
treatment. For type 2 diabetes (T2D), lifestyle changes like weight loss and
exercise enhance insulin sensitivity and maintain β-cell function. Additionally,
various pharmacological approaches, such as cytokine inhibitors and protein
kinase inhibitors, are being investigated to protect β-cells from inflammation
and glucotoxicity. Bariatric surgery emerges as an effective treatment for
obesity and T2D by promoting β-cell survival and function. It improves insulin
sensitivity, modulates gut hormones, and expands β-cell mass, leading to
diabetes remission and better glycemic control. In conclusion, preserving
β-cells offers a promising approach to managing both types of diabetes. By
combining lifestyle modifications, targeted pharmacological interventions, and
advanced therapies like stem cell transplantation and bariatric surgery, we have
a significant chance to preserve β-cell function and enhance glucose regulation
in diabetic patients.
Improving the performance of low-frequency magnetic energy harvesters using an internal magnetic-coupled mechanism
Authors: You Zhixiong , Miao Huining , Shi Yang , Beer Michael
Published: February 2024

In this study, we present a novel low-frequency magnetic field energy harvester (EH) employing beryllium bronze/Pb(Zr,Ti)O3 ceramic composited dual-beam structures with tip magnets attached to the inner and outer beams. This design incorporates the internal magnetic-coupled (IMC) effect, resulting in significantly enhanced coupling ability and a wide bandwidth. The validity of the IMC mechanism is confirmed through theoretical formulas and numerical simulations. By leveraging the IMC condition, the EH achieves an expanded bandwidth, which increases from 22 to 43 Hz. Moreover, the total output voltages at the inherent resonance and internal resonance are boosted by 15.4% and 32%, respectively. The performance of the IMC-EH can be further improved by increasing the number of the endmost magnets. Experimental investigations reveal that the IMC-EH generates a maximum RMS output power density of 56.25 μW Oe−2 cm−3, surpassing existing magnetically coupled piezoelectric energy harvesters. Remarkably, even under an ambient magnetic field as low as 1 Oe, the proposed IMC-EH still yields a total output power of 185 μW, sufficient to continuously power 26 LEDs in real time. This demonstrates its potential as a promising solution for low-power consumption small electronics. Furthermore, the implications of this work extend beyond its immediate benefits, as it inspires the design of future self-powered wireless sensor networks in the context of the Internet of Things.
Bioenergetic costs and the evolution of noise regulation by microRNAs
Authors: Ilker Efe , Hinczewski Michael
Published: February 2024

Noise control, together with other regulatory functions facilitated by microRNAs (miRNAs), is believed to have played important roles in the evolution of multicellular eukaryotic organisms. miRNAs can dampen protein fluctuations via enhanced degradation of messenger RNA (mRNA), but this requires compensation by increased mRNA transcription to maintain the same expression levels. The overall mechanism is metabolically expensive, leading to questions about how it might have evolved in the first place. We develop a stochastic model of miRNA noise regulation, coupled with a detailed analysis of the associated metabolic costs. Additionally, we calculate binding free energies for a range of miRNA seeds, the short sequences which govern target recognition. We argue that natural selection may have fine-tuned the Michaelis–Menten constant

K
M

describing miRNA–mRNA affinity and show supporting evidence from analysis of experimental data.

K
M

is constrained by seed length, and optimal noise control (minimum protein variance at a given energy cost) is achievable for seeds of 6 to 7 nucleotides in length, the most commonly observed types. Moreover, at optimality, the degree of noise reduction approaches the theoretical bound set by the Wiener–Kolmogorov linear filter. The results illustrate how selective pressure toward energy efficiency has potentially shaped a crucial regulatory pathway in eukaryotes.
Increasing accuracy of pulse arrival time estimation in low frequency recordings
Authors: Montree Roel J H , Peri Elisabetta , Haakma Reinder , Dekker Lukas R C , Vullings Rik
Published: February 2024

Objective. Wearable devices that measure vital signals using photoplethysmography are becoming more commonplace. To reduce battery consumption, computational complexity, memory footprint or transmission bandwidth, companies of commercial wearable technologies are often looking to minimize the sampling frequency of the measured vital signals. One such vital signal of interest is the pulse arrival time (PAT), which is an indicator of blood pressure. To leverage this non-invasive and non-intrusive measurement data for use in clinical decision making, the accuracy of obtained PAT-parameters needs to increase in lower sampling frequency recordings. The aim of this paper is to develop a new strategy to estimate PAT at sampling frequencies up to 25 Hertz. Approach. The method applies template matching to leverage the random nature of sampling time and expected change in the PAT. Main results. The algorithm was tested on a publicly available dataset from 22 healthy volunteers, under sitting, walking and running conditions. The method significantly reduces both the mean and the standard deviation of the error when going to lower sampling frequencies by an average of 16.6% and 20.2%, respectively. Looking only at the sitting position, this reduction is even larger, increasing to an average of 22.2% and 48.8%, respectively. Significance. This new method shows promise in allowing more accurate estimation of PAT even in lower frequency recordings.
A piecewise inverse finite element method for shape sensing of the morphing wing fishbone
Authors: Huang Tianxiang , Dong Tianyu , Yuan Shenfang
Published: February 2024

The shape sensing technology plays a significant role in enhancing the structural performance and flight efficiency of the morphing aircraft by providing feedback to actuation and control systems in real time. The inverse finite element method (iFEM) is a fast, accurate, and robust shape-sensing method based on in-situ surface strain measurements. However, the conventional iFEM becomes less effective when applied to real engineering structures. Thus, this paper proposes a piecewise iFEM (P-iFEM) based on a two-node inverse Hermite beam element (iHB2) for the load-bearing structure of the morphing wing. The P-iFEM method discretizes the structure into a combination of rigid and elastic parts, based on the geometry of the structure when assembling the inverse elements. The Hermite polynomial shape function in iHB2 is adopted to increase the reconstruction efficiency, as only one degree of freedom of deflection is required to achieve the C1-continuity to reconstruct the displacement fields. The high accuracy and efficiency of the proposed method are validated with a numerical fishbone model. Finally, the proposed method is applied to a fishbone structure of a real adaptive deformed wing with high accuracy.
Interfacial charge associated reliability improvement in arsenide/antimonide tunneling interfaced-junctionless TFET
Authors: Sharma Samriti , Madan Jaya , Chaujar Rishu
Published: February 2024

This article focuses on the investigation of reliability improvement in the arsenide/antimonide tunable bandgap tunneling interfaced junctionless TFET (HD-HJLTFET) by introducing positive (donor) and negative (acceptor) localized interfacial trap charges (ITCs) at the semiconductor/oxide (S/O) and semiconductor/semiconductor (S/S) interface. The compound semiconducting materials, InAs (lower bandgap) and AlGaSb (higher bandgap) have been incorporated in the source and channel regions in the proposed device (HJLTFET). Further, to improve the device reliability against ITCs, a hetero dielectric engineered gated device has also been designed and analysed (HD-HJLTFET). In HD-HJLTFET, a high-k dielectric near source to channel (S/C) interface and low-k dielectric region towards drain to channel (D/C) interface has been used. It has been obtained that HD engineering enhances the microwave and harmonic distortion performance of HD-HJLTFET. It has been evaluated that HD-HJLTFET/ HJLTFET delivers ON current of 38.3 μA/14μA, transconductance 108 μS/23.2μS, cut-off frequency 805.8GHz/406.7GHz and gain of 223.5/197.4. Further results show that HD delivers gm2 (∼28% ↓), gm3 (∼9 times), second-order and third-order harmonic distortion (∼42% ↓ and ∼90% ↓), and total harmonic distortion (∼26% ↓) as compared to HJLTFET. The linearity parameters of HD-HJLTFET (VIP2, VIP3, IIP3, 1dB compression point, and IMD3) also showed marked improvement with negligible variation against different ITC polarity than its counter device, making it more reliable for low power microwave and distortion-free wireless communication systems.
Dark count of 20-inch PMTs generated by natural radioactivity
Authors: Zhang Yu , Wang Zhimin , Li Min , Liu Caimei , Rodphai Narongkiat , Zhang Yongpeng , Xu Jilei , Yang Changgen , Heng Yuekun
Published: February 2024

The primary objective of the JUNO experiment is to determine
the ordering of neutrino masses using a 20-kton liquid-scintillator
detector. The 20-inch photomultiplier tube (PMT) plays a crucial
role in achieving excellent energy resolution of at least 3 % at
1 MeV. Understanding the characteristics and features of the PMT
is vital for comprehending the detector's performance, particularly
regarding the occurrence of large pulses in PMT dark counts. This
research paper aims to further investigate the origin of these large
pulses in the 20-inch PMT dark count through measurements and
simulations. Our results confirm that natural radioactivity and
muons striking the PMT glass are the main sources of the large
pulses. We evaluate their contribution quantitatively by performing
spectrum fitting. By analyzing the PMT dark count spectrum, it
becomes possible to roughly estimate the radioactivity levels in the
surrounding environment.
(Non-)unitarity of strictly and partially massless fermions on de Sitter space II: an explanation based on the group-theoretic properties of the spin-3/2 and spin-5/2 eigenmodes
Authors: Letsios Vasileios A
Published: February 2024

In our previous article (Letsios 2023 J. High Energy Phys. JHEP05(2023)015), we showed that the strictly massless spin-3/2 field, as well as the strictly and partially massless spin-5/2 fields, on N-dimensional (

N
⩾
3

) de Sitter (dS) spacetime (dS

N
) are non-unitary unless N = 4. The (non-)unitarity was demonstrated by simply observing that there is a (mis-)match between the representation-theoretic labels that correspond to the unitary irreducible representations (UIR’s) of the dS algebra spin

(
N
,
1
)

and the ones corresponding to the space of eigenmodes of the field theories. In this paper, we provide a technical representation-theoretic explanation for this fact by studying the (non-)existence of positive-definite, dS invariant scalar products for the spin-3/2 and spin-5/2 strictly/partially massless eigenmodes on dS

N
(

N
⩾
3

). Our basic tool is the examination of the action of spin

(
N
,
1
)

generators on the space of eigenmodes, leading to the following findings. For odd N, any dS invariant scalar product is identically zero. For even N > 4, any dS invariant scalar product must be indefinite. This gives rise to positive-norm and negative-norm eigenmodes that mix with each other under spin

(
N
,
1
)

boosts. In the N = 4 case, the positive-norm sector decouples from the negative-norm sector and each sector separately forms a UIR of spin(4, 1). Our analysis makes extensive use of the analytic continuation of tensor-spinor spherical harmonics on the N-sphere (S

N
) to dS

N
and also introduces representation-theoretic techniques that are absent from the mathematical physics literature on half-odd-integer-spin fields on dS

N
.
High-performance broadband SnS photodetector based on photoconductive-bolometric coupling effect
Authors: Zhang Bo , Liu Yunjie , Hu Bing , Guo Fuhai , Zhang Mingcong , Li Siqi , Yu Weizhuo , Hao Lanzhong
Published: February 2024

Due to its large absorption coefficient and high carrier mobility, SnS exhibits strong promise in the area of optoelectronic devices. Nevertheless, the fabrication of large-area, high-quality films for SnS photodetectors (PDs) with superior photoresponse remains a formidable task, seriously limiting its further practical application. In the present study, we report a superior-performance broadband PD founded on the epitaxial SnS film. Large-area uniform SnS films were grown epitaxially on (100)-oriented KBr using magnetron sputtering technique, further exfoliated, and transferred in a wafer size to fabricated two-ends PD devices. Benefitting from high crystallization and unique photoconductive-bolometric coupling effect, the two modes of operation exhibit a wide range of spectral responses from the visible to near-infrared wavelength (405–1920 nm). Particularly noteworthy is the SnS device fabricated, which demonstrates an impressive responsivity of 95.5 A W−1 and a detectivity of 7.8 × 1011 Jones, outperforming other devices by 1–2 orders of magnitude. In addition, SnS PD shows excellent environmental durability. This work provides a robust approach to develop high-performance broadband SnS PDs, while simultaneously offering deep insight into the light–matter interactions.
Wideband radar cross-section reduction by a double-layer-plasma-based metasurface
Authors: ZHAO 赵 Zhiming 智明 , LI 李 Xiaoping 小平 , DONG 董 Guoxiang 果香 , LIU 刘 Xu 旭 , MU 牟 Xiangchao 相超
Published: February 2024

Reduction of the radar cross-section (RCS) is the key to stealth technology. To improve the RCS reduction effect of the designed checkerboard metasurface and overcome the limitation of thin-layer plasma in RCS reduction technology, a double-layer-plasma-based metasurface—composed of a checkerboard metasurface, a double-layer plasma and an air gap between them—was investigated. Based on the principle of backscattering cancellation, we designed a checkerboard metasurface composed of different artificial magnetic conductor units; the checkerboard metasurface can reflect vertically incident electromagnetic (EM) waves in four different inclined directions to reduce the RCS. Full-wave simulations confirm that the double-layer-plasma-based metasurface can improve the RCS reduction effect of the metasurface and the plasma. This is because in a band lower than the working band of the metasurface, the RCS reduction effect is mainly improved by the plasma layer. In the working band of the metasurface, impedance mismatching between the air gap and first plasma layer and between first and second plasma layers cause the scattered waves to become more dispersed, so the propagation path of the EM waves in the plasma becomes longer, increasing the absorption of the EM waves by the plasma. Thus, the RCS reduction effect is enhanced. The double-layer-plasma-based metasurface can be insensitive to the polarization of the incoming EM waves, and can also maintain a satisfactory RCS reduction band when the incident waves are oblique.
Electrochemical anodic oxidation assisted fabrication of memristors
Authors: Hua Shuai-Bin , Jin Tian , Guo Xin
Published: February 2024

Highlights

A low-cost, efficient and convenient anodic oxidation assisted fabrication of memristors is introduced.

The process and device performance of anodizing various forms of memristors are demonstrated.

The characteristics and issues of the anodic oxidation process for the fabrication of memory resistors are summarised and analysed.
Efficacy and Pain Tolerance of Alexandrite Laser Hair Removal at Different Stages of the Menstrual Cycle
Authors: Karanfil Ertuğrul , Görgü Metin
Published: February 2024

Background

Several different parameters play a role in the transition of hair follicles to the anagen phase, with the role of androgens, progesterone, and estrogen hormones and receptors being significant.

Objectives

The effectiveness of laser hair removal (LHR) and pain tolerance during procedure were investigated during 3 different phases of the menstrual cycle.

Methods

Forty-eight axillae were randomly divided into 3 groups: menstruation, ovulation, and luteal. Three laser sessions were performed on each axilla at a 1-month interval. Blood hormone levels were measured in the patients. An alexandrite laser was applied during LHR sessions. Before each LHR session and 1 month after the third session, hair follicles in 4-cm2 areas in the center of the axillae were counted. Patients self-assessed the pain they felt during the laser application in each session with a visual pain scale.

Results

The average values for hair counting in the groups were as follows (M, menstruation; O, ovulation; L, luteinization): M0 = 47.6, M1 = 27.4, M2 = 16.1, M3 = 9.9; O0 = 41.8, O1 = 21.1, O2 = 13.8, O3 = 8.6; and L0 = 49.4, L1 = 27.1, L2 = 15.1, L3 = 9.8. The average values on the visual analog scale scores in the groups were: M1 = 3.94, M2 = 3.06, M3 = 1.94; O1 = 3.50, O2 = 3.06, O3 = 1.69; and L1 = 3.63, L2 = 2.50, L3 = 1.56. Statistical analysis was conducted with Tukey post hoc analysis after analysis of variance.

Conclusions

The results of LHR are not affected by changes in hormone levels during the menstrual cycle in females. Although not statistically significant, it has been observed that pain tolerance during laser application is lower during the menstruation cycle.

Level of Evidence: 3
Variation in growth rates between cultures hinders the cultivation of ammonia-oxidizing bacteria
Authors: Isshiki Rino , Fujitani Hirotsugu , Tsuneda Satoshi
Published: February 2024

Ammonia-oxidizing bacteria, key players in the nitrogen cycle, have been the focus of extensive research. Numerous novel species have been isolated and their growth dynamics were studied. Despite these efforts, controlling their growth to obtain diverse physiological findings remains a challenge. These bacteria often fail to grow, even under optimal conditions. This unpredictable growth pattern could be viewed as a survival strategy. Understanding this heterogeneous behavior could enhance our ability to culture these bacteria. In this study, the variation in the growth rate was quantified for the ammonia-oxidizing bacterium Nitrosomonas mobilis Ms1. Our findings revealed significant growth rate variation under low inoculum conditions. Interestingly, higher cell densities resulted in more stable cultures. A comparative analysis of three Nitrosomonas species showed a correlation between growth rate variation and culture failure. The greater the variation in growth rate, the higher the likelihood of culture failure.
The impact of age and sex on the inflammatory response during bone fracture healing
Authors: Molitoris Kristin Happ , Balu Abhinav Reddy , Huang Mingjian , Baht Gurpreet Singh
Published: February 2024

Inflammation is thought to be dysregulated with age leading to impaired bone fracture healing. However, broad analyses of inflammatory processes during homeostatic bone aging and during repair are lacking. Here, we assessed changes in inflammatory cell and cytokine profiles in circulation and in bone tissue to identify age- and sex-dependent differences during homeostasis and repair. During homeostatic aging, male mice demonstrated accumulation of CD4+ helper T cells and CD8+ cytotoxic T cells within bone while both pro-inflammatory “M1” and anti-inflammatory “M2” macrophage numbers decreased. Female mice saw no age-associated changes in immune-cell population in homeostatic bone. Concentrations of IL-1β, IL-9, IFNγ, and CCL3/MIP-1α increased with age in both male and female mice, whereas concentrations of IL-2, TNFα, TNFR1, IL-4, and IL-10 increased only in female mice – thus we termed these “age-accumulated” cytokines. There were no notable changes in immune cell populations nor cytokines within circulation during aging. Sex-dependent analysis demonstrated slight changes in immune cell and cytokine levels within bone and circulation, which were lost upon fracture injury. Fracture in young male mice caused a sharp decrease in number of M1 macrophages; however, this was not seen in aged male mice nor in female mice of any age. Injury itself induced a decrease in the number of CD8+ T cells within the local tissue of aged male and of female mice but not of young mice. Cytokine analysis of fractured mice revealed that age-accumulated cytokines quickly dissipated after fracture injury, and did not re-accumulate in newly regenerated tissue. Conversely, CXCL1/KC-GRO, CXCL2/MIP-2, IL-6, and CCL2/MCP-1 acted as “fracture response” cytokines: increasing sharply after fracture, eventually returning to baseline. Collectively, we classify measured cytokines into three groups: (1) age-accumulated cytokines, (2) female-specific age-accumulated cytokines, and (3) fracture response cytokines. These inflammatory molecules represent potential points of intervention to improve fracture healing outcome.
Impact of diapause on the cuticular hydrocarbons and physiological status of Hippodamia variegata
Authors: Khabir Mahsa , Izadi Hamzeh , Mahdian Kamran
Published: February 2024

The spotted amber ladybird, Hippodamia variegata (Goeze) (Coleoptera: Coccinellidae), is known to be a potent predator of aphids, psyllids, whiteflies, mealybugs, and some butterfly species. This ladybeetle overwinters in the diapausing adult stage. The current study aimed to evaluate the impact of diapause on the energy resources and cuticular hydrocarbons (CHCs) of the female ladybeetle, specifically comparing the changes in glycogen, lipid, and protein contents, and CHCs profile of diapausing and non-diapausing adults. In this study, gas chromatography-mass was used to analyze whole-body extracts of the beetles. Results showed no significant differences between the amount of glycogen, lipid, and protein contents of diapausing and non-diapausing ladybeetle. The CHCs profile of H. variegata consisted of 24 hydrocarbons categorized into 2 groups: linear aliphatic hydrocarbons (n-alkanes) and methyl-branched hydrocarbons (17 molecules), as well as unsaturated cyclic compounds (7 molecules). The n-alkanes, with 14 compounds, were identified as the primary constituents of the CHCs of the ladybeetle. Six molecules were common to non-diapausing and diapausing beetles, 5 were exclusive to non-diapausing beetles, and 13 were exclusive to diapausing beetles. Moreover, we noted a significant difference in the quantity and quality of CHCs between diapausing and non-diapausing beetles, with diapausing beetles synthesizing more CHCs with longer chains. This disparity in CHC profiles was concluded to be an adaptation of H. variegata to survive harsh environmental conditions during diapause.