bluuebunny/crossref_metadata_2025 huggingface dataset:
Giant goos–hanchen shift with heigh reflection base on guided mode resonance in trapezoidal hBN/dielectric metasurface
Authors: Zhao Yue , Jin Gao , Zhou Sheng , Zhang Qiang , Fu Shu Fang , Wang Xiang Guang , Wang Xuan Zhang
Published: April 2024

hBN is a natural hyperbolic van der Waals material that can enhance light–matter interactions. In this work, the maximum Goos-Hanchen(GH) shift has a magnitude of −4680 μm with high reflection using the central beam method in the trapezoidal dielectric/hBN grating (TDG) metasurface (MS) where the beam waist

w

0

≥
4
λ
.

Analysis of the electromagnetic field distribution indicated that the amplified GH shift was a result of guided mode resonances excited in the waveguide dielectric layer. The frequency and magnitude of GH shifts can be effectively controlled by adjusting the height of the trapezoidal hBN, as well as by manipulating the widths of the top and bottom dielectric layers, the period of the TDG structure, and the height of the multi-layered structure. Moreover, an evaluation of the structure-sensing properties based on the GH shift was conducted. The enhanced and controllable GH shift exhibited by the TDG MS presents promising prospects for applications in optical sensors, optical switches, and optoelectronic detectors.
Unveiling the pressure-driven metal–semiconductor–metal transition in the doped TiS2
Authors: Chen 陈 Jiajun 佳骏 , Lv 吕 Xindeng 心邓 , Li 李 Simin 思敏 , Dan 但 Yaqian 雅倩 , Huang 黄 Yanping 艳萍 , Cui 崔 Tian 田
Published: April 2024

Conventional theories expect that materials under pressure exhibit expanded valence and conduction bands, leading to increased electrical conductivity. Here, we report the electrical properties of the doped 1T-TiS2 under high pressure by electrical resistance investigations, synchrotron x-ray diffraction, Raman scattering and theoretical calculations. Up to 70 GPa, an unusual metal–semiconductor–metal transition occurs. Our first-principles calculations suggest that the observed anti-Wilson transition from metal to semiconductor at 17 GPa is due to the electron localization induced by the intercalated Ti atoms. This electron localization is attributed to the strengthened coupling between the doped Ti atoms and S atoms, and the Anderson localization arising from the disordered intercalation. At pressures exceeding 30.5 GPa, the doped TiS2 undergoes a re-metallization transition initiated by a crystal structure phase transition. We assign the most probable space group as P212121. Our findings suggest that materials probably will eventually undergo the Wilson transition when subjected to sufficient pressure.
Physical information-enhanced graph neural network for predicting phase separation
Authors: Zhang 张 Yaqiang 亚强 , Wang 王 Xuwen 煦文 , Wang 王 Yanan 雅楠 , Zheng 郑 Wen 文
Published: April 2024

Although phase separation is a ubiquitous phenomenon, the interactions between multiple components make it difficult to accurately model and predict. In recent years, machine learning has been widely used in physics simulations. Here, we present a physical information-enhanced graph neural network (PIENet) to simulate and predict the evolution of phase separation. The accuracy of our model in predicting particle positions is improved by 40.3% and 51.77% compared with CNN and SVM respectively. Moreover, we design an order parameter based on local density to measure the evolution of phase separation and analyze the systematic changes with different repulsion coefficients and different Schmidt numbers. The results demonstrate that our model can achieve long-term accurate predictions of order parameters without requiring complex handcrafted features. These results prove that graph neural networks can become new tools and methods for predicting the structure and properties of complex physical systems.
Anomalous bond lengthening in compressed magnetic doped semiconductor Ba(Zn0.95Mn0.05)2As2
Authors: Sun Fei , Peng Yi , Zhao Guoqiang , Wang Xiancheng , Deng Zheng , Jin Changqing
Published: April 2024

Applying pressure has been evidenced as an effective method to control the properties of semiconductors, owing to its capability to modify the band configuration around Fermi energy. Correspondingly, structural evolutions under external pressures are required to analyze the mechanisms. Herein high-pressure structure of a magnetic doped semiconductor Ba(Zn0.95Mn0.05)2As2 is studied with combination of in-situ synchrotron X-ray diffractions and diamond anvil cells. The materials become ferromagnetic with Curie temperature of 105 K after further 20% K doping. The title material undergoes an isostructural phase transition at around 19 GPa. Below the transition pressure, it is remarkable to find lengthening of Zn/Mn−As bond within Zn/MnAs layers, since chemical bonds are generally shortened with applying pressures. Accompanied with the bond stretch, interlayer As−As distances become shorter and the As−As dimers form after the phase transition. With further compression, Zn/Mn−As bond becomes shortened due to the recovery of isotropic compression on the Zn/MnAs layers.
Improvement of Ga2O3 vertical Schottky barrier diode by constructing NiO/Ga2O3 heterojunction
Authors: Ji Xueqiang , Wang Jinjin , Qi Song , Liang Yijie , Hu Shengrun , Zheng Haochen , Zhang Sai , Yue Jianying , Qi Xiaohui , Li Shan , Liu Zeng , Shu Lei , Tang Weihua , Li Peigang
Published: April 2024

The high critical electric field strength of Ga2O3 enables higher operating voltages and reduced switching losses in power electronic devices. Suitable Schottky metals and epitaxial films are essential for further enhancing device performance. In this work, the fabrication of vertical Ga2O3 barrier diodes with three different barrier metals was carried out on an n–-Ga2O3 homogeneous epitaxial film deposited on an n+-β-Ga2O3 substrate by metal−organic chemical vapor deposition, excluding the use of edge terminals. The ideal factor, barrier height, specific on-resistance, and breakdown voltage characteristics of all devices were investigated at room temperature. In addition, the vertical Ga2O3 barrier diodes achieve a higher breakdown voltage and exhibit a reverse leakage as low as 4.82 ×10−8 A/cm2 by constructing a NiO/Ga2O3 heterojunction. Therefore, Ga2O3 power detailed investigations into Schottky barrier metal and NiO/Ga2O3 heterojunction of Ga2O3 homogeneous epitaxial films are of great research potential in high-efficiency, high-power, and high-reliability applications.
Countermeasure against blinding attack for single-photon detectors in quantum key distribution
Authors: Jiang Lianjun , Li Dongdong , Fang Yuqiang , Zhao Meisheng , Liu Ming , Xie Zhilin , Zhao Yukang , Tang Yanlin , Jiang Wei , Fang Houlin , Ma Rui , Cheng Lei , Yang Weifeng , Han Songtao , Tang Shibiao
Published: April 2024

Quantum key distribution (QKD), rooted in quantum mechanics, offers information-theoretic security. However, practical systems open security threats due to imperfections, notably bright-light blinding attacks targeting single-photon detectors. Here, we propose a concise, robust defense strategy for protecting single-photon detectors in QKD systems against blinding attacks. Our strategy uses a dual approach: detecting the bias current of the avalanche photodiode (APD) to defend against continuous-wave blinding attacks, and monitoring the avalanche amplitude to protect against pulsed blinding attacks. By integrating these two branches, the proposed solution effectively identifies and mitigates a wide range of bright light injection attempts, significantly enhancing the resilience of QKD systems against various bright-light blinding attacks. This method fortifies the safeguards of quantum communications and offers a crucial contribution to the field of quantum information security.
Biochemical and immunomodulatory insights of extracellular matrix from decellularized human whole cervix: recellularization and in vivo ECM remodeling interplay
Authors: Ojha Atul Kumar , Rajasekaran Ragavi , Hansda Arman Kunwar , Choudhury Priyanka , Biswas Asmita , Sharma Sunita , Chaudhuri Prithwis Pal , Dogra Nantu , Goswami Ritobrata , Chaudhury Koel , Dhara Santanu
Published: April 2024

Extracellular matrix (ECM) rich whole organ bio-scaffolds, preserving structural integrity and essential growth factors, has potential towards regeneration and reconstruction. Women with cervical anomalies or trauma can benefit from clinical cervicovaginal repair using constructs rich in site specific ECM. In this study, complete human cervix decellularization was achieved using a modified perfusion-based stir bench top decellularization method. This was followed by physico-chemical processes including perfusion of ionic agents, enzymatic treatment and washing using detergent solutions for a duration of 10–12 d. Histopathological analysis, as well as DNA quantification confirmed the efficacy of the decellularization process. Tissue ultrastructure integrity was preserved and the same was validated via scanning electron microscopy and transmission electron microscopy studies. Biochemical analysis and structural characterizations like Fourier transform infrared, Raman spectroscopy of decellularized tissues demonstrated preservation of important proteins, crucial growth factors, collagen, and glycosaminoglycans. In vitro studies, using THP-1 and human umbilical vein endothelial cell (HUVEC) cells, demonstrated macrophage polarization from M1 to M2 and vascular functional genes enhancement, respectively, when treated with decellularized human cervical matrix (DHCp). Crosslinked DHC scaffolds were recellularized with site specific human cervical epithelial cells and HUVEC, showing non-cytotoxic cell viability and enhanced proliferation. Furthermore, DHC scaffolds showed immunomodulatory effects in vivo on small rodent model via upregulation of M2 macrophage genes as compared to decellularized rat cervix matrix scaffolds (DRC). DHC scaffolds underwent neo-vascularization followed by ECM remodeling with enhanced tissue integration.
Dynamic trust security approach for edge computing-based mobile IoT devices using artificial intelligence
Authors: Jedidi Ahmed
Published: April 2024

The Industrial Internet of Things (IIoT) encompasses various applications such as smart cities, healthcare, and agriculture, which rely on a multitude of interconnected devices. These applications demand specific performance requirements, including low latency and sufficient bandwidth. Edge computing has emerged as a promising solution to address the challenges associated with data flow processing. Particularly, in scenarios like smart cities, where a massive number of IIoT devices are deployed, edge computing serves as the primary data processing layer. However, the limited resources of edge computing, compared to cloud computing, pose significant security concerns for IIoT applications. In fact, this paper proposes a novel security system to secure the relation between the IIoT devices and edge computing. Dynamic Trust Security Approach (DTSA) leverages Artificial Intelligence to analyze, evaluate and enhance the security and privacy aspects of the IIoT devices’ interaction with edge computing. DTSA improve the security level of the IIoT system and improve the performance with more than 45% compare to the traditional method.
Distilling particle knowledge for fast reconstruction at high-energy physics experiments
Authors: Bal A , Brandes T , Iemmi F , Klute M , Maier B , Mikuni V , Årrestad T K
Published: April 2024

Knowledge distillation is a form of model compression that allows artificial neural networks of different sizes to learn from one another. Its main application is the compactification of large deep neural networks to free up computational resources, in particular on edge devices. In this article, we consider proton-proton collisions at the High-Luminosity Large Hadron Collider (HL-LHC) and demonstrate a successful knowledge transfer from an event-level graph neural network (GNN) to a particle-level small deep neural network (DNN). Our algorithm, DistillNet, is a DNN that is trained to learn about the provenance of particles, as provided by the soft labels that are the GNN outputs, to predict whether or not a particle originates from the primary interaction vertex. The results indicate that for this problem, which is one of the main challenges at the HL-LHC, there is minimal loss during the transfer of knowledge to the small student network, while improving significantly the computational resource needs compared to the teacher. This is demonstrated for the distilled student network on a CPU, as well as for a quantized and pruned student network deployed on an field programmable gate array. Our study proves that knowledge transfer between networks of different complexity can be used for fast artificial intelligence (AI) in high-energy physics that improves the expressiveness of observables over non-AI-based reconstruction algorithms. Such an approach can become essential at the HL-LHC experiments, e.g. to comply with the resource budget of their trigger stages.
Hybrid quantum physics-informed neural networks for simulating computational fluid dynamics in complex shapes
Authors: Sedykh Alexandr , Podapaka Maninadh , Sagingalieva Asel , Pinto Karan , Pflitsch Markus , Melnikov Alexey
Published: April 2024

Finding the distribution of the velocities and pressures of a fluid by solving the Navier–Stokes equations is a principal task in the chemical, energy, and pharmaceutical industries, as well as in mechanical engineering and in design of pipeline systems. With existing solvers, such as OpenFOAM and Ansys, simulations of fluid dynamics in intricate geometries are computationally expensive and require re-simulation whenever the geometric parameters or the initial and boundary conditions are altered. Physics-informed neural networks (PINNs) are a promising tool for simulating fluid flows in complex geometries, as they can adapt to changes in the geometry and mesh definitions, allowing for generalization across fluid parameters and transfer learning across different shapes. We present a hybrid quantum PINN (HQPINN) that simulates laminar fluid flow in 3D Y-shaped mixers. Our approach combines the expressive power of a quantum model with the flexibility of a PINN, resulting in a 21% higher accuracy compared to a purely classical neural network. Our findings highlight the potential of machine learning approaches, and in particular HQPINN, for complex shape optimization tasks in computational fluid dynamics. By improving the accuracy of fluid simulations in complex geometries, our research using hybrid quantum models contributes to the development of more efficient and reliable fluid dynamics solvers.
Functionalization of silver nanoparticles coating cotton fabrics through hydrothermal synthesis for improved antimicrobial properties
Authors: Tooklang Pises , Audtarat Sasiporn , Chaisen Konkanok , Thepsiri Jaruwan , Chingsungnoen Artit , Jittabut Pongsak , Dasri Thananchai
Published: April 2024

Deposition of silver nanoparticles (AgNPs) on the surfaces of cotton fabric (CF) is an approach for producing antimicrobial textile products. CF-AgNPs composites were fabricated ex situ using a simple hydrothermal synthesis of AgNPs, while the fabric was surface modified using a plasma to improve adhesion prior to coating. The morphology and chemical composition of CF-AgNPs nanocomposites were examined using UV–vis spectrophotometry (UV–vis), x-ray diffraction (XRD), transmission electron microscopy (TEM) and field emission scanning electron microscopy (FESEM). Study results show uniform deposition of AgNPs on cotton fabrics. The CF-AgNPs composite material exhibits excellent laundering durability and antimicrobial performance against Gram-positive, Staphylococcus aureus and Gram-negative, Escherichia coli pathogens. These findings indicate that the developed fabric can be used in a wide range of biomedical applications, health care and various packaging systems.
Complex submanifolds of indefinite complex space forms
Authors: Cheng Xiaoliang , Hao Yihong , Yuan Yuan , Zhang Xu
Published: April 2024

In this short paper, we derive a new result on Umehara algebra. As a consequence, we prove that an indefinite complex hyperbolic space and an indefinite complex projective space do not share a common complex submanifold with induced metrics, answering a question raised in Cheng et al.
Defining the Ideal Reduction Mammaplasty: A Crowdsourcing Study
Authors: Zibitt Meira , Shauly Orr , Ash Makenna , Menon Ambika , Gould Daniel J , Faulkner Heather , Losken Albert
Published: April 2024

Background

Reduction mammaplasty relieves macromastia symptoms while improving breast aesthetics, although the ideal breast aesthetically has been shown to differ culturally in previous crowdsourcing studies. Better understanding these differences can aid in setting postoperative expectations.

Objectives

The aim of this study was to characterize the ideal reduction mammaplasty according to demographics such as gender, ethnicity, socioeconomic status, and education.

Methods

A crowdsourcing platform was utilized to collect 10,169 deidentified responses. Users completed 1 of 3 surveys, either a preoperative, postoperative, or preoperative and postoperative paired survey. The preoperative and postoperative surveys addressed 10 breast measurements, including upper breast slope, projection proportion, nipple position, breast width, and breast fullness. The paired preoperative and postoperative survey assessed the nipple-areola complex (NAC), chest fit, symmetry improvement, and scarring.

Results

Preoperative images were rated more aesthetic than postoperative images. This was consistent across all demographics evaluated. Females, African Americans, Asians, participants ages 55+, and participants with no high school degree or a graduate degree found the most improvement in breast symmetry (P = .001, P = .002, P = .027, P < .001, P = .01). Male and Hispanic participants were most likely to see no change in symmetry (P = .008, P = .04), and South Asian participants found breasts less symmetric postoperatively (P < .001). There were significant demographic differences in aesthetic ratings of the NAC, scarring, and breast fit.

Conclusions

Perceived breast aesthetics after reduction mammaplasty vary significantly across demographics, including gender, ethnicity, age, socioeconomic status, and educational achievement. Surgeons should consider demographics when planning each patient's reduction mammaplasty.

Level of Evidence: 5
Automated 3D Perioral Landmark Detection Using High-Resolution Network: Artificial Intelligence–based Anthropometric Analysis
Authors: Yang Yuyan , Zhang Mengyuan , An Yicheng , Huang Qi , Shi Yongwang , Jin Lin , Zeng Ang , Long Xiao , Yu Nanze , Wang Xiaojun
Published: April 2024

Background

Three-dimensional facial stereophotogrammetry, a convenient, noninvasive and highly reliable evaluation tool, has in recent years shown great potential in plastic surgery for preoperative planning and evaluating treatment efficacy. However, it requires manual identification of facial landmarks by trained evaluators to obtain anthropometric data, which takes much time and effort. Automatic 3D facial landmark localization has the potential to facilitate fast data acquisition and eliminate evaluator error.

Objectives

The aim of this work was to describe a novel deep-learning method based on dimension transformation and key-point detection for automated 3D perioral landmark annotation.

Methods

After transforming a 3D facial model into 2D images, High-Resolution Network is implemented for key-point detection. The 2D coordinates of key points are then mapped back to the 3D model using mathematical methods to obtain the 3D landmark coordinates. This program was trained with 120 facial models and validated in 50 facial models.

Results

Our approach achieved a satisfactory mean [standard deviation] accuracy of 1.30 [0.68] mm error in landmark detection with a mean processing time of 5.2 [0.21] seconds per model. Subsequent analysis based on these landmarks showed mean errors of 0.87 [1.02] mm for linear measurements and 5.62° [6.61°] for angular measurements.

Conclusions

This automated 3D perioral landmarking method could serve as an effective tool that enables fast and accurate anthropometric analysis of lip morphology for plastic surgery and aesthetic procedures.
CASCC: a co-expression-assisted single-cell RNA-seq data clustering method
Authors: Cai Lingyi , Anastassiou Dimitris
Published: April 2024

Existing clustering methods for characterizing cell populations from single-cell RNA sequencing are constrained by several limitations stemming from the fact that clusters often cannot be homogeneous, particularly for transitioning populations. On the other hand, dominant cell populations within samples can be identified independently by their strong gene co-expression signatures using methods unrelated to partitioning. Here, we introduce a clustering method, CASCC (co-expression-assisted single-cell clustering), designed to improve biological accuracy using gene co-expression features identified using an unsupervised adaptive attractor algorithm. CASCC outperformed other methods as evidenced by multiple evaluation metrics, and our results suggest that CASCC can improve the analysis of single-cell transcriptomics, enabling potential new discoveries related to underlying biological mechanisms.

Availability and implementation

The CASCC R package is publicly available at https://github.com/LingyiC/CASCC and https://zenodo.org/doi/10.5281/zenodo.10648327.
RecGraph: recombination-aware alignment of sequences to variation graphs
Authors: Avila Cartes Jorge , Bonizzoni Paola , Ciccolella Simone , Della Vedova Gianluca , Denti Luca , Didelot Xavier , Monti Davide Cesare , Pirola Yuri
Published: April 2024

Motivation

Bacterial genomes present more variability than human genomes, which requires important adjustments in computational tools that are developed for human data. In particular, bacteria exhibit a mosaic structure due to homologous recombinations, but this fact is not sufficiently captured by standard read mappers that align against linear reference genomes. The recent introduction of pangenomics provides some insights in that context, as a pangenome graph can represent the variability within a species. However, the concept of sequence-to-graph alignment that captures the presence of recombinations has not been previously investigated.

Results

In this paper, we present the extension of the notion of sequence-to-graph alignment to a variation graph that incorporates a recombination, so that the latter are explicitly represented and evaluated in an alignment. Moreover, we present a dynamic programming approach for the special case where there is at most a recombination—we implement this case as RecGraph. From a modelling point of view, a recombination corresponds to identifying a new path of the variation graph, where the new arc is composed of two halves, each extracted from an original path, possibly joined by a new arc. Our experiments show that RecGraph accurately aligns simulated recombinant bacterial sequences that have at most a recombination, providing evidence for the presence of recombination events.

Availability and implementation

Our implementation is open source and available at https://github.com/AlgoLab/RecGraph.
Improving traumatic fracture detection on radiographs with artificial intelligence support: a multi-reader study
Authors: Bachmann Rikke , Gunes Gozde , Hangaard Stine , Nexmann Andreas , Lisouski Pavel , Boesen Mikael , Lundemann Michael , Baginski Scott G
Published: April 2024

Objectives

The aim of this study was to evaluate the diagnostic performance of nonspecialist readers with and without the use of an artificial intelligence (AI) support tool to detect traumatic fractures on radiographs of the appendicular skeleton.

Methods

The design was a retrospective, fully crossed multi-reader, multi-case study on a balanced dataset of patients (≥2 years of age) with an AI tool as a diagnostic intervention. Fifteen readers assessed 340 radiographic exams, with and without the AI tool in 2 different sessions and the time spent was automatically recorded. Reference standard was established by 3 consultant radiologists. Sensitivity, specificity, and false positives per patient were calculated.

Results

Patient-wise sensitivity increased from 72% to 80% (P < .05) and patient-wise specificity increased from 81% to 85% (P < .05) in exams aided by the AI tool compared to the unaided exams. The increase in sensitivity resulted in a relative reduction of missed fractures of 29%. The average rate of false positives per patient decreased from 0.16 to 0.14, corresponding to a relative reduction of 21%. There was no significant difference in average reading time spent per exam. The largest gain in fracture detection performance, with AI support, across all readers, was on nonobvious fractures with a significant increase in sensitivity of 11 percentage points (pp) (60%-71%).

Conclusions

The diagnostic performance for detection of traumatic fractures on radiographs of the appendicular skeleton improved among nonspecialist readers tested AI fracture detection support tool showed an overall reader improvement in sensitivity and specificity when supported by an AI tool. Improvement was seen in both sensitivity and specificity without negatively affecting the interpretation time.

Advances in knowledge

The division and analysis of obvious and nonobvious fractures are novel in AI reader comparison studies like this.
Recalcitrant oropharyngeal and genital warts in XMEN disease
Authors: Aboluwarin Oluwamayowa , Kyaw Khin Y , Odega Emmanuel , Huet Hannah , Nambi Rabi
Published: April 2024

The identification of primary immunodeficiencies is often delayed because of the inherent clinical heterogeneity and gaps in clinicians’ understanding of the clinical landscape. We present an unusual case of a patient with X-linked immunodeficiency with magnesium defect, Epstein–Barr virus infection and neoplasia (XMEN) disease. To the best of our knowledge, this is the first case report of an individual with XMEN disease presenting with recalcitrant oropharyngeal and genital warts.
Current prescribing for pyoderma gangrenosum in the UK and access to biologic medications: results from a UK Dermatology Clinical Trials Network survey of dermatologists
Authors: Jenkins Myfanwy , Watson Nicola , McPhee Margaret , Levell Nick J , Arden-Jones Mike , D Ormerod Anthony , Hampton Philip J
Published: April 2024

Pyoderma gangrenosum (PG) is an ulcerative inflammatory disorder affecting the lower legs in 80% of patients. The use of biologic medications to treat PG is increasing, although there is a limited evidence base to guide treatment choices. In some health systems, such as the UK National Health Service, limitations are placed on biologic prescribing for PG, leading to wide variations in prescribing. A survey of mainly UK clinicians showed that prednisolone remains the first-line treatment for PG (90%, 34/38). Biologics have been used by 66% (25/38) of clinicians as second-line therapy, but 19% (7/38) have had prescribing requests declined. Further research is needed to determine optimal treatment strategies for PG.
Predictive Value of Microfilariae-Based Stop-MDA Thresholds After Triple Drug Therapy With IDA Against Lymphatic Filariasis in Treatment-Naive Indian Settings
Authors: James Ananthu , Coffeng Luc E , Blok David J , King Jonathan D , de Vlas Sake J , Stolk Wilma A
Published: April 2024

Mass drug administration (MDA) of antifilarial drugs is the main strategy for the elimination of lymphatic filariasis (LF). Recent clinical trials indicated that the triple-drug therapy with ivermectin, diethylcarbamazine, and albendazole (IDA) is much more effective against LF than the widely used two-drug combinations (albendazole plus either ivermectin or diethylcarbamazine). For IDA-based MDA, the stop-MDA decision is made based on microfilariae (mf) prevalence in adults. In this study, we assess how the probability of eventually reaching elimination of transmission depends on the critical threshold used in transmission assessment surveys (TAS-es) to define whether transmission was successfully suppressed and triple-drug MDA can be stopped. This analysis focuses on treatment-naive Indian settings. We do this for a range of epidemiological and programmatic contexts, using the established LYMFASIM model for transmission and control of LF. Based on our simulations, a single TAS, one year after the last MDA round, provides limited predictive value of having achieved suppressed transmission, while a higher MDA coverage increases elimination probability, thus leading to a higher predictive value. Every additional TAS, conditional on previous TAS-es being passed with the same threshold, further improves the predictive value for low values of stop-MDA thresholds. An mf prevalence threshold of 0.5% corresponding to TAS-3 results in ≥95% predictive value even when the MDA coverage is relatively low.
Improving the Cost-efficiency of Preventive Chemotherapy: Impact of New Diagnostics on Stopping Decisions for Control of Schistosomiasis
Authors: Coffeng Luc E , Graham Matthew , Browning Raiha , Kura Klodeta , Diggle Peter J , Denwood Matthew , Medley Graham F , Anderson Roy M , de Vlas Sake J
Published: April 2024

Background

Control of schistosomiasis (SCH) relies on the regular distribution of preventive chemotherapy (PC) over many years. For the sake of sustainable SCH control, a decision must be made at some stage to scale down or stop PC. These “stopping decisions” are based on population surveys that assess whether infection levels are sufficiently low. However, the limited sensitivity of the currently used diagnostic (Kato-Katz [KK]) to detect low-intensity infections is a concern. Therefore, the use of new, more sensitive, molecular diagnostics has been proposed.

Methods

Through statistical analysis of Schistosoma mansoni egg counts collected from Burundi and a simulation study using an established transmission model for schistosomiasis, we investigated the extent to which more sensitive diagnostics can improve decision making regarding stopping or continuing PC for the control of S. mansoni.

Results

We found that KK-based strategies perform reasonably well for determining when to stop PC at a local scale. Use of more sensitive diagnostics leads to a marginally improved health impact (person-years lived with heavy infection) and comes at a cost of continuing PC for longer (up to around 3 years), unless the decision threshold for stopping PC is adapted upward. However, if this threshold is set too high, PC may be stopped prematurely, resulting in a rebound of infection levels and disease burden (+45% person-years of heavy infection).

Conclusions

We conclude that the potential value of more sensitive diagnostics lies more in the reduction of survey-related costs than in the direct health impact of improved parasite control.
An Updated Economic Assessment of Moxidectin Treatment Strategies for Onchocerciasis Elimination
Authors: Turner Hugo C , Kura Klodeta , Roth Barbara , Kuesel Annette C , Kinrade Sally , Basáñez Maria-Gloria
Published: April 2024

Background

Concerns that annual mass administration of ivermectin, the predominant strategy for onchocerciasis control and elimination, may not lead to elimination of parasite transmission (EoT) in all endemic areas have increased interest in alternative treatment strategies. One such strategy is moxidectin. We performed an updated economic assessment of moxidectin- relative to ivermectin-based strategies.

Methods

We investigated annual and biannual community-directed treatment with ivermectin (aCDTI, bCDTI) and moxidectin (aCDTM, bCDTM) with minimal or enhanced coverage (65% or 80% of total population taking the drug, respectively) in intervention-naive areas with 30%, 50%, or 70% microfilarial baseline prevalence (representative of hypo-, meso-, and hyperendemic areas). We compared programmatic delivery costs for the number of treatments achieving 90% probability of EoT (EoT90), calculated with the individual-based stochastic transmission model EPIONCHO-IBM. We used the costs for 40 years of program delivery when EoT90 was not reached earlier. The delivery costs do not include drug costs.

Results

aCDTM and bCDTM achieved EoT90 with lower programmatic delivery costs than aCDTI with 1 exception: aCDTM with minimal coverage did not achieve EoT90 in hyperendemic areas within 40 years. With minimal coverage, bCDTI delivery costs as much or more than aCDTM and bCDTM. With enhanced coverage, programmatic delivery costs for aCDTM and bCDTM were lower than for aCDTI and bCDTI.

Conclusions

Moxidectin-based strategies could accelerate progress toward EoT and reduce programmatic delivery costs compared with ivermectin-based strategies. The costs of moxidectin to national programs are needed to quantify whether delivery cost reductions will translate into overall program cost reduction.
Echocardiographic findings in cancer-associated non-bacterial thrombotic endocarditis: clinical series of 111 patients from a single institution
Authors: Kurmann Reto D , Klarich Kyle W , Wysokinska Ewa , Houghton Damon , Kaminska Alicja , Patrzalek Patryk , Hodge David , Wysokinski Waldemar E
Published: April 2024

Aims

Echocardiographic assessment of cancer-associated non-bacterial thrombotic endocarditis (Ca-NBTE) is limited to case reports and small clinical series. The study aimed to identify heart valve abnormalities and its relation to embolic complications and cancer types.

Methods and results

Manual review of echocardiographic images and medical records of Mayo Clinic patients (31 March 2002–30 June 2022) was performed. Ca-NBTE in 111 patients (mean age 63.2 ± 9.7 years, 66.7% female) predominantly affected mitral valves (MV) (69), 56 aortic (AV), 8 tricuspid (TV), and rarely pulmonic (PV) (1). In 18 patients, 2 valves were involved, 3 and 4 valve involvement in only a single patient each. Embolic complications were prevalent (n = 102, 91.9%). Ca-NBTE affected MV more frequently on the upstream (atrial) (90% vs. 49.3%) and TV downstream (ventricular) side (75% vs. 37.5%). NBTE size (cm) varied significantly among valves, with TV hosting the largest masses (0.63–2.40 × 0.39–1.77), compared with MV [(0.11–1.81 × 0.11–1.62), (length P = 0.001; width P = 0.03)] and AV [(0.20–2.70 × 0.11–1.51), (length P = 0.001; width P = 0.056)]; MV masses were borderline longer in systemic compared with cerebral emboli (P = 0.057). Majority of MV (79.6%) and AV (69.6%) had thickened leaflets. NBTE lesions commonly affected closing margins (73.9% MV, 85.7% AV, and 62.5% of TV) but rarely commissures of MV (8.7%), yet fairly frequently of AV (41.1%). Five patients had severe regurgitation of MV and 5 AV.

Conclusion

Ca-NBTE manifests mainly as thrombotic mobile masses attached to thickened MV and AV, with distinct variations in size based on valve type. Embolic destination but not cancer type is associated with NBTE mass size and location.
High-output heart failure due to a giant left circumflex coronary aneurysm with a left atrial fistula and atrial septal defect: a case report
Authors: Lee Moses , Thomas Mariam , Joodi Golsa , Koppula Anthony , Soverow Jonathan
Published: April 2024

Background

A coronary artery aneurysm is a rare cardiac anomaly that may be incidentally detected on echocardiography. When associated with a coronary cameral fistula, an aneurysm can become symptomatic. We present a unique case of a giant left circumflex coronary aneurysm with a fistula to the left atrium and a large atrial septal defect causing acute heart failure in a young woman during the peripartum period.

Case summary

A 32 year-old woman who presented with hypoxia after the delivery of her fourth child was found to have heart failure with severe mitral regurgitation and multiple abnormal intracardiac shunts. Echocardiography showed a large circular structure with Doppler color flow into the left atrium and between the atria. Cardiac computed tomography showed multiple dilated coronary arteries including a left circumflex coronary artery aneurysm measuring >10 cm in diameter with fistulous communication to the left atrium and a large atrial septal defect. A right heart catheterization was performed, and the patient was diagnosed with high-output heart failure. Surgical closure of the coronary cameral fistula was deferred due to the risk of worsening pressure in the coronary aneurysm, and the patient was referred for cardiac transplantation.

Discussion

This case illustrates severe heart failure as a complication of a giant coronary artery aneurysm with fistulization to the left atrium and subsequent shunting through a large atrial defect. Echocardiography allows for the detection of a coronary aneurysm and shunting, and cardiac computed tomography provides detailed visualization of a coronary cameral fistula.
Selection maintains a nonadaptive floral polyphenism
Authors: Gómez José María , González-Megías Adela , Armas Cristina , Narbona Eduardo , Navarro Luis , Perfectti Francisco
Published: April 2024

Adaptive phenotypic plasticity evolves in response to the contrasting selection pressures that arise when organisms face environmental heterogeneity. Despite its importance for understanding how organisms successfully cope with environmental change, adaptive plasticity is often assumed but rarely demonstrated. We study here the adaptive nature of the extreme seasonal within-individual floral polyphenism exhibited by the crucifer Moricandia arvensis, a Mediterranean species that produces two different types of flowers depending on the season of the year. During spring, this species has large, cross-shaped, lilac flowers, while during summer, it develops small, rounded, white flowers. Although floral polyphenism was associated with increased plant fitness, selection moved floral traits away from their local optimum values during the harsh summer. This result strongly suggests that floral polyphenism is not adaptive in M. arvensis. The main factor selecting against floral polyphenism was pollinators, as they select for the same floral morph in all environments. Despite not being adaptive, floral polyphenism occurs throughout the entire distribution range of M. arvensis and has probably been present since the origin of the species. To solve this paradox, we explored the factors causing floral polyphenism, finding that floral polyphenism was triggered by summer flowering. Summer flowering was beneficial because it led to extra seed production and was favored by adaptive plasticity in leaf functional traits. Taken together, our study reveals a complex scenario in which nonadaptive floral polyphenism has been indirectly maintained over M. arvensis evolutionary history by selection operating to favor summer flowering. Our study provides thus strong evidence that nonadaptive plasticity may evolve as a byproduct of colonizing stressful environments.
The genome of the Arctic snow alga Limnomonas spitsbergensis (Chlamydomonadales)
Authors: Hulatt Chris J , Suzuki Hirono , Détain Alexandre , Wijffels René H , Leya Thomas , Posewitz Matthew C
Published: April 2024

Snow algae are a diverse group of extremophilic microeukaryotes found on melting polar and alpine snowfields. They play an important role in the microbial ecology of the cryosphere, and their propagation on snow and ice surfaces may in part accelerate climate-induced melting of these systems. High-quality snow algae genomes are needed for studies on their unique physiology, adaptive mechanisms, and genome evolution under multiple forms of stress, including cold temperatures and intense sunlight. Here, we assembled and annotated the genome of Limnomonas spitsbergensis, a cryophilic biciliate green alga originally isolated from melting snow on Svalbard, in the Arctic. The L. spitsbergensis genome assembly is based primarily on the use of PacBio long reads and secondly Illumina short reads, with an assembly size of 260.248 Mb in 124 contigs. A combination of 3 alternative annotation strategies was used including protein homology, RNA-seq evidence, and PacBio full-length transcript isoforms. The best merged set of annotations identified 18,277 protein-coding genes, which were 95.2% complete based on Benchmarking Universal Single-Copy Orthologs analysis. We also provide the annotated mitogenome, which is a relatively large 77.942 kb circular mapping sequence containing extensive repeats. The L. spitsbergensis genome will provide a new resource for research on snow algae adaptation, behavior, and natural selection in unique, low-temperature terrestrial environments that are under threat from climate change.
The Affordable Care Act and income-based disparities in health care coverage and spending among nonelderly adults with cancer
Authors: Olateju Olajumoke A , Shen Chan , Thornton James Douglas
Published: April 2024

The Patient Protection and Affordable Care Act (ACA) significantly reduced uninsured individuals and improved financial protection; however, escalating costs of cancer treatment has led to substantial out-of-pocket expenses, causing severe financial and mental health distress for individuals with cancer. Mixed evidence on the ACA's ongoing impact highlights the necessity of assessing health-spending changes across income groups for informed policy interventions. In our nationally representative survey evaluating the early- and long-term effects of the ACA on nonelderly adult patients with cancer, we categorized individuals-based income subgroups defined by the ACA for eligibility. We found that ACA implementation increased insurance coverage, which was particularly evident after 2 years of implementation. Early post-ACA (within two years of implementation), there were declines in out-of-pocket spending for the lowest and low-income groups by 26.52% and 38.31%, respectively, persisting long-term only for the lowest-income group. High-income groups experienced continuously increased out-of-pocket and premium spending by 25.39% and 34.28%, respectively, with a notable 122% increase in the risk of high-burden spending. This study provides robust evidence of income-based disparities in financial burden for cancer care, emphasizing the need for health care policies promoting equitable care and addressing spending disparities across income brackets.
Four novel Cit7GlcTs functional in flavonoid 7-O-glucoside biosynthesis are vital to flavonoid biosynthesis shunting in citrus
Authors: Yuan Ziyu , Li Gu , Zhang Huixian , Peng Zhaoxin , Ding Wenyu , Wen Huan , Zhou Hanxin , Zeng Jiwu , Chen Jiajing , Xu Juan
Published: April 2024

Citrus fruits have abundant flavonoid glycosides (FGs), an important class of natural functional and flavor components. However, there have been few reports about the modification of UDP-glycosyltransferases (UGTs) on flavonoids in citrus. Notably, in flavonoid biosynthesis, 7-O-glucosylation is the initial and essential step of glycosylation prior to the synthesis of flavanone disaccharides, the most abundant and iconic FGs in citrus fruits. Here, based on the accumulation of FGs observed at the very early fruit development stage of two pummelo varieties, we screened six novel flavonoid 7-O-glucosyltransferase genes (7GlcTs) via transcriptomic analysis and then characterized them in vitro. The results revealed that four Cg7GlcTs possess wide catalytic activities towards various flavonoid substrates, with CgUGT89AK1 exhibiting the highest catalytic efficiency. Transient overexpression of CgUGT90A31 and CgUGT89AK1 led to increases in FG synthesis in pummelo leaves. Interestingly, these two genes had conserved sequences and consistent functions across different germplasms. Moreover, CitUGT89AK1 was found to play a role in the response of citrus to Huanglongbing infection by promoting FG production. The findings improve our understanding of flavonoid 7-O-glucosylation by identifying the key genes, and may help improve the benefits of flavonoid biosynthesis for plants and humans in the future.
Heat pipes and nanofluids utilization for cooling photovoltaic panels: an application of hybrid machine learning and optimization models
Authors: Abdulrahman Aysar A
Published: April 2024

This study explores the synergies between advanced cooling technologies and photovoltaic systems, seeking to improve their overall efficiency and contribute to the broader goal of mitigating greenhouse gas emissions. To cool photovoltaic panels in more efficiently maner, understanding heat pipes, nanofluids, and panels interaction play key roles. For analysis and optimization, hybrid models of convolutional neural network (CNN) and firefly optimization algorithm are employed. The firefly optimization algorithm is used to optimize the thermosiphon heat pipe’s operational conditions, taking into account inputs such as the filling ratio, nanofluid concentration and panel angle. The study compared the predicted outcomes of a classic CNN model to laboratory experiments. While the CNN model was consistent with experimental findings, it struggled to predict high power values with precision. The proposed model improved high power value predictions by 4.05 W root mean square error (RMSE). The proposed model outperformed the classic CNN model for values greater than 50 W, with an RMSE of 3.95 W. The optimal values for the filling ratio, nanofluid concentration and panel angle were determined after optimization with the firefly algorithm. The research contributes to the advancement of renewable energy technologies and the optimization of photovoltaic panel cooling and energy production. Nanofluid with 1% mass concentration improves photovoltaic collector thermal efficiency due to its higher thermal conductivity coefficient. The photovoltaic collector’s electrical efficiency peaks in the morning, drops at noon due to temperature and radiation and recovers by morning. Electrical efficiency is best with nanofluid at 0.86%. Exergy efficiency closely matches electrical efficiency, with nanofluid at the optimal percentage achieving the highest efficiency and water cooling the lowest.
Short-term power load forecasting based on sparrow search algorithm-variational mode decomposition and attention-long short-term memory
Authors: Duan Qinwei , He Xiangzhen , Chao Zhu , Tang Xuchen , Li Zugang
Published: April 2024

To improve the forecasting accuracy of power load, the forecasting model based on sparrow search algorithm (SSA), variational mode decomposition (VMD), attention mechanism and long short-term memory (LSTM) was proposed. Firstly, SSA is used to optimize the number of decomposition and penalty factor in VMD and realize the decomposition operation of the initial data. Then, LSTM is used to predict each component, and on this basis, feature and temporal attention mechanisms are introduced. Feature attention mechanism is introduced to calculate the contribution rate of relevant input features in real time, and the feature weights are modified to avoid the limitations of traditional methods relying on the threshold of expert experience association rules. Temporal attention mechanism is applied to extract the historical key moments and improve the stability of the time series prediction effect. Finally, the final result is obtained by superimposing the prediction results of each component to complete the power load prediction. Practical examples show that, compared with other methods, the proposed model achieves the highest prediction accuracy, with an RMSE of 1.23, MAE of 0.99 and MAPE of 11.62%.