bluuebunny/crossref_metadata_2025 huggingface dataset:
Wideband decoupling technique for two‐element antenna array by using pixel neutralization line
Authors: Cheng Yi‐Feng , He Yangyang , Wu Wen‐Jing , Chen Shichang , Wang Gaofeng
Published: June 2022

This letter proposes a high isolation two‐element multiple input multiple output (MIMO) antenna by using a wideband pixel neutralization line (NL). The design procedures are simplified as follows: (1) Obtaining the Y‐parameters of the original two‐element antenna with a grid of microstrip stubs, and discrete ports are inserted among microstrip stubs; (2) obtaining the binary codes of the optimum route. Importing Y‐parameters into MATLAB, and using a genetic algorithm to obtain the optimum connection route by design formulas upon scattering matrix which guarantees high isolation; (3) translating the binary codes into the actual connection metallic lines; (4) adding the designed pixel NL and appropriate matching branches into EM simulator to optimize the antenna; (5) obtaining a high isolation two‐element antenna. The original two‐element antenna has poor isolation with the main path coupling, and the pixel NL provides an auxiliary coupling path between two elements. By adjusting pixel NL, the magnitude strengths of two coupling signals realize the same, while the phases are exactly opposite. Therefore, the wideband high isolation between antenna elements is realized. To verify the practicability of the proposed pixel decoupling neutral line, a reference and proposed two‐element MIMO antennas are fabricated and measured. In the experiment, the isolation of the proposed two‐element antenna with an edge‐to‐edge distance of 0.0943λ0 (λ0 is the wavelength in free space at the center frequency) is enhanced by about 17 dB in the working frequency band from 0.975 to 1.025 GHz. Besides, an L‐typed feeding network is added to guarantee a good matching condition. The proposed two‐element antenna has a size of 0.617λ0 × 0.667λ0, and the dimension of each radiation patch is 0.3267λ0 × 0.0725λ0. The proposed GA algorithm‐based decoupling technique has a significant superiority over traditional ones. Efficient, simple, and one‐time EM simulation are its major advantages, which can liberate the RF engineer from the heavy debugging work.
Artificial intelligence–based CT metrics used in predicting clinical outcome of COVID‐19 in young and middle‐aged adults
Authors: Xudong Yu , Weihong Liu , Feng Xia , Yanli Li , Weishun Lan , Fengjun Zhang , Jiao Gao , Jiawei Li , Xiaolu Huang , Huailiang Huang , Jianye Liang , Sihui Zeng , Chuanmiao Xie , Hanhui Li , Liang Mao
Published: June 2022

Background

Currently, most researchers mainly analyzed coronavirus disease 2019 (COVID‐19) pneumonia visually or qualitatively, probably somewhat time‐consuming and not precise enough.

Purpose

This study aimed to excavate more information, such as differences in distribution, density, and severity of pneumonia lesions between males and females in a specific age group using artificial intelligence (AI)‐based computed tomography (CT) metrics. Besides, these metrics were incorporated into a clinical regression model to predict the short‐term outcome.

Materials and methods

The clinical, laboratory information and a series of HRCT images from 49 patients, aged from 20 to 50 years and confirmed with COVID‐19, were collected. The volumes and percentages of infection (POIs) among bilateral lungs and each bronchopulmonary segment were extracted using uAI‐Discover‐NCP software (version R001). The POI in three HU ranges (i.e., <−300, −300–49, and ≥50 HU representing ground‐glass opacity [GGO], mixed opacity, and consolidation) were also extracted. Hospital stay was predicted with several POI after adjusting days from illness onset to admission, leucocytes, lymphocytes, C‐reactive protein, age, and gender using a multiple linear regression model. A total of 91 patients aged 20–50 from public database were selected.

Results

Right lower lobes had the highest POI, followed by left lower lobes, right upper lobes, middle lobes, and left upper lobes. The distributions in lung lobes and segments were different between the sexes. Men had a higher total POI and GGO of the lungs, but less consolidation than women in initial CT (all p < 0.05). The total POI, percentage of consolidation on initial CT, and changed POI were positively correlated with hospital stay in the model. A total of 91 patients aged 20–50 years in the public database were selected, and AI segmentation was performed. The POI of the lower lobes was obviously higher than that in the upper lobes; the POI of each segment of the right upper lobe in the males was higher than that in the females, which was consistent with the result of the 49 patients previously.

Conclusion

Both men and women had characteristic distributions in lung lobes and bronchopulmonary segments. AI‐based CT quantitative metrics can provide more precise information regarding lesion distribution and severity to predict clinical outcome.
Size‐adaptive mediastinal multilesion detection in chest CT images via deep learning and a benchmark dataset
Authors: Wang Jun , Ji Xiawei , Zhao Mengmeng , Wen Yaofeng , She Yunlang , Deng Jiajun , Chen Chang , Qian Dahong , Lu Hongbing , Zhao Deping
Published: June 2022

Purpose

Many deep learning methods have been developed for pulmonary lesion detection in chest computed tomography (CT) images. However, these methods generally target one particular lesion type, that is, pulmonary nodules. In this work, we intend to develop and evaluate a novel deep learning method for a more challenging task, detecting various benign and malignant mediastinal lesions with wide variations in sizes, shapes, intensities, and locations in chest CT images.

Methods

Our method for mediastinal lesion detection contains two main stages: (a) size‐adaptive lesion candidate detection followed by (b) false‐positive (FP) reduction and benign–malignant classification. For candidate detection, an anchor‐free and one‐stage detector, namely 3D‐CenterNet is designed to locate suspicious regions (i.e., candidates with various sizes) within the mediastinum. Then, a 3D‐SEResNet‐based classifier is used to differentiate FPs, benign lesions, and malignant lesions from the candidates.

Results

We evaluate the proposed method by conducting five‐fold cross‐validation on a relatively large‐scale dataset, which consists of data collected on 1136 patients from a grade A tertiary hospital. The method can achieve sensitivity scores of 84.3% ± 1.9%, 90.2% ± 1.4%, 93.2% ± 0.8%, and 93.9% ± 1.1%, respectively, in finding all benign and malignant lesions at 1/8, 1/4, ½, and 1 FPs per scan, and the accuracy of benign–malignant classification can reach up to 78.7% ± 2.5%.

Conclusions

The proposed method can effectively detect mediastinal lesions with various sizes, shapes, and locations in chest CT images. It can be integrated into most existing pulmonary lesion detection systems to promote their clinical applications. The method can also be readily extended to other similar 3D lesion detection tasks.
Patterns of Hatchery-Produced Returns of American Shad in the James River, Virginia
Authors: McGrath Patrick E. , Watkins Brian E. , Magee Ashleigh , Hilton Eric J.
Published: June 2022

American Shad Alosa sapidissima is an anadromous clupeid that once supported a robust fishery but has declined drastically throughout its native range due to overfishing, dam proliferation, and poor water quality. A hatchery program on the James River in Virginia was introduced in 1992 to support the recovery of stocks. Following a moratorium of the fishery enacted in 1994, a fisheries-independent survey was initiated in 1998 to monitor the population recovery efforts and status of American Shad stocks in Virginia. This paper examined 22 years of monitoring data for the James River and determined the effect of hatchery inputs on the James River stock of American Shad. The spawning stock index increased from 2.57 in 1998 to a peak of 9.33 in 2003 but has generally been declining since and has been at very low levels in most recent years. The hatchery prevalence for female American Shad (i.e., the percentage of fish derived from the hatchery) ranged between 3.6% and 60.5%. Years with higher spawning stock index values were significantly correlated to higher percentages of hatchery fish returning to spawn. The stock–recruitment relationship was best explained by the Ricker model, which had the lowest residual standard error and Akaike information criterion value. A threshold level of hatchery-released individuals (approximately 4 million larvae) was necessary to achieve the highest numbers of returning spawners, but stocking above 7 million larvae correlated with declining returns. Long-term monitoring of the James River American Shad spawning population allowed for the critical examination of the contribution of hatchery individuals to the yearly spawning run and the relative success rate of each hatchery year-class. From these data, we consider that the James River spawning stock of American Shad was dependent upon hatchery inputs, with ideal hatchery returns occurring during years of moderate levels of hatchery stocking.
Spatial Variability of Silver Carp Population Demographics in a Large Tributary River
Authors: Werner Jacob P. , Dean Quintin J. , Pegg Mark A. , Hamel Martin J.
Published: June 2022

Silver Carp Hypophthalmichthys molitrix have expanded their range to encompass most of the Mississippi River basin, including much of the Missouri River. However, there is a paucity of information concerning Silver Carp in the Missouri River basin, especially in tributaries. Little is known about how Silver Carp function in these tributaries or how connectivity with a main-stem river can influence population demographics within either system. The Kansas River is a tributary to the Missouri River and has multiple physical anthropogenic barriers creating varying levels of connectivity within the system, as well as with the Missouri River. These varying levels of connectivity, or lack thereof, provide a unique opportunity to examine population demographics in river segments separated by barriers. We collected Silver Carp from upstream and downstream of the first two barriers on the Kansas River in the summers of 2018 and 2019. No Silver Carp were captured upstream of a hydropower dam at river kilometer 84 but were found upstream of a water diversion weir at river kilometer 24. Catch rates of adult Silver Carp were lower in the reach above the weir, but Silver Carp caught in this reach exhibited greater growth rates than Silver Carp captured below the weir. Catch rates of juveniles were also lower in the reach above the weir. Limited connectivity within the Kansas River via the water diversion weir could influence size structure and catch rates of Silver Carp captured above and below the weir. Lack of juveniles above the weir indicates that reproduction may be limited in this reach, and river conditions below the weir may be more suitable for rearing juvenile Silver Carp. This information is important for understanding Silver Carp population demographics across a range of river environments, providing critical information for the development and implementation of broadscale control plans.
Distributionally risk‐receptive and risk‐averse network interdiction problems with general ambiguity set
Authors: Kang Sumin , Bansal Manish
Published: June 2022

We introduce generalizations of stochastic network interdiction problem with distributional ambiguity. Specifically, we consider a distributionally risk‐averse (or robust) network interdiction problem (DRA‐NIP) and a distributionally risk‐receptive network interdiction problem (DRR‐NIP) where a leader maximizes a follower's minimal expected objective value for either the worst‐case or the best‐case, respectively, probability distribution belonging to ambiguity set (a set of distributions). The DRA‐NIP arises in applications where a risk‐averse leader interdicts a follower to cause delays in their supply convoy. In contrast, the DRR‐NIP provides network vulnerability analysis where a network‐user seeks to identify vulnerabilities in the network against potential disruptions by an adversary (or leader) who is receptive to risk for improving the expected objective values. We present finitely convergent algorithms for solving DRA‐NIP and DRR‐NIP with a general ambiguity set. To evaluate their performance, we provide results of our extensive computational experiments performed on instances known for (risk‐neutral) stochastic NIP.
Deep learning‐based reduced order models for the real‐time simulation of the nonlinear dynamics of microstructures
Authors: Fresca Stefania , Gobat Giorgio , Fedeli Patrick , Frangi Attilio , Manzoni Andrea
Published: June 2022

We propose a non‐intrusive deep learning‐based reduced order model (DL‐ROM) capable of capturing the complex dynamics of mechanical systems showing inertia and geometric nonlinearities. In the first phase, a limited number of high fidelity snapshots are used to generate a POD‐Galerkin ROM which is subsequently exploited to generate the data, covering the whole parameter range, used in the training phase of the DL‐ROM. A convolutional autoencoder is employed to map the system response onto a low‐dimensional representation and, in parallel, to model the reduced nonlinear trial manifold. The system dynamics on the manifold is described by means of a deep feedforward neural network that is trained together with the autoencoder. The strategy is benchmarked against high fidelity solutions on a clamped‐clamped beam and on a real micromirror with softening response and multiplicity of solutions. By comparing the different computational costs, we discuss the impressive gain in performance and show that the DL‐ROM truly represents a real‐time tool which can be profitably and efficiently employed in complex system‐level simulation procedures for design and optimization purposes.
Multiple occurrences of the rare Uto‐Aztecan premolar variant in Hungary point to ancient ties between populations of western Eurasia and the Americas
Authors: Scott G. Richard , Dern Laresa L. , Evinger Sandor , O'Rourke Dennis H. , Hoffecker John F.
Published: June 2022

The Uto‐Aztecan premolar (UAP) is a rare dental morphological variant long thought to be restricted to non‐Arctic Native Americans. The recent discovery of four individuals with this trait in a Hungarian sample invites reassessment of its geographic distribution. Our goal is to assess the variation of this trait on a global level and provide an explanation for its distribution. Observations on over 300 medieval Hungarian dentitions, along with data from the C.G. Turner II database, provide the authors with a global perspective on the distribution of UAP. In addition to four instances of UAP from Hungary, additional European cases have been reported from Germany, Spain, Yugoslavia, and France. Although the trait is most common in non‐Arctic Native Americans, it is absent in Africa, Arctic America, the Pacific, and Asia with a few isolated and problematic exceptions. Most papers on UAP have focused on the trait's presence in the Americas with some authors suggesting a possible New World mutation. Although rare outside of the Americas, four examples from Hungary, in addition to other reported cases from Europe, suggest a more complex history of the UAP. Recent paleogenomic research indicates that direct gene flow from a west Eurasian lineage to an Ancient Native American population may have taken place after their divergence from the ancestral Arctic Native American population (Ancient Paleo‐Siberians), thus explaining its current distribution among Europeans and non‐Arctic Native Americans.
Development of efficient energy absorption components for crashworthiness applications: An experimental study
Authors: Alshahrani Hassan , Sebaey Tamer A. , Hegazy Dalia A. , El‐baky Marwa A. Abd
Published: June 2022

This work experimentally investigates the quasi‐static crush response and energy absorption of glass‐reinforced epoxy thin‐walled crash box filled with nano‐aluminum oxide (Al2O3). The effect of the triggering (45 edge chamfering) and the weight percentage (wt%) of Al2O3 on the crushing performance have been studied. Field emission scanning electron microscope (FE‐SEM) and energy‐dispersive X‐ray spectroscopy (EDX) were adapted to show the elemental composition of the fabricated samples' surfaces. To follow the fracture mechanism, visual inspection, and scanning electron microscope (SEM) were performed. Two‐parameter Weibull distribution function was employed to statistically analyze the experimental results. Failure probability curves were established to help the designers in selecting the suitable material for energy‐absorbing applications. Results indicated that for untriggered glass/epoxy composite crash boxes, the inclusion of 1, 2, and 3 wt% of nano‐Al2O3 leads to an increase of, respectively, 16.34%, 48.46%, and 68.70% in the absorbed energy (U). While there is a decrease of 32.72% in (U) when adding 4 wt% of nano‐Al2O3. An enrichment of 9.00%, 18.04%, 31.53%, and 11.30% in crush force efficiency (CFE) was reached by the inclusion of, respectively, 1, 2, 3, and 4 wt% of nano‐Al2O3. Triggering has a considerable effect on the crashworthiness parameters of the fabricated composite crash boxes. A decrease of 6.56%, 10.11%, 4.01%, 4.76%, and 11.62% in the initial peak load (), an enrichment of 34.10%, 26.06%, 26.77%, 18.08%, and 28.97% in (CFE) and an improvement of 36.43%, 31.32%, 29.27%, 12.99%, and 52.47% in (U) were reported for composite crash boxes filled with 0, 1, 2, 3, and 4 wt% of nano‐Al2O3. It is obvious that glass/epoxy triggered composite crash boxes filled with 3 wt% of nano‐Al2O3 are appropriate to be used as energy absorbing device employed in vehicles due to their enhanced energy absorbing capabilities.
Congenital lymphocytic choriomeningitis virus: A review
Authors: Pencole Lucile , Sibiude Jeanne , Weingertner A. S. , Mandelbrot Laurent , Vauloup‐Fellous Christelle , Picone Olivier
Published: June 2022

Introduction

Lymphocytic choriomeningitis virus (LCMV) uses rodents such as mice and hamsters as its principal reservoir. When women acquire LCMV during pregnancy because of contact with rodents, it can lead to congenital LCMV infection, which is associated with high mortality and morbidity. Although the number of cases reported in the literature is increasing, LCMV is rarely mentioned because a history of exposure to rodents is uncommon and mostly unknown.

Objectives

The main objective of this article was to summarize all morphological, antenatal, and postnatal abnormalities that may suggest a congenital LCMV infection.

Methods

We reviewed PubMed case reports and case series where an antenatal and/or a postnatal description of at least one case of congenital LCMV infection was documented.

Results

We found 70 cases of congenital LCMV infection, 68 of which had antenatal or postnatal brain abnormalities, which were mainly chorioretinitis (59/70), hydrocephaly (37/70), microcephaly (22/70), ventriculomegaly (11/70) and periventricular calcifications (11/70). Antenatal and postnatal extracerebral abnormalities were mainly small for gestational age, ascites, cardiomegaly or anemia. Other organ damage was rare, but could include skin abnormalities, hydrops or hepatosplenomegaly. Seventy percent (49/70) of cases had major cerebral abnormalities that could have been detected by antenatal ultrasound examination. Congenital LCMV infection is associated with a significant mortality rate (30%) and survivors often have severe neurologic sequelae.

Conclusion

LCMV is a rare congenital infection, but awareness of the various prenatal ultrasound morphological abnormalities should be improved, and LCMV should be considered when first‐line etiological explorations are negative, especially when the mother's medical history indicates exposure to rodents.
Association between opioid therapy trajectories and potential opioid‐related adverse health events
Authors: Hayes Corey J. , Koonce Ruston M. , Gressler Laura Elisabeth , Hu Bo , Williams James Silas , Martin Bradley C.
Published: June 2022

Purpose

We identified associations between membership in seven group‐based trajectories based on supply of filled opioid prescriptions and potential opioid‐related adverse health events over a 720‐day window.

Methods

We identified two veteran cohorts with chronic non‐cancer pain who initiated treatment with long‐term opioid therapy between 2008 and 2015, excluding those with prior substance use disorder (n = 373 941) or non‐SUD, opioid‐related adverse outcome (n = 405 631) diagnoses. Outcomes of interest included opioid use disorder, non‐opioid drug use disorder, and alcohol use disorder for the first cohort; or accidents resulting in wounds or injuries, self‐inflicted injuries, opioid‐related accidents and overdoses, alcohol and non‐opioid drug‐related accidents and overdoses, and violence‐related injuries for the second cohort. Using a cross‐sectional design, Veterans were followed until the specific outcome of interest was diagnosed, they died, the study ended, or they were lost to follow up. Accelerated failure time models were estimated for each outcome.

Results

Membership in persistent moderate days covered and persistent modest days covered trajectories was associated with decreased risk of opioid use disorder (Moderate: θ = 0.59, 95%CI:0.54, 0.64; Modest: θ = 0.54, 95%CI:0.50, 0.59) and opioid overdose (Moderate: θ = 0.67,95%CI: 0.57, 0.79; Modest: θ = 0.72, 95%CI:0.61, 0.85) versus higher‐utilizing persistent users. Rapid discontinuation was associated with decreased risk of opioid use disorder (θ = 0.86, 95% CI:0.77, 0.95) and opioid overdose (θ = 0.54, 95%CI:0.41, 0.71), but increased risk of alcohol use disorder (θ = 1.07, 95%CI:1.00, 1.15) and other substance use disorders. Delayed discontinuation or delayed reduction was associated with increased risk for most opioid related adverse health events.

Conclusion

Persistent use trajectories with low levels of opioid utilization were associated with lower risks of potential opioid‐related adverse health events.
A dataset resource for clinically associated phosphosites in hepatocellular carcinoma
Authors: Meng Qian , Wang Yuqiu , Lu Dayun , Song Nixue , Zhou Hu , Zhu Hongwen
Published: June 2022

Phosphorylation is one of the most common post‐translational modifications (PTMs) and is closely related to protein activity and function, playing a critical role during cancer development. Quantitative phosphoproteomic strategies have been widely used to study the underlying mechanisms of cancer progression or drug resistance. In this report, we analyzed the association of phosphosite levels originated from our previously reported proteogenomic study in hepatocellular carcinoma (HCC) with clinical parameters, including prognosis, recurrence, and Tumor–Node–Metastasis (TNM) stages. By using both the log‐rank test and univariate Cox proportional hazards regression analysis, we found that the abundance levels of 1712 phosphosites were associated with prognosis and those of 393 phosphosites associated with recurrence. Besides, 692 phosphosites had different abundance levels among TNM stages (I, II, III+IV) by Analysis of Variance (ANOVA) test. Gene ontology (GO) biological process and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed using proteins with these statistically significant phosphosites. In conclusion, we provided a dataset resource for clinically associated phosphosites in HCC, which may be beneficial to liver cancer related basic research.
Patient‐specific synthetic magnetic resonance imaging generation from cone beam computed tomography for image guidance in liver stereotactic body radiation therapy
Authors: Zhang Zeyu , Jiang Zhuoran , Zhong Hualiang , Lu Ke , Yin Fang‐Fang , Ren Lei
Published: June 2022

Objective

Despite its prevalence, cone beam computed tomography (CBCT) has poor soft‐tissue contrast, making it challenging to localize liver tumors. We propose a patient‐specific deep learning model to generate synthetic magnetic resonance imaging (MRI) from CBCT to improve tumor localization.

Methods

A key innovation is using patient‐specific CBCT‐MRI image pairs to train a deep learning model to generate synthetic MRI from CBCT. Specifically, patient planning CT was deformably registered to prior MRI, and then used to simulate CBCT with simulated projections and Feldkamp, Davis, and Kress reconstruction. These CBCT‐MRI images were augmented using translations and rotations to generate enough patient‐specific training data. A U‐Net‐based deep learning model was developed and trained to generate synthetic MRI from CBCT in the liver, and then tested on a different CBCT dataset. Synthetic MRIs were quantitatively evaluated against ground‐truth MRI.

Results

The synthetic MRI demonstrated superb soft‐tissue contrast with clear tumor visualization. On average, the synthetic MRI achieved 28.01, 0.025, and 0.929 for peak signal‐to‐noise ratio, mean square error, and structural similarity index, respectively, outperforming CBCT images. The model performance was consistent across all three patients tested.

Conclusion

Our study demonstrated the feasibility of a patient‐specific model to generate synthetic MRI from CBCT for liver tumor localization, opening up a potential to democratize MRI guidance in clinics with conventional LINACs.
Stratosphere–troposphere coupling enhances subseasonal predictability of Northern Eurasian cold spells
Authors: Statnaia Irina , Karpechko Alexey , Kämäräinen Matti , Järvinen Heikki
Published: June 2022

Here we explore the stratospheric influence on the predictability of Eurasian cold‐spell events using the European Centre for Medium‐Range Weather Forecasts (ECMWF) ensemble hindcasts obtained from the Subseasonal‐to‐Seasonal (S2S) archive. To isolate the stratospheric influence, we subsampled two groups of hindcasts according to the strength of the stratospheric polar vortex preceding the cold spells at the surface. The predicted probability of cold spells, defined as the lowest 10th percentile of weekly mean temperature anomalies over northern Eurasia (10° W–130° E and 50° N–65° N), is systematically higher, by 0.05–0.2, at lags 7–24 days in the forecasts initialized during the weak stratospheric vortex compared to the strong stratospheric vortex group, extending the predictability of cold spells by 3–5 days. Our results suggest that, in the case of the weak polar vortex, stratosphere–troposphere coupling favors the negative Northern Annular Mode (NAM) regime and the cold‐air outbreaks in Eurasia. As a consequence, the long stratospheric predictability extends the predictability of the cold spells. On the other hand, when the polar vortex is strong, the stratospheric anomalies do not favor the observed negative NAM regime, which thus results from the internal tropospheric processes only. In this case the predictability of cold‐air spells is limited. Furthermore, we show that the extended predictability of cold spells arising from the stratosphere–troposphere coupling is captured by a simple statistical model, suggesting that governing large‐scale dynamics behave effectively linearly over some limited periods. Quantified contribution of the stratosphere–troposphere coupling to the enhanced skill of the extended‐range cold‐spell forecasts documented in our paper may prove useful in the development of forecasting tools.
Theoretical investigations on the properties of graphene supported metal (Al, Zn, Fe) catalysts and the reaction mechanism of catalyzing water to hydrogen peroxide
Authors: Wan Xu‐Jiang , Wu Yang , Mao Dan , Qin Qiao‐Qiao , Liu Xiang‐Yang , Li Lai‐Cai
Published: June 2022

In this paper, density functional theory (DFT) was used to study the reaction mechanism of the production of hydrogen peroxide from oxygen and water catalyzed by graphene supported metal (Al, Zn, and Fe) catalysts. By comparing the supported stability of metal at different sites on graphene surface, the optimal support sites are determined and then a stable catalyst model is selected. Two different reaction paths for the synthesis of hydrogen peroxide and a competitive reaction path for the generation of hydrogen are discussed, the microscopic reaction mechanism of the synthesis of hydrogen peroxide catalyzed by water and oxygen is investigated in detail. The stable structures of reactants, intermediates, and products in each path are optimized. By comparing the activation energies of different reaction paths, the optimal reaction paths are obtained, and the possibility of side reaction products is predicted. At the same time, the electron density, band structure, and density of states characteristics of these graphene supported metal catalysts are studied. The correlation between the physical properties of the three catalysts and their catalytic performances is analyzed. It is predicted that Al, Zn, and Fe catalysts supported by graphene may have the ability to directly generate hydrogen peroxide in industrial wastewater treatment.
Safe reward‐based deep reinforcement learning control for an electro‐hydraulic servo system
Authors: Wu Minling , Liu Lijun , Yu Zhen , Li Weizhou
Published: June 2022

In this article, a safe deep reinforcement learning (DRL) control method based on a safe reward shaping method is proposed and applied to the constrained control for an electro‐hydraulic servo system (EHSS). The proposed control method improves the safety of the constrained control for a nonlinear system with the minimal intervention to the optimization of the performance objective, while the convergence speed of the DRL process has accelerated. By introducing control barrier functions (CBFs) to the reward shaping, a CBF‐based potential difference term is designed to shape the safe reward, which not only provides the safe guidance for the DRL process by encoding the safety constraints of the nonlinear system, but also considers effects of the complex safety transformation on the convergence process in the DRL. Then the safe reward‐based DRL control method is presented to learn the optimal safety policy of position tracking for the EHSS with position error constraints by planning and optimizing the safety together with the performance objective. Theoretical analysis is given to demonstrate that the proposed control method with the safe reward can achieve the optimal safety performance for the constrained control system. Experimental results of the constrained control for the EHSS with system uncertainties and perturbations are also exhibited, to show that the proposed control method converges fast and performs safer and better than the conventional control methods.
Sample size calculation for randomized selection trials with a time‐to‐event endpoint and a margin of practical equivalence
Authors: Dehbi Hakim‐Moulay , Embleton‐Thirsk Andrew , McCaw Zachary Ryan
Published: June 2022

Selection trials are used to compare potentially active experimental treatments without a control arm. While sample size calculation methods exist for binary endpoints, no such methods are available for time‐to‐event endpoints, even though these are ubiquitous in clinical trials. Recent selection trials have begun using progression‐free survival as their primary endpoint, but have dichotomized it at a specific time point for sample size calculation and analysis. This changes the clinical question and may reduce power to detect a difference between the arms. In this article, we develop the theory for sample size calculation in selection trials where the time‐to‐event endpoint is assumed to follow an exponential or Weilbull distribution. We provide a free web application for sample size calculation, as well as an R package, that researchers can use in the design of their studies.
Spermine‐Responsive Intracellular Self‐Aggregation of Gold Nanocages for Enhanced Chemotherapy and Photothermal Therapy of Breast Cancer
Authors: Xie Beibei , Zhao Huichao , Shui Mingju , Ding Yuan‐Fu , Sun Chen , Wang Ziyi , Gao Cheng , Chen Guosong , Wang Ruibing
Published: June 2022

Improving the precise accumulation and retention of nanomedicines in tumor cells is one of the keys to effective therapy of tumors. Herein, supramolecular peptides capped Au nanocages (AuNCs) that may self‐aggregate into micron‐sized clusters intracellularly in response to spermine (SPM), leading to specific accumulation and retention of AuNCs in SPM‐overexpressed tumor cells, are developed. In this design, polydopamine (PDA) is in situ coated on the surface of AuNCs with doxorubicin (DOX) encapsulated. A small peptide, Phe‐Phe‐Val‐Leu‐Lys (FFVLK), is conjugated with PDA via esterification, and cucurbit[7]uril (CB[7]) is threaded onto the N‐terminal Phe via host‐guest interactions. Once the supramolecular peptide (CB[7]‐FFVLK) capped AuNCs are internalized in SPM‐overexpressed breast cancer cells, CB[7] can be competitively removed from FFVLK by SPM, due to the much higher binding affinity between CB[7] and SPM than that between CB[7] and Phe, leading to exposure of free FFVLK, which can subsequently self‐assemble and induce the aggregation of AuNCs to micron‐sized clusters, resulting in the significantly enhanced accumulation and retention of DOX‐loaded AuNCs in tumor cells. Under NIR laser irradiation, the enhanced photothermal conversion of AuNCs aggregates, together with photothermia‐induced release of DOX leads to synergistic photothermal therapy and chemotherapy against breast cancer.
An Efficient Electron Donor for Conjugated Microporous Polymer Photocatalysts with High Photocatalytic Hydrogen Evolution Activity
Authors: Han Changzhi , Xiang Sihui , Ge Mantang , Xie Peixuan , Zhang Chong , Jiang Jia‐Xing
Published: June 2022

Conjugated microporous polymers (CMPs) with donor‐acceptor (D‐A) molecular structure show high photocatalytic activity for hydrogen evolution due to the efficient light‐induced electron/hole separation, which is mostly determined by the nature of electron donor and acceptor units. Therefore, the selection of electron donor and acceptor holds the key point to construct high performance polymer photocatalysts. Herein, two dibenzo[b,d]thiophene‐S,S‐dioxide (BTDO) containing CMP photocatalysts using tetraphenylethylene (TPE) or dibenzo[g,p]chrysene (DBC) as the electron donor to investigate the influence of the geometry of electron donor on the photocatalytic activity are design and synthesized. Compared with the twisted TPE donor, DBC has a planar molecular structure with extended π‐conjugation, which promotes the charges transmission and light‐induced electron/hole separation. As a result, the polymer DBC‐BTDO produced from DBC donor shows a remarkable photocatalytic hydrogen evolution rate (HER) of 104.86 mmol h‐1 g‐1 under full arc light (λ > 300 nm), which is much higher than that of the polymer TPE‐BTDO (1.80 mmol h‐1 g‐1), demonstrating that DBC can be an efficient electron donor for constructing D‐A polymer photocatalysts with high photocatalytic activity for hydrogen evolution.
A High Potential Polyanion Cathode Material for Rechargeable Mg‐Ion Batteries
Authors: Li Cuicui , Lin Lu , Wu Wanlong , Sun Xiaoqi
Published: June 2022

The development of Mg‐ion batteries is hindered by the lack of cathode materials that allow facile and reversible Mg2+ intercalation at high potential. Herein, the authors present a polyanion cathode material of K2(VO)2(HPO4)2(C2O4)⋅4.5H2O (KVPCH) for Mg‐ion batteries. The inductive effect of polyanions ensures the high redox potential of the vanadium centers. In addition, the material contains structural water located between the layers. It helps with Mg2+ desolvation at the electrode–electrolyte interface and facilitates its diffusion in the structure, as confirmed by experimental analysis and theoretical calculations. Thanks to those factors, the KVPCH electrode presents excellent Mg storage capability at room temperature. It delivers 121 mAh g–1 capacity at 1C with a high average discharge potential of 0.16 V versus Ag/Ag+ (3.2 V vs Mg/Mg2+). A capacity retention of 87% is realized after 1500 cycles at 5C. A rocking‐chair Mg‐ion full cell is also demonstrated with the KVPCH cathode and a MoOx anode, which achieves 46 mAh g–1 capacity (based on the total active material mass of two electrodes). This work would bring effective paths for the design of cathode materials for Mg‐ion batteries.
Potential Applications of Nickel‐Based Metal‐Organic Frameworks and their Derivatives
Authors: Helal Aasif , Shaheen Shah Syed , Usman Muhammad , Khan Mohd Yusuf , Aziz Md. Abdul , Mizanur Rahman Mohammad
Published: June 2022

Metal‐Organic Frameworks (MOFs), a novel class of porous extended crystalline structures, are favored in different fields of heterogeneous catalysis, CO2separation and conversion, and energy storage (supercapacitors) due to their convenience of synthesis, structural tailor‐ability, tunable pore size, high porosity, large specific surface area, devisable structures, and adjustable compositions. Nickel (Ni) is a ubiquitous element extensively applied in various fields of catalysis and energy storage due to its low cost, high abundance, thermal and chemical stability, and environmentally benign nature. Ni‐based MOFs and their derivatives provide us with the opportunity to modify different properties of the Ni center to improve their potential as heterogeneous catalysts or energy storage materials. The recent achievements of Ni−MOFs and their derivatives as catalysts, membrane materials for CO2separation and conversion, electrode materials and their respective performance have been discussed in this review.
The interplay between students' motivational profiles and science learning
Authors: Kubsch Marcus , Fortus David , Neumann Knut , Nordine Jeffrey , Krajcik Joseph
Published: June 2022

Students' motivation plays an important role in successful science learning. However, motivation is a complex construct. Theories of motivation suggests that students' motivation must be conceptualized as a motivational system with numerous components that interact in complex ways and influence metacognitive processes such as self‐evaluation. This complexity is further increased because students' motivation and success in science learning influence each other as they develop over time. It is challenging to study the co‐development of motivation and learning due to these complex interactions which can vary widely across individuals. Recently, person‐centered approaches that capture students' motivational profiles, that is, the multiplicity of motivational factors as they co‐occur in students, have been successfully used in educational psychology to better understand the complex interplay between the co‐development of students' motivation and learning. We employed a person‐centered approach to study how the motivational profiles, constructed from goal‐orientation, self‐efficacy, and engagement data of N = 401 middle school students developed over the course of a 10‐week energy unit and how that development was related to students' learning. We identified four characteristic motivational profiles with varying temporal stability and found that students' learning over the course of the unit was best characterized by considering the type of students' motivational profiles and the transitions that occurred between them. We discuss implications for the design and implementation of interventions and future research into the complex interplay between motivation and learning.
Frame Accuracy of Combined EPN Weekly Coordinate Solutions
Authors: Kotsakis Christopher , Chatzinikos Miltiadis
Published: June 2022

The scope of this paper is to perform an internal quality assessment, at frame parameter level, on the combined EPN weekly coordinate solutions. Specifically, the weekly SINEX solution files from the EPN Analysis Combination Centre are analyzed in order to infer the internal accuracy of the origin, orientation and scale of the respective epoch solutions. Our investigation covers almost the entire operational period of EPN starting from 1999 up to present time, and it uses both the routine and re-processed (repro2) series of combined weekly solutions. Through the results of this study we are able to assess the impact of various changes or updates that have been applied into the routine GNSS data processing and combination strategies on the quality of the estimated EPN weekly frames.
An Entrepreneurial Process for Exploiting Vulnerable People’s Labor
Authors: Shepherd Dean A. , Parida Vinit , Wincent Joakim
Published: June 2022

In this chapter—“An Entrepreneurial Process for Exploiting Vulnerable People’s Labor”—we take an even bigger step toward the dark side of entrepreneurial action in response to chronic adversity. In this chapter, we take the perspective of victims to explore a destructive entrepreneurial process that involves multiple actors—namely, that of exploiting vulnerable women and girls for human trafficking. We focus on the destructive entrepreneurial practices used to exploit vulnerable individuals for their labor to explain how entrepreneurs (as actors within the human-trafficking system) methodically target impoverished women and girls and transform their autonomous objections into unquestioned compliance. We show that through the entrepreneurial practices of (1) deceptive recruiting of the vulnerable, (2) entrapping through isolation, (3) extinguishing alternatives by building barriers, and (4) converting the exploited into exploiters, these entrepreneurs diminish and eventually eliminate vulnerable workers’ autonomy. In doing so, we shed light on the illegal entrepreneurial process of exploiting vulnerable individuals’ labor and ruining their lives by eliminating their free will.
Designing Online Learning Environments to Support Problem-Based Learning
Authors: Ge Xun , Huang Kun
Published: June 2022

Problem-based learning (PBL) represents an instructional approach through which learning is gained by investigating, negotiating, and resolving meaningful problems. PBL can be challenging to implement, and the online learning ecology adds another layer of challenges as it demands effective interactions between pedagogy and technology. To inform the design of online learning environments to support PBL, this chapter presents a practical pedagogical framework to support four key aspects of PBL implementation: (1) preparation and planning, (2) design and development, (3) implementation and facilitation, and (4) assessment. Strategies, tools, and examples were drawn from the literature to address each aspect.
Effectivity of Semi-positive Line Bundles
Authors: Anella F. , Huybrechts D.
Published: June 2022

We review work by Campana–Oguiso–Peternell (J Differ Geom 85(3):397–424, 2010) and Verbitsky (Geom Funct Anal 19(5):1481–1493, 2010) showing that a semi-positive line bundle on a hyperkähler manifold admits at least one non-trivial section. This is modest but tangible evidence towards the SYZ conjecture for hyperkähler manifolds.
Trends in data quality and quality indicators 5 years after implementation of the Dutch Hip Fracture Audit
Authors: Würdemann F. S. , Krijnen P. , van Zwet E. W. , Arends A. J. , Heetveld M. J. , Trappenburg M. C. , Hegeman J. H. , Schipper I. B. ,   The Dutch Hip Fracture Audit Group, Calf A. H. , van Egmond P. W. , van Eijk M. , van Heijl M. , Luyten C. , Schutte B. G. , Voeten S. C.
Published: June 2022

Purpose

The Dutch Hip Fracture Audit (DHFA), a nationwide hip fracture registry in the Netherlands, registers hip fracture patients and aims to improve quality of care since 2016. This study shows trends in the data quality during the first 5 years of data acquisition within the DHFA, as well as trends over time for designated quality indicators (QI).

Methods

All patients registered in the DHFA between 1-1-2016 and 31-12-2020 were included. Data quality-registry case coverage and data completeness-and baseline characteristics are reported. Five QI are analysed: Time to surgery < 48 h, assessment for osteoporosis, orthogeriatric co-management, registration of functional outcomes at three months, 30-day mortality. The independent association between QI results and report year was tested using mixed-effects logistic models and in the case of 30-day mortality adjusted for casemix.

Results

In 2020, the case capture of the DHFA comprised 85% of the Dutch hip fracture patients, 66/68 hospitals participated. The average of missing clinical values was 7.5% in 2016 and 3.2% in 2020. The 3 months follow-up completeness was 36.2% (2016) and 46.8% (2020). The QI ‘time to surgery’ was consistently high, assessment for osteoporosis remained low, orthogeriatric co-management scores increased without significance, registration of functional outcomes improved significantly and 30-day mortality rates remained unchanged.

Conclusion

The DHFA has successfully been implemented in the past five years. Trends show improvement on data quality. Analysis of several QI indicate points of attention. Future perspectives include lowering the burden of registration, whilst improving (registration of) hip fracture patients outcomes.
The local cohomology spectral sequence for topological modular forms
Authors: Bruner Robert , Greenlees John , Rognes John
Published: June 2022

We discuss proofs of local cohomology theorems for topological modular forms, based on Mahowald–Rezk duality and on Gorenstein duality, and then make the associated local cohomology spectral sequences explicit, including their differential patterns and hidden extensions.
Hematologic malignancies following immune checkpoint inhibition for solid tumors
Authors: van Eijs Mick J. M. , van der Wagen Lotte E. , Mous Rogier , Leguit Roos J. , van de Corput Lisette , van Lindert Anne S. R. , Suelmann Britt B. M. , Kamphuis Anna M. , Nierkens Stefan , Suijkerbuijk Karijn P. M.
Published: June 2022

Immune checkpoint inhibition (ICI) can induce durable responses in patients with advanced malignancies. Three cases of hematological neoplasia following ICI for solid tumors have been reported to date. We present five patients treated at our tertiary referral center between 2017 and 2021 who developed chronic myeloid leukemia (two patients), acute myeloid leukemia, myelodysplastic syndrome and chronic eosinophilic leukemia during or after anti-PD-1-based treatment. Molecular analyses were performed on pre-ICI samples to identify baseline variants in myeloid genes. We hypothesize that PD-1 blockade might accelerate progression to overt myeloid malignancies and discuss potential underlying mechanisms.
Core body temperatures during final stages of life—an evaluation of data from in-hospital decedents
Authors: Scheidemann Patrick , Schwender Holger , Ritz-Timme Stefanie , Kindgen-Milles Detlef , Hartung Benno
Published: June 2022

Temperature-based methods are widely accepted as the gold standard for death time estimation. In the absence of any other information, the nomogram method generally assumes that a person died with a core body temperature of approximately 37.2 °C. Nevertheless, several external and internal factors may alter the body temperature during agony. A retrospective medical record analysis was carried out on in-hospital death cases from two consecutive years of surgical intensive care units to determine the effects of factors influencing the core body temperature at the point of death. Data from 103 case files were included in the statistical data evaluation. The body temperature fluctuated between and within individuals over time. No clear correlation to certain death groups was observed. Even primary cardiac deaths showed broad intervals of temperatures at the point of death. Men seem to die with higher body temperatures than women. The presented data highlight potential biases for death time estimations when generally assuming a core body temperature of 37.2 °C. In conclusion, the estimation of the time of death should include various methods, including a non-temperature-dependent method. Any uncertainties regarding the body temperature at point of death need to be resolved (e.g. by identifying fever constellations) and elucidated if elimination is not possible.