bluuebunny/crossref_metadata_2025 huggingface dataset:
Genome sequencing reveals novel noncoding variants in PLA2G6 and LMNB1 causing progressive neurologic disease
Authors: Borja Nicholas , Bivona Stephanie , Peart Lé Shon , Johnson Brittany , Gonzalez Joanna , Barbouth Deborah , Moore Henry , Guo Shengru ,   Undiagnosed Disease Network, Bademci Guney , Tekin Mustafa
Published: March 2022

Neurodegenerative disorders and leukodystrophies are progressive neurologic conditions that can occur following the disruption of intricately coordinated patterns of gene expression. Exome sequencing has been adopted as an effective diagnostic tool for determining the underlying genetic etiology of Mendelian neurologic disorders, however genome sequencing offer advantages in its ability to identify and characterize copy number, structural, and sequence variants in noncoding regions. Genome sequencing from peripheral leukocytes was performed on two patients with progressive neurologic disease of unknown etiology following negative genetic investigations including exome sequencing. RNA sequencing from peripheral blood was performed to determine gene expression patterns in one of the patients. Potential causative variants were matched to the patients’ clinical presentation. The first proband was found to be heterozygous for a likely pathogenic missense variant in PLA2G6 (c.386T>C; p.Leu129Pro) and have an additional deep intronic variant in PLA2G6 (c.2035‐926G>A). RNA sequencing indicated this latter variant created a splice acceptor site leading to the incorporation of a pseudo‐exon introducing a premature termination codon. The second proband was heterozygous for a 261 kb deletion upstream of LMNB1 that included an enhancer region. Previous reports of copy number variants spanning this region of cis‐acting regulatory elements corroborated its pathogenicity. When combined with clinical presentations, these findings led to a definitive diagnosis of autosomal recessive infantile neuroaxonal dystrophy and autosomal dominant adult‐onset demyelinating leukodystrophy, respectively. In patients with progressive neurologic disease of unknown etiology, genome sequencing with the addition of RNA analysis where appropriate should be considered for the identification of causative noncoding pathogenic variants.
Double‐diffusive convection on peristaltic flow of hyperbolic tangent nanofluid in non‐uniform channel with induced magnetic field
Authors: Akram Safia , Razia Alia , Umair Mir Yasir , Abdulrazzaq Tuqa , Homod Raad Z.
Published: March 2022

Consequence of thermal and concentration convection on peristaltic pumping of hyperbolic tangent nanofluid in a non‐uniform channel and induced magnetic field is discussed in this article. The brief mathematical modeling, along with induced magnetic field, of hyperbolic tangent nanofluid is given. The governing equations are reduced to dimensionless form by using appropriate transformations. Exact solutions are calculated for temperature, nanoparticle volume fraction, and concentration. Numerical technique is manipulated to solve the highly non‐linear differential equations. The roll of different variables is graphically analyzed in terms of concentration, temperature, volume fraction of nanoparticles, axial induced magnetic field, magnetic force function, stream functions, pressure rise, and pressure gradient.
Results on approximate controllability of fractional stochastic Sobolev‐type Volterra–Fredholm integro‐differential equation of order 1 < r < 2
Authors: Dineshkumar Chendrayan , Udhayakumar Ramalingam
Published: March 2022

The main motivation of our conversation is the approximate controllability of fractional stochastic Sobolev‐type Volterra–Fredholm integro‐differential equation of order 1 < r < 2. Using principles and ideas from stochastic analysis, the theory of cosine family, fractional calculus, and Banach fixed point techniques, the key findings are established. We begin by emphasizing the existence of mild solutions and then demonstrate the approximate controllability of the fractional stochastic control equation. We then apply our findings to the theory of nonlocal conditions. At last, an application is established for drawing the theory of the main results.
Inversion of the windowed linear canonical transform with Riemann sums
Authors: Han Yaoyao , Sun Wenchang
Published: March 2022

In this paper, we study the inversion of the windowed linear canonical transform. We show that for certain window functions, a function can be recovered from its windowed linear canonical transform with a discrete series. We give necessary and sufficient conditions for the convergence of the series. Both the convergence in norm and the pointwise convergence are studied. Moreover, we get an inversion formula for integrable functions with the Cesàro summability.
Design of miniaturized 5‐elements array GPS microstrip antenna for anti‐jamming
Authors: Lee Hyo‐Jin , Choi Dong‐Su , Choi Yoon‐Seon , Lee Dong‐Kook , Woo Jong‐Myung
Published: March 2022

In this article, we proposed a miniaturized 5‐elements array GPS microstrip antenna for anti‐jamming. For mounting on small air vehicles such as drones, the size of the proposed array antenna was set to 100 mm × 100 mm. To implement this, the radiating element was miniaturized through perturbation theory and high dielectric. For miniaturization of the radiating element, the size of the rectangular radiating element was reduced, and an extension line up to the size of the basic radiating element was formed in each of the four corners. It was folded in an “L” shape and lowered at a right angle to the radiation opening. When arranging, the antenna was rotated by 90 degrees and arrayed sequentially to arrange the feeding point at the corner, avoiding an influence on the interference. In addition, the centered antenna was designed with lowered height of the dielectric to minimize interference with the other four. The consequent single antenna resulted in the size of 19.7 mm × 19.3 mm, achieving 94.5% of miniaturization. This led average isolation between the corner and the center to be −17.59 dB or less. At the center frequency of 1.575 GHz, the average bandwidth for the five radiating elements was at 17.8 MHz. Additionally, the average gain of the Eθ component was −4.62 dBi in the yz‐plane and − 3.58 dBi in the xz‐plane, and efficiency value was 69% in simulation. As a miniaturized 5‐elements array GPS microstrip antenna, it obtained sufficient bandwidth and succeeded to gain to location information in the GPS L1 band.
ConCeptCNN: A novel multi‐filter convolutional neural network for the prediction of neurodevelopmental disorders using brain connectome
Authors: Chen Ming , Li Hailong , Fan Howard , Dillman Jonathan R. , Wang Hui , Altaye Mekibib , Zhang Bin , Parikh Nehal A. , He Lili
Published: March 2022

Background

Deep convolutional neural network (CNN) and its derivatives have recently shown great promise in the prediction of brain disorders using brain connectome data. Existing deep CNN methods using single global row and column convolutional filters have limited ability to extract discriminative information from brain connectome for prediction tasks.

Purpose

This paper presents a novel deep Connectome–Inception CNN (ConCeptCNN) model, which is developed based on multiple convolutional filters. The proposed model is used to extract topological features from brain connectome data for neurological disorders classification and analysis.

Methods

The ConCeptCNN uses multiple vector‐shaped filters extract topological information from the brain connectome at different levels for complementary feature embeddings of brain connectome. The proposed model is validated using two datasets: the Neuro Bureau ADHD‐200 dataset and the Cincinnati Early Prediction Study (CINEPS) dataset.

Results

In a cross‐validation experiment, the ConCeptCNN achieved a prediction accuracy of 78.7% for the detection of attention deficit hyperactivity disorder (ADHD) in adolescents and an accuracy of 81.6% for the prediction of cognitive deficits at 2 years corrected age in very preterm infants. In addition to the classification tasks, the ConCeptCNN identified several brain regions that are discriminative to neurodevelopmental disorders.

Conclusions

We compared the ConCeptCNN with several peer CNN methods. The results demonstrated that proposed model improves overall classification performance of neurodevelopmental disorders prediction tasks.
Machine learning based oxygen and carbon concentration derivation using dual‐energy CT for PET‐based dose verification in proton therapy
Authors: Liu Yuxiang , Zhou Long , Peng Hao
Published: March 2022

Purpose

Online dose verification based on proton‐induced positron emitters requires high accuracy in the assignment of elemental composition (e.g., C and O). We developed a machine learning framework for deriving oxygen and carbon concentration based on dual‐energy CT (DECT).

Methods

Digital phantoms at the head site were constructed based on single‐energy CT (SECT) and stoichiometric calibration. DECT images (80 and 140 kVp) were synthesized using two methods: (1) theoretical CT numbers with Gaussian noise (method 1) and (2) forward/backward image reconstruction with poly‐energetic energy spectrum and Poisson noise modeled (method 2). Two architectures of convolutional neural networks, UNet and ResNet, were investigated to map from DECT images to C/O weights. Four cases (UNet‐1: Method 1+UNet, ResNet‐1: Method 1+ResNet, UNet‐2: Method 2+UNet, and ResNet‐2: Method 2 +ResNet) were tested for different tissue types and different noise levels. Monte‐Carlo simulation was employed to identify the impact of fluctuation in oxygen and carbon concentration on activity/dose distribution.

Results

When no noise is present, all four cases are able to obtain <2% mean absolute errors and <4% root mean square error (RMSE). For the worst image quality (e.g., lowest image SNR), the RMSE for O among all tissue types is 3.02% (UNet‐1), 4.46% (ResNet‐1), 4.38% (UNet‐2), and 6.31% (ResNet‐2), respectively. For UNet‐1 and ResNet‐1, the model performed slightly better in terms of RMSE for skeletal tissue than soft tissues. Such a trend is not observed for UNet‐2 and ResNet‐2. With regard to the comparison between UNet and ResNet, different accuracy and noise immunity are observed. The activity profiles exhibit 3%–5% difference in terms of mean relative error between the ground truth and machine learning outcome.

Conclusion

We explored the feasibility of a machine learning framework to derive elemental concentration of oxygen and carbon based on DECT images. Two machine learning models, UNet and ResNet, are able to utilize spatial correlation and obtain accurate carbon and oxygen concentration. This study lays a foundation for us to apply the proposed approach to clinical DECT images.
Potential of multiparametric characterization of foodstuffs by nuclear magnetic resonance to better predict microbial behavior
Authors: Recht Raphael , Omhover‐Fougy Lysiane , Stahl Valérie , Hamon Erwann
Published: March 2022

Numerous predictive microbiology models have been proposed to describe bacterial population behaviors in foodstuffs. These models depict the growth kinetics of particular bacterial strains based on key physico‐chemical parameters of food matrices and their storage temperature. In this context, there is a prominent issue to accurately characterize these parameters, notably pH, water activity (aw), and NaCl and organic acid concentrations. Usually, all these product features are determined using one destructive analysis per parameter at macroscale (>5 g). Such approach prevents an overall view of these characteristics on a single sample. Besides, it does not take into account the intra‐product microlocal variability of these parameters within foods. Nuclear magnetic resonance (NMR) is a versatile non‐invasive spectroscopic technique. Experiments can be recorded successively on a same collected sample without damaging it. In this work, we designed a dedicated NMR approach to characterize the microenvironment of foods using 10‐mg samples. The multiparametric mesoscopic‐scale approach was validated on four food matrices: a smear soft cheese, cooked peeled shrimps, cold‐smoked salmon, and smoked ham. Its implementation in situ on salmon fillets enabled to observe the intra‐product heterogeneity and to highlight the impact of process on the spatial distribution of pH, NaCl, and organic acids. This analytical development and its successful application can help address the shortcomings of monoparametric methods traditionally used for predictive microbiology purposes.
A comparable study of the optical spectra and EPR parameters for 3d1‐ and 3d9‐doped MgNH4PO4·6H2O
Authors: Chen Baojin , Zhang Junlong , Li Rong , Liang Yajin , Feng Cuidi , Zhang Huaming
Published: March 2022

VO2+ (3d1) and Cu2+ (3d9) are the two complementary states that usually show opposite distortions when they are doped in crystals. In this work, the optical absorption spectra (OAS), electron paramagnetic resonance (EPR) parameters, and local structure (LS) for VO2+ (and Cu2+) in MgNH4PO4·6H2O (MPPH) are uniformly investigated on the basis of the high‐order perturbation formulas for a 3d1 (and 3d9) ion in tetragonally compressed (and elongated) octahedra, respectively. In the calculated formulas, the required crystal‐field parameters can be obtained from the superposition model and reasonably linked with the LS distortion for VO2+ and Cu2+ centers. Based on the calculations, the tetragonal compressed [VO(H2O)5]2+ cluster (and tetragonal elongated [Cu(H2O)6]2+ cluster) is found to suffer tetragonal compression ratio of 1.65% and tetragonal elongation ratio of 3.8% along C4‐axis, respectively, due to the Jahn–Teller (JT) effect. The theoretical EPR parameters based on the above lattice distortions agree well with the experimental data, and the LS of the VO2+ and Cu2+ centers in MPPH is discussed.
Polyvinyl chloride modifications, properties, and applications: Review
Authors: Lieberzeit Peter , Bekchanov Davron , Mukhamediev Mukhtar
Published: March 2022

The present study provides an overview of the latest scientific developments in the field of application and modification of ion exchange sorbents and membranes made of granular and powdery polyvinyl chloride (PVC), focusing on some scientific works, such as water and wastewater treatment, ion exchange, gas separation, etc. For this purpose, an introduction to the various methods of modifying PVC is first given, and then the application of ion exchange sorbents and membrane is discussed. Methods of modification of PVC under homogeneous and heterogeneous conditions using modifiers containing N, S, and O atoms are also described. Various ion‐exchange sorbents and membranes based on PVC, methods for modifying PVC and the use of the obtained ion‐exchange sorbents and membranes are viewed. A comparison of the sorption properties of ion‐exchange sorbents based on PVC and sorbents used in industry has also been carried out.
Microfluidic fabrication of calcium alginate helical microfibers for highly stretchable wound dressing
Authors: Ma Wenjun , Ling Sida , Zhang Jingwei , Chen Zhuo , Xu Jianhong
Published: March 2022

Due to suitable biocompatibility and biodegradability, natural polymers have a wide range of applications in the biomedical field, but the defects of mechanical properties limit their performance in some practical scenarios. Here, the microfluidic method was used to spin alginate into helical fibers, and then the gaps of packed microfibers were filled with polyacrylamide (PAM) to obtain a calcium alginate/PAM composite polymer membrane. Compared with pure calcium alginate, this composite film greatly improved the flexibility and stretchability, and could be stretched up to 14 times of its original length, and not deform significantly under 300% strain for 8 cycles. It also had good transparency and skin adhesion, further guaranteeing the application potential in the field of wound dressings. The loading and release experiments showed that the calcium alginate fibers maintained a dense morphology, and could achieve higher loading efficiency and more controllable release than pure PAM. Above all, this film has great application potential in joint wound dressings, especially when loading with antibacterial substances or healing‐promoting drugs is needed. In addition, our research of achieving substantial optimization of elasticity and stretchability through the introduction of helical shape also has certain reference significance for other natural polymers limited by mechanical properties.
Strength and the cracking behavior of frozen sandstone containing ice‐filled flaws under uniaxial compression
Authors: Jia Hai‐liang , Han Li , Zhao Tao , Sun Qiang , Tan Xian‐jun
Published: March 2022

Understanding the mechanical properties of frozen flawed rock masses is fundamental to conducting safe rock engineering in frozen rock strata. However, there has been scarce research in this area, especially on key issues such as the strength and deformability of frozen flawed rock masses and failure processes under load. In this paper, frozen flawed sandstone was subjected to uniaxial compression and the cracking process was observed. The influences of flaw inclination angle and freezing temperature on the strength and cracking behavior of frozen flawed sandstone under load were determined. The results show that: (a) the strength of frozen flawed sandstone increases with increases in flaw inclination and decreases in temperature; (b) the flaw inclination has a dramatic influence on both the crack coalescence behavior and the final failure form of frozen flawed samples under compression; and (c) the significant influence of freezing temperature on the cracking behavior of frozen flawed sandstone is caused by the interaction between flaw ice and its surrounding rock. Strengthening of flawed sandstone by freezing results because (i) pore ice provides support and cohesion at the pore scale, while (ii) at the crack scale ice can support the flaw and resist its deformation during compression, and cementation of the ice–rock interface provides normal and tangential cracking resistance.
Sonochemical Fabrication of s‐Scheme Hierarchical CdS/BiOBr Heterojunction Photocatalyst with High Performance for Carbon Dioxide Reduction
Authors: Xiao Yunxue , Maimaitizi Hujiabudula , Okitsu Kenji , Tursun Yalkunjan , Abulizi Abulikemu
Published: March 2022

CO2 conversion to methanol becomes a promising strategy by using semiconductor‐based photocatalyst for environmental remediation and converting solar energy. In this study, a series of CdS‐modified BiOBr (CdS/BiOBr) microspheres are fabricated by mild hydrolysis‐ultrasonic method and the effect of CdS growing on the photocatalytic CO2 reduction activities of BiOBr are systematically investigated. Among all CdS/BiOBr composite photocatalysis, the highest value of CH3OH yields (876 µmol gcat−1, 4 h) is achieved with 15% CdS/BiOBr, which is nearly double higher than alone BiOBr (435 µmol gcat−1). Comparatively, the CdS/BiOBr microspheres with s‐scheme heterostructure exhibit the surprising photocatalytic performance and CH3OH selectivity, which are attributed to the enhanced light absorption, as well as effective separation and migration of the photoinduced electron–hole pairs induced by the s‐scheme heterojunction between BiOBr and CdS. This study provides a mild hydrolysis‐ultrasonic method for environmental remediation and converting energy using cost‐effective semiconductor materials.
Facile pathway to construct mesoporous silica nanoparticles loaded with pyraclostrobin: Physicochemical properties, antifungal activity, and biosafety
Authors: Feng Jianguo , Chen Zhiyang , Chen Wang , Sun Li , Yang Jinghan , He Kangli , Dong Sa , Yuan Shuzhong
Published: March 2022

BACKGROUND

A controlled‐release formulation based on mesoporous silica nanoparticles (MSNs) provides an effective way for reducing pesticide use and protecting the ecological environment. In this study, MSNs loaded with pyraclostrobin (PYR@MSNs) were prepared using a one‐pot method.

RESULTS

The characteristics of PYR@MSNs were systematically investigated, including morphology, loading content, ultraviolet (UV) resistance, release behavior, control effects against pathogens, and safety to nontarget organisms. The results show that the prepared PYR@MSNs presented characteristics of regular spherical shapes, uniform particle size (200 nm), high drug loading (38.9%), and enhanced UV resistance. Compared with traditional formulation, PYR@MSNs exhibited improved control effects against Fusarium graminearum, an extended control period, and lower toxicity to zebrafish, earthworms and BEAS‐2B cells.

CONCLUSIONS

This research will facilitate the development of efficient and safe pesticide delivery systems. The PYR@MSNs has showed its potential as a new controlled‐release formulation with increased efficacy and is expected to benefit the sustainable development of agriculture. © 2022 Society of Chemical Industry.
Toward Miniaturized Undulators with L10 Phase FePt Micromagnet Array
Authors: Gurel Derya Berkin , Gunduz Akdogan Nilay , Aksoy Avni , Akdogan Ozan
Published: March 2022

An undulator is a required part for building free‐electron lasers (FELs) upon which a large body of the literature has expressed interest for the applications in various areas such as the defense industry, material science, and medicine. The current state of the art of X‐FEL uses an undulator period down to 3 cm, which creates an output radiation wavelength down to 1.5 A using ≈14 GeV e‐beam. By developing a mm/sub‐mm period undulator (i.e., a period of 300 μm), it is possible to obtain the same output radiation wavelength with a much less e‐beam energy of ≈1.4 GeV. Thus, compact XFELs could become a reality. In this work, FePt thin films and micromagnets are synthesized by the sputtering deposition technique, and their properties are studied. The X‐ray diffraction (XRD) pattern indicated that the crystal structure transformed from face‐centered cubic (FCC) to L10 face‐centered tetragonal (FCT) phase upon annealing. Room temperature coercivity of the structures reached up to 1.4 Tesla. Undulator prototype is developed and the performance tests are done using Genesis simulation. Simulations yield output radiation with 0.52 nm wavelength and 0.7 GW peak power. Synthesized FePt micromagnets could be utilized in next‐generation miniaturized undulators.
Theoretical Analysis of Solar Cell Performance with Different Backsurface‐Filed Layers Utilizing Experimental Results of CdS Films Deposited by Pulsed Laser
Authors: Houimi Amina , Yiğit Gezgin Serap , Kılıç Hamdi Şükür
Published: March 2022

Herein, three different backsurface‐filed (BSF) layers “SnS, PbS, and V2O5” are investigated on Mo/BSF/CZTS/CdS/AZO heterojunction solar cells using experimental data of CdS thin films. CdS thin films are produced by means of the pulsed laser deposition (PLD) technique with three different deposition periods. With increasing deposition time, the crystalline sizes of CdS thin films are larger and their crystal structures are developed. In addition, the optical bandgap of CdS thin films is calculated to be 2.4 eV using the absorbance data. Using the solar cell–capacitance–simulator‐1D (SCAPS‐1D) program, the experimental properties of CdS thin films to estimate the performance of p‐CZTS/n‐CdS/AZO heterojunction solar cells are introduced. The best efficiency is 9.32% when the thickness of CdS reaches 150 nm. To further improve the efficiency, different BSF layers (SnS, PbS, and V2O5) are tested in Mo/BSF/CZTS/CdS/AZO solar cells. According to the thickness of the BSF layer, the efficiency of the solar cell increases up to 13.47%, 14.7%, and 17.41% using SnS, PbS, and V2O5as BSF layers with 0.1 μm thickness.
Electronic and Optical Properties of the Type‐II GaN/SiH van der Waals Heterostructure: A First‐Principles Study
Authors: Lv Lin , Ma Xin , Lou Wenbo , Zhang Xiaomei , Shen Chenhai , Xia Congxin , Liu Yufang
Published: March 2022

In recent years, constructing van der Waals (vdW) heterostructures based on different 2D materials has been a highly effective way to obtain desired electronic and optical properties. Herein, on the basis of first‐principles calculations, a 2D vdW heterostructure is constructed by vertically stacking the indirect‐bandgap gallium nitride (GaN) and silicane (SiH) monolayers. For the formed heterostructure, the structural, electronic, and optical properties are all computed. The obtained results show that the heterostructure is a direct‐bandgap semiconductor with typical type‐II band alignment. Furthermore, the linearly tunable bandgap, together with the robust type‐II band alignment, can be realized by applying vertical strains or external electric fields. It is also found that both monolayers exhibit the same UV absorption range and the notably enhanced UV absorption is obtained after forming the heterostructure. In particular, the maximum absorptivity can reach to 21.6%. These results are expected to provide useful references for the design of ultraviolet optoelectronic devices based on the 2D GaN/SiH vdW heterostructure.
Nonadiabatic Geometric Gates with a Shortened Loop in a Superconducting Circuit
Authors: Li Yong , Dong Yuqian , Zheng Wen , Zhang Yu , Ma Zhuang , Liu Qiang , Wang Jianhua , Li Yanzhen , Liu Youhang , Zhao Jie , Lan Dong , Li Shaoxiong , Tan Xinsheng , Yu Yang
Published: March 2022

Scalable quantum computation demands high‐fidelity gate operation, which is required to be fast and robust. The geometric gate is considered to be robust to certain types of noises, while its duration time is normally longer than a dynamical routine. Herein, a universal nonadiabatic geometric gate with a shortened loop (NAGGSL) in a superconducting circuit is demonstrated. The methods of quantum state tomography (QST) and randomized benchmarking (RB) are used to characterize the gate fidelity, proving that the decoherence effect can be reduced by this protocol. Furthermore, the robustness of this approach against certain errors is demonstrated, indicating that this scheme is promising for future scalable quantum circuits.
Delphi consensus recommendation for optimization of pulmonary hypertension therapy focusing on switching from a phosphodiesterase 5 inhibitor to riociguat
Authors: Rahaghi Franck F. , Balasubramanian Vijay P. , Bourge Robert C. , Burger Charles D. , Chakinala Murali M. , Eggert Michael S. , Elwing Jean M. , Feldman Jeremy , King Christopher , Klinger James R. , Mathai Stephen C. , McConnell John Wesley , Palevsky Harold I. , Restrepo‐Jaramillo Ricardo , Safdar Zeenat , Sager Jeffrey S. , Sood Namita , Sulica Roxana , White R. James , Hill Nicholas S.
Published: March 2022

Dual combination therapy with a phosphodiesterase‐5 inhibitor (PDE5i) and endothelin receptor antagonist is recommended for most patients with intermediate‐risk pulmonary arterial hypertension (PAH). The RESPITE and REPLACE studies suggest that switching from a PDE5i to a soluble guanylate cyclase (sGC) activator may provide clinical improvement in this situation. The optimal approach to escalation or transition of therapy in this or other scenarios is not well defined. We developed an expert consensus statement on the transition to sGC and other treatment escalations and transitions in PAH using a modified Delphi process. The Delphi process used a panel of 20 physicians with expertise in PAH. Panelists answered three questionnaires on the management of treatment escalations and transitions in PAH. The initial questionnaire included open‐ended questions. Later questionnaires consolidated the responses into statements that panelists rated on a Likert scale from −5 (strongly disagree) to +5 (strongly agree) to determine consensus. The Delphi process produced several consensus recommendations. Escalation should be considered for patients who are at high risk or not achieving treatment goals, by adding an agent from a new class, switching from oral to parenteral prostacyclins, or increasing the dose. Switching to a new class or within a class should be considered if tolerability or other considerations unrelated to efficacy are affecting adherence. Switching from a PDE5i to an SGC activator may benefit patients with intermediate risk who are not improving on their present therapy. These consensus‐based recommendations may be helpful to clinicians and beneficial for patients when evidence‐based guidance is unavailable.
Suppression of BMP signaling by PHD2 deficiency in Pulmonary Arterial hypertension
Authors: Liu Bin , Yi Dan , Pan Jiakai , Dai Jingbo , Zhu Maggie M. , Zhao You‐Yang , Oh S. Paul , Fallon Michael B. , Dai Zhiyu
Published: March 2022

BMP signaling deficiency is evident in the lungs of patients with pulmonary arterial hypertension. We demonstrated that PHD2 deficiency suppresses BMP signaling in the lung endothelial cells, suggesting the novel mechanisms of dysregulated BMP signaling in the development of pulmonary arterial hypertension.
Long‐term safety of a structured transition protocol from parenteral prostanoids to selexipag in pulmonary arterial hypertension
Authors: Tamura Yuichi , Furukawa Asuka , Tamura Yudai , Yamada Kenta , Taniguchi Hirohisa , Fukuda Keiichi , Kawamura Akio , Satoh Toru
Published: March 2022

There was no structured method for safely transition from parenteral prostanoids to oral medication. We enrolled 37 idiopathic/hereditary pulmonary arterial hypertension patients receiving triple combination therapy including parenteral prostanoids into structured transition program to oral selexipag. Four (10.8%) patients successfully transitioned under the protocol, and all of them presented long‐term safety.
A deep learning framework for real‐time 3D model registration in robot‐assisted laparoscopic surgery
Authors: Padovan Erica , Marullo Giorgia , Tanzi Leonardo , Piazzolla Pietro , Moos Sandro , Porpiglia Francesco , Vezzetti Enrico
Published: March 2022

Introduction

The current study presents a deep learning framework to determine, in real‐time, position and rotation of a target organ from an endoscopic video. These inferred data are used to overlay the 3D model of patient's organ over its real counterpart. The resulting augmented video flow is streamed back to the surgeon as a support during laparoscopic robot‐assisted procedures.

Methods

This framework exploits semantic segmentation and, thereafter, two techniques, based on Convolutional Neural Networks and motion analysis, were used to infer the rotation.

Results

The segmentation shows optimal accuracies, with a mean IoU score greater than 80% in all tests. Different performance levels are obtained for rotation, depending on the surgical procedure.

Discussion

Even if the presented methodology has various degrees of precision depending on the testing scenario, this work sets the first step for the adoption of deep learning and augmented reality to generalise the automatic registration process.
From evidence‐informed to evidence‐based: An evidence building framework for education
Authors: Owen Kaydee L. , Watkins Richard C. , Hughes J. Carl
Published: March 2022

Developing an evidence‐base for educational provision can be an arduous journey. To facilitate consistent and accurate implementation of promising approaches, research efforts need to answer questions relating to theoretical coherence, efficacy, effectiveness, cost, ease of use, and acceptability. An evidence‐building framework can help us to think critically about the current state of evidence and plan a long‐term research programme. In this conceptual paper, we draw attention to an evidence‐building framework from medical and psychosocial science that conceptualises the phases and challenges along this journey. We have adapted this framework to help researchers and other education practitioners conceptualise how to review, synthesise, generate and communicate evidence in education. This framework facilitates a questions‐to‐methods approach in our journey to evidence, dissolving the idea that some research and analysis methods are superior to others. We argue that this evidence building framework can help us to distinguish between key terms in education, such as evidence‐informed and evidence‐based practice, as well as teacher enquiry and research—helping to distinguish the roles of researchers and practitioners. This paper has direct relevance to informing how we build evidence in education and identifies a need for collaboration as we work towards an evidence‐based teaching profession.
Fidelity to participants when researching multilingual language teachers: A systematic review
Authors: Calafato Raees
Published: March 2022

The research field of multilingualism in education has grown exponentially over the last two decades, with more and more studies published every year on the need for teachers to validate the whole linguistic repertoire of their students and help them draw on their multilingualism as a resource. What has, conversely, not been accorded sufficient attention by researchers is the multilingualism of the teachers tasked with realising this. This oversight, as it were, raises ethical issues for researchers that go beyond macro ethical considerations like the need to ensure participant anonymity, their protection from harm, and data confidentiality. Education is itself a complex, ethical enterprise, where engagement with teachers and students requires greater faithfulness, exactitude, and respect on the part of researchers. The need for such engagement, from an ethical standpoint, has been magnified as governments globally implement multilingual initiatives in schools and universities that encourage teachers to harness the growing linguistic and cultural diversity that surrounds them (and of which they are a part). Based on a systematic review of 59 published works between 2016 and 2021, this article discusses the importance of adopting a fidelity‐to‐participants approach when researching multilingual language teachers. Such an approach has been missing from most studies, yet it would benefit researchers and their participants, as well as policymakers and educators in several ways.
COVID‐19 outcomes in paediatric cancer: A large scale pooled meta‐analysis of 984 cancer patients
Authors: El‐Qushayri Amr Ehab , Benmelouka Amira Yasmine , Dahy Abdullah , Hashan Mohammad Rashidul
Published: March 2022

We aimed to study the outcomes of COVID‐19 in paediatric cancer patients. On 26 October 2021, we did a systematic search for relevant articles in seven electronic databases followed by manual search. We included cancer patients aged ≤18 years. Event rates and the 95% confidence interval (95%CI) were used to report the results. We included 21 papers after screening of 2759 records. The pooled rates of hospitalisation, intensive care unit (ICU) admission and mortality were 44% (95%CI: 30–59), 14% (95%CI: 9–21) and 9% (95%CI: 6–12), respectively. Moreover, subgroup analysis revealed that high income countries had better COVID‐19 outcomes compared to upper middle income countries and lower middle income countries in terms of hospitalisation 30% (95%CI: 17–46), 60% (95%CI: 29–84) and 47% (95%CI: 36–58), ICU admission 7% (95%CI: 1–32), 13% (95%CI: 7–23) and 18% (95%CI: 6–41), and mortality 3% (95%CI: 2–5), 12% (95%CI: 8–18) and 13% (95%CI: 8–20), in order. In general, absence of specific pharmacologic intervention to prevent infection with the scarcity of vaccination coverage data among paediatric groups and its impact, high priority caution is required to avoid SARS‐CoV‐2 infection among paediatric cancer patients. Furthermore, our results highlight the importance of promoting care facilities for this vulnerable population in low and middle income regions to ensure quality care among cancer patients during pandemic crisis.
Effects of cardiovascular arousal on emotional experience
Authors: Chen Wei‐Ju , Johnson Hanna B. , Nelson Alese M. , Fleming Raymond
Published: March 2022

Studies of arousal and emotion show that generalized physiological arousal can enhance emotional experience for a range of different emotions. Other research shows that different emotions may be associated with specific patterns of physiological reactivity. Together these findings suggest that while nonspecific autonomic activation can be sufficient in the generation of emotion, specific patterns of reactivity may appear once the emotion is established. This study aimed to test this hypothesis by examining the effects of generalized arousal on emotional experience, as well as the physiological responses associated with positive and negative emotions. One hundred and nine participants either sat or stood during the viewing of positive and negative film clips while emotion ratings and cardiorespiratory measures were taken. Those who stood during the videos reported greater levels of emotion than those who sat, indicating that generalized arousal due to standing heightened emotional experience. In addition, participants exhibited greater high‐frequency heart rate variability and lower respiration rate during the negative video than the positive video, indicating that physiological reactivity differed between the positive and negative emotions. These results suggest that while patterns of physiological reactivity may be specific to individual emotions, nonspecific arousal is sufficient to enhance diverse emotions.
Cancer Stem Cell DNA Enabled Real‐Time Genotyping with Self‐Functionalized Quantum Superstructures—Overcoming the Barriers of Noninvasive cfDNA Cancer Diagnostics
Authors: Haldavnekar Rupa , Ganesh Swarna , Venkatakrishnan Krishnan , Tan Bo
Published: March 2022

Cancer diagnosis and determining its tissue of origin are crucial for clinical implementation of personalized medicine. Conventional diagnostic techniques such as imaging and tissue biopsy are unable to capture the dynamic tumor landscape. Although circulating tumor DNA (ctDNA) shows promise for diagnosis, the clinical relevance of ctDNA remains largely undetermined due to several biological and technical complexities. Here, cancer stem cell‐ctDNA is used to overcome the biological complexities like the inability for molecular analysis of ctDNA and dependence on ctDNA concentration rather than the molecular profile. Ultrasensitive quantum superstructures overcome the technical complexities of trace‐level detection and rapid diagnosis to detect ctDNA within its short half‐life. Activation of multiple surface enhanced Raman scattering mechanisms of the quantum superstructures achieved a very high enhancement factor (1.35 × 1011) and detection at ultralow concentration (10−15M) with very high reliability (RSD: 3–12%). Pilot validation with clinical plasma samples from an independent validation cohort achieved a diagnosis sensitivity of ≈95% and specificity of 83%. Quantum superstructures identified the tissue of origin with ≈75–86% sensitivity and ≈92–96% specificity. With large scale clinical validation, the technology can develop into a clinically useful liquid biopsy tool improving cancer diagnostics.
Tuning Molecular Interaction in Polymer Solar Cells via a Multifunctional Discotic Component to Enhance Photovoltaic Response
Authors: Li Han , Gong Hongkang , Sun Mengjie , Zhang Huimin , Ji Chao , Liang Chunjun , You Fangtian , Jing Xiping , Kong Xiangfei , He Zhiqun
Published: March 2022

A donor–acceptor (D–A)‐type discotic organic material (TP‐2‐PIE), having a self‐organization ability, is selected to be the third component blending with poly[4,8‐bis(5‐(2‐ethylhexyl)thiophen‐2‐yl)benzo[1,2‐b:4,5‐b’]dithiophene‐co‐3‐fluorothieno [3,4‐b]‐thiophene‐2‐carboxylate] (PTB7‐Th): [6,6]‐phenyl‐C71‐butyric acid methyl ester (PC71BM) in ternary bulk‐heterojunction polymer solar cells. The complementary absorption and energy transfer between TP‐2‐PIE and PTB7‐Th contributes to the enhancement in photocurrent generation, improving the short‐circuit current. In addition, TP‐2‐PIE alters the molecular interaction leading to an enhanced phase separation, which promotes carrier transport with a good balance and minimizes the density of trap states simultaneously. In this way, the overall photovoltaic performances are markedly enhanced at an optimal condition of 10 wt% TP‐2‐PIE in donors with a 12.6% efficiency increase. Current understanding on the functionality of this third component in ternary solar cells may be able to guide future device development.
Assessing high‐school students' modeling performance on Newtonian mechanics
Authors: Zhai Xiaoming
Published: March 2022

Assessing scientific modeling competence (SMC) is challenging because of the multi‐dimensionality of the construct and the potential variability of student performance across tasks. To deal with the challenges, this study applied Kane's validity framework to assess high‐school students' SMC in Newtonian mechanics and examined how students' performance depended on tasks. We first specified students' SMC in three dimensions: Conceptualization, Deploying Scientific Knowledge, and Representation, incorporating 11 components (e.g., conceptualization of objects). We assessed 305 high‐school students' modeling performance on two Newtonian mechanics tasks, taking task dependency into account. We applied the Many‐facet Rasch measurement (MFRM) to examine students' ability and discriminate students' performance variability across tasks. MFRM analyses revealed that among the three dimensions of SMC, Representation is most challenging for students to achieve compared to Conceptualization and Deploying Scientific Knowledge, especially among higher‐performing students. Five out of the 11 SMC components were task‐dependent, suggesting significant score variance due to the variability of tasks. After excluding task variance, we found that students were grouped into four levels (i.e., primitive non‐model, intuitive model, qualitative model, and quantitative model), and the majority of students were distributed at the medium two levels. We conclude the study by introducing three putative theories that may account for task dependency: depth of cognition, knowledge transfer, and construct irrelevant interest. The study suggests that task dependency does not necessarily compromise the interpretation of scores, as long as assessors appropriately consider potential theories in their interpretive arguments when designing tasks and interpreting scores.
Safety of intravenous iodinated contrast medium injection in rabbits undergoing conscious computed tomography
Authors: Isaac Ingrid , Richardson Jenna , Liuti Tiziana , Longo Maurizio
Published: March 2022

Background

Contrast media in CT is widely used in dogs and cats to provide superior tissue delineation and increase the diagnostic capabilities. These contrast‐enhanced imaging techniques are gaining popularity in rabbits; published studies reporting the safety of doing so are lacking.

Methods

This retrospective observational study aimed to determine the incidence of adverse events following the intravenous administration of iodinated non‐ionic contrast medium in 350 rabbits. The medical records of this subset of rabbits admitted between January 2009 and November 2018, that underwent CT examination and received intravenous contrast media, were evaluated.

Results

From the 350 rabbits, 342 rabbits were still alive 7 days after the scan. A total of eight rabbits died within 7 days of the scan, seven of which within the first 24 h. All deaths were presumed to be sequelae to the diseases they were being investigated for and not thought to be related to the administration of intravenous contrast medium.

Conclusions

The results indicated that the use of intravenous non‐iodinated contrast medium was well tolerated and safe in rabbits undergoing conscious CT examination.
Generative models for molecular discovery: Recent advances and challenges
Authors: Bilodeau Camille , Jin Wengong , Jaakkola Tommi , Barzilay Regina , Jensen Klavs F.
Published: March 2022

Development of new products often relies on the discovery of novel molecules. While conventional molecular design involves using human expertise to propose, synthesize, and test new molecules, this process can be cost and time intensive, limiting the number of molecules that can be reasonably tested. Generative modeling provides an alternative approach to molecular discovery by reformulating molecular design as an inverse design problem. Here, we review the recent advances in the state‐of‐the‐art of generative molecular design and discusses the considerations for integrating these models into real molecular discovery campaigns. We first review the model design choices required to develop and train a generative model including common 1D, 2D, and 3D representations of molecules and typical generative modeling neural network architectures. We then describe different problem statements for molecular discovery applications and explore the benchmarks used to evaluate models based on those problem statements. Finally, we discuss the important factors that play a role in integrating generative models into experimental workflows. Our aim is that this review will equip the reader with the information and context necessary to utilize generative modeling within their domain.

This article is categorized under:

Data Science > Artificial Intelligence/Machine Learning
Flavour alignment of New Physics in light of the (g − 2)μ anomaly
Authors: Isidori Gino , Pagès Julie , Wilsch Felix
Published: March 2022

Abstract

We investigate the flavour alignment conditions that New Physics (NP) models need to satisfy in order to address the (g − 2)μ anomaly and, at the same time, be consistent with the tight bounds from μ → eγ and τ → μγ. We analyse the problem in general terms within the SMEFT, considering the renormalisation group evolution of all the operators involved. We show that semileptonic four-fermion operators, which are likely to generate a sizeable contribution to the (g − 2)μ anomaly, need to be tightly aligned to the lepton Yukawa couplings and the dipole operators in flavour space. While this tuning can be achieved in specific NP constructions, employing particular dynamical assumptions and/or flavour symmetry hypotheses, it is problematic in a wide class of models with broken flavour symmetries, such as those proposed to address both charged- and neutral-current B anomalies. We quantify this tension both in general terms, and in the context of explicit NP constructions.
Quantifying scrambling in quantum neural networks
Authors: Garcia Roy J. , Bu Kaifeng , Jaffe Arthur
Published: March 2022

Abstract

We quantify the role of scrambling in quantum machine learning. We characterize a quantum neural network’s (QNNs) error in terms of the network’s scrambling properties via the out-of-time-ordered correlator (OTOC). A network can be trained by minimizing a loss function. We show that the loss function can be bounded by the OTOC. We prove that the gradient of the loss function can be bounded by the gradient of the OTOC. This demonstrates that the OTOC landscape regulates the trainability of a QNN. We show numerically that this landscape is flat for maximally scrambling QNNs, which can pose a challenge to training. Our results pave the way for the exploration of quantum chaos in quantum neural networks.