bluuebunny/crossref_metadata_2025 huggingface dataset:
Research on the model of high robustness computational optical imaging system
Authors: Su Yun , Xi Teli , Shao Xiaopeng
Published: October 2022

Computational optical imaging is an interdisciplinary subject integrating optics, mathematics, and information technology. It introduces information processing into optical imaging and combines it with intelligent computing, subverting the imaging mechanism of traditional optical imaging which only relies on orderly information transmission. To meet the high-precision requirements of traditional optical imaging for optical processing and adjustment, as well as to solve its problems of being sensitive to gravity and temperature in use, we establish an optical imaging system model from the perspective of computational optical imaging and studies how to design and solve the imaging consistency problem of optical system under the influence of gravity, thermal effect, stress, and other external environment to build a high robustness optical system. The results show that the high robustness interval of the optical system exists and can effectively reduce the sensitivity of the optical system to the disturbance of each link, thus realizing the high robustness of optical imaging.
A novel monoclinic phase and electrically tunable magnetism of van derWaals layered magnet CrTe2
Authors: Ren Qidi , Lai Kang , Chen Jiahao , Yu Xiaoxiang , Dai Jiayu
Published: October 2022

Exploring the novel structural phase of van der Waals (vdW) magnets would promote the development of spintronics. Here, through first-principles calculations, we report a novel monoclinic structure of vdW layered 1T-CrTe2, which is one of the popular vdW magnets normally exhibiting a trigonal structure. The new monoclinic phase emerges from a switchable magnetic state between ferromagnetism and antiferromagnetism through changing hole doping concentration, which suggests a practical approach to obtain such a structure. The results of phonon dispersion and energy analysis convince us that the monoclinic structure is a metastable phase even without hole doping. When the hole doping concentration increases, the stability analysis indicates the preference for a novel monoclinic phase rather than a conventional trigonal phase, and meanwhile, the magnetic properties are accordingly tuned. This work provides new insights into the phase engineering of the chalcogenide family and the electrical control of magnetism of vdW layered magnets.
Electrospun Polyethylene Oxide (PEO)-Based Composite polymeric nanofiber electrolyte for Li-Metal Battery
Authors: Zhang L X , Li Y Z , Shi L W , Yao R J , Xia S S , Wang Y , Yang Y P
Published: October 2022

Composite polymer electrolytes (CPEs) based on polyethylene oxide (PEO) offer manufacturing feasibility and outstanding mechanical flexibility. However, the low ionic conductivity of the CPEs at room temperature, as well as the poor mechanical properties, have hindered their commercialization. In this work, Solid-state electrolytes based on polyethylene oxide (PEO) with and without fumed SiO2 (FS) nanoparticles are prepared by electrostatic spinning process. The as-spun PEO hybrid nanofiber electrolyte with 6.85 wt% FS has a relatively high lithium ion conductivity and electrochemical stability, which is 4.8 × 10-4 S/cm and up to 5.2 V vs. Li+/Li, respectively. Furthermore, it also shows a higher tensile strength (2.03 MPa) with % elongation at break (561.8). Due to the superior electrochemical and mechanical properties, it is promising as high-safety and all-solid-state polymer electrolyte for advanced Li-metal battery.
Effect of filament winding process parameters on interlaminar performance for CF/PP thermoplastic composite
Authors: Chang C , Geng H B , Feng Y , Han Z Y , Sun S Z
Published: October 2022

This paper focuses on the in-situ consolidation process of thermoplastic composites by winding, aiming to explore the influence of key process parameters on samples’ quality. During the consolidation of thermoplastic composites, they need to go through resin melting-bonding-consolidation process, in which each parameter affects the interlaminar bond strength. Through preliminary simulation and experiments, the process parameters were selected. In this paper, wound NOL ring samples made of carbon fiber reinforced polypropylene thermoplastic composite prepregs were obtained with a hot gas assisted filament winding equipment. The influence rule of winding temperature, winding tension and winding speed on the interlaminar shear strength were analyzed based on response surface methodology. Through the analysis, in the range of the experiments winding tension and temperature had more effect on the shear strength while speed’s influence was small. With the increase of tension and temperature, the interlaminar shear strength increased, but after reaching a certain value, the laminar shear strength decreased instead.
Analysis and Comparison of Sliding Mode Controller for the Boost Driver in LED Headlamps
Authors: Cheng Xufeng , Liu Chenyang , Zhang Yuliang , Wang Dianlong
Published: October 2022

In this paper, the performance of several sliding mode control strategies used for the boost driver in LED headlamps is analysed and compared. At first the topology, control framework, and mathematical model of the boost LED driver is presented. Based on the mathematical model, a traditional differential sliding mode control law, a terminal sliding mode control law with finite convergence time, and a 2nd-order sliding mode control law with the Super-Twisting algorithm are derived and designed. Finally the simulation models of these sliding mode control laws are built. Simulation results show that the terminal sliding mode control has a faster convergence speed than the traditional differential sliding mode control. And the 2nd-order sliding mode control has a fastest convergence speed and low chattering, but the control result has a certain overshoot.
Electrical Transport Properties of Few-Layer SnS2 Field-effect Transistors
Authors: Zhang Lu , Li Tuo , Yao Peng , Zou Xiaofeng , Ji Chao , Zhan Yongzheng , He Jiaqi , Zhang Qing
Published: October 2022

After the discovery of graphene in 2004, two dimensional (2D) materials have fascinated a lot of view due to the excellent properties. Nowadays, the research on 2D materials has spread to other graphene-like layer structured materials, especially transition metal dichalcogenides (TMDCs). Tin disulfide (SnS2) is a kind of TMDCs with a sizable bandgap. Here we introduce few-layer SnS2field-effect transistors (FETs) fabricated using micromechanical exfoliation method. The FETs show n-type behavior, the on/off ratio exceeding 0.54×104and the carrier mobility is 0.61 cm2V−1s−1. The electronic and optical characteristics of SnS2 flakes with a finite bandgap illustrate their potential applications in optoelectronics device.
Development of Solar Energy: Current Status and Future Challenges from a Global Perspective
Authors: Khan U , Rauf A , Feng S , Akbar A R , Wu R , Khan M , Liu F
Published: October 2022

With the development of civilization and the growth of the world’s population, the need for electricity also increases. Today, the main electricity sources are nuclear power plants (NPPs) and hydroelectric power plants (HPPs) that run on hydrocarbon fuels such as coal, peat, gas, and fuel oil. But these generating electricity methods have serious drawbacks, for example, the depletion of hydrocarbon natural resources, which leads to their shortage and rise in price. Nuclear and hydroelectric power plants cannot fully cover the need for electricity. In addition, the tragic events in the history of nuclear energy, e.g., the accident at the Chernobyl nuclear power plant, the nuclear power plant disaster in the city of Fukushima, etc., show great risks associated with the operation of nuclear power plants. Thus, solar energy engineering is the most efficient type of alternative, safe energy in the foreseeable future of mankind. This review is an effort to highlight the major progress and future challenges of using renewable energy sources.
Analysis of 5G Signal for Radar Application
Authors: Liu Baojin , Lyu Xiaoyong , Fan Wenbing
Published: October 2022

In this paper we evaluate the fifth generation (5G) communication signal from the perspective of radar sensing. The passive radars exploit the third-part transmitted signals in the space as the illuminators of opportunity (IoO), and has gained renewed interest. The 5G signal has large bandwidth and advanced modulation technique, offering great potential for radar uses. This paper takes an analysis of the 5G signal from the perspective of radar sensing. We provide a detailed description of the 5G signal protocol, and evaluate the detection capability of the 5G signal based passive radar in terms of bistatic range resolution, range resolution, the signal to noise ratio distribution. Furthermore, we introduce a signal processing method that may be a candidate for target sensing in the 5G signal based passive radar. Simulation verifies the effectiveness of this method.
Selection of Optimal Focusing Evaluation Function Based on Sparse Microscopic Images
Authors: Lv Meini , Gan Hui , Liu Xin , Chen Jia , Yang Qiuhui
Published: October 2022

The auto focusing process is affected by the amount of image content, resulting in the focus curve not meeting the characteristics of the ideal focus curve. In this paper, aiming at the problem that the traditional autofocus cannot find the focal plane successfully in the case of microscopic sparse content, the qualitative analysis and quantitative analysis of 12 traditional focus evaluation functions are carried out. The experimental results show that the F
Tenengrad function is suitable for the optimal focus evaluation function of sparse microscopic images.
Study on Comprehensive Efficiency Evaluation of Farmland Irrigation Water Based on Compound Fuzzy Mathematical Model
Authors: Hu Zijang , Yang Chao , Jiang Bing
Published: October 2022

China’s water resources are extremely scarce. Statistics show that agricultural water consumption accounts for more than 60% of the total water consumption in the country every year, and farmland irrigation water accounts for the largest proportion, accounting for about 90% of agricultural water consumption. It can be seen that irrigation water is the key to water saving. Taking the south of Jiangsu Province as the research background, this paper constructs an evaluation index system of farmland irrigation water use efficiency from four dimensions of water consumption level, irrigation water saving, water use efficiency and water production efficiency. A method based on complex fuzzy matter-element method is proposed to evaluate the benefits of farmland irrigation water. Taking the irrigation water for rice crops in southern Jiangsu as a case, the entropy value and weight are calculated by entropy weight method, and the evaluation results of the benefits of rice water use over the years are calculated by Euclidean closeness degree. This conclusion can provide decision support for rational allocation of farmland irrigation water, efficient utilization of water resources and comprehensive reform of agricultural water price.
Research and Application of Data Fusion and Data Mining in Early Warning Detection Intelligence Processing System
Authors: Zhang Zhixun , Shi Ziyan , Liu Jianhao , Du Xinglin
Published: October 2022

As a key technology of modern intelligence systems, Intelligence processing is a famous research area, and plays a basic role in the economy of the country especially in the early warning detection intelligence processing system. The basic theory of data fusion and date mining is comprehensively expounded, and real-time requirements of multi-target track data fusion, as well as offline demodulation timely information on characteristics of data mining, is deeply studied. Firstly, this paper discusses roundly the theory of association rules, which is an important research method of early warning intelligence data mining, proposes a new weighted probabilistic data association algorithm and improves joint probabilistic data association algorithm. Secondly, the knowledge of early warning intelligence data warehouse is detailed, and Law of cosines-text clustering algorithm based on distance is highlighted and extended. Finally, through the integration of real-time data integration and off-line data mining, the practical problems in information processing are effectively solved.
All-orders asymptotics of tensor model observables from symmetries of restricted partitions
Authors: Ben Geloun Joseph , Ramgoolam Sanjaye
Published: October 2022

The counting of the dimension of the space of

U
(
N
)
×
U
(
N
)
×
U
(
N
)

polynomial invariants of a complex 3-index tensor as a function of degree n is known in terms of a sum of squares of Kronecker coefficients. For

n
⩽
N

, the formula can be expressed in terms of a sum of symmetry factors of partitions of n denoted

Z
3

(
n
)

, which also counts the number of bipartite ribbon graphs with n edges. We derive the large n all-orders asymptotic formula for

Z
3

(
n
)

making contact with high order results previously obtained numerically. We explain how the different terms in the asymptotics are associated with probability distributions over ribbon graphs. The derivation of the asymptotics relies on the dominance in the sum, of partitions with many parts of length 1. This large n dominance of small parts also leads to conjectured formulae for the asymptotics of invariants for general d-index tensors. The coefficients of powers of

1

/

n

in these expansions involve Stirling numbers of the second kind along with restricted partition sums.
Dynamic behaviors of a stochastic new logistic model for microbial growth in foods
Authors: Li Pengzhe , Ai Xiaohui
Published: October 2022

In this paper, a stochastic new logistic model is proposed, and dynamic behaviors of the model have been analyzed. The existence of global positive solution of the model is proved. In the persistence analysis of the model, the weak persistence and stochastic persistence of the model are proved. Some numerical simulations are presented to illustrate the dynamic properties of the model.
Isomonodromic deformations along a stratum of the coalescence locus
Authors: Guzzetti Davide
Published: October 2022

We consider deformations of a differential system with Poincaré rank 1 at infinity and Fuchsian singularity at zero along a stratum of a coalescence locus. We give necessary and sufficient conditions for the deformation to be strongly isomonodromic, both as an explicit Pfaffian system (integrable deformation) and as a non linear system of PDEs on the residue matrix A at the Fuchsian singularity. This construction is complementary to that of (Cotti et al 2019 Duke Math. J.
168 967–1108). For the specific system here considered, the results generalize those of (Jimbo et al 1981 Physica D 2 306), by giving up the generic conditions, and those of (Bertola and Mo 2005 Int. Math. Res. Pap.
2005 565–635), by giving up the Lidskii generic assumption. The importance of the case here considered originates form its applications in the study of strata of Dubrovin-Frobenius manifolds and F-manifolds.
Toward new opportunities in the study of the biological potential of plants
Authors: Yu Rud V , Kosolapov V M , Hogland W , Savchenko I V , Diuldin M V , Bairamov B H , Terukov E I , Switala F
Published: October 2022

This work is devoted to the discussion of the peculiarities of studying the optical and photovoltaic properties of plants in order to increase the effectiveness of the study of the biological potential of plants and their protection. In the article we try to analyze the validity of our conclusions, citing proven experimental methods of solid state physics for studying plants. These studies were conducted on a wide range of plants. The analysis of the obtained results allows us to conclude that the main the result obtained in the studies of photoelectrical properties with the application of the methods developed and improved by us can actually serve to control the condition of the plant, acting as a kind of markers in the study of their biological potential.
Generating asymmetric aberration laser beams with controlled intensity distribution
Authors: Singh Sachleen , Dev Vasu , Pal Vishwa
Published: October 2022

We present generation of asymmetric aberration laser beams (aALBs) with controlled intensity distribution, using a diffractive optical element (DOE) involving phase asymmetry. The asymmetry in the phase distribution is introduced by shifting the coordinates in a complex plane. The results show that autofocusing properties of aALBs remain invariant with respect to the asymmetry parameters. However, a controlled variation in the phase asymmetry allows to control the spatial intensity distribution of aALBs. In an ideal ALB containing equal intensity bright lobes, by introducing asymmetry most of the intensity can be transferred to any one of single bright lobe, and forms a high-power density lobe. For a given beam parameter m, the precise spatial position of high-power density lobe can be controlled by the asymmetry parameter β, and we have determined the empirical relations for them. We have found that for the specific values of β, the intensity in the high-power density lobe can be enhanced by several times the intensity in other lobes. The experimental results show a good agreement with the numerical simulations. The findings can be suitable for applications such as in optical trapping and manipulation as well as material processing.
Two-step method for growth of adlayer-free large-area monolayer graphene on Cu foil
Authors: Liang Yijian , Zhang Wenjing
Published: October 2022

Chemical vapor deposition is the most promising approach for synthesis of large-area monolayer graphene on Cu foil. However, numerous factors can result in formation of adlayers, such as the morphology of the Cu foil, methane concentration, and growth temperature. Here, we report atmospheric pressure chemical vapor deposition growth of large-area adlayer-free monolayer graphene by the two-step ‘bottom-up-etching’ method. The experimental results showed that a temperature increase in the second step can dramatically accelerate etching of the bottom graphene layer. A growth model for adlayer-free monolayer graphene on Cu foil is proposed.
Heterogeneous warming impacts of desert wind farms on land surface temperature and their potential drivers in Northern China
Authors: Liu Naijing , Zhao Xiang , Zhang Xin , Zhao Jiacheng , Wang Haoyu , Wu Donghai
Published: October 2022

To address rapid climate change, wind energy has been widely developed in China in the last two decades. However, wind farm (WF) turbulence effects can change the local climate by redistributing temperature, humidity, and heat fluxes. Previous studies indicate that WFs can significantly increase nighttime land surface temperature (LST); however, their conclusions are mainly derived from individual WFs and ignore heterogeneous impacts among multi-WFs in China. Another large source of uncertainty is that the WFs used in previous studies are mainly located in croplands or grasslands, which may obscure direct WF impacts because of the interactions between vegetation and the atmosphere. In this study, we detect impacts with MODIS LST products during 2001–2018 at sixteen WFs in the desert of northern China. The results suggest that the averaged warming impacts of WFs on LST are similar between nighttime (0.237 °C) and daytime (0.250 °C). However, the uncertainty is much greater for daytime (SD = 0.519 °C) than for nighttime (SD = 0.146 °C) due to spatially heterogeneous impacts of desert WFs on LST. Optimal structural equation models suggest that wind speed, precipitation, and distribution patterns of wind turbines mainly explain the spatial heterogeneity of the desert WF impacts on nighttime LST. Given the rapid development of WFs globally, the local warming impacts of WFs and their corresponding mechanisms should be highlighted as a high priority in the fields of energy and climate.
Nano-additive manufacturing of multilevel strengthened aluminum matrix composites
Authors: Shao Chenwei , Li Haoyang , Zhu Yankun , Li Peng , Yu Haoyang , Zhang Zhefeng , Gleiter Herbert , McDonald André , Hogan James
Published: October 2022

Nanostructured materials are being actively developed, while it remains an open question how to rapidly scale them up to bulk engineering materials for broad industrial applications. This study propose an industrial approach to rapidly fabricate high-strength large-size nanostructured metal matrix composites and attempts to investigate and optimize the deposition process and strengthening mechanism. Here, advanced nanocrystalline aluminum matrix composites (nanoAMCs) were assembled for the first time by a novel nano-additive manufacturing method that was guided by numerical simulations (i.e. the in-flight particle model and the porefree deposition model). The present nanoAMC with a mean grain size <50 nm in matrix exhibited hardness eight times higher than the bulk aluminum and shows the highest hardness among all Al–Al2O3 composites reported to date in the literature, which are the outcome of controlling multiscale strengthening mechanisms from tailoring solution atoms, dislocations, grain boundaries, precipitates, and externally introduced reinforcing particles. The present high-throughput strategy and method can be extended to design and architect advanced coatings or bulk materials in a highly efficient (synthesizing a nanostructured bulk with dimensions of 50 × 20 × 4 mm3 in 9 min) and highly flexible (regulating the gradient microstructures in bulk) way, which is conducive to industrial production and application.
Effect of local inhomogeneous permeability of Ni-Mn-Ga in dependency of constrains
Authors: Titsch Christian , Henkner Rick , Drossel Welf-Guntram
Published: October 2022

Magnetic shape memory alloys are a promising but rather novel smart material class. A test stand was developed and verified to characterize commercially available samples. The test stand generates a homogeneous magnetic field within the air gap when no sample is inserted. Once a Ni-Mn-Ga sample is inserted, the field remains homogeneous in the horizontal but not in the vertical direction. Rotating the sample around the long edge leads to a mirrored behavior. An FEM simulation based on the simplified description of the switching effect was built up. The simulation reproduced the experimental data principle but not in detail. The simplified description of the effect helps to understand the behavior of magnetic memory alloys, but for a deeper understanding micro-simulations with precise boundary conditions are necessary.
Machine-learning accelerated identification of exfoliable two-dimensional materials
Authors: Tohidi Vahdat Mohammad , Varoon Agrawal Kumar , Pizzi Giovanni
Published: October 2022

Two-dimensional (2D) materials have been a central focus of recent research because they host a variety of properties, making them attractive both for fundamental science and for applications. It is thus crucial to be able to identify accurately and efficiently if bulk three-dimensional (3D) materials are formed by layers held together by a weak binding energy that, thus, can be potentially exfoliated into 2D materials. In this work, we develop a machine-learning (ML) approach that, combined with a fast preliminary geometrical screening, is able to efficiently identify potentially exfoliable materials. Starting from a combination of descriptors for crystal structures, we work out a subset of them that are crucial for accurate predictions. Our final ML model, based on a random forest classifier, has a very high recall of 98%. Using a SHapely Additive exPlanations analysis, we also provide an intuitive explanation of the five most important variables of the model. Finally, we compare the performance of our best ML model with a deep neural network architecture using the same descriptors. To make our algorithms and models easily accessible, we publish an online tool on the Materials Cloud portal that only requires a bulk 3D crystal structure as input. Our tool thus provides a practical yet straightforward approach to assess whether any 3D compound can be exfoliated into 2D layers.
‘Flux+Mutability’: a conditional generative approach to one-class classification and anomaly detection
Authors: Fanelli C , Giroux J , Papandreou Z
Published: October 2022

Anomaly Detection is becoming increasingly popular within the experimental physics community. At experiments such as the Large Hadron Collider, anomaly detection is growing in interest for finding new physics beyond the Standard Model. This paper details the implementation of a novel Machine Learning architecture, called Flux+Mutability, which combines cutting-edge conditional generative models with clustering algorithms. In the ‘flux’ stage we learn the distribution of a reference class. The ‘mutability’ stage at inference addresses if data significantly deviates from the reference class. We demonstrate the validity of our approach and its connection to multiple problems spanning from one-class classification to anomaly detection. In particular, we apply our method to the isolation of neutral showers in an electromagnetic calorimeter and show its performance in detecting anomalous dijets events from standard QCD background. This approach limits assumptions on the reference sample and remains agnostic to the complementary class of objects of a given problem. We describe the possibility of dynamically generating a reference population and defining selection criteria via quantile cuts. Remarkably this flexible architecture can be deployed for a wide range of problems, and applications like multi-class classification or data quality control are left for further exploration.
Bielliptic quotient modular curves of 𝑋₀(𝑁)
Authors: Bars Francesc , Kamel Mohamed , Schweizer Andreas
Published: October 2022

Let

N
≥
1

N\geq 1

be a non-square free integer and let

W
N

W_N

be a nontrivial subgroup of the group of the Atkin-Lehner involutions of

X
0

(
N
)

X_0(N)

such that the modular curve

X
0

(
N
)

/

W
N

X_0(N)/W_N

has genus at least two. We determine all pairs

(
N
,

W
N

)

(N,W_N)

such that

X
0

(
N
)

/

W
N

X_0(N)/W_N

is a bielliptic curve and the pairs

(
N
,

W
N

)

(N,W_N)

such that

X
0

(
N
)

/

W
N

X_0(N)/W_N

has an infinite number of quadratic points over

Q

\mathbb {Q}

.
Coefficient multipliers in the Hardy space associated with Jacobi expansions
Authors: Shi Yehao , Li Zhongkai
Published: October 2022

In this paper a multiplier theorem in the Hardy space

H
1

(

T

)

H^1(\mathbb {T})

associated with Jacobi expansions of exponential type is proved, that is, a bilateral sequence

{

λ
n

}

n
=
−
∞

∞

\left \{\lambda _n\right \}_{n=-\infty }^{\infty }

is a multiplier from

H
1

(

T

)

H^1(\mathbb {T})

into the sequence space

ℓ
1

(

Z

)

\ell ^1(\mathbb {Z})

associated with Jacobi expansions of exponential type, if
\[
<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" alttext="sup Underscript upper N Endscripts sigma-summation Underscript k equals 1 Overscript normal infinity Endscripts left-parenthesis sigma-summation Underscript k upper N greater-than StartAbsoluteValue j EndAbsoluteValue less-than-or-equal-to left-parenthesis k plus 1 right-parenthesis upper N Endscripts StartAbsoluteValue lamda Subscript j Baseline EndAbsoluteValue right-parenthesis squared greater-than normal infinity period">

sup
N

∑

k
=
1

∞

(

∑

k
N
>

|

j

|

≤
(
k
+
1
)
N

|

λ
j

|

)

2

>
∞
.

\sup _N\sum _{k=1}^{\infty }\left (\sum _{kN>|j|\le (k+1)N}|\lambda _j|\right )^2>\infty .

\]
This is a generalization of a multiplier theorem on usual Fourier expansions in the Hardy space

H
1

(

T

)

H^1(\mathbb {T})

, and for

λ
n

=
(

|

n

|

+
1

)

−
1

\lambda _n=(|n|+1)^{-1}

, a Hardy type inequality for Jacobi expansions is immediate which has ever been proved by Kanjin and Sato [Math. Inequal. Appl. 7 (2004), pp. 551–555].
The Effect of Automatic Text Simplification on L2 Readers’ Text Comprehension
Authors: Murphy Odo Dennis
Published: October 2022

Texts used in L2 classrooms have traditionally been simplified manually, but recent technological advances allow us to investigate whether automatic text simplification (ATS) software can help L2 learners comprehend texts in second and foreign languages. Participants were divided into low and high L2 reading proficiency groups and assigned to read either the authentic or automatically simplified version of a text and completed a free recall task and MC comprehension test. The results did not show any significant correlations among the variables of topic knowledge, topic interest, and MC comprehension, but there were correlations among L2 reading comprehension, MC comprehension, and free recall results. Results also showed that the automatically simplified text facilitated the comprehension of the more proficient readers but not the less proficient readers according to their performance on the free recall assessment. Implications are that L2 teachers cannot blindly use whatever text they want with ATS, and ATS software designers may need to reconsider the current conservative approach to simplification that many ATS tools use.
Identification of drug-side effect association via restricted Boltzmann machines with penalized term
Authors: Qian Yuqing , Ding Yijie , Zou Quan , Guo Fei
Published: October 2022

In the entire life cycle of drug development, the side effect is one of the major failure factors. Severe side effects of drugs that go undetected until the post-marketing stage leads to around two million patient morbidities every year in the United States. Therefore, there is an urgent need for a method to predict side effects of approved drugs and new drugs. Following this need, we present a new predictor for finding side effects of drugs. Firstly, multiple similarity matrices are constructed based on the association profile feature and drug chemical structure information. Secondly, these similarity matrices are integrated by Centered Kernel Alignment-based Multiple Kernel Learning algorithm. Then, Weighted K nearest known neighbors is utilized to complement the adjacency matrix. Next, we construct Restricted Boltzmann machines (RBM) in drug space and side effect space, respectively, and apply a penalized maximum likelihood approach to train model. At last, the average decision rule was adopted to integrate predictions from RBMs. Comparison results and case studies demonstrate, with four benchmark datasets, that our method can give a more accurate and reliable prediction result.
ATLIGATOR: editing protein interactions with an atlas-based approach
Authors: Kynast Josef Paul , Schwägerl Felix , Höcker Birte
Published: October 2022

Motivation

Recognition of specific molecules by proteins is a fundamental cellular mechanism and relevant for many applications. Being able to modify binding is a key interest and can be achieved by repurposing established interaction motifs. We were specifically interested in a methodology for the design of peptide binding modules. By leveraging interaction data from known protein structures, we plan to accelerate the design of novel protein or peptide binders.

Results

We developed ATLIGATOR—a computational method to support the analysis and design of a protein’s interaction with a single side chain. Our program enables the building of interaction atlases based on structures from the PDB. From these atlases pocket definitions are extracted that can be searched for frequent interactions. These searches can reveal similarities in unrelated proteins as we show here for one example. Such frequent interactions can then be grafted onto a new protein scaffold as a starting point of the design process. The ATLIGATOR tool is made accessible through a python API as well as a CLI with python scripts.

Availability and implementation

Source code can be downloaded at github (https://www.github.com/Hoecker-Lab/atligator), installed from PyPI (‘atligator’) and is implemented in Python 3.
Cognitive Impairment in Tuberculous Meningitis
Authors: Davis Angharad G , Dreyer Anna J , Albertyn Christine , Maxebengula Mpumi , Stek Cari , Wasserman Sean , Marais Suzaan , Bateman Kathleen , Solms Mark , Joska John , Wilkinson Robert J , Nightingale Sam
Published: October 2022

Background

Cognitive impairment is reported as a common complication in adult tuberculous meningitis (TBM), yet few studies have systematically assessed the frequency and nature of impairment. Moreover, the impact of impairment on functioning and medication adherence has not been described.

Methods

A cognitive test battery (10 measures assessing 7 cognitive domains) was administered to 34 participants with human immunodeficiency virus (HIV)–associated TBM 6 months after diagnosis. Cognitive performance was compared with that a comparator group of 66 people with HIV without a history of tuberculosis. A secondary comparison was made between participants with TBM and 26 participants with HIV 6 months after diagnosis of tuberculosis outside the central nervous system (CNS). Impact on functioning was evaluated, including through assessment of medication adherence.

Results

Of 34 participants with TBM, 16 (47%) had low performance on cognitive testing. Cognition was impaired across all domains. Global cognitive performance was significantly lower in participants with TBM than in people with HIV (mean T score, 41 vs 48, respectively; P < .001). These participants also had lower global cognition scores than those with non-CNS tuberculosis (mean global T score, 41 vs 46; P = .02). Functional outcomes were not significantly correlated with cognitive performance in the subgroup of participants in whom this was assessed (n = 19).

Conclusions

Low cognitive performance following HIV-associated TBM is common. This effect is independent of, and additional to, effects of HIV and non-CNS tuberculosis disease. Further studies are needed to understand longer-term outcomes, clarify the association with treatment adherence, a key predictor of outcome in TBM, and develop context-specific tools to identify individuals with cognitive difficulties in order to improve outcomes in TBM.
Randomized Trials With Repeatedly Measured Outcomes: Handling Irregular and Potentially Informative Assessment Times
Authors: Pullenayegum Eleanor M , Scharfstein Daniel O
Published: October 2022

Randomized trials are often designed to collect outcomes at fixed points in time after randomization. In practice, the number and timing of outcome assessments can vary among participants (i.e., irregular assessment). In fact, the timing of assessments may be associated with the outcome of interest (i.e., informative assessment). For example, in a trial evaluating the effectiveness of treatments for major depressive disorder, not only did the timings of outcome assessments vary among participants but symptom scores were associated with assessment frequency. This type of informative observation requires appropriate statistical analysis. Although analytic methods have been developed, they are rarely used. In this article, we review the literature on irregular assessments with a view toward developing recommendations for analyzing trials with irregular and potentially informative assessment times. We show how the choice of analytic approach hinges on assumptions about the relationship between the assessment and outcome processes. We argue that irregular assessment should be treated with the same care as missing data, and we propose that trialists adopt strategies to minimize the extent of irregularity; describe the extent of irregularity in assessment times; make their assumptions about the relationships between assessment times and outcomes explicit; adopt analytic techniques that are appropriate to their assumptions; and assess the sensitivity of trial results to their assumptions.
INITIAL ELECTROCARDIOGRAPHIC PROFILE OF THE POPULATION OF TANGIERS – MOROCCO INFECTED WITH SARS CoV2: ABOUT 1087 CASES
Authors: Ouafdel Ousama
Published: October 2022

Introduction

Coronavirus disease 2019 (COVID-19) is a pathology which initially affects the respiratory system, but also many other noble organs due to his inflammatory phase (Cytokine Storm), especially the cardiovascular system.

The cardiovascular risk factors present in a population infected with SARS-COV 2 are of particular interest.

The ECG is a fast available means to get an idea about the cardiac status.

This permits not only to diagnose an unknown pre-existing pathology but also to detect a killing cardiac complication of the SARS COV-2 infection.

Methods

We performed a cross-sectional study on COVID-19 patients passing through Tangiers sorting center. Clinical characteristics and ECG variables were manually abstracted from the electronic health record and first ECG. Our aim was to describe the electrocardiographic features of Covid-19 Patients in Morocco.

Results

1087 patients who presented to the COVID 19 triage center in Tangier-Morocco were systematically given a pre-treatment ECG before deciding on the type of management: outpatient, ward, intensive care.The mean age was 42.78 years, 30.5% of the cases had at least one cardiovascular risk factor, 8.6% of the patients were followed for hypertension, 8.2% for type 1 or 2 diabetes, 10.9% of the patients were obese with a BMI greater than 30, and 26.4% of the patients were either men over 50 or women over 60.

The mean heart rate was 80.89 bpm ± 15.58; The mean PR interval was 149.51 ± 21.70; The mean QRS duration was 98.59 ms ± 11.71; The mean QTc interval was 406.62 ms ± 24.32.

We found: A conduction disorder in 11.1% of patients, 1.6% of 1st degree BAV, 2 of incomplete right bundle branch block, 5.7% of complete BBD, 0.9% of BBG and 1.4% of left anterior hemiblock.

A rhythm disorder in 5.1% of our patients, 2.1% of ventricular extrasystole, 1.6% of supraventricular extrasystole, 1.1% of atrial fibrillation, wolf- parkinson-white syndrome in 0.3% of patients and 0.5% of Brugada pattern.

A repolarization disorder in 5.2% of our population. 3.6% of patients had negative T waves and 1.6% had ST segment abnormalities. We also found a significant association between the presence of cardiovascular risk factors and electrical abnormality.

Conclusion

We found that the majority of EKG were normal and all critically ill patients had a large spectrum of EKG abnormalities. Pending the results, we still believe that we can potentially establish a severity score including EKG to predict inpatient mortality in Moroccan covid-19 patients.

Additional Content

An author video to accompany this abstract is available on https://academic.oup.com/eurheartjsupp. Please click on the arrow next to ‘More Content’ and then click on ‘Author videos’.
Long Term Results of LAD Reconstruction with LIMA Patch in Patients with Multiple Significant LAD disease
Authors: Leon Khaled N , Soliman Rafik
Published: October 2022

Background

Diffusely diseased left anterior descending (LAD) coronary artery with multiple significant stenoses is commonly encountered and is a surgically challenging condition.

Aim

This study aimed to evaluate the long-term patency of LAD reconstruction with a left internal mammary artery (LIMA) patch in patients with multiple significant LAD stenoses.

Methods

We enrolled 50 patients who presented with multi-vessel disease and multiple significant LAD stenoses between January 2012 and January 2022. The LAD was opened all the way through leaving the most proximal lesion until probe 1.5 can pass smoothly through the proximal and distal LAD. Then, the LIMA was widely opened, 1.3 times the LAD opening, and they were anastomosed in the usual way with long length anastomosis. All patients were discharged on a combination of aspirin and clopidogrel for the first year and then aspirin alone for life. Postoperatively, patients were followed-up using coronary CT angiography at 5- and 10-years intervals.

Results

The mean age of the studied patients was 59.08±2.06, and the highest percent (72%) were males. Hypertension, dyslipidemia, and diabetes mellitus comprised the common comorbidities (84%, 68%, and 54%, respectively). the mean ejection fraction was 49.29±3.5 and the mean EuroScore II was 1.02±0.37. The number of grafts was either 5 (8%), 4 (70%), or 3 (22%). Follow-up revealed LAD patency in all the assessed patients at 5 years (49, 98%) and 10-years (46, 92%), while we lost follow-up of 1 (2%) patient at 5 years and 4 (8%) patients at 10-years.

Conclusion

Reconstruction with LIMA patch was effective in maintaining long-term patency of LAD in patients with multiple significant LAD stenosis.

Additional Content

An author video to accompany this abstract is available on https://academic.oup.com/eurheartjsupp. Please click on the arrow next to ‘More Content’ and then click on ‘Author videos’.
Proton pump inhibitors and myocardial infarction: an application of active comparators in a self-controlled case series
Authors: Chui Celine S L , Cheung Ka Shing , Brown Jeremy P , Douglas Ian J , Wong Ian C K , Chan Esther W , Wong Angel Y S
Published: October 2022

Background

Previous studies investigating potential cardiovascular adverse events of acid-suppressing drugs are susceptible to protopathic bias and confounding. We aimed to investigate the association between short-term risk of myocardial infarction (MI) and proton pump inhibitors (PPIs) using a self-controlled case series (SCCS) with an active comparator.

Methods

We conducted a SCCS using a population-wide database from Hong Kong from 2003–2014. Adult with ≥1 outpatient oral PPI prescription or H2 receptor antagonist (H2RA) and MI during the observation period were included. We used both simple ratio and effect modifier approaches to SCCS with active comparators to obtain comparator adjusted estimates.

Results

A total of 2802 and 1889 people with MI who had exposure to PPIs and H2RA were included respectively. We observed a higher risk of MI during days 1–14 following the start of PPI prescription (Incidence rate ratio (IRR): 2.30, 95% confidence interval (CI): 1.76–3.00) versus baseline. Similarly, we observed a higher risk of MI during days 1–14 following the start of H2RA prescription (IRR: 2.46, 95%CI: 1.92–3.16) versus baseline. In the novel SCCS analyses, comparator adjusted estimates were 0.93 (95%CI: 0.57–1.30) and 0.83 (95%CI: 0.58–1.20) during days 1–14 in simple ratio and effect modifier approach, respectively.

Conclusions

We observed no difference in risk of MI associated with PPIs compared with baseline using H2RA as the active comparator. The elevated risk of MI associated with PPIs is likely due to protopathic bias. More studies are required to explore the feasibility of using active comparators in SCCS to address protopathic bias in addition to confounding.
Priorities to accelerate workflow automation in health care
Authors: Zayas-Cabán Teresa , Okubo Tracy H , Posnack Steven
Published: October 2022

Inefficient workflows affect many health care stakeholders including patients, caregivers, clinicians, and staff. Widespread health information technology adoption and modern computing provide opportunities for more efficient health care workflows through automation. The Office of the National Coordinator for Health Information Technology (ONC) led a multidisciplinary effort with stakeholders across health care and experts in industrial engineering, computer science, and finance to explore opportunities for automation in health care. The effort included semistructured key informant interviews, a review of relevant literature, and a workshop to understand automation lessons across nonhealth care industries that could be applied to health care. In this article, we describe considerations for advancing workflow automation in health care that were identified through these activities. We also discuss a set of six priorities and related strategies developed through the ONC-led effort and highlight the role the informatics and research communities have in advancing each priority and the strategies.
A guiding framework for creating a comprehensive strategy for mHealth data sharing, privacy, and governance in low- and middle-income countries (LMICs)
Authors: Hussein Rada , Griffin Ashley C , Pichon Adrienne , Oldenburg Jan
Published: October 2022

With the numerous advances and broad applications of mobile health (mHealth), establishing concrete data sharing, privacy, and governance strategies at national (or regional) levels is essential to protect individual privacy and data usage. This article applies the recent Health Data Governance Principles to provide a guiding framework for low- and middle-income countries (LMICs) to create a comprehensive mHealth data governance strategy. We provide three objectives: (1) establish data rights and ownership to promote equitable benefits from health data, (2) protect people through building trust and addressing patients’ concerns, and (3) promote health value by enhancing health systems and services. We also recommend actions for realizing each objective to guide LMICs based on their unique mHealth data ecosystems. These objectives require adopting a regulatory framework for data rights and protection, building trust for data sharing, and enhancing interoperability to use new datasets in advancing healthcare services and innovation.
Presidential Address 2022: Economic Development and the Organisation Of Labour: Evidence from the Jobs of the World Project
Authors: Bandiera Oriana , Elsayed Ahmed , Heil Anton , Smurra Andrea
Published: October 2022

The Jobs of the World Project is a public resource designed to enable research on jobs and poverty across and within countries over the entire development spectrum. At its core is a new dataset assembled by harmonising Demographic and Health Surveys (DHS) and National Censuses (IPUMS) for all countries and all years after 1990 where data is available. The current version covers 115 countries, observed four times on average. We use the data to show how the nature of jobs and their allocation vary within countries by wealth and gender and across countries by stages of development. We discuss evidence that shows how disparities at the micro level lead to a misuse of human potential that links individual poverty to national income.
Establishment of a Culex tarsalis (Diptera: Culicidae) Cell Line and its Permissiveness to Arbovirus Infection
Authors: Schirtzinger Erin E , Jasperson Dane C , Swanson Dustin A , Mitzel Dana , Drolet Barbara S , Richt Juergen A , Wilson William C
Published: October 2022

A cell line was established from Culex tarsalis Coquillett embryonated eggs and designated as CxTr. The cell line is heterogeneous, composed predominantly of small, round cells, and spindle-shaped cells with a doubling time of approximately 52–60 h. The identity of the cell line was verified as Cx. tarsalis by sequencing of cytochrome oxidase I and the cells were found to be free of contaminating cells, bacteria, fungi, and mycoplasma. The permissiveness of CxTr cells to arbovirus infection was investigated with vaccine and wildtype arboviruses from four viral families: Flaviviridae (Japanese encephalitis virus), Phenuiviridae (Rift Valley fever phlebovirus), Rhabdoviridae (vesicular stomatitis virus), and Togaviridae (Mayaro virus). All viruses were able to infect and replicate within CxTr cells.