bluuebunny/crossref_metadata_2025 huggingface dataset:
EFFECTS OF POROUS g-C3N4 NANOSHEETS AND STEARIC ACID ON THE DURABILITY OF WATERBORNE ACRYLIC RESIN COATING
Authors: SUN CAIXIA , DAI JINGJIE , ZHANG HONGXIA , WANG WEI , GUO LIJUAN , HOU CAIFENG , ZHANG XIAOHUA , FANG RANRAN
Published: April 2023

Durability is a key factor to determine the service life of organic coating. The addition of nanomaterials can improve the mechanical properties and compactness of the organic coatings. As a kind of nanomaterial, g-C3N4 has lamellar structure and can be excited by visible light. At the same time, its cost is low. So it can be selected as a filler to prepare organic coating. The lamellar structure of g-C3N4 is favorable for its dispersion in organic coatings. Stearic acid is an environmentally friendly material with low surface energy. It can improve the hydrophobicity of the coating. In this research, porous g-C3N4 nanosheets were used as filler and stearic acid was used as surface modifier to prepare waterborne acrylic resin-based organic composite coating. The chemical reagent durability, electrochemical durability and mechanical properties of the composite coating were tested. At the same time, the photocatalytic degradation performance of the coating surface was also tested. The results showed that g-C3N4 as filler and stearic acid could effectively improve the durability of the waterborne acrylic resin coating. Meanwhile, the coating surface has obvious visible light-activated photocatalytic performance due to the addition of g-C3N4.
Political Investments and the Winner of Government Grants
Authors: Lin Hsuan-Chu , Chiu She-Chih , Wang Hsing-Chu
Published: April 2023

This paper investigates whether corporate political connections and corporate donations to national-level political campaigns are associated with the allocation of government resources. Based on a sample of Taiwanese publicly held companies, the findings show that political campaign contributions are associated with successful applications for government innovation subsidies as well as more government innovation subsidies. The findings also show that companies that show their loyalty by only donating to the ruling party’s candidates in campaigns receive higher amounts of government innovation subsidies than other companies. Overall, the findings provide evidence that political connections through political campaign contributions may affect government’s decision for resource allocation.
Numerical Investigation of Pipe Deformation Under Pressure With Branch
Authors: Rukavishnikov Viktor A. , Ryabokon Anna S. , Tkachenko Oleg P.
Published: April 2023

The stress–strain state of a pipeline segment with a branch pipe of smaller diameter, which is under internal pressure, is investigated. The mathematical model of this mechanical object is a boundary value problem for a system of six partial differential equations. This boundary value problem describes the deformation of an elastic surface containing a singular line and immersed in three-dimensional space. From this three-dimensional mathematical model in a domain with curved boundary, a resolving boundary value problem in a planar domain is obtained. An algorithm for numerical analysis of the deformed state of a pipeline with a branch pipe by the finite element method is created and implemented. An approach to suppress the error of the numerical solution, which significantly improved the accuracy of the results, is proposed. As a result of numerical experiments, it is found that the proposed algorithms and methods make it possible to approximate a given solution of the reduced pipe deformation problem with a branch pipe by its numerical solution with high accuracy.
Establishment of magneto-dielectric effect and magneto-resistance in composite of PLT and Ba-based U-type hexaferrite
Authors: Aggarwal Kanika , Sharma Madan , Kaur Shubhpreet , Arora Vishal , Sharma Indu , Kumar Rakesh , Singh Anupinder
Published: April 2023

We are examining the behavior of a composite made of ferroelectrics with strong dielectric properties and ferrites with magnetic properties due to the rising need for materials for multipurpose devices. Many application avenues will be favored by the pairing of these materials’ individual qualities with one another. Perovskite and [Formula: see text]-type hexaferrite composite materials have been chosen for this study based on their magnetic and dielectric properties. The composites, (1[Formula: see text][Formula: see text]) [Formula: see text][Formula: see text]([Formula: see text][Formula: see text]Nd2[Formula: see text])4Co2[Formula: see text][Formula: see text] where [Formula: see text] = 0.52, 0.54, 0.56, 0.58 are prepared by solid state reaction method and phase formation was examined. Consideration has been given to the magnetic, dielectric, and magneto-dielectric properties. This work has established the link between the electric and magnetic domains while applying electric and magnetic forces to the materials. The magneto-dielectric research revealed magneto-electric coupling in all of the samples. However, the sample shows the maximum coupling for [Formula: see text] = 0.54 with MDR% values of 93.17%, which might be because this sample appears to have a high magneto-resistance (161%).
The first mapping of the Moine Thrust Belt, NW Scotland: the progress of Peach, Horne and colleagues (1883–1936)
Authors: Butler Robert W. H.
Published: April 2023

The Moine Thrust Belt in NW Scotland is fundamental for developing an understanding of complex fault systems and continental tectonics. The high-quality geological mapping, exceptional structural interpretation and insight of the late nineteenth century that underpins this is chronicled here. The Geological Survey of Great Britain mapped the thrust belt over a 14 year period, at 1:10 560, but it took five decades for the individual 1:63 360 map sheets to be published. The mapping itself was hampered by access problems, illness and prevailing weather. The deployment of expert staff to this region of few apparent economic resources threatened the status of the Geological Survey. Map publication was hindered by the transition from hand-coloured to full-colour printing, together with the restrictions of publishing to a strict grid that incorporated complex geology outside the thrust belt itself. This history of fieldwork, publication and outreach by the Geological Survey is placed in an environmental and logistical context to identify the challenges not only for the mapping itself but also in sharing the results in publication. The execution of these activities provides lessons for developing coherent interpretation in complex geology and the challenges in charting their uncertainties and alternative explanations.
Decentralized Inverse Transparency with Blockchain
Authors: Zieglmeier Valentin , Loyola Daiqui Gabriel , Pretschner Alexander
Published: April 2023

Employee data can be used to facilitate work, but their misusage may pose risks for individuals.Inverse transparencytherefore aims to track all usages of personal data, allowing individuals to monitor them to ensure accountability for potential misusage. This necessitates a trusted log to establish an agreed-upon and non-repudiable timeline of events. The unique properties of blockchain facilitate this by providing immutability and availability. For power asymmetric environments such as the workplace, permissionless blockchain is especially beneficial as no trusted third party is required. Yet, two issues remain: (1) In a decentralized environment, no arbiter can facilitate and attest to data exchanges. Simple peer-to-peer sharing of data, conversely, lacks the required non-repudiation. (2) With data governed by privacy legislation such as the GDPR, the core advantage of immutability becomes a liability. After a rightful request, an individual’s personal data need to be rectified or deleted, which is impossible in an immutable blockchain.

To solve these issues, we presentKovacs, a decentralized data exchange and usage logging system for inverse transparency built on blockchain. Its new-usage protocol ensures non-repudiation, and therefore accountability, for inverse transparency. Its one-time pseudonym generation algorithm guarantees unlinkability and enables proof of ownership, which allows data subjects to exercise their legal rights regarding their personal data. With our implementation, we show the viability of our solution. The decentralized communication impacts performance and scalability, but exchange duration and storage size are still reasonable. More importantly, the provided information security meets high requirements. We conclude thatKovacsrealizes decentralized inverse transparency through secure and GDPR-compliant use of permissionless blockchain.
Bagging: An Ensemble Approach for Recognition of Handwritten Place Names in Gurumukhi Script
Authors: Kaur Harmandeep , Kumar Munish , Gupta Aastha , Sachdeva Monika , Mittal Ajay , Kumar Krishan
Published: April 2023

In this article, the authors present an effort to recognize handwritten Gurumukhi place names for use in postal automation. Five feature extraction techniques (zoning, horizontal peak extent, vertical peak extent, diagonal, and centroid) have been analyzed and optimized using Principal Component Analysis (PCA). Four classification methods (
k
-Nearest Neighbor (
k
-NN), decision tree, random forest, and Convolutional Neural Network (CNN)) have been utilized to classify the handwritten word images. To enhance the recognition results, the authors have employed Bootstrap Aggregation (Bagging) with a majority voting scheme. The authors used a public benchmark dataset of 40,000 handwritten place-name samples in the Punjabi language for their experimental work. The experiments were conducted using a 70:30 partitioning approach, where 70% of the data was utilized for training and the remaining 30% for testing. The system achieved a maximum recognition accuracy of 96.98% by utilizing a combination of zoning, vertical peak extent, and diagonal features, and a minimum Mean Squared Error (MSE) of 0.86% based on a combination of zoning and horizontal peak extent features with a majority voting scheme through ensemble (Bagging) methodology.
Exploiting Local Shape and Material Similarity for Effective SV-BRDF Reconstruction from Sparse Multi-Light Image Collections
Authors: Pintus Ruggero , Ahsan Moonisa , Zorcolo Antonio , Bettio Fabio , Marton Fabio , Gobbetti Enrico
Published: April 2023

We present a practical solution to create a relightable model from small
Multi-light Image Collections (MLICs)
acquired using standard acquisition pipelines. The approach targets the difficult but very common situation in which the optical behavior of a flat, but visually and geometrically rich object, such as a painting or a bas relief, is measured using a fixed camera taking a limited number of images with a different local illumination. By exploiting information from neighboring pixels through a carefully-crafted weighting and regularization scheme, we are able to efficiently infer subtle and visually pleasing per-pixel analytical
Bidirectional Reflectance Distribution Functions (BRDFs)
representations from few per-pixel samples. The method has a low memory footprint and is easily parallelizable. We qualitatively and quantitatively evaluated it on both synthetic and real data in the scope of image-based relighting applications.
On Exponential-time Hypotheses, Derandomization, and Circuit Lower Bounds
Authors: Chen Lijie , Rothblum Ron D. , Tell Roei , Yogev Eylon
Published: April 2023

The
Exponential-Time Hypothesis (ETH)
is a strengthening of the 𝒫 ≠ 𝒩𝒫 conjecture, stating that 3-
SAT
on
n
variables cannot be solved in (uniform) time 2

εċ
n

, for some ε > 0. In recent years, analogous hypotheses that are “exponentially strong” forms of other classical complexity conjectures (such as 𝒩𝒫⊈ ℬ𝒫𝒫 or
co
𝒩𝒫⊈𝒩𝒫) have also been introduced and have become widely influential.

In this work, we focus on the interaction of exponential-time hypotheses with the fundamental and closely related questions of
derandomization and circuit lower bounds
. We show that even relatively mild variants of exponential-time hypotheses have far-reaching implications to derandomization, circuit lower bounds, and the connections between the two. Specifically, we prove that:

(1)

The
Randomized Exponential-Time Hypothesis (rETH)
implies that ℬ𝒫𝒫 can be simulated on “average-case” in
deterministic (nearly-)polynomial-time
(i.e., in time 2

Õ(log(
n
))

= n

loglog(
n
)
O(1)

). The derandomization relies on a conditional construction of a pseudorandom generator with
near-exponential stretch
(i.e., with seed length Õ(log (
n
))); this significantly improves the state-of-the-art in uniform “hardness-to-randomness” results, which previously only yielded pseudorandom generators with sub-exponential stretch from such hypotheses.

(2)

The
Non-Deterministic Exponential-Time Hypothesis (NETH)
implies that derandomization of ℬ𝒫𝒫 is
completely equivalent
to circuit lower bounds against ℰ, and in particular that pseudorandom generators are necessary for derandomization. In fact, we show that the foregoing equivalence follows from a
very weak version of
NETH, and we also show that this very weak version is necessary to prove a slightly stronger conclusion that we deduce from it.

Last, we show that
disproving
certain exponential-time hypotheses requires proving breakthrough circuit lower bounds. In particular, if
CircuitSAT
for circuits over
n
bits of size poly(n) can be solved by
probabilistic algorithms
in time 2

n
/polylog(n)

, then ℬ𝒫ℰ does not have circuits of quasilinear size.
Synthesis of Nanostructured Mixed-Valence Fe(II,III) Metal-Organic Framework and Its Application in Electrochemical Sensing of Amoxicillin
Authors: Nguyen Thi Kim Ngan , Nguyen Tien Hung , Nguyen Manh B. , Nguyen Hoang Anh , Vu Thi Thu Ha , Le Quoc Hung , Tran Quang Hai , Pham Thi Hai Yen
Published: April 2023

The study reports the development of a nanostructured mixed-valence Fe(II)Fe(III)BTC metal-organic framework (BTC = 1, 3, 5-benzenetricarboxylate) modified carbon paste electrode as a novel sensor for the amoxicillin detection in aqueous solutions using square wave voltammetry. The physicochemical properties of FeBTC were characterized using X-ray diffraction spectroscopy, Fourier-transform infrared spectroscopy, Brunauer–Emmett–Teller analysis, electron microscopy (SEM), transmission electron microscopy (TEM), and X-ray photoelectron spectroscopy. These techniques revealed that FeBTC has a surface area of 1211 m2 g−1, a total pore volume of 1.46 cm3 g−1, particle sizes ranging from 10 to 20 nm, and a mixed-valence structure. Furthermore, SEM, TEM, and energy-dispersive X-ray spectroscopy exhibited the homogeneous distribution of FeBTC throughout the modified electrode. The electrochemical study showed that the mixed-valence FeBTC improved the electron transfer capabilities of the electrode. Under optimal conditions, the modified electrode exhibited a significant increase in peak height compared to the unmodified electrode (4.6 times higher), with an acceptable reproducibility of 4.88% relative standard deviation. The linear range of the sensor was 1–100 μM with a good coefficient of determination of 0.9985, and a detection limit of 0.107 μM. Additionally, the sensor demonstrated excellent performance with the satisfactory recoveries and a good correlation with LC-MS/MS analysis.
Aloe Vera Extract-Mediated CuO NPs as Catalysts for the Synthesis of 4-Hydroxy-3-Methoxybenzaldehyde-Connected Piperidine Derivatives and Their Antibacterial Activity
Authors: Packialakshmi Ponnusamy , Gobinath Perumal , Ahamed Anis , Alodaini Hissah Abdulrahman , Hatamleh Ashraf Atef , Yassin Mohamed Taha , Idhayadhulla Akbar , Surendrakumar Radhakrishnan
Published: April 2023

We have designed an easy, affordable, and eco-friendly technique for Schiff base preparation of vanillin-coupled piperidine analogues using CuO NPs as a catalyst. Using a green chemistry strategy using copper oxide nanoparticles (CuO NPs) as a catalyst, a unique one-pot synthesis of Schiff base vanillin-linked piperidine derivatives (2, 2a-2j) may be generated, with a potential yield in a short reaction time. The CuO NPs were synthesized with the aloe vera extract. The newly synthesized piperidin-4-ylidene analogues were investigated using FT-IR, NMR (1H, 13C), mass spectra, and elemental analysis. The morphology of piperidine derivatives was studied using XRD and TEM. The compound 2a-2j was evaluated for antibacterial activity against gram +ve and gram −ve bacteria. Compound 2d is exceptionally active against (5.0 μg/mL, E. coli), and 2c is very effective against (4.0 μg/mL, L. plantarum) when compared to reference drug and other Schiff base of vanillin-associated piperidine derivatives. Finally, we concluded the compounds 2c and 2d have strong antibacterial activity and can be used as antibacterial drugs in the future.
Environmental Risk Assessment of Low Back Pain in ICU Nurses: An Instrument Development Study
Authors: Zhang Lihui , Liu Yangyang , Yuan Su’e
Published: April 2023

Aim. To develop a valid, reliable assessment tool to measure risk factors associated to low back pain (LBP) in intensive care unit (ICU) nurses. Background. LBP is defined as the pain extending from the 12th rib to the iliac crest and often coexists with buttock pain. Nursing has been identified among the top professions at risk of LBP. A mean of 70% prevalence per year in ICU nurses was reported, exceeding those employed in heavy industry. Environmental factors in workplace were also most important risks related to LBP in this population except factors including individual, physical, psychosocial, and lifestyle. However, there is lack of tools to assess environmental risk related to LBP for nurse managers currently. Methods. Focus group interviews, field research, and panel discussion were used to develop item pool. Two-round expert reviews and preinvestigation were carried out to form initial scale named Environmental Risk Assessing Instrument-Occupational Low Back Pain in Nurses (ERAI-N). A cross-sectional survey with 188 ICU participants in Hunan Province in China was implemented to collect data. Cronbach’s alpha, split-half reliability, and test-retest reliability were used to test ERAI-N’s reliability. Expert review was performed to test ERAI-N’s content validity, and confirmatory factor analysis (CFA) was performed to assess its construct validity, being carried out in IBM SPSS Amos 26 Graphics. Results. Final version of ERAI-N scale had five dimensions with 18 items that were space, equipment, belief, guideline, and safe culture. ERAI-N scale’s score of Cronbach’s alpha, Guttman split-half, and intraclass correlation coefficient (ICC) was 0.958, 0.927, and 0.994, respectively. Item-level content validity scores ranged from 0.89 to 1.0, and scale-level content validity was 0.983. Standardized factor loadings ranged from 0.567 to 0.974. Model adjusted fit statistics were as follows: the chi-square statistic and degrees of freedom (χ2/df) = 3.943, root mean square error of approximation (RMSEA) = 0.071, incremental fit index (IFI) = 0.905, comparative fit index (CFI) = 0.904, parsimony normed fit index (PNFI) = 0.641, and parsimonious comparative fit index (PCFI) = 0.661. Conclusions. ERAI-N scale had moderate reliability, content validity, and construct validity. Implications for Nursing Management. Designers may use ERAI-N scale to plan the interior layout when design a new ICU. Nurse managers might utilize this instrument as a managing tool to assess whether there is environmental risk factors related to LBP in ICU.
Floristic Composition, Structure, and Regeneration Status of Woody Plants in Wonjeta St Micheal Church Forest, Northwestern Ethiopia
Authors: Mekonnen Amare Bitew , Wassie Wubetie Adnew
Published: April 2023

The study was conducted in a historian Wonjeta St Michael Church Forest, believed to be constructed in 11th century in Northwestern Ethiopia. The composition, structure, and management of this forest is not documented. Fifty plots of 20 m × 20 m (400 m2) were laid along five-line transect for vegetation data collection. In addition, 5 m × 5 m subplots were laid within the main plot to sample seedlings and saplings. All plots were laid at a distance of 50 m along the transect lines. The diversity and population structure of woody individuals of trees and shrubs with a diameter at breast height (DBH) ≥ 2.5 cm and height ≥2 m were measured, and DBH <2.5 cm and height <2 m were counted as seedlings and saplings. All trees and shrubs recorded in the 50 plots were used for vegetation structure analysis. A total of 65 woody plant species in 53 genera and 33 families were recorded. Out of the total number of species, three were found to be endemic to Ethiopia. The family Fabaceae had the highest number of species, followed by Moraceae, and then Euphorbiaceae with 14, 6, and 4 species, respectively. The results of Shannon Wiener diversity and evenness indices of woody species were 2.8 and 0.68, respectively. Woody species densities for mature individuals were 2,202.5 stems ha−1, seedling 2419.2 stems ha−1, and sapling 1737.6 stems ha−1. Priority for conservation should be given using population structure, important value index, and regeneration status as criteria. Results of the structural analysis revealed that the Forest is highly dominated by small-sized trees and shrubs indicating that it is in the stage of secondary development and there are species that require urgent conservation measures.
The Spillover Effect among CET Market, Coal Market, and New Energy Market for Dual-Carbon Target: New Evidence from China
Authors: Gao Feng-Wei , Wu Yi-Min , Chen Ding , Hu Meng-Yao
Published: April 2023

The spillover effect of the energy markets and the CET plays an important role in guiding the realization of two-carbon target; using the network spillover methodology of Diebold, Yilmaz, Jozef Barunı´k, and Toma´sKrehlı´k, we examine both the static and dynamic connectedness of CO2 emissions trading (CET) market, steam coal market, new energy, and traditional energy market in China from early Dec 2013 to the end of July 2021. At last, we verified the stability of the model and obtained the following findings: (1) the total spillover effect index is 13.91% between those markets, and it is mainly focused on short term. Moreover, the dynamic spillover effect is time-varying, and it is greatly influenced by the domestic and international environment; (2) the connectedness of the CET market with other energy markets is neutral, the development of new energy market is strong, it is the main transmitter to other markets, especially to the traditional energy market except for the steam coal market, and the coal market is an effect transmitter. These results provide a theoretical reference for investors and policy makers who are concerned with the return connectedness among the CET market, new energy market, and steam coal market in China.
Two Statistical Approaches to Justify the Use of the Logistic Function in Binary Logistic Regression
Authors: Zaidi Abdelhamid , Al Luhayb Asamh Saleh M.
Published: April 2023

Logistic regression is a commonly used classification algorithm in machine learning. It allows categorizing data into discrete classes by learning the relationship from a given set of labeled data. It learns a linear relationship from the given dataset and then introduces nonlinearity through an activation function to determine a hyperplane that separates the learning points into two subclasses. In the case of logistic regression, the logistic function is the most used activation function to perform binary classification. The choice of logistic function for binary classifications is justified by its ability to transform any real number into a probability between 0 and 1. This study provides, through two different approaches, a rigorous statistical answer to the crucial question that torments us, namely where does this logistic function on which most neural network algorithms are based come from? Moreover, it determines the computational cost of logistic regression, using theoretical and experimental approaches.
Barriers and Facilitators for the Implementation of Exercise Oncology Provision in Germany: A Multilevel, Mixed-Methods Evaluation of the Network OnkoAktiv
Authors: Voland Annelie , Lohmann Annette , Ansmann Lena , Wiskemann Joachim
Published: April 2023

Background. Strong evidence supports the beneficial impact of exercise on cancer patients. However, the provision of exercise programs in Germany is highly heterogeneous. Therefore, the network OnkoAktiv (OA) enables patient consultations and referrals from coordinating regional OA centers (RE) into community-based exercise programs (CBEP). Objective. The aim of this study was to identify barriers and facilitators for the implementation of OA network structures from the perspective of RE and certified CBEP. Methods. This evaluation was executed in a sequential mixed methods design. We conducted 16 qualitative interviews with each leader in RE and the certified CBEP. Then, 89 certified CBEP were invited to a quantitative, cross-sectional survey. Results. We identified 11 facilitators each for RE and certified CBEP, 7 barriers for RE and 5 for certified CBEP. Barriers dealt with, for example, financing OA network structures, a lack of knowledge of exercise trainers, inadequate patient referral, and missing collaborations by healthcare professionals (HCPs). Most of the named facilitators were adequate internal organizational resources, support and reachability of OA staffs, and collaboration with HCPs. Conclusion. Our findings indicate different challenges for the implementation of OA network structures. Future implementation efforts should consider the evaluation of individual barriers and the development of specific solutions.
Understanding the Impact of the Intercropping System on Carbon Dioxide (CO2) Emissions and Soil Carbon Stocks in Limpopo Province, South Africa
Authors: Mogale Tlou E. , Ayisi Kwabena K. , Munjonji Lawrence , Kifle Yehenew G. , Mabitsela Kabisheng E.
Published: April 2023

Understanding the carbon dioxide emission rates under different agricultural practices is a critical step in determining the role of agriculture in greenhouse gas emissions. One of the challenges in advocating for an intercropping system as a sustainable practice in the face of climate change is the lack of information on how much CO2 is emitted by the system. A factorial randomized complete block design study was set up at two distinct agroecological locations (Syferkuil and Ofcolaco) in the Limpopo Province of South Africa to investigate carbon dynamics in sorghum-cowpea intercropping and sole cropping system over two seasons. Intercropping system emitted less CO2 compared to sole cropping system. In 2018/19 at Syferkuil and 2020/21 at Ofcolaco, intercropping systems emitted 11% and 19% less CO2, respectively, than sole cropping systems. In both agroecological regions, low cowpea density consistently resulted in higher CO2 emissions than high density. During the 2018/19 cropping season, sorghum emitted more CO2 of 5.87 t·ha−1 than cowpea with 5.14 t·ha−1 in a sole cropping system at Syferkuil. Cowpea, on the other hand, emitted more CO2 of 6.5 t·ha−1 and 10.18 t·ha−1 than sorghum during the 2020/21 cropping season at Syferkuil and Ofcolaco, respectively. Furthermore, intercropping improved the carbon emission efficiency (CEE) of the individual crops in the system. The treatments used in the intercropping and sole cropping systems had a significant impact on the strength of the relationship between carbon stocks and CEE. Our results revealed that sorghum-cowpea intercropping system at a relatively higher cowpea density in a no-till system reduces the amount of CO2 lost to the atmosphere. The system can thus, be promoted as one of the sustainable farming practices to reduce emissions and improve carbon storage in the soil.
Attention-Based Gated Recurrent Graph Convolutional Network for Short-Term Traffic Flow Forecasting
Authors: Lou Ping , Wu Zihao , Hu Jiwei , Liu Quan , Wei Qin
Published: April 2023

Traffic flow prediction is the basis of dynamic strategies and applications of intelligent transportation systems (ITS). Accurate traffic flow prediction is of great practical significance in alleviating road congestion and reducing urban road traffic safety hazards. It is challenging since the traffic flow has highly non-linear and complex patterns due to external factors such as time and space. Due to the high stochasticity and uncertainty of traffic flow, the difficulty of traffic flow prediction increases gradually with increasing time steps. The prediction performance of most existing short-term traffic flow prediction methods deteriorates rapidly for longer time steps. In addition, different methods are compared on the same time-granularity dataset, leaving the adaptability and robustness of these methods undervalidated. To address the above challenges, a new traffic forecasting method, named Attention-Based Gated Recurrent Graph Convolutional Network (AGRGCN) is presented for short-term traffic flow prediction. The method can extract spatialtemporal dependencies in traffic flow. In addition, an attention mechanism, which can adaptively capture traffic data relationships at different time steps, is introduced to alleviate the problem of faster deterioration of model prediction performance for longer time steps. Using a road network distance-based graph enables the method better to capture the topological information in traffic flow data. Experiments were conducted on two traffic datasets with different time granularity to predict traffic flow in highway and urban contexts. The experimental results show that our model has certain advantages.
UAV Tilt Photography Control for Numerical Simulation of High and Steep Rock Slopes
Authors: Wang Yani , Zhou Yinpeng , Wang Bo
Published: April 2023

In order to provide accurate image information for the analysis and treatment of dangerous rocks and rockfalls during the early investigation, a UAV tilt photography control method for numerical simulation of high and steep rock slopes is proposed. Based on the UAV tilting photography technology, the slope section was obtained through a real 3D modeling and poststage point cloud data processing. Numerical simulation is used to study the motion characteristics of dangerous rock falling in a high and steep slope of a railway station. This essay introduces the application of a UAV tilting photography and real 3D modeling technology in the process of rock fall analysis and realizes the real scene restoration of the site. The point cloud data of the site is obtained, and the processing process of the point cloud is introduced in detail. The slope section of the site was obtained based on the point cloud, and RocFall software was used to obtain the motion characteristics of dangerous rock falling (falling trajectory, bouncing height impact energy, and impact velocity). The simulation results show that because of the rugged slope, the falling rocks collide and rebound on the slope for many times. In addition, near the bottom of the slope, there is a steep cliff with a height of 136.21 m, which is approximately 54° from the horizontal line, causing the falling rock to bounce and eventually fall at a higher height. It moves to the bottom of the slope and bounces off the level of the railway line before finally settling on the railway road. The maximum bounce height of falling rock in the process of slope rolling motion reaches 30 m. When falling rock moves near the railway line (coordinate is on the right side of zero), the bounce height is 15∼25 m, which threatens the safety of the railway operation. Conclusion. The UAV tilt photography technology can be well applied to the analysis of rockfall motion characteristics of dangerous rocks, and provide an accurate cross-section data information for the study of rockfall motion characteristics of dangerous rocks.
Optical Design and Simulation of Snapshot Hyperspectral Dental Imaging Spectrometer with One-Dimensional Random Coding
Authors: Cao Jiajing , Chang Jun , Huang Yi , Wang Wenxi , Guo Xinran , Zhao Shangnan
Published: April 2023

To achieve perfect teeth color reproduction, we propose the design of a snapshot hyperspectral imaging spectrometer that can accurately measure the teeth spectrum. In this paper, the optical system of a snapshot hyperspectral dental imaging spectrometer is designed. In particular, to encode images in both the spatial and spectral dimensions, a one-dimensional random coding mask rotated 45 degrees around the optical axis is used. The system has a spectral resolution of approximately 2.2∼10 nm in the 450∼700 nm spectral range, and the total length of the system is less than 150 mm. The whole design can be used as a miniaturized handheld instrument. To verify the feasibility of whiteness measuring, a simulation experiment is carried out. The target spectral information is reconstructed through the reconstruction algorithm. The simulation result shows that spectral imaging has the potential to improve the accuracy and precision of teeth whiteness measurements.
Panoramic Assessment Method of Substation Equipment Health Status Based on Multisource Monitoring and Deep Convolution Neural Network under Edge Computing Architecture
Authors: Ma Zhu-xing , Zhang Li-shuo , Gu Hao , Xin Zi-zhong , Kang Zhe , Wang Zhao-lei
Published: April 2023

In view of the low efficiency of the traditional manual evaluation method of substation equipment status under the background of complex environment, a panoramic evaluation method of substation equipment health status based on multisource monitoring and deep convolution neural network under edge computing architecture is proposed. Firstly, a panoramic sensing system for substation equipment is built based on edge computing, and an edge computing server is deployed in the substation to process the massive data obtained from multisource monitoring nearby. Then, the improved YOLOv4 network is used to detect the equipment state in the substation, in which the Squeeze-and-Excitation attention module and deep separable convolution are used to optimize the YOLOv4 network. Finally, based on the status image of substation equipment, the health status of equipment is evaluated on the panoramic platform of substation combined with the characteristics of multisource data, and four states are divided according to the evaluation criteria. Based on the selected dataset, the experimental analysis of the proposed method is carried out. The results show that the index values of accuracy, recall, and mean precision are 91.53%, 93.07%, and 92.28%, respectively. The overall performance is better than other methods and has certain application value.
Biosynthesis-Based Al2O3 Nanofiller from Cymbopogon citratus Leaf/Jute/Hemp/Epoxy-Based Hybrid Composites with Superior Mechanical Properties
Authors: Natrayan L. , Rao Yenda Srinivasa , Prasad Puthalapattu Reddy , Bhaskar Kul , Patil Pravin P. , Abdeta Dereje Bayisa
Published: April 2023

Metallic nanoparticles (NPs) manufactured by ecofriendly strategies have also received much interest because of their elastic scattering properties and performance in nanomaterials. Aluminium oxide nanomaterials stand out among nanomaterials due to their tremendous uses in ceramic products, fabrics, therapeutic agents, catalyst supports, sewage sludge, and biosensors. The current paper investigates the effect of the nanoparticle composition and layer sequential on the mechanical characteristics of jute (J)-hemp (H) incorporated with an aluminium oxide polymer composite. NaOH is used to change the physical aspects of both plant fibres. A total of 20 specimens were tested with varying stacking sequences and padding weight ratios. Mechanical properties like a nanocomposite’s tension, bending, and ILSS was measured. Stacked series and flowability substantially impact the nanocomposite. The Group 3 nanocomposite with 2% Al2O3 has the highest tensile strength, 54.28% of the Group 1 and 2 combinations. The stack series significantly influences the material properties of nanomaterials. Because of the alternating layers of natural fabrics, Group 4 specimens have the maximum flexural strength. Group 3 composite materials have the highest ILSS because they have hemp on the outermost surface. It has been discovered that Group 4 material with a 2% Al2O3 concentration is possibly the most substantial material. The existence of Al2O3 nanoparticles in the green synthesis was confirmed by XRD analysis.
Postfire Residual Strength and Morphology of Concrete Incorporating Natural Rubber Latex Exposed to Elevated Temperatures
Authors: Awoyera Paul O. , Mohammed Najm Hadee , David Adefarati Olusegun , Eldirderi Moutaz Mustafa A. , Mohamed Khedher Khaled , Al Dughaishi Husam , Al Lawati Jawad , Milad Abdalrhman
Published: April 2023

The exposure of concrete to elevated temperatures is known to cause diverse severe damages in concrete composites. Hence, measures to improve the performance of concrete during exposure to fire are continually proposed. The present study investigated the postfire residual strength and morphology of concrete incorporating natural rubber latex exposed to elevated temperature. Four different concrete mixes were considered for the investigation, namely, a control sample made without natural rubber latex, the second sample containing 1% natural rubber latex, the third sample containing 1.5% natural rubber latex, and the fourth sample containing 3% of natural rubber latex. The concrete samples (150 mm cubes and 100 × 200 mm cylinders) were exposed to varying temperatures 300°C, 800°C, and 1000°C, after the curing process. Nondestructive tests using Schmidt rebound hammer and ultrasonic pulse tester were carried out on samples. The compressive strength and split-tensile strength of concrete cubes and cylinders, respectively, were determined. Micrographs and elemental distribution in the sample were studied using the scanning electron microscopy (SEM-EDX) apparatus. It could be seen from the results that the concrete strength properties reduced as the exposure temperature increased. The results also showed that NRL could be sparingly utilized as a concrete admixture, at 1% content. The performance of concrete was not stable at over 300°C when NRL addition was above 1%.
Data from Collagen-Anchored Interleukin-2 and Interleukin-12 Safely Reprogram the Tumor Microenvironment in Canine Soft-Tissue Sarcomas
Authors: Stinson Jordan A. , Sheen Allison , Momin Noor , Hampel Jordan , Bernstein Rebecca , Kamerer Rebecca , Fadl-Alla Bahaa , Samuelson Jonathan , Fink Elizabeth , Fan Timothy M. , Wittrup K. Dane
Published: April 2023

AbstractPurpose:
Cytokine therapies such as IL2 and IL12 suffer from impractically small therapeutic windows driven by their on-target, off-tumor activity, limiting their clinical potential despite potent antitumor effects. We previously engineered cytokines that bind and anchor to tumor collagen following intratumoral injection, and sought to test their safety and biomarker activity in spontaneous canine soft-tissue sarcomas (STS).
Experimental Design:
Collagen-binding cytokines were canine-ized to minimize immunogenicity and were used in a rapid dose-escalation study in healthy beagles to identify a maximum tolerated dose. Ten client-owned pet dogs with STS were then enrolled into trial, receiving cytokines at different intervals prior to surgical tumor excision. Tumor tissue was analyzed through IHC and NanoString RNA profiling for dynamic changes within treated tumors. Archived, untreated STS samples were analyzed in parallel as controls.
Results:
Intratumorally administered collagen-binding IL2 and IL12 were well tolerated by STS-bearing dogs, with only Grade 1/2 adverse events observed (mild fever, thrombocytopenia, neutropenia). IHC revealed enhanced T-cell infiltrates, corroborated by an enhancement in gene expression associated with cytotoxic immune function. We found concordant increases in expression of counter-regulatory genes that we hypothesize would contribute to a transient antitumor effect, and confirmed in mouse models that combination therapy to inhibit this counter-regulation can improve responses to cytokine therapy.
Conclusions:
These results support the safety and activity of intratumorally delivered, collagen-anchoring cytokines for inflammatory polarization of the canine STS tumor microenvironment. We are further evaluating the efficacy of this approach in additional canine cancers, including oral malignant melanoma.
Defective Immunity Against SARS-CoV-2 Omicron Variants Despite Full Vaccination in Hematologic Malignancies
Authors: Zitvogel Laurence , Derosa Lisa , Kroemer Guido
Published: April 2023

In patients with multiple myeloma, completion of mRNA-based vaccination schemes failed to yield detectable SARS-CoV-2 Omicron-neutralizing antibodies and S1-RBD–specific CD8+ T cells in approximately 60% and 80% of the cases, respectively. Patients who develop breakthrough infections exhibited very low levels of live-virus neutralizing antibodies and the absence of follicular T helper cells.

See related article by Azeem et al., p. 106 (9).

See related article by Chang et al., p. 1684 (10).
Table S2 from Systemic LRG1 Expression in Melanoma is Associated with Disease Progression and Recurrence
Authors: Hoefsmit Esmee P. , Völlmy Franziska , Rozeman Elisa A. , Reijers Irene L.M. , Versluis Judith M. , Hoekman Liesbeth , van Akkooi Alexander C.J. , Long Georgina V. , Schadendorf Dirk , Dummer Reinhard , Altelaar Maarten , Blank Christian U.
Published: April 2023

Table S2 shows the patient characteristics OpACIN-neo
Table S1 from Systemic LRG1 Expression in Melanoma is Associated with Disease Progression and Recurrence
Authors: Hoefsmit Esmee P. , Völlmy Franziska , Rozeman Elisa A. , Reijers Irene L.M. , Versluis Judith M. , Hoekman Liesbeth , van Akkooi Alexander C.J. , Long Georgina V. , Schadendorf Dirk , Dummer Reinhard , Altelaar Maarten , Blank Christian U.
Published: April 2023

Table S1 shows an overview evaluated immuno-oncology markers by Olink proteomic assay
Figure S6 from Systemic LRG1 Expression in Melanoma is Associated with Disease Progression and Recurrence
Authors: Hoefsmit Esmee P. , Völlmy Franziska , Rozeman Elisa A. , Reijers Irene L.M. , Versluis Judith M. , Hoekman Liesbeth , van Akkooi Alexander C.J. , Long Georgina V. , Schadendorf Dirk , Dummer Reinhard , Altelaar Maarten , Blank Christian U.
Published: April 2023

Figure S6 shows that neutrophil count and neutrophil-to-lymphocyte ratio (NLR) are not associated with recurrence in non-responding patients
Figure S4 from Systemic LRG1 Expression in Melanoma is Associated with Disease Progression and Recurrence
Authors: Hoefsmit Esmee P. , Völlmy Franziska , Rozeman Elisa A. , Reijers Irene L.M. , Versluis Judith M. , Hoekman Liesbeth , van Akkooi Alexander C.J. , Long Georgina V. , Schadendorf Dirk , Dummer Reinhard , Altelaar Maarten , Blank Christian U.
Published: April 2023

Figure S4 shows the serum analysis using Olink proteomic assay
A Systematic Review of LINE-1 Methylation Profile in Psychiatric Disorders
Authors: Alves Vitória Rodrigues Guimarães , Micali Danilo , Ota Vanessa Kiyomi , Bugiga Amanda Victória Gomes , Muniz Carvalho Carolina , Belangero Sintia Iole
Published: April 2023

Introduction: Long interspersed nuclear elements (LINEs) are endogenous retrotransposable elements. A few studies have linked the methylation pattern of LINE-1 to different mental disorders (e.g., post-traumatic stress disorder [PTSD], autism spectrum disorder [ASD], panic disorder [PD]). We sought to unify the existing knowledge in the field and provide a better understanding of the association between mental disorders and LINE-1 methylation. Methods: A systematic review was executed with 12 eligible articles according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Results: For psychotic disorders, PTSD, ASD, and PD, lower LINE-1 methylation levels were detected, whereas for mood disorders, the findings are controversial. The studies were conducted with subjects aged 18–80 years. Peripheral blood samples were utilized in 7/12 articles. Conclusion: Although most studies have shown that LINE-1 hypomethylation was associated with mental disorders, there were still some divergences (i.e., hypermethylation associated with mental disorders). These studies suggest that LINE-1 methylation may be an important factor related to the development of mental disorders and highlight the need to better comprehend the biological mechanisms underlying the role of LINE-1 in mental disorders pathophysiology.
Radiogenomic Associations Clear Cell Renal Cell Carcinoma: An Exploratory Study
Authors: Liu Derek H , Dani Komal A , Reddy Sharath S , Lei Xiaomeng , Demirjian Natalie L , Hwang Darryl H , Varghese Bino A , Rhie Suhn Kyong , Yap Felix Y. , Quinn David I. , Siddiqi Imran , Aron Manju , Vaishampayan Ulka , Zahoor Haris , Cen Steven Y , Gill Inderbir S , Duddalwar Vinay A
Published: April 2023

Introduction: This study investigates how quantitative texture analysis can be used to non-invasively identify novel radiogenomic correlations with clear cell renal cell carcinoma (ccRCC) biomarkers. Methods: The Cancer Genome Atlas-Kidney Renal Clear Cell Carcinoma open-source database was used to identify 190 sets of patient genomic data that had corresponding multiphase contrast-enhanced CT images in The Cancer Imaging Archive. 2,824 radiomic features spanning fifteen texture families were extracted from CT images using a custom-built MATLAB software package. Robust radiomic features with strong inter-scanner reproducibility were selected. Random forest, AdaBoost, and elastic net machine learning (ML) algorithms evaluated the ability of the selected radiomic features to predict the presence of 12 clinically relevant molecular biomarkers identified from the literature. ML analysis was repeated with cases stratified by stage (I/II vs. III/IV) and grade (1/2 vs. 3/4). 10-fold cross validation was used to evaluate model performance. Results: Before stratification by tumor grade and stage, radiomics predicted the presence of several biomarkers with weak discrimination (AUC 0.60–0.68). Once stratified, radiomics predicted KDM5C, SETD2, PBRM1, and mTOR mutation status with acceptable to excellent predictive discrimination (AUC ranges from 0.70 to 0.86). Conclusions: Radiomic texture analysis can potentially identify a variety of clinically relevant biomarkers in patients with ccRCC and may have a prognostic implication.
Cortexin® Ameliorates High Glucose-Induced Neuropathy in Cultured Rat Sensory Neurons
Authors: Yazar Uğur , Ayar Ahmet
Published: April 2023

Introduction: The aim of this study was to investigate whether Cortexin®, a brain peptide-containing agent, has any mitigating effect on high glucose-induced neuropathy, using primary cultured rat sensory neurons. Materials and Methods: Dorsal root ganglia (DRG) were excised from decapitated adult rats. Individual neurons were isolated following enzymatic and mechanical procedures. Cells were seeded on E-plate® with gold microelectrodes and maintained in conventional culture media in a CO2 incubator at 37°C. After allowing for 24 h for cell adhesion and recovery from acute enzymatic trauma, neurons were exposed to high glucose (HpG) in the absence and presence of different concentrations of Cortexin® (2–40 µg/mL). Neuroprotective effects were followed with the Real-Time Cell Analyzer® by utilizing measurement of Cell Index, a parameter representing cell viability, cell attachment, and neurite outgrowth. Results: Exposure of DRGs to HpG (50 mm) caused a rapid and sustained decrease in the mean area under the curve (AUC, values derived from time vs. Cell Index curve) compared to the mean AUC values in normoglycemic (NG) wells. Co-treatment with Cortexin® attenuated this HpG-induced effect, in a concentration-dependent manner (NG: 1.00 ± 0.00 vs. HG: 0.18 ± 0.02, p < 0.05; and HpG + Cortexin® [40 µg/mL]: 0.66 ± 0.17, p = 0.002 versus HpG). In normoglycemic conditions, Cortexin® treatment led to a concentration-dependent increase in the mean AUC values. Conclusions: Data from this in vitro study suggest that Cortexin® has potential neuroprotective effects against chronic hyperglycemic insult in rat sensory neurons. Our results warrant further in vivo studies and may have clinical implications for diabetes-associated peripheral neuropathy.