bluuebunny/crossref_metadata_2025 huggingface dataset:
Identifying influential nodes in complex networks based on network embedding and local structure entropy
Authors: Lu Pengli , Yang Junxia , Zhang Teng
Published: August 2023

The identification of influential nodes in complex networks remains a crucial research direction, as it paves the way for analyzing and controlling information diffusion. The currently presented network embedding algorithms are capable of representing high-dimensional and sparse networks with low-dimensional and dense vector spaces, which not only keeps the network structure but also has high accuracy. In this work, a novel centrality approach based on network embedding and local structure entropy, called the ELSEC, is proposed for capturing richer information to evaluate the importance of nodes from the view of local and global perspectives. In short, firstly, the local structure entropy is used to measure the self importance of nodes. Secondly, the network is mapped to a vector space to calculate the Manhattan distance between nodes by using the Node2vec network embedding algorithm, and the global importance of nodes is defined by combining the correlation coefficients. To reveal the effectiveness of the ELSEC, we select three types of algorithms for identifying key nodes as contrast approaches, including methods based on node centrality, optimal decycling based algorithms and graph partition based methods, and conduct experiments on ten real networks for correlation, ranking monotonicity, accuracy of high ranking nodes and the size of the giant connected component. Experimental results show that the ELSEC algorithm has excellent ability to identify influential nodes.
Tradeoff of generalization error in unsupervised learning
Authors: Kim Gilhan , Lee Hojun , Jo Junghyo , Baek Yongjoo
Published: August 2023

Finding the optimal model complexity that minimizes the generalization error (GE) is a key issue of machine learning. For the conventional supervised learning, this task typically involves the bias-variance tradeoff: lowering the bias by making the model more complex entails an increase in the variance. Meanwhile, little has been studied about whether the same tradeoff exists for unsupervised learning. In this study, we propose that unsupervised learning generally exhibits a two-component tradeoff of the GE, namely the model error (ME) and the data error (DE)—using a more complex model reduces the ME at the cost of the DE, with the DE playing a more significant role for a smaller training dataset. This is corroborated by training the restricted Boltzmann machine to generate the configurations of the two-dimensional Ising model at a given temperature and the totally asymmetric simple exclusion process with given entry and exit rates. Our results also indicate that the optimal model tends to be more complex when the data to be learned are more complex.
Large deviations for the Pearson family of ergodic diffusion processes involving a quadratic diffusion coefficient and a linear force
Authors: Monthus Cécile
Published: August 2023

The Pearson family of ergodic diffusions with a quadratic diffusion coefficient and a linear force is characterized by explicit dynamics of their integer moments and by explicit relaxation of spectral properties towards their steady state. Besides the Ornstein–Uhlenbeck process with a Gaussian steady state, other representative examples of the Pearson family are the square root or the Cox–Ingersoll–Ross process converging towards the gamma distribution, the Jacobi process converging towards the beta distribution, the reciprocal gamma process (corresponding to an exponential functional of the Brownian motion) that converges towards the inverse-gamma distribution, the Fisher–Snedecor process and the Student process. The last three steady states display heavy tails. The goal of the present paper is to analyze the large deviation properties of these various diffusion processes in a unified framework. We first consider level 1 concerning time-averaged observables over a large time windowT. We write the first rescaled cumulants for generic observables and identify specific observables whose large deviations can be explicitly computed from the dominant eigenvalue of the appropriate deformed generator. The explicit large deviations at level 2 concerning the time-averaged density are then used to analyze the statistical inference of model parameters from data on a very long stochastic trajectory in order to obtain the explicit rate function for the two inferred parameters of the Pearson linear force.
Exploring outputs from concatenated stochastic heat engines
Authors: Kumari Aradhana , Marathe Rahul , Lahiri Sourabh
Published: August 2023

Recent work on the concatenation of two simple heat engines has shown that it may lead to non-monotonic variations in the efficiency and power with parameters like driving amplitudes and asymmetries in cycle periods. Motivated by this study, we investigate the effect of the concatenation between two stochastic heat engines where colloidal particles have been trapped in harmonic potentials. The stiffness parameters of each engine are varied cyclically, but with different cycle periods, with a common thermal bath that acts as a sink for the first engine but as a source for the second. We consider two types of protocol, the first where the trap strength undergoes sudden jumps, and the second where it varies linearly with time. In both we find several non-trivial effects, like the non-monotonic functional dependence of the engine outputs on several parameters used in the setup. For the protocol that varies linearly with time, the concatenation leads to enhanced output power as compared to a single effective engine, in a suitable range of parameters. It has been shown that the output from the combined system shows a peak with respect to the asymmetry in the cycle times of the engines that have been concatenated. A general relation for the efficiency of an arbitrary number of concatenated engines driven quasistatically has been provided.
Computationally studying H- extraction and beamlet formation: the impact of the plasma model
Authors: den Harder Niek , Lindqvist Max , Mimo Alessandro , Minea Tiberiu , Mochalskyy Serhiy , Nocentini Riccardo , Revel Adrien , Wünderlich Dirk , Fantz Ursel
Published: August 2023

The ITER NBI requires H-/D- beamlets with a low divergence, to maximize the
transmitted power through the beamline. Ion extraction and beamlet formation are typically
studied with gun-type codes such as IBSimu, which do not treat the plasma explicitly. These codes
neglect many physical processes, such as the surface production of negative ions, particle drifts
in the plasma as a result of magnetic fields, and sheath formation at surfaces. 3D PIC
simulations show that the Debye sheath, which forms between the plasma and the plasma grid, has an
impact on the optics of negative ions extracted from the plasma. In this paper, a repelling
potential around the plasma grid is implemented ad-hoc in the IBSimu plasma model. The impact of
the sheath is investigated for the BUG-MLE grid system for negative ions that come from the
plasma. An electron repelling sheath increases the H- extraction probability since fewer
particles are lost on the plasma grid, however the extracted current density at the edge of the
aperture is reduced. The sheath increases the perpendicular energy distribution of the extracted
H-, because particles are reflected towards the extraction region. In the underperveant
regime, the sheath decreases the divergence, since it prevents H- from being extracted at the
edge of the aperture, and these particles are highly divergent in the underperveant regime. The
divergence optimum is shifted towards lower extracted current density with the sheath. The sheath
leads to a higher minimum divergence due to the increased perpendicular energy distribution in the
extraction region and the changed current density distribution.
More assistance of entanglement, less rounds of classical communication
Authors: Bhunia Atanu , Biswas Indranil , Chattopadhyay Indrani , Sarkar Debasis
Published: August 2023

Classical communication plays a crucial role to distinguish locally a class of quantum states. Despite considerable advances, we have very little knowledge about the number of measurement and communication rounds needed to implement a discrimination task by local quantum operations and classical communications (in short, LOCC). In this paper, we are able to show the relation between round numbers with the local discrimination of a set of pure bipartite orthogonal quantum states. To demonstrate the possible strong dependence on the round numbers, we consider a class of orthogonal product states in

d
⊗
d

, which require at least

2
d
−
2

round of classical communications. Curiously the round number can be reduced to d by the assistance of one-ebit of entanglement as resource and can be reduced further by assistance of more entanglement. We are also able to show that the number of LOCC rounds needed for a discrimination task may depend on the amount of entanglement assistance.
Revisiting the rationale of mandatory masking
Authors: Beauchamp Jonathan D , Mayhew Chris A
Published: August 2023

In this perspective, we review the evidence for the efficacy of face masks to reduce the transmission of respiratory viruses, specifically severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), and consider the value of mandating universal mask wearing against the widespread negative impacts that have been associated with such measures. Before the SARS-CoV-2 pandemic, it was considered that there was little to no benefit in healthy people wearing masks as prophylaxis against becoming infected or as unwitting vectors of viral transmission. This accepted policy was hastily reversed early on in the pandemic, when districts and countries throughout the world imposed stringent masking mandates. Now, more than three years since the start of the pandemic, the amassed studies that have investigated the use of masks to reduce transmission of SARS-CoV-2 (or other pathogens) have led to conclusions that are largely inconsistent and contradictory. There is no statistically significant or unambiguous scientific evidence to justify mandatory masking for general, healthy populations with the intention of lessening the viral spread. Even if mask wearing could potentially reduce the transmission of SARS-CoV-2 in individual cases, this needs to be balanced against the physical, psychological and social harms associated with forced mask wearing, not to mention the negative impact of innumerable disposed masks entering our fragile environment. Given the lack of unequivocal scientific proof that masks have any effect on reducing transmission, together with the evident harms to people and the environment through the use of masks, it is our opinion that the mandatory use of face masks in the general population is unjustifiable and must be abandoned in future pandemic countermeasures policies.
Comparative Study of Different Types of Slab for Same Structural Condition.
Authors: Hulke Pankaj , Solanke S. S.
Published: August 2023

The regular slab is often supported by a beam in modern construction, With a modest slab width and a big beam deep, the weight is transmitted from beam to column. Because of the flat slab, architects may construct partition walls wherever they are required. It is popular since it assists with weight reduction, stimulates quick development, and is did-not expensive. Similarly, since its debut, the classic slab has brought benefits such as greater rigidity. It offers a higher weight bearing capacity while also being good and economical. Grid slabs are required if the span is higher than one span, while grid beams are given if the span is less than one span. Grid slabs are good for longer spans with large loads because they eliminate voids that would otherwise result in dead load. Some slabs are less costly and more resistant to vibration. The study’s purpose is to determine which of the three slab varieties, regular slab, flat slab with drop, and grid slab, is the most benefits. a G+5 This study looked at storey displacement, shear force, bending moment, and storey drift in a residential multi-story structure with different slab.
Sustainable Solution for Disaster Management of Cement Concrete Constructions
Authors: Sharma Anuj kumar , Abhyuanker Snehal
Published: August 2023

This research aims at quantifying the effect of Polypropylene fibres in Pavement quality concrete mixes. Rigid pavement construction is based on conventional cement concrete. It is a well-known fact that conventional concrete is comparatively stronger in compression and weaker in tension. It also shows the properties like brittle material and it results in the development of cracks. In this laboratory investigation, different percentages of steel and polypropylene fibres were used to check their effect on the compressive and flexural strength of concrete mixes. The final combination was named SPFRC i.e., steel polypropylene fibre-reinforced concrete. Tests were conducted with different percentages of steel fibres and polypropylene fibres. IS:10262 [1] guidelines were followed for the design of the concrete mix. The outcome shows that there is a marginal increase in compressive strength but a considerable increase in the flexural strength of concrete.
Experimental Investigation of Bamboo Reinforced With Conventional Slab Panel
Authors: Ingole A , Shrikhande A , Choudhari S
Published: August 2023

The requirement for building materials is rising gradually. Concrete is embedded in steel to strengthen the tensile carrying properties. However the price of steel is increasing day by day, this attempt is made by providing low cost locally available, ecofriendly material as a replacement of Steel.

In this study the properties of bamboo as a reinforced material has been studied. Various properties like surface treatment, bond strength; flexural strength has been investigated through experimentation. Surface treatment is done by using different material and bond strength has been investigated. Total 27 slab panel has been casted as per the codal provision. The effect of total replacement of steel reinforcement by bamboo in flexural behavior, load –deflection characteristic has been observed. Finally the recommendation based on the result for slab panel is proposed.
Interlinking of Lakes to Combat Impacts of Climate Change
Authors: Meshram Kumud , Kadu M. S.
Published: August 2023

According to the Intergovernmental Panel on Climate Change (IPCC AR5, 2014), the global mean temperature may increase up to 4 °C by 2100, and will severely affect the availability of water resources and the water demand across the world. Understanding of the hydrological impacts of climate change enables water resource managers to make robust decisions on future policy adaptations. The concept of inter-basin transfer on a large scale has been under consideration for some time. In the present scenario there is great increase in demand for fresh water; thus, proper planning for conservation and judicious utilization is important to create balance between the availability and demand of water supply. Maharashtra State Adaptation Action Plan on Climate Change (MSAAPCC) for water resources sector recommended concrete efforts on conservation and renaturalisation of rivers and water bodies, enhancement of water storage and groundwater recharge and improvement of water use efficiency. Bhandara District of state of Maharashtra (India) is called as a district of lakes due to the existence of hundreds of lakes in the district called as Mama or Malguzari lakes. These lakes are developed in pre-independence era by the Gond king of the region for the purpose of irrigation and drinking purposes. These lakes were managed by the people; however, after independence, they came under the control of the govt and most of them got encroached or faced lack of attention and care by the local people. The district is being developed in various sectors and also the population is increasing in unpresented way leading to increased demand for water. The climate change has started showing signs; number of extreme weather events are increasing; recently, Bhandara received 186 mm of rainfall in a day; some of the areas in the district are facing the issues related to availability and quality of water irrespective of receiving average annual rainfall of more than 1100 mm. The linking of the lakes in the Bhandara District, Maharashtra, in a scientific manner using advanced tools and techniques will pave the way for sustainable development of water resources and its management. The linking of lakes will lead to creation of carbon sinks, enhancement of biodiversity, mitigation of drought and flood, and enhancement of food security. Peoples’ participation and multipronged approach on Awareness, action and accountability will hold the key to success through localization of SDGs as recommended by NITI Aayog, Govt. of India. The proposed integrated SWAT-MODFLOW model will provide scientific insights required for cost effective planning for interlinking and management of lakes in the region. The outcome of the study can be used as a rule base for adoption and development of similar proposals in the suitable areas in other regions.
Planning and Design of Sustainable Water Harvesting Structures using Geospatial System
Authors: Bhorkar M P , Shukla J , Pitale N H , Vinchurkar S M
Published: August 2023

The most precious & essential resource on the earth surface is water for survival of life. Though the annual rainfall is between 900 to 1500 mm in southern region of India. From the southwest monsoon, still most part of the southern region of India experience water scarcity. To increase the ground water storage & surface water, water harvesting is widely suggested approach which traps the surface runoff effectively. The location to locate water harvesting structures is depends upon the availability of sufficient water quantity which enhance the infiltration. The analysis of these structures in regard of planning & site suitability involves consideration of multiple terrain and weather parameters. In this context, Remote & GIS technologies are widely adopted while planning and implementation of water harvesting structures. The aim of this paper is to identify suitable sites for water harvesting structures and to propose the design for it using geo-spatial data and GIS technology. In this study various sites are opted for development of water resource planning in Southern region of India using geospatial techniques. ArcGIS software is used for the spatial analysis and the intermediate layer was formed by overlying thematic maps of land cover land use, soil, slope, stream order map, runoff potential map.
Comparison of Bursting Forces in Concrete Post-Tensioned Beam using Two Modeling Approaches
Authors: Jain Monika , Khapre Rajendra
Published: August 2023

A case study on a rectangular post-tensioned concrete beam end block with 3-dimensional analysis is presented in this paper. ANSYS software is used to model the end-block of a post-tensioned concrete specimen i.e., beam. An actual anchorage plate, widely used in construction is modeled with two different approaches, and a concentrated jacking force is applied to the same anchorage area. A case study is performed in which two different modeling approaches are used to model the end plate. For both modeled plates, the results are obtained and findings are compared in terms of stresses, its location and bursting force. Different equations from various design manuals are used to compare the calculated bursting tensile force.
Interoperability Between Building Information Modeling (BIM) and Structural Engineering
Authors: Khungar Hariom P. , Bhandari Hardik
Published: August 2023

The aim is to understand how structural engineers might benefited from the adoption of Building Information Modeling (BIM). Aside from that, the ease with which the structure can be redesigned and modified within a single model is also explored.

The analysis of the interoperability issues related to the process of transferring models between pieces of software was the primary emphasis of this investigation’s findings. The study shows that there is still a sizable amount of supplemental work that must be done, particularly about the reinforcing detailing
Study of Natural Fiber over Strength and Density of Cement Stabilized Rammed Earth Blocks.
Authors: Rajurkar Vaishali , Chitade A. Z.
Published: August 2023

The promotion of sustainable materials is needed in the construction industry; in this study demolishing waste (DW) is used to replace natural sand. Initially, the test blocks were cast with the local soil and DW stabilized with 8% of cement at optimum moisture content. The blocks were prepared and tested; the required density of blocks was achieved through dynamic compaction and cured in a Gunny bag for 28 days. The effects of different compositions and different mix ratios between soil, DW, and FA (5–20%) and curtailing cement by 1% of the total mix. To improve the strength and durability of the material three different natural fibers i.e. wheat straw, jute, and coconut coir (0–2%) are randomly added by total weight.

The density, tangent modulus (Ei) and wet strengthl of the geo material are investigated. The density of the block is reduced from 17.012 to 15.845kN/m3 with the addition in FA. The density of the mix increases considerably up to 10% FA and 1.5% of all fibers. Further addition of FA and fibers decreases the wet density and eventually the strength. The thermal conductivity of wheat straw is better but the wet cube compressive strength of blocks with coconut coir is 5.735 MPa around 40 to 45 % more than wheat straw at 1.5% fiber of total mix. Referring to the above study higher the density higher the strength and stiffness. It is observed from the above study that the range of Ei values is in between 5.5 to 9.75 MPa in moist conditions. The material developed in the study can be used as an energy-efficient, non-toxic and sustainable alternative to burnt bricks for load-bearing walls of low-rise buildings.
Effect of Copper Percentage in Copper Tungsten Electrode on Ti6Al4V by Electrical Discharge Machining
Authors: Muttamara A , Nakwong P , Pararach S
Published: August 2023

The aim of this study was to identify the optimal parameters for electrical discharge machining of Ti6Al4V titanium alloy using copper tungsten electrodes with tungsten compositions of 70% and 80%, respectively. The experiment involved varying current, pulse on time, and duty factor were determined using the Taguchi experimental method L-18 orthogonal arrays. The level of importance of each machining parameter on material removal rate (MRR) was determined using analysis of variance (ANOVA), and the optimal machining parameter combination was obtained using the analysis of signal-to-noise (S/N) ratio. The results showed that a Cu30/W70% electrode performed the best in terms of MRR, electrode wear, and surface roughness. The optimal machining conditions for achieving maximum MRR were found to be a current of 30 A, a pulse on time of 50 μs, and a duty factor of 40%.
Synthesis of Lignin Extracted from Black Liquor to Nano Porous Carbon Materials for Tetracycline Adsorption Application
Authors: Tempiam Tassanai , Jaruvanawat Anuchit , Srifa Atthapon , Kiatkittipong Worapon , Eiad-Ua Apiluck , Assabumrungrat Suttichai
Published: August 2023

Tetracycline is an antibiotic that suppresses the growth of bacteria, treats infections in the urinary tract, treats intestinal inflammation, bronchitis, treats dysentery, treats wounds, abscesses, pus, various inflammations due to infections. However, antibiotics have attracted extensive attention from the scientists because a variety of antibiotics have been. detected in soil, surface water, groundwater, and even in drinking water in the recent years. Antibiotics are among the most potent pollutants due to their overuse. This is because most antibiotics are metabolized and poorly absorbed by humans and treated animals, so many fractions are excreted through urine and feces into water. Therefore, it is urgent to remove tetracycline from water environment. There are several techniques used to remove tetracycline from aqueous solutions, coagulation, photo electrocatalytic degradation, ion exchange, membrane processing, and adsorption. Among them, adsorption is a widely used efficient technology, because it has the advantages of easy operation, low cost, high efficiency, and there is no risk of highly toxic by-products. In this work, lignin from black liquor in chemical pulping processes is used as a precursor for nano porous carbon synthesis. The physical and chemical properties of nano porous carbon was investigated by field-emission scanning electron microscope (FESEM), X-ray diffractometer (XRD), Energy Dispersive X-ray Spectroscopy (EDX), and Nitrogen sorption isotherm, respectively. The maximum surface area appears at 1,676.5 m2/g and a total pore volume of 1.091 cm3/g, this sample was used as an adsorbent and could perform its functions perfectly.
Effect of microstructural rearrangement as a result of annealing on the corrosion behavior of 7075 aluminum alloy
Authors: Anawati Anawati , Aliyah Aisyah Nur , Tanji Ayoub , Hermawan Hendra
Published: August 2023

Understanding of the relationship between microstructural change and corrosion behavior is essential for achieving the optimum benefit of strengthening precipitates in providing high strength without sacrificing the corrosion resistance of 7000 series aluminum alloys. This work aims at revealing the relationship between the microstructural rearrangement and corrosion behavior of a 7075 series aluminum alloy as a result of annealing at the temperature range of 300 °C–600 °C. Microstructural observation indicated a gradual dissolution of Cu in the solid solution matrix with increasing annealing temperature. At 600 °C, a formation of segregated Al2Cu phase occurred along the grain boundaries. After subjected to corrosion tests, exfoliation corrosion was observed on the as-received specimen, as well as on the specimens annealed at 300, 400 and 500 °C, whilst an intergranular corrosion occurred on that annealed at 600 °C. The corrosion resistance was higher on the specimen annealed at 500 °C compared those annealed at other temperatures, as the result of Cu enrichment the solid solution matrix.
Quantum two-way time transfer over a hybrid free-space and fiber link
Authors: Xiang Xiao , Shi Bingke , Quan Runai , Liu Yuting , Xia Zhiguang , Hong Huibo , Liu Tao , Wu Jincai , Qiang Jia , Jia Jianjun , Zhang Shougang , Dong Ruifang
Published: August 2023

As the superiority of quantum two-way time transfer (Q-TWTT) has been proved convincingly over fiber links, its implementation on free-space links becomes an urgent need for remote time transfer expanding to the transcontinental distance. In this paper, the first Q-TWTT experimental demonstration over a hybrid link of 2 km-long turbulent free-space and 7 km-long field fiber is reported. Despite the significant loss of ∼30 dB and atmospheric turbulence, reliable time transfer performance lasting for overnights has been realized with time stability in terms of time deviation far below 1 picosecond. This achievement shows the good feasibility of quantum-enhanced time transfer in the space-ground integrated optical links and nicely certifies the capability of Q-TWTT in comparing and synchronizing the state-of-the-art space microwave atomic clocks.
Euclidean Structures and Operator Theory in Banach Spaces
Authors: Kalton Nigel , Lorist Emiel , Weis Lutz
Published: August 2023

We present a general method to extend results on Hilbert space operators to the Banach space setting by representing certain sets of Banach space operators

Γ
\Gamma

on a Hilbert space. Our assumption on

Γ
\Gamma

is expressed in terms of

α
\alpha

-boundedness for a Euclidean structure

α
\alpha

on the underlying Banach space

X
X

. This notion is originally motivated by

R

\mathcal {R}

- or

γ
\gamma

-boundedness of sets of operators, but for example any operator ideal from the Euclidean space

ℓ
n
2

\ell ^2_n

to

X
X

defines such a structure. Therefore, our method is quite flexible. Conversely we show that

Γ
\Gamma

has to be

α
\alpha

-bounded for some Euclidean structure

α
\alpha

to be representable on a Hilbert space.

By choosing the Euclidean structure

α
\alpha

accordingly, we get a unified and more general approach to the Kwapień–Maurey factorization theorem and the factorization theory of Maurey, Nikišin and Rubio de Francia. This leads to an improved version of the Banach function space-valued extension theorem of Rubio de Francia and a quantitative proof of the boundedness of the lattice Hardy–Littlewood maximal operator. Furthermore, we use these Euclidean structures to build vector-valued function spaces. These enjoy the nice property that any bounded operator on

L
2

L^2

extends to a bounded operator on these vector-valued function spaces, which is in stark contrast to the extension problem for Bochner spaces. With these spaces we define an interpolation method, which has formulations modelled after both the real and the complex interpolation method.

Using our representation theorem, we prove a transference principle for sectorial operators on a Banach space, enabling us to extend Hilbert space results for sectorial operators to the Banach space setting. We for example extend and refine the known theory based on

R

\mathcal {R}

-boundedness for the joint and operator-valued

H
∞

H^\infty

-calculus. Moreover, we extend the classical characterization of the boundedness of the

H
∞

H^\infty

-calculus on Hilbert spaces in terms of

B
I
P

BIP

, square functions and dilations to the Banach space setting. Furthermore we establish, via the

H
∞

H^\infty

-calculus, a version of Littlewood–Paley theory and associated spaces of fractional smoothness for a rather large class of sectorial operators. Our abstract setup allows us to reduce assumptions on the geometry of

X
X

, such as (co)type and UMD. We conclude with some sophisticated counterexamples for sectorial operators, with as a highlight the construction of a sectorial operator of angle

0
0

on a closed subspace of

L
p

L^p

for

1
>
p
>
∞

1>p>\infty

with a bounded

H
∞

H^\infty

-calculus with optimal angle

ω

H
∞

(
A
)
>
0

\omega _{H^\infty }(A) >0

.
Subjective Social Status and Longitudinal Changes in Systemic Inflammation
Authors: Jones Emily J , Marsland Anna L , Kraynak Thomas E , Votruba-Drzal Elizabeth , Gianaros Peter J
Published: August 2023

Background

Subjective social status (SSS) refers to a person’s perception of their social rank relative to others and is cross-sectionally linked to systemic inflammation independently of objective socioeconomic status.

Purpose

We test the extent to which SSS relates to multiyear changes in inflammation, or if associations differ by race or sex.

Methods

Healthy adults (N = 331; 30–51 years) completed a baseline visit and 278 participants returned for a second visit 2.85 years later. At both visits, participants underwent a fasting blood draw and completed community (SSSC) and US (SSSUS) versions of the MacArthur Scale. Multiple linear regression analyses examined change in interleukin-6 (IL-6) and C-reactive protein (CRP) predicted by each type of SSS, adjusting for time between visits, sex, race, age, body mass index, smoking, baseline inflammation, and objective socioeconomic status. Additional analyses further adjusted for hopelessness and depressive symptoms. Interactions examined moderations by sex and race.

Results

Lower SSSC was longitudinally associated with greater IL-6 independently of all covariates, including education and income (β = −0.06), hopelessness (β = −0.06), and depressive symptoms (β = −0.06). Lower SSSUS was longitudinally associated with greater IL-6 independently of demographic covariates including education and income (β = −0.06), but was slightly attenuated after adjusting for hopelessness (β = −0.06) and depressive symptoms (β = −0.06). There were no associations for CRP or moderation by race or sex.

Conclusions

Lower SSS may be associated with greater circulating markers of inflammation over time as suggested by increases in IL-6.
Choosing Wisely and reducing the simultaneous ordering of erythrocyte sedimentation rate and C-reactive protein testing in a large safety net system
Authors: Cho Hyung J , Talledo Joseph , Alaiev Daniel , Israilov Sigal , Chandra Komal , Tsega Surafel , Garcia Mariely , Shin Da Wi , Zaurova Milana , Alarcon Manchego Peter , Krouss Mona
Published: August 2023

Objectives

C-reactive protein (CRP) and erythrocyte sedimentation rate (ESR) are commonly used inflammatory markers. C-reactive protein is more sensitive and specific for monitoring acute inflammation. However, it is commonly co-ordered with ESR despite recommendations against this. Our objective was to reduce unnecessary ESR orders and ESR/CRP co-ordering rates across a large safety net health system.

Methods

This was a quality improvement project that used a quasi-experimental pre- and postintervention interrupted time-series regression analysis. Patients with a positive COVID-19 test were excluded. We designed a nonintrusive, normative nudge within the ESR order that recommended against co-ordering ESR and CRP. In addition, a best practice advisory triggered when ESR and CRP were simultaneously ordered. The outcome measures were ESR order rates per 1000 patient days in the inpatient setting and per 1000 patient encounters in the outpatient setting, as well as ESR/CRP co-ordering rates.

Results

Inpatient ESR orders decreased from 12.02 preintervention to 5.61 per 1000 patient days (–53.3%, P < .001). Outpatient ESR orders decreased from 6.09 to 4.07 per 1000 patient encounters (–33.2%, P < .001). Relative co-ordering rates decreased by 50%.

Conclusions

This electronic health record initiative successfully reduced ESR testing across 11 hospitals and 70 ambulatory centers in a safety net setting.
Identifying spatial domains of spatially resolved transcriptomics via multi-view graph convolutional networks
Authors: Shi Xuejing , Zhu Juntong , Long Yahui , Liang Cheng
Published: August 2023

Motivation: Recent advances in spatially resolved transcriptomics (ST) technologies enable the measurement of gene expression profiles while preserving cellular spatial context. Linking gene expression of cells with their spatial distribution is essential for better understanding of tissue microenvironment and biological progress. However, effectively combining gene expression data with spatial information to identify spatial domains remains challenging. Results: To deal with the above issue, in this paper, we propose a novel unsupervised learning framework named STMGCN for identifying spatial domains using multi-view graph convolution networks (MGCNs). Specifically, to fully exploit spatial information, we first construct multiple neighbor graphs (views) with different similarity measures based on the spatial coordinates. Then, STMGCN learns multiple view-specific embeddings by combining gene expressions with each neighbor graph through graph convolution networks. Finally, to capture the importance of different graphs, we further introduce an attention mechanism to adaptively fuse view-specific embeddings and thus derive the final spot embedding. STMGCN allows for the effective utilization of spatial context to enhance the expressive power of the latent embeddings with multiple graph convolutions. We apply STMGCN on two simulation datasets and five real spatial transcriptomics datasets with different resolutions across distinct platforms. The experimental results demonstrate that STMGCN obtains competitive results in spatial domain identification compared with five state-of-the-art methods, including spatial and non-spatial alternatives. Besides, STMGCN can detect spatially variable genes with enriched expression patterns in the identified domains. Overall, STMGCN is a powerful and efficient computational framework for identifying spatial domains in spatial transcriptomics data.
Single-cell causal network inferred by cross-mapping entropy
Authors: Li Lin , Xia Rui , Chen Wei , Zhao Qi , Tao Peng , Chen Luonan
Published: August 2023

Gene regulatory networks (GRNs) reveal the complex molecular interactions that govern cell state. However, it is challenging for identifying causal relations among genes due to noisy data and molecular nonlinearity. Here, we propose a novel causal criterion, neighbor cross-mapping entropy (NME), for inferring GRNs from both steady data and time-series data. NME is designed to quantify ‘continuous causality’ or functional dependency from one variable to another based on their function continuity with varying neighbor sizes. NME shows superior performance on benchmark datasets, comparing with existing methods. By applying to scRNA-seq datasets, NME not only reliably inferred GRNs for cell types but also identified cell states. Based on the inferred GRNs and further their activity matrices, NME showed better performance in single-cell clustering and downstream analyses. In summary, based on continuous causality, NME provides a powerful tool in inferring causal regulations of GRNs between genes from scRNA-seq data, which is further exploited to identify novel cell types/states and predict cell type-specific network modules.
HiBrowser: an interactive and dynamic browser for synchronous Hi-C data visualization
Authors: Li Pingjing , Liu Hong , Sun Jialiang , Lu Jianguo , Liu Jian
Published: August 2023

With the development of chromosome conformation capture technology, the genome-wide investigation of higher-order chromatin structure by using high-throughput chromatin conformation capture (Hi-C) technology is emerging as an important component for understanding the mechanism of gene regulation. Considering genetic and epigenetic differences are typically used to explore the pathological reasons on the chromosome and gene level, visualizing multi-omics data and performing an intuitive analysis by using an interactive browser become a powerful and welcomed way. In this paper, we develop an effective sequence and chromatin interaction data display browser called HiBrowser for visualizing and analyzing Hi-C data and their associated genetic and epigenetic annotations. The advantages of HiBrowser are flexible multi-omics navigation, novel multidimensional synchronization comparisons and dynamic interaction system. In particular, HiBrowser first provides an out of the box web service and allows flexible and dynamic reconstruction of custom annotation tracks on demand during running. In order to conveniently and intuitively analyze the similarities and differences among multiple samples, such as visual comparisons of normal and tumor tissue samples, and pan genomes of multiple (consanguineous) species, HiBrowser develops a clone mode to synchronously display the genome coordinate positions or the same regions of multiple samples on the same page of visualization. HiBrowser also supports a pluralistic and precise search on correlation data of distal cis-regulatory elements and navigation to any region on Hi-C heatmap of interest according to the searching results. HiBrowser is a no-build tool, and could be easily deployed in local server. The source code is available at https://github.com/lyotvincent/HiBrowser.
A model-agnostic framework to enhance knowledge graph-based drug combination prediction with drug–drug interaction data and supervised contrastive learning
Authors: Gu Jeonghyeon , Bang Dongmin , Yi Jungseob , Lee Sangseon , Kim Dong Kyu , Kim Sun
Published: August 2023

Combination therapies have brought significant advancements to the treatment of various diseases in the medical field. However, searching for effective drug combinations remains a major challenge due to the vast number of possible combinations. Biomedical knowledge graph (KG)-based methods have shown potential in predicting effective combinations for wide spectrum of diseases, but the lack of credible negative samples has limited the prediction performance of machine learning models. To address this issue, we propose a novel model-agnostic framework that leverages existing drug–drug interaction (DDI) data as a reliable negative dataset and employs supervised contrastive learning (SCL) to transform drug embedding vectors to be more suitable for drug combination prediction. We conducted extensive experiments using various network embedding algorithms, including random walk and graph neural networks, on a biomedical KG. Our framework significantly improved performance metrics compared to the baseline framework. We also provide embedding space visualizations and case studies that demonstrate the effectiveness of our approach. This work highlights the potential of using DDI data and SCL in finding tighter decision boundaries for predicting effective drug combinations.
The challenges of success: Future wolf conservation and management in the United States
Authors: Ausband David E , Mech L David
Published: August 2023

Gray wolf (Canis lupus) recovery and conservation has been a remarkable success over the last 30 years in the United States. Remarkable success yields remarkable challenges, however. As populations expand, wolves will colonize more human-dominated landscapes and face numerous challenges, such as fragmented habitats, barriers to dispersal, and increased encounters with humans, pets, and livestock. In such areas, conflicts between humans and wolves will increase. We summarize several major scientific and social challenges that wolf conservation, recovery, and management will face in the coming years. In addition, we suggest actions to help address each challenge. Future wolf conservation in the United States will be affected by the ability of managers to predict colonization and dispersal dynamics, to reduce hybridization and disease transmission, to mitigate and deter wolf–livestock conflicts, to harvest wolves sustainably while satisfying diverse stakeholders, to avert a reduction in tolerance for wolves due to a disinterest in nature, and to engage diverse stakeholders in wolf conservation to avoid management by ballot initiative or legislative and judicial decrees.
Skin ageing and topical rejuvenation strategies
Authors: Griffiths Tamara W , Watson Rachel E B , Langton Abigail K
Published: August 2023

Skin ageing is a complex process involving the additive effects of skin’s interaction with its external environment, predominantly chronic sun exposure, upon a background of time-dependent intrinsic ageing. Skin health and beauty is considered one of the principal factors perceived to represent overall ‘health and wellbeing’; thus, the demand for skin rejuvenation strategies has rapidly increased, with a worldwide annual expenditure expected to grow from $US24.6 billion to around $US44.5 billion by 2030 (https://www.databridgemarketresearch.com/reports/global-facial-rejuvenation-market). Skin rejuvenation can be achieved in several ways, ranging from laser and device-based treatments to chemical peels and injectables; however, topical skin care regimes are a mainstay treatment for ageing skin and all patients seeking skin rejuvenation can benefit from this relatively low-risk intervention. While the most efficacious topical rejuvenation treatment is application of tretinoin (all-trans retinoic acid) – a prescription-only medicine considered to be the clinical ‘gold standard’ – a hybrid category of ‘cosmeceutical’ products at the midpoint of the spectrum of cosmetics and pharmaceutical has emerged. This article reviews the clinical manifestations of skin ageing and the available topical treatments for skin rejuvenation, including retinoids, peptides and antioxidants.
Liver transplantation for elderly patients with early-stage hepatocellular carcinoma
Authors: Endo Yutaka , Sasaki Kazunari , Moazzam Zorays , Lima Henrique A , Alaimo Laura , Munir Muhammad Musaab , Shaikh Chanza F , Schenk Austin , Kitago Minoru , Pawlik Timothy M
Published: August 2023

Background

Although liver resection is a viable option for patients with early-stage hepatocellular carcinoma (HCC), liver transplantation is the optimal treatment. The aim of this study was to identify characteristics of liver transplantation for elderly patients, and to assess the therapeutic benefit derived from liver transplantation over liver resection.

Methods

This was a population-based study of patients undergoing liver transplantation for HCC in the USA between 2004 and 2018. Data were retrieved from the National Cancer Database. Elderly patients were defined as individuals aged 70 years and over. Propensity score overlap weighting was used to control for heterogeneity between the liver resection and liver transplantation cohorts.

Results

Among 4909 liver transplant recipients, 215 patients (4.1 per cent) were classified as elderly. Among 5922 patients who underwent liver resection, 1907 (32.2 per cent) were elderly. Elderly patients who underwent liver transplantation did not have a higher hazard of dying during the first 5 years after transplantation than non-elderly recipients. After propensity score weighting, liver transplantation was associated with a lower risk of death than liver resection. Other factors associated with overall survival included diagnosis during 2016–2018, non-white/non-African American race, and α-fetoprotein level over 20 ng/dl.

Conclusion

Elderly patients with HCC should not be excluded from liver transplantation based on age only. Transplantation leads to favourable survival compared with liver resection.
Regional diversification and labour market upgrading: local access to skill-related high-income jobs helps workers escaping low-wage employment
Authors: Elekes Zoltán , Baranowska-Rataj Anna , Eriksson Rikard
Published: August 2023

This article investigates how the evolution of local labour market structure enables or constrains workers as regards escaping low-wage jobs. Drawing on the network-based approach of evolutionary economic geography, we employ a detailed individual-level panel dataset to construct skill-relatedness networks for 72 functional labour market regions in Sweden. Subsequent fixed-effect panel regressions indicate that increasing density of skill-related high-income jobs within a region is conducive to low-wage workers moving to better-paid jobs, hence facilitating labour market upgrading through diversification. While metropolitan regions offer a premium for this relationship, it also holds for smaller regions, and across various worker characteristics.
Claude McKay’s vagabond classicisms: empire, uplift, and antiquity
Authors: Gregson Ben
Published: August 2023

This article examines the classicisms of the influential Jamaican writer, Claude McKay. Taking as paradigmatic an allusion to the myth of Laocoön in Banjo, it analyses McKay’s troubling of the classical notion of translatio imperii et studii throughout his work. Consistently rejecting imperium, McKay nevertheless embraced classical studium as a potential source of racial uplift and new creative expression. He resists both hegemonic Euro-American classicisms which appropriated Greco-Roman antiquity to authorize their imperial projects and simplistic Afrocentric classicisms which relocated imperial fantasies in Egypt and Ethiopia. However, McKay still admired the cultural legacies of Greco-Roman and African ancient civilizations. Freely and selectively enlisting these various, often-contradictory, classical traditions, McKay’s vagabond classicisms attacked empire, in all its forms, while reaffirming the aesthetic and social potential of decolonized and heterogeneous antiquities.