bluuebunny/crossref_metadata_2025_split huggingface dataset:
Modeling psychopathology: 4D multiplexes to the rescue
Authors: Kästner Lena 
Published: December 2022

AbstractAccounts of mental disorders focusing either on the brain as neurophysiological substrate or on systematic connections between symptoms are insufficient to account for the multifactorial nature of mental illnesses. Recently, multiplexes have been suggested to provide a holistic view of psychopathology that integrates data from different factors, at different scales, or across time. Intuitively, these multi-layered network structures present quite appealing models of mental disorders that can be constructed by powerful computational machinery based on increasing amounts of real-world data. In this paper, I systematically examine what challenges psychopathology models face and to what extent different species of psychopathology models can address them. My analysis highlights that while multiplexes, as they are usually conceived, appear promising, they suffer from the same problems as other approaches. To remedy this, I suggest, we must go a step further and combine different kinds of multiplexes into 4D models. Once we embrace 4D multiplexes and identify appropriate ways to constrain them, we might unlock the true potential of multiplexes for making headway in psychopathology research.
Artificial intelligence-based volumetric analysis of muscle atrophy and fatty degeneration in patients with hip osteoarthritis and its correlation with health-related quality of life
Authors: Iwasa Makoto , Takao Masaki , Soufi Mazen , Uemura Keisuke , Otake Yoshito , Hamada Hidetoshi , Sato Yoshinobu , Sugano Nobuhiko , Okada Seiji 
Published: December 2022

Abstract
Purpose
Artificial intelligence (AI) technologies have enabled precise three-dimensional analysis of individual muscles on computed tomography (CT) or magnetic resonance images via automatic segmentation. This study aimed to perform three-dimensional assessments of pelvic and thigh muscle atrophy and fatty degeneration in patients with unilateral hip osteoarthritis using CT and to evaluate the correlation with health-related quality of life (HRQoL).

Methods
The study included one man and 43 women. Six muscle groups were segmented, and the muscle atrophy ratio was calculated volumetrically. The degree of fatty degeneration was defined as the difference between the mean CT values (Hounsfield units [HU]) of the healthy and affected sides. HRQoL was evaluated using the Western Ontario and McMaster Universities Osteoarthritis (WOMAC) index and the Japanese Orthopaedic Association Hip Disease Evaluation Questionnaire (JHEQ).

Results
The mean muscle atrophy rate was 16.3%, and the mean degree of muscle fatty degeneration was 7.9 HU. Multivariate correlation analysis revealed that the WOMAC stiffness subscale was significantly related to fatty degeneration of the hamstrings, the WOMAC physical function subscale was significantly related to fatty degeneration of the iliopsoas muscle, and the JHEQ movement subscale was significantly related to fatty degeneration of the hip adductors.

Conclusion
We found that fatty degeneration of the hamstrings, iliopsoas, and hip adductor muscles was significantly related to HRQoL in patients with hip osteoarthritis. These findings suggest that these muscles should be targeted during conservative rehabilitation for HOA and perioperative rehabilitation for THA.
Active biomonitoring of potentially toxic elements in urban air by two distinct moss species and two analytical techniques: a pan-Southeastern European study
Authors: Urošević M. Aničić , Lazo P. , Stafilov T. , Nečemer M. , Andonovska K. Bačeva , Balabanova B. , Hristozova G. , Papagiannis S. , Stihi C. , Suljkanović M. , Špirić Z. , Vassilatou V. , Vogel-Mikuš K. 
Published: December 2022

Abstract
This is the first study to use moss transplants as a biomonitoring technique and inductively plasma mass spectrometry to investigate airborne potentially toxic element pollution and air quality in urban areas on a regional scale across nine Southeastern European countries. The mosses in bags were exposed for 2 months during the winter season (2019/2020) at five sites in each of the selected urban areas next to air quality (AQ) monitoring stations. The sites were selected concerning different land use classes (typical urban, residential, urban background, and rural sites). The concentrations of 35 elements were determined using inductively coupled plasma mass spectrometry. A comparison with elemental analysis performed by total reflection X-ray fluorescence is also presented. Concentrations of the potentially toxic element in moss bags exposed in urban areas were significantly higher, while those exposed in rural areas did not differ significantly from the initial content of unexposed moss. Linear regression analysis revealed no significant differences between the average concentrations of elements in H. cupressiforme and S. girgensohnii moss bags (linearity R2 = 0.94). It shows similar trends in elements in both moss species. The median values of contamination factors in both moss species ranged mostly from 1.2 to 2.17, indicating the exposure sites show no contamination to slight contamination status (C1 to C2 scales). High values of relative accumulation factors were found for Cr, Cu, Fe, Ni, Sb, and V in moss bags, indicating these elements are the most abundant in most sampling sites, which may increase human exposure through inhalation and could lead to harmful health problems.
Temperature and Particle-size Effects on the Formation of Silica Gels from Silica Sols
Authors: Sögaard Christian , Hagström Magnus , Abbas Zareen 
Published: December 2022

AbstractSilica nanoparticles (silica sols) based gels have increasingly been used as alternative grouting material for sealing the small fractures in the tunnel walls. Gelling of silica nanoparticles at room temperature has been investigated thoroughly but gelling at different temperatures scarcely investigated. At the same time temperature is one of major factor which can affect the long-term stability of grouted silica. In this work we have investigated the gelling of three different types of silica sols (Levasil CS40-213, Levasil CS40-222, and Levasil CS30-236) having different particle sizes, in 0.28 M NaCl at 10, 20 and 30 °C. Aggregation process, starting from the addition of salt to the gelling point, was monitored by measuring the time dependent particle size distribution. Electrospray scanning mobility particle sizer (ES-SMPS) was used to measure the aggregating. These measurements were complemented by rheological measurements in order to get a relationship between changes in aggregate structure and in the viscosity of silica suspension. Data from the temperature dependent gel time measurements were used to calculate the activation energy. At room temperature, silica sols with smallest average particle size showed the shortest gel times whereas the sols with the largest particle size showed the longest gel time. However, at increasing temperature shorter gel times were seen for all the sols. Temperature dependent rheological measurements showed similar trends in viscosity changes as seen for gel times i.e., increased temperature leads to quicker increase in the viscosity and a sharp increase in viscosity near the gelling point. Our calculations of fractal dimensions showed that in the gel network there are still many free particles which continuously incorporated into the gel network. Apparent activation energies calculated for CS40-213, CS40-222, CS30-236 were 13.40, 23.36 and 41.45 kJ/mol, respectively. These values are lower than values reported for silica in the literature. Moreover, temperature dependent zeta potential measurements show that zeta potential get less negative as temperature increase. The above mentioned measurements are at odd what has been reported in literature but we have provided plausible explanation of these results.
The Presence of Residual Vascular and Adipose Tissue Inflammation on 18F-FDG PET in Patients with Chronic Coronary Artery Disease
Authors: Toivonen Sini , Lehtinen Miia , Raivio Peter , Sinisalo Juha , Loimaala Antti , Uusitalo Valtteri 
Published: December 2022

Abstract

Purpose
We evaluated the residual vascular and adipose tissue inflammation in patients with chronic coronary artery disease (CAD) using positron emission tomography (PET).

Methods
Our study population consisted of 98 patients with known CAD and 94 control subjects who had undergone 18F-fluorodeoxyglucose (18F-FDG) PET due to non-cardiac reasons. Aortic root and vena cava superior 18F-FDG uptake were measured to obtain the aortic root target-to-background ratio (TBR). In addition, adipose tissue PET measurements were done in pericoronary, epicardial, subcutaneous, and thoracic adipose tissue. Adipose tissue TBR was calculated using the left atrium as a reference region. Data are presented as mean ± standard deviation or as median (interquartile range).

Results
The aortic root TBR was higher in CAD patients compared to control subjects, 1.68 (1.55–1.81) vs. 1.53 (1.43–1.64), p < 0.001. Subcutaneous adipose tissue uptake was elevated in CAD patients 0.30 (0.24–0.35) vs. 0.27 (0.23–0.31), p < 0.001. Metabolic activity of CAD patients and control subjects was comparable in the pericoronary (0.81 ± 0.18 vs. 0.80 ± 0.16, p = 0.59), epicardial (0.53 ± 0.21 vs. 0.51 ± 0.18, p = 0.38) and thoracic (0.31 ± 0.12 vs. 0.28 ± 0.12, p = 0.21) adipose tissue regions. Aortic root or adipose tissue 18F-FDG uptake was not associated with the common CAD risk factors, coronary calcium score, or aortic calcium score (p value > 0.05).

Conclusion
Patients with a chronic CAD had a higher aortic root and subcutaneous adipose tissue 18F-FDG uptake compared to control patients, which suggests residual inflammatory risk.
Effect of concentration on the properties of nitrogen-doped zinc oxide thin films grown by electrodeposition
Authors: Musiliyu K. A. , Ogunmola E. D. , Ajayi A. A. , Abodunrin O. W. 
Published: December 2022

AbstractZinc oxide is one of the most researched semiconductors owing to the outstanding properties that make it useful in various industrial applications, such as solar cells and other optoelectronics. In this work, ZnO thin films were prepared in five different concentrations and doped with four nitrogen atoms from triethylene tetramine (TETA) to fabricate a ZnO for optoelectronic applications using an electrodeposition technique. The doped ZnO thin films were synthesized and deposited on ITO glass substrates. The deposited thin films were annealed at 400°Cfor 60min in a furnace under the same conditions. The thin films' optical, electrical, and surface morphological properties were characterized using UV–Vis Spectrophotometer, Four Point Probe (FPP), and Scanning Electron Microscope (SEM), respectively. The optical properties confirmed the film's suitability for various transparent device applications with a high optical transmittance of about 90% at the wavelength between 250 and 950 nm. The optical band gaps of 3.25 eV to 3.50 eV were obtained at ZnO concentrations from 0.2 M to 1.0 M. The SEM images depicted a polycrystalline nature of the films with irregular nanoparticle shapes across the substrates. Electrical results established the high conductivity of nitrogen-doped ZnO thin films, thereby making the thin films suitable as transparent conducting oxides for devices such as solar cells and optoelectronics.
On b-acyclic chromatic number of a graph
Authors: Anholcer Marcin , Cichacz Sylwia , Peterin Iztok 
Published: December 2022

AbstractLet G be a graph. We introduce the acyclic b-chromatic number of G as an analogue to the b-chromatic number of G. An acyclic coloring of a graph G is a map $$c:V(G)\rightarrow \{1,\ldots ,k\}$$

c
:
V
(
G
)
→
{
1
,
…
,
k
}

such that $$c(u)\ne c(v)$$

c
(
u
)
≠
c
(
v
)

for any $$uv\in E(G)$$

u
v
∈
E
(
G
)

and the induced subgraph on vertices of any two colors $$i,j\in \{1,\ldots ,k\}$$

i
,
j
∈
{
1
,
…
,
k
}

induces a forest. On the set of all acyclic colorings of G we define a relation whose transitive closure is a strict partial order. The minimum cardinality of its minimal element is then the acyclic chromatic number A(G) of G and the maximum cardinality of its minimal element is the acyclic b-chromatic number $$A_{\textrm{b}}(G)$$

A
b

(
G
)

of G. We present several properties of $$A_{\textrm{b}}(G).$$

A
b

(
G
)

.

In particular, we derive $$A_{\textrm{b}}(G)$$

A
b

(
G
)

for several known graph families, derive some bounds for $$A_{\textrm{b}}(G),$$

A
b

(
G
)

,

compare $$A_{\textrm{b}}(G)$$

A
b

(
G
)

with some other parameters and generalize some influential tools from b-colorings to acyclic b-colorings.
Data-driven Harris Hawks constrained optimization for computationally expensive constrained problems
Authors: Fu Chongbo , Dong Huachao , Wang Peng , Li Yihong 
Published: December 2022

AbstractAiming at the constrained optimization problem where function evaluation is time-consuming, this paper proposed a novel algorithm called data-driven Harris Hawks constrained optimization (DHHCO). In DHHCO, Kriging models are utilized to prospect potentially optimal areas by leveraging computationally expensive historical data during optimization. Three powerful strategies are, respectively, embedded into different phases of conventional Harris Hawks optimization (HHO) to generate diverse candidate sample data for exploiting around the existing sample data and exploring uncharted region. Moreover, a Kriging-based data-driven strategy composed of data-driven population construction and individual selection strategy is presented, which fully mines and utilizes the potential available information in the existing sample data. DHHCO inherits and develops HHO's offspring updating mechanism, and meanwhile exerts the prediction ability of Kriging, reduces the number of expensive function evaluations, and provides new ideas for data-driven constraint optimization. Comprehensive experiments have been conducted on 13 benchmark functions and a real-world expensive optimization problem. The experimental results suggest that the proposed DHHCO can achieve quite competitive performance compared with six representative algorithms and can find the near global optimum with 200 function evaluations for most examples. Moreover, DHHCO is applied to the structural optimization of the internal components of the real underwater vehicle, and the final satisfactory weight reduction effect is more than 18%.
Discrete matrix factorization cross-modal hashing with multi-similarity consistency
Authors: Li Yiru , Hu Peiwen , Li Ying , Peng Shouyong , Zhang Xiaofeng , Yue Jun , Yao Tao 
Published: December 2022

AbstractRecently, matrix factorization-based hashing has gained wide attention because of its strong subspace learning ability and high search efficiency. However, some problems need to be further addressed. First, uniform hash codes can be generated by collective matrix factorization, but they often cause serious loss, degrading the quality of hash codes. Second, most of them preserve the absolute similarity simply in hash codes, failing to capture the inherent semantic affinity among training data. To overcome these obstacles, we propose a Discrete Multi-similarity Consistent Matrix Factorization Hashing (DMCMFH). Specifically, an individual subspace is first learned by matrix factorization and multi-similarity consistency for each modality. Then, the subspaces are aligned by a shared semantic space to generate homogenous hash codes. Finally, an iterative-based discrete optimization scheme is presented to reduce the quantization loss. We conduct quantitative experiments on three datasets, MSCOCO, Mirflickr25K and NUS-WIDE. Compared with supervised baseline methods, DMCMFH achieves increases of $$0.22\%$$

0.22
%

, $$3.00\%$$

3.00
%

and $$0.79\%$$

0.79
%

on the image-query-text tasks for three datasets respectively, and achieves increases of $$0.21\%$$

0.21
%

, $$1.62\%$$

1.62
%

and $$0.50\%$$

0.50
%

on the text-query-image tasks for three datasets respectively.
Robust neural dynamics with adaptive coefficient applied to solve the dynamic matrix square root
Authors: Jiang Chengze , Wu Chaomin , Xiao Xiuchun , Lin Cong 
Published: December 2022

AbstractZeroing neural networks (ZNN) have shown their state-of-the-art performance on dynamic problems. However, ZNNs are vulnerable to perturbations, which causes reliability concerns in these models owing to the potentially severe consequences. Although it has been reported that some models possess enhanced robustness but cost worse convergence speed. In order to address these problems, a robust neural dynamic with an adaptive coefficient (RNDAC) model is proposed, aided by the novel adaptive activation function and robust evolution formula to boost convergence speed and preserve robustness accuracy. In order to validate and analyze the performance of the RNDAC model, it is applied to solve the dynamic matrix square root (DMSR) problem. Related experiment results show that the RNDAC model reliably solves the DMSR question perturbed by various noises. Using the RNDAC model, we are able to reduce the residual error from 10$$^1$$

1

to 10$$^{-4}$$

-
4

with noise perturbed and reached a satisfying and competitive convergence speed, which converges within 3 s.
Stratifying the space of barcodes using Coxeter complexes
Authors: Brück Benjamin , Garin Adélie 
Published: December 2022

AbstractEmbeddings of the space of barcodes in Euclidean spaces are unstable due to the permutation of the bars of a barcode. We use tools from geometric group theory to produce a stratification of the space $${\mathcal {B}}_n$$

B
n

of barcodes with n bars that takes into account these permutations. This gives insights in the combinatorial structure of $${\mathcal {B}}_n$$

B
n

. The top-dimensional strata are indexed by permutations associated to barcodes as defined by Kanari, Garin and Hess. More generally, the strata correspond to marked double cosets of parabolic subgroups of the symmetric group $${\text {Sym}}_{ n }$$

Sym
n

. This subdivides $${\mathcal {B}}_n$$

B
n

into regions that consist of barcodes with the same averages and standard deviations of birth and death times and the same permutation type. We obtain coordinates that form a new invariant of barcodes, extending the one of Kanari–Garin–Hess. This description also gives rise to metrics on $${\mathcal {B}}_n$$

B
n

that coincide with modified versions of the bottleneck and Wasserstein metrics.
A review of supersonic molecular beam injection for plasma fueling and physical studies in magnetic fusion devices
Authors: Xiao G. L. , Zhong W. L. , Duan X. R. , Feng B. B. , Chen C. Y. , Bucalossi J. , Zou X. L. , Hu J. S. , Kwak Jong-Gu , Xiao W. W. , Takenaga H. , Chen Z. Y. , Sun H. J. , Zhang Y. P. , Yin J. , Zhu Y. R. , Tong R. H. , Yu D. L. , Shi Z. B. , Xu M. 
Published: December 2022

AbstractIn magnetic confinement fusion devices, supersonic molecular beam injection (SMBI) is commonly used as a fueling method, which has also performed well in physical studies since it was first proposed on the HL-1 tokamak by Southwestern Institute of Physics. This study presents the development of the SMBI technique since its first use in fusion experimental devices and reviews the progress on the investigation of plasma physics using the SMBI. In addition, this study further discusses the potential applications of the SMBI technique on future fusion devices.
Progress in the development and understanding of a high poloidal-beta tokamak operating scenario for an attractive fusion pilot plant
Authors: Ding Siye , Garofalo Andrea M. 
Published: December 2022

AbstractThe high poloidal-beta ($$\beta _{\textrm{P}}$$

β
P

) regime was first proposed as a high bootstrap current scenario for a steady-state fusion pilot plant (FPP) in the 1990s (Kikuchi in Nucl Fusion 30:265, 1990). Since then, there have been many theoretical, modeling, and experimental research activities on this topic. A joint DIII-D/EAST research team began exploring the high-$$\beta _{\textrm{P}}$$

β
P

regime in 2013, focusing on addressing the needs of attractive FPP design by taking advantage of the extensive diagnostic set and sophisticated plasma control system on DIII-D and the well-developed integrated modeling capability at General Atomics. The ultimate goal is to demonstrate such a scenario on EAST with truly long pulse and metal wall compatibility. This paper summarizes the highlights of the research results on DIII-D by the joint team in the past decade. Experimental evidence and modeling analysis show the high-$$\beta _{\textrm{P}}$$

β
P

scenario has great advantages in addressing key needs for an attractive FPP design, such as high-energy confinement quality at low rotation, excellent core-edge integration, high line-averaged density above the Greenwald limit, low disruption risk, and high bootstrap current fraction for steady-state operation. This provides a relatively safe and economical option to base an FPP design on that will lead to commercial fusion energy.
Sovereignty in the Digital and Contact Tracing Apps
Authors: Tretter Max 
Published: December 2022

AbstractRecently, the concept of sovereignty in the digital has attracted much attention. Several publications dealing with this concept assume that it can best be described as a network of different, overlapping exercises of power. Nevertheless, there is a need for further research on how exactly sovereignty in the digital can be understood. In order to contribute to a better understanding of this concept, I illustrate its complex structure using contact tracing apps as a paradigmatic example. I conduct a narrative review to show what sovereignty looks like in the context of these apps. In the context of digital contact tracing apps, sovereignty is best understood as a complex network of three actors—nations, (big tech) companies, and individuals—that exercise various forms of power against or on behalf of each other to claim sovereignty for themselves and to either weaken or strengthen the sovereignty claims of other actors. Since large parts of the results can be generalized from the particular context of contact tracing apps, they contribute to a better overall understanding of the concept of sovereignty in digital. This might, in turn, be helpful for discussions about this technology as well as about the regulation and governance of the digital in general.
Investor Behavior at the 52-Week High
Authors: Della Vedova Joshua , Grant Andrew , Westerholm P. Joakim 
Published: December 2022

AbstractThis study uncovers how household investors intensify the effect of the 52-week high (52WH): increased volume and momentum-like returns at the 52WH price. Using daily household and institutional trading data, we find that households sharply increase their selling, particularly with limit orders at the 52WH price. This behavior is indicative of anchoring, as it is robust to past returns and intensified by proximity, market uncertainty, and salience of the 52WH. This uninformed limit order selling at and prior to the 52WH leads to a doubling of unconditional 52WH anomaly returns. Post-event returns benefit institutions, which act as counterparties.