bluuebunny/crossref_metadata_2025 huggingface dataset:
Analysis and application of a 3D chaotic system with an extremely extensive range of amplitudes and offset boosting
Authors: Shi Shuaishuai , Lu Hanyu , Du Chuanhong , Zhang Zefeng , Liu Licai
Published: December 2024

The study of high-dimensional chaotic systems has been the subject of considerable research interest, whereas the complex characteristics of low-dimensional chaotic systems have been largely overlooked. A new 3 dimensional (3D) chaotic system containing only two kinds of nonlinear terms is constructed based on the Lorenz system to enrich the theory of chaotic systems and improve the complex properties of low-dimensional chaotic systems. The system lacks a symmetric structure; however, under the influence of the symmetric parameter α, the system attains a symmetric state and can produce attractors with a symmetric structure. Under the parameter β, the system can realize the regulation of amplitude, frequency, and nonlinear offset boosting of three signals simultaneously. The parameter γ can realize the control of two signal amplitude and frequency at the same time. The system always remains chaotic when the parameters β and γ are varied in a great range. In addition, this 3D chaotic system has offset boosting behavior in arbitrary single and multiple directions, and the offset constant has a wide range of values. These features provide great convenience for secure communications and weak signal engineering applications. Further, analog circuit simulations and DSP (Digital Signal Processor) hardware circuits confirm the parametric modulation of the system and the offset boosting behavior in any direction. Moreover, taking advantage of the extensive offset range, a synchronization controller is designed for the drive and response systems. Finally, the modulation of offsets with a wide range of values realizes the encrypted transmission of binary digital information and lays the foundation for future engineering applications.
Non-parametric full cross mapping (NFCM): a highly-stable measure for causal brain network and a pilot application
Authors: Yang Danni , Lin Wentao , Liu Minghui , Zhou Yuanfeng , Wang Yalin
Published: December 2024

Objective. Measuring causal brain network from neurophysiological signals has recently attracted much attention in the field of neuroinformatics. Traditional data-driven algorithms are computationally time-consuming and unstable due to parameter settings. Approach. To resolve these limits, we proposed a novel parameter-free technique, called ‘non-parametric full cross mapping (NFCM)’. The NFCM adapts current convergent cross-mapping concept, and makes two improvements: (1) an improved phase-space reconstruction with constant embedding parameters and (2) cross-mapping estimate of all embedding vectors on manifolds following simplex projection. Main results. Numerical experiments verify that our NFCM has the highest quantization stability even when perturbed by system noise, and its coefficient of variation is almost lower than that of the six baseline methods. The developed NFCM is finally used in stereoelectroencephalogram analysis of drug-resistant epilepsy in children (DREC). A total of 36 seizures, comprising 18 surgical successes and 18 failures, were included to explore the brain network dynamics. The average causal coupling in epileptogenic zones of successful surgery (0.81 ± 0.04) is significantly higher than that in non-epileptogenic zones (0.40 ± 0.03) with

P
<
0.001

via Mann–Whitney-U-test. While there is no significant difference among the 18 failed surgeries. Significance. The causal brain network measured by our NFCM is confirmed as a credible biomarker for localizing epileptogenic zones in DREC. These findings promise to advance precision medicine for DREC.
Reparametrization Invariant Scaling Symmetry and the Value of the Einstein Cosmological Constant ΛE
Authors: Gueorguiev Vesselin G.
Published: December 2024

The nature of Dark Energy (DE) remains an enigma. This work explores the non-zero Einstein Cosmological Constant (Λ
E
) as a manifestation of DE – viewing it through the lens of Reparametrization Invariant Scaling Symmetry (RISS), where Λ
E
is interpreted as a “kinetic energy” term within the energy density. The scale factor λ(t) relevant for cosmic reparametrization removes Λ
E
from the extended Einstein GR, its defining equations, and their relations to Λ
E
are derived. The value for Λ
E
= 1.8 × 10−52 m−2 is consistent with the current observations for Λ
E
. The current approach avoids the puzzles associated with interpreting Λ
E
as vacuum zero-point energy (often called dark energy). Further applications are related to the Dark Matter problem by insisting on a reparametrization symmetry for the equations of motion, where un-proper (non-co-moving) time parametrization gives rise to fictitious forces.
Building Artificial Intelligence, Machine Learning, and Causal Models to Improve Cardiac Health
Authors: Haynatzki Roman , Windle Thomas A , Dai Ran , Horner Ronnie D , McClay James C , Revesz Peter Z , Haynatzki Gleb , Windle John R
Published: December 2024

The prediction of myocardial infarction (MI) outcomes remains pivotal for advancing treatment strategies in cardiology. This study proposes to compare the variable selection efficacy and predictive power of LASSO logistic regression and XGBoost, incorporating a causal mediation approach to elaborate on the underlying mechanisms influencing MI risks. Leveraging the GUSTO-I dataset on MI patients, this research has employed LASSO logistic regression to facilitate variable selection, aiming to identify critical predictors with substantial impacts on MI outcomes. Alternatively, the XGBoost algorithm has been utilized to assess its approach to variable selection and prediction. Both methods have been evaluated based on their Area Under the Receiver Operating Characteristic Curve (AUC) to determine their predictive accuracy. Furthermore, causal mediation analysis has been integrated to explore the putative effects of key predictors, identified in previous studies. The analysis aimed to reveal which method offers superior predictive performance and how well each can be interpreted in a clinical context. This study can contribute valuable insights into the comparative advantages of using LASSO logistic regression versus XGBoost in the field of cardiovascular disease research. By integrating causal mediation analysis, we aim to extend beyond mere prediction to offer a deeper understanding of the causal relationships and mechanisms at play.
Mathematical Modeling of the Operation of a Hydrophoric Installation
Authors: Nikolaev I N , Raeva E R , Mihova V A
Published: December 2024

In this paper, the performance of a pumping system is considered in its operation with a hydrophore vessel connected in parallel. The filling and emptying processes of the hydrophore and their influence on the flow rate to the system and the pump outlet pressure are experimentally investigated. An automated measuring system is used for the measurements of the flow rate and the pressure. That has cyclically recorded the values at equal time intervals. The measurement cycles are synchronized in time and the maximum errors of the measured quantities are known. From the experimental data, empirical relationships are obtained for flow rate and pressure as a function of time, as well as the relationships between the two quantities. The time periods of each of the two processes and the average cycle length are also empirically determined. Confidence intervals of the flow rate are constructed for vessel filling and emptying, respectively, and measurement errors were accounted for. Codes have been created to determine the filling time of a hydrophore vessel and to calculate confidence intervals for this type of pumping systems, thanks to which all calculations have been automated. The described dependencies can be used in planning future experiments.
Asphalt Concrete Mixtures with Coal Bottom Ash as Fine Aggregate Substitution and Crumb Rubber as Asphalt Substitution
Authors: Saleh Sofyan M , Isya M , Darma Yusria , Salmannur Alfi , Ramadhana Fadillah
Published: December 2024

This research conducting the substitution of coal bottom ash and crumb rubber in asphalt concrete wearing course (AC-WC) mixtures. The objective is to help reduce waste materials and obtaining Marshall parameters that meet the requirements for asphalt mixtures. The percentage variations used for the substitution were 6%, 9%, and 12% coal bottom ash and 5%, 8%, and 11% crumb rubber. In Marshall test used varies asphalt content, the optimum asphalt contents (OAC) obtained were 5.85%, 6.03%, and 6.2%. Then, the OAC was used in asphalt concrete mixtures with coal bottom ash as fine aggregate substitution. The best results were obtained at the combination of 6% coal bottom ash and 5.85% asphalt content. Consequently, the combination was used in the mixtures by adding crumb rubber as the substitution of the asphalt. The results shows that the Marshall parameters obtained by all percentages of crumb rubber substitution have fulfilled the requirements with the highest stability of 1928.16 kg. The durability test on asphalt concrete mixtures with 6% coal bottom ash as fine aggregate substitution and 11% crumb rubber as asphalt substitution with 5.85% asphalt content obtained 92.82%, so that the requirement of ≥90% of the Bina Marga 2018 Specifications Revision 2 (2020) have been fulfilled.
Investigating the thermal performance of a subsea liquid piston air compressor pipeline operating at very high pressure ratios
Authors: Cutajar Charise , Sant Tonio , Aquilina Luke
Published: December 2024

Liquid piston air compression is presently gaining significant interest as a means for long duration energy storage at large scale. However, various aspects attributed to the thermal performance of liquid piston air compressors at high operating pressure ratios remain yet unanswered. This paper presents a transient thermal analysis of a novel, subsea liquid piston air compressor pipeline operating at pressure ratios up to 200. A thermal model implementing different empirical correlations for the convective heat transfer phenomena is presented. The study reveals a major knowledge gap in terms of Nusselt number correlations available to define the internal heat transfer coefficients explicit to liquid piston pipelines. Results from a parametric study suggest that the internal heat transfer inside a liquid piston having a very large length-to-diameter ratio was characterised by natural convection effects. Furthermore, it was found that to attain a thermal efficiency higher than 0.90, the power density had to be limited to not more that 0.22 kW/m3, with a compression time required per stroke being at least 25minutes.
CFD Analysis of a Subsea Liquid Piston Accumulator for Energy Storage Applications
Authors: Aquilina Luke , Sant Tonio , Cutajar Charise
Published: December 2024

Hydro-pneumatic energy storage uses liquid pistons and hydraulic machinery to store energy by compressing air. The technology offers significant potential for co-location with offshore wind farms, where the sea water may be used to augment the heat exchange between the air undergoing compression or expansion and the surrounding environment, hence improving the thermal efficiency by operating at isothermal conditions. A major challenge for the numerical simulations to assess the transient thermal behaviour of such a system is the lack of appropriate models for the convective heat transfer coefficients. This paper addresses this knowledge gap through the use of CFD by simulating a subsea accumulator housing a liquid piston compressing the air from atmospheric conditions up to a pressure of 100 Bar. The adopted numerical approach examines the heat exchange between the air undergoing compression and the surrounding sea water, with the internal and external heat transfer coefficients being derived concurrently. It is noted that the internal heat transfer coefficient is significantly dependent on the state of charge of the accumulator. Yet, quasi-isothermal conditions were predicted by the CFD model for the simulated conditions. The paper provides insight about the complexity of the heat transfer phenomena related to subsea liquid pistons and the need to derive correlations specifically for this application.
Correlation Analysis of Vegetation Index Impact on Rice Paddy Productivity Estimation using Landsat-8 and Sentinel-2A Images (Case Study: Blitar District)
Authors: Rizqika Ayu Karina , Muljo Sukojo Bangun , Ayu Retno Mukti Dyah
Published: December 2024

Rice is consumed by most of the population in Indonesia. The generative phase, the final stage of rice growth cycle, produces raw grains that are processed into rice, forming the basis of rice production. To estimate rice paddy productivity in March 2023, vegetation indices such as the Normalized Difference Vegetation Index (NDVI) and the Optimized Soil-Adjusted Vegetation Index (OSAVI) are used. These indices are crucial as they correlate with rice paddy areas in the generative phase. Sentinel-2A imagery calculations have shown strong correlations, with NDVI at R = 0.61 and OSAVI at R = 0.75. The OSAVI index from Sentinel-2A yielded an average productivity estimate of 31.35 ton/ha with an RMSE of 5.7041, while NDVI gave an average of 63.63 ton/ha with an RMSE of 12.3224. In comparison, Landsat-8 imagery estimates using NDVI showed a moderate correlation (R = 0.54), with an average productivity of 20.75 ton/ha and an RMSE of 3.2321. The OSAVI index with Landsat-8 provided an average estimate of 64.27 ton/ha with an RMSE of 12.3338 and a moderate correlation (R = 0.41). The correlation coefficients from Sentinel-2A are higher than those from Landsat-8, indicating that the choice of imagery significantly affects rice productivity estimates.
Mapping LSD Locations by Integrating Land Documents and Spatial Planning in Cepu District
Authors: Asyita Rahmawaty Mitha , Firdaus Wibowo Jatiar , Noor Alina Aldea , Gustin Oktavianto , Warasambi Mispaki Syachril
Published: December 2024

The conversion of agricultural land to non-agricultural land in Cepu Regency presents a challenge for the government to maintain food security and the agricultural sector in a sustainable manner. This research aims to identify and analyze gaps between data on rice fields and land and spatial planning, assess the potential for land conversion, and make recommendations for protected rice fields. Spatial analysis methods using Geographic Information Systems (GIS) and quantitative methods are used to process data and provide appropriate recommendations, taking into account decreasing and increasing factors in identifying rice fields for conservation (LSD). The existing LSD determination has a total area of 2,662 Ha which can be utilized to maintain food security in Blora Regency. The evaluation object is protected rice fields that have the potential for conversion such as subsidized residential land, expansion of the Ngeloram airport and construction of residential houses. Recommendations for LSDs that experience conversion are conditionally permitted to change land use, and permitted to change land use.
A Preliminary Study: Gaussian Splatting Technique in Generating a 3D Model of Textureless Object
Authors: Qoyimah Shofiyatul , Sugiastu Firdaus Hana
Published: December 2024

The traditional static method faces limitations and challenges in reconstructing a 3D model of a real object with a textureless surface, in various environmental lighting conditions. Gaussian Splatting is approached as a superior method to reduce the processing time and draw back those limitations. To assess the visualization and accuracy, a project was designed to create a 3D model of a wooden board and a metal cube under different lighting scenarios using Gaussian Splat Creator & Viewer web-based software. The results show that the model can obviously represent the object’s color, shape, and shadow spot. The additional light source can increase the brightness, and draw different impacts on the models to recognize the fine features on the surface. Furthermore, the translucent effect was exposed on all models, except the wooden board without an additional light source. The models have RMSE less than 6 cm and are categorized as the Level of Detail 4. The highest accuracy was achieved by performing the adjusting scale option, even though a rescaling factor is not defined. Meanwhile, defining the rescale factor and neglecting the scale adjustment process simultaneously, can decrease the accuracy. Last, the 3D reconstruction process of 300 to 400 images takes around 30 to 45 minutes, and the storage size is 1 to 3 Megabytes only.
The Effect of Port Growth on the Safety Index in Madura Strait
Authors: Hardhita DW , Asmara IPS , Widiarti Y
Published: December 2024

This research examines ship safety level in port development through environmental stress method, which involves assessing the safety level in current conditions and simulating the addition of new ports to enhance shipping efficiency. This method evaluates safety levels based on each ship’s COG degree and identifies obstacle characteristics. Analysis results are visualized using the perception safety index matrix. These findings determine the permissible speed tolerance for ships navigating the Madura Strait under current and planned conditions. As per sample, simulation will be using MV PIS Mahakam for this research. The simulation indicates that safety index in the existing condition or scenario X is at a Marginal level, with the highest value being 749. Furthermore, in planned scenario with addition of 2 new ports and combination of 2 ports which called scenario A, B, and C, safety index values are 749 thus all considered marginal. The maximum speed tolerance under planned conditions ranges from 1.5 – 1.6 knots for a 114m ship.
Development of Measurement Tool for Energy Efficiency Operational Indicator (EEOI)
Authors: Prastowo H , Pitana T , Artana K B , Ariana I M , Pramana A T
Published: December 2024

The Energy Efficiency Operational Index (EEOI) is a value that represents the energy efficiency of a ship’s operations in relation to CO2 emissions. Improving energy efficiency is one of the important ways to achieve cleaner shipping. Statistical methods are used to predict a number of parameters that determine the value of the EEOI. The aim of this research is an EEOI measurement tool. The analysis was carried out with 100 container ships. The Ship Traffic Emission Model (STEAM) and Multiple Linear Regression (MLR) methods were used in this research. STEAM modeling is based on estimated fuel oil consumption and MLR generated from STEAM EEOI results. This modeling also considers the following parameters overall length, width, draft, depth, service speed, container capacity, average speed of last trip, average draft of last trip, installed main engine power, and travel time. Furthermore, EEOI measurement tools were created in the Android-based version which represent EEOI values based on the ship’s last trip per voyage.
Development Study of Direct Damage Stability Algorithm Based on 3D Geometry Data Processing for Onboard Loading Instrument
Authors: Andinuari Fajar , Widjaja Sjarief , Nugroho Setyo
Published: December 2024

The maritime world experienced a very significant development such as the process of cargo planning is the existence of a system called loading instrument which is regulated by several regulations from both Classification and IACS. Damage stability calculation is also very important for loading instruments. Currently in Indonesia, there is no known algorithm to calculate direct damage stability from 3D models. And also there is still no loading instrument in Indonesia that applies the algorithm. Therefore, this research aims to develop a direct damage stability calculation algorithm for the development of loading instruments in Indonesia. Direct damage stability uses the lost buoyancy method which is calculated from 3D geometry model directly. The calculation process starts by dividing the ship geometry and compartment with the desired station. In general, the numerical integration used in the calculation process is the Simpson method. Then Newton’s iteration is used to find an equilibrium condition by predetermined conditions. Finally, the calculation results will be compared with the cases of LR Rules and IACS Rules UR L5 as a form of validation. The calculation algorithm can later be applied to the onboard loading software computer needed by the ship for the loading process with damage applications.
Potential carbon stocks of hardwood, softwood, and varied growth rate species in Pasir Hantap Research Forest, Sukabumi, West Java
Authors: Fatimah G , Wasis B , Prameswari D
Published: December 2024

Climate change has become a global phenomenon with signi2icant impacts on the environment. Indonesia has committed to reducing its emissions by 29% by 2030 through domestic efforts and 41% through international cooperation. The forestry sector plays a crucial role, with a potential reduction of 17.2% in emissions. One of the tropical forest areas that has the potential to help store carbon stocks is the Pasir Hantap Research Forest, Sukabumi. Pasir Hantap Research Forest is located in the tropics and is characterized by diverse, naturally occurring and planted vegetation. The forest has varying slopes, ranging from 10° to 45°, which can affect tree growth and biomass. The study will analyze the carbon stock potential of hardwood groups (Shorea sp. mixed), softwood groups (Pinus sp. mixed), fast-growing species groups (Eucalyptus sp. mixed), and slow-growing species groups (Swietenia macrophylla mixed) and examine the in2luence of slope on carbon storage. The overall results of carbon stock estimation in the four groups of stands did not show signi2icantly different results. The highest average carbon stock was in the mixed Swietenia macrophylla group at 423.84 tons/ha, while the lowest average was in the mixed Shorea sp. group at 128.76 tons/ha. The results of carbon stock estimation are negatively correlated with slope. The estimated value of carbon stocks in the mixed Swietenia macrophylla group decreased as the degree of slope increased. Meanwhile, the estimation of carbon stocks in the mixed Pinus group increased as the degree of the slope increased.
Ethnomycology species of mushrooms as food and medicine in Rao-Rao village, Batang Natal district, North Sumatra
Authors: Rambey R , Kembaren Y , Rahmawaty  , Widianti P , Suratman M N , Pardi F , Abdullah M F , Gandaseca S
Published: December 2024

Mushrooms have been used by people for many years, both as food and medicine. The lack of research on ethnomycology has resulted in the threat to local knowledge regarding the use of mushrooms as food, medicine, a source of income, and their sociological impact in Rao-Rao Village, Batang Natal District, North Sumatra. This research explores the uses of mushrooms and traditional knowledge associated with ethnic groups living in Rao-Rao Village. The interview method is used to collect information regarding the use of mushrooms. To determine respondents using a purposive sampling technique. Based on the interviews conducted with the people of Rao-Rao Village, eight mushrooms were found and used as food and medicine. Species of mushrooms used as food include Auricularia auricula-judae, Auricularia delicate, Volvariella volvacea, Schizophyllum commune, Lentinus conatus, and those used as medicine are Coltricia perennis, Geastrum triplex, and Lignosus rhinoceros.
Investigation & analysis of Electrical Discharge Machining on Titanium Diboride Ceramic material with various Electrode materials and dielectric fluids
Authors: S Karthik , Annamalai Sivakumar
Published: December 2024

Titanium Diboride is a highly used material in aerospace industry due of its remarkable longevity. Its strength poses a problem to traditional machining methods. This work aims to compare two different dielectric fluids and four different electrode materials to improve EDM process parameters in TiB2 material. The input parameters were adjusted to find the optimal combination. By studying the fluctuations of output parameters such as MRR, TWR, SR and overcut when processing titanium diboride, researchers can gain valuable insights. This is achieved through experimental studies and the results are then verified using a theoretical regression model. Experimental results confirmed that discharge current, voltage and Ton had a remarkable influence on MRR, TWR and surface roughness in TiB2 material. It has been observed that tool wear rate when using kerosene-based dielectric fluids is higher than that of deionized water-based dielectric fluids. Tungsten copper electrodes cause slightly less tool wear than tungsten electrodes, and produce higher MRR overall, when compared to other three electrode materials. Using deionized water as a dielectric fluid and a copper as an electrode material can help to obtain a smoother surface. When deionized water is used as a dielectric fluid with tungsten electrodes, the overcut value drops dramatically. Brass electrodes produce a higher overcut value compared to the other three electrode materials. The microstructure of the EDM hole was distinguished by SEM analysis, and the material composition of TIB2 was determined by EDS analysis.
Spatial-temporal analysis of carbon benefit and land use for low-carbon development strategies in Shandong Province, China
Authors: Wen Hui , Zhong Ziyu , Kong Xujie , Wang Jichun , Li Renqiang , Wang Zhaosheng , Yu Shulin , Xu Zhen , Chen Hexin , Zhu Qi , Wang Pan , Duan Jiaquan , Ren Yan
Published: December 2024

Assessing the carbon sequestration capacity of regional ecosystems is essential for achieving carbon neutrality goals. However, existing research often fails to comprehensively evaluate the spatial-temporal dynamic changes of ecosystem carbon emission and absorption. This study introduces a Carbon Benefit Index (CBI) to assess carbon neutrality potential and classifies Shandong’s 16 cities into four regions based on their carbon storage and emission profiles. We conducted an in-depth analysis of ecosystem carbon benefit in Shandong Province from 2000 to 2020 using the multimodel random forest ensemble method, which enhances the accuracy of carbon sink simulations across terrestrial ecosystems. Our results showed that from 2000 to 2020, Shandong’s carbon emission increased by 1.45 × 108 tons (a 203.8% rise), while carbon storage decreased by 3.40 × 107 tons (a 2.05% decline). Compared to previous studies, our findings underscore the significance of both above-ground and below-ground carbon storage. Grey correlation analysis of land use, anthropogenic CO2 emission, and ecosystem carbon storage revealed that cultivated and forest lands were most significantly correlated with carbon storage, whereas built-up areas were most closely linked to carbon emission. The CBI analysis and classification of the 16 cities into four categories highlights the spatial-temporal heterogeneous of the carbon efficiency, and diverse roles cities play in the province’s overall carbon balance, informing city-specific, targeted carbon reduction strategies. The study emphasizes the need for spatially differentiated, comprehensive carbon accounting to improve carbon efficiency. Based on these findings, we propose tailored low-carbon improvement strategies for different regions. This research not only contributes to existing literature by incorporating below-ground carbon storage but also provides valuable insights for policy and land management, with practical implications for promoting sustainable development and advancing efforts toward carbon neutrality.
A unified differential equation solver approach for separable convex optimization: Splitting, acceleration and nonergodic rate
Authors: Luo Hao , Zhang Zihang
Published: December 2024

This paper provides a self-contained ordinary differential equation solver approach for separable convex optimization problems. A novel primal-dual dynamical system with built-in time rescaling factors is introduced, and the exponential decay of a tailored Lyapunov function is established. Then several time discretizations of the continuous model are considered and analyzed via a unified discrete Lyapunov function. Moreover, two families of accelerated primal-dual methods are obtained, and nonergodic optimal mixed-type convergence rates shall be proved for the primal objective residual, the feasibility violation and the Lagrangian gap. Finally, numerical experiments are provided to validate the practical performances of the proposed methods.
Sobolev regularity of the Bergman and Szegö projections in terms of \overline{∂}⊕\overline{∂}* and \overline{∂}_{𝑏}⊕\overline{∂}_{𝑏}*
Authors: Straube Emil
Published: December 2024

Let

Ω
\Omega

be a smooth bounded pseudoconvex domain in

C

n

\mathbb {C}^{n}

. It is shown that for

0
≤
q
≤
n

0\leq q\leq n

,

s
≥
0

s\geq 0

, the embedding
<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" alttext="j Subscript q Baseline colon d o m left-parenthesis ModifyingAbove partial-differential With bar right-parenthesis intersection d o m left-parenthesis ModifyingAbove partial-differential With bar Superscript asterisk Baseline right-parenthesis right-arrow with hook upper L Subscript left-parenthesis 0 comma q right-parenthesis Superscript 2 Baseline left-parenthesis normal upper Omega right-parenthesis">

j

q

:
d
o
m
(

∂
¯

)
∩
d
o
m
(

∂
¯

∗

)
↪

L

(
0
,
q
)

2

(
Ω
)

j_{q}: dom(\overline {\partial })\cap dom(\overline {\partial }^{*}) \hookrightarrow L^{2}_{(0,q)}(\Omega )

is continuous in

W

s

(
Ω
)

W^{s}(\Omega )

-norms if and only if the Bergman projection

P

q

P_{q}

is (see below for the modification needed for

j

0

j_{0}

). The analogous result for the operators on the boundary is also proved (for

n
≥
3

n\geq 3

). In particular,

j

1

j_{1}

is always regular in Sobolev norms in

C

2

\mathbb {C}^{2}

, notwithstanding the fact that

N

1

N_{1}

need not be.
Associations of hearing and visual loss with cognitive decline and dementia risk: a 25-year follow-up of the Maastricht Aging Study
Authors: Soons Lion M , Deckers Kay , Tange Huibert , van Boxtel Martin P J , Köhler Sebastian
Published: December 2024

Background

Hearing loss (HL) and visual loss (VL) are recently identified as promising dementia risk factors, but long-term studies with adequate control of other modifiable dementia risk factors are lacking. This 25-year follow-up study investigated the association between objectively measured HL and VL with cognitive decline and incident dementia.

Methods

1823 participants (age 24–82 years) of the Maastricht Aging Study were assessed at baseline, 6, 12 and 25 years. Baseline HL was defined as pure-tone hearing loss ≥20 dB at frequencies of 1, 2 and 4 kHz and VL as binocular, corrected visual acuity <0.5. Associations with cognitive decline (verbal memory, information processing speed, executive function) and incident dementia were tested using linear mixed models and Cox proportional hazard models, respectively. Analyses were adjusted for demographics and 11 modifiable dementia risk factors (LIfestyle for BRAin health index).

Results

Participants with HL (n = 520, 28.7%) showed faster decline in all cognitive domains than participants without HL. No consistent association was found for VL (n = 58, 3.2%), but below-average visual acuity (<1) showed significant associations with information processing speed and executive function. No significant associations with dementia risk were found. Findings were independent of demographics and modifiable dementia risk factors.

Conclusions

HL predicts faster cognitive decline but not dementia risk in adults aged 24–82 years. VL shows no consistent associations, though below-average visual acuity is linked to faster cognitive decline. This study supports HL as an independent risk factor for cognitive decline. Future studies should further evaluate the roles of HL and VL in dementia risk reduction.
Silica exposure controls usage in masonry and concrete trades: before and after enactment of the OSHA Silica Construction Rule (1926.1153)
Authors: Dickerson Deborah E , Goldberg Ari Joseph
Published: December 2024

Introduction

In 2017, The Occupational Safety and Health Administration (OSHA) Construction Industry Respirable Crystalline Silica rule (1926.1153) became effective. This regulation stipulates silica exposure control methods to be used in specific construction tasks (1926.1153 Table 1). The present study examined the impact of the regulation on usage of control methods. Reported are findings from 2 surveys of concrete and masonry contractors conducted 3 years prior to, and 3 years following, the OSHA rule.

Method

In 2014 and 2021, a telephone survey was conducted of the following trade associations: the Mason Contractors Association of America (n = 700), the Concrete Sawing and Drilling Association (n = 541), and the American Concrete Pavement Association (n = 450). Collected were frequency of use of the following dust mitigation strategies: stationary masonry saw wet methods, stationary masonry saw dust capture, handheld saw wet methods, handheld saw dust capture, fiber-cement saw dust capture, walk-behind saws wet methods, walk-behind saws dust capture, impact and rotary hammer drills dust capture, jack hammer wet methods, jack hammer dust capture, handheld grinder dust capture, floor grinder wet method, floor grinder dust capture, and sweeping compound. The 5-point Likert-scale data were analyzed via the Welch’s t-test. Open-ended questions about benefits, barriers, and motivations for using dust mitigation methods were analyzed via Content Analysis.

Results

Significant increases in usage were found across many control methods. Highly significant increases in frequency of use were found for handheld saw dust capture, fiber-cement dust capture, handheld grinder dust capture, and impact and rotary hammer dust capture.

Conclusion

Overall, the study provides evidence that the OSHA rule has been effective in effecting change in these silica-exposing trades.
Heterogeneous graph contrastive learning with gradient balance for drug repositioning
Authors: Cui Hai , Duan Meiyu , Bi Haijia , Li Xiaobo , Hou Xiaodi , Zhang Yijia
Published: December 2024

Drug repositioning, which involves identifying new therapeutic indications for approved drugs, is pivotal in accelerating drug discovery. Recently, to mitigate the effect of label sparsity on inferring potential drug–disease associations (DDAs), graph contrastive learning (GCL) has emerged as a promising paradigm to supplement high-quality self-supervised signals through designing auxiliary tasks, then transfer shareable knowledge to main task, i.e. DDA prediction. However, existing approaches still encounter two limitations. The first is how to generate augmented views for fully capturing higher-order interaction semantics. The second is the optimization imbalance issue between auxiliary and main tasks. In this paper, we propose a novel heterogeneous Graph Contrastive learning method with Gradient Balance for DDA prediction, namely GCGB. To handle the first challenge, a fusion view is introduced to integrate both semantic views (drug and disease similarity networks) and interaction view (heterogeneous biomedical network). Next, inter-view contrastive learning auxiliary tasks are designed to contrast the fusion view with semantic and interaction views, respectively. For the second challenge, we adaptively adjust the gradient of GCL auxiliary tasks from the perspective of gradient direction and magnitude for better guiding parameter update toward main task. Extensive experiments conducted on three benchmarks under 10-fold cross-validation demonstrate the model effectiveness.
MORE: a multi-omics data-driven hypergraph integration network for biomedical data classification and biomarker identification
Authors: Wang Yuhan , Wang Zhikang , Yu Xuan , Wang Xiaoyu , Song Jiangning , Yu Dong-Jun , Ge Fang
Published: December 2024

High-throughput sequencing methods have brought about a huge change in omics-based biomedical study. Integrating various omics data is possibly useful for identifying some correlations across data modalities, thus improving our understanding of the underlying biological mechanisms and complexity. Nevertheless, most existing graph-based feature extraction methods overlook the complementary information and correlations across modalities. Moreover, these methods tend to treat the features of each omics modality equally, which contradicts current biological principles. To solve these challenges, we introduce a novel approach for integrating multi-omics data termed Multi-Omics hypeRgraph integration nEtwork (MORE). MORE initially constructs a comprehensive hyperedge group by extensively investigating the informative correlations within and across modalities. Subsequently, the multi-omics hypergraph encoding module is employed to learn the enriched omics-specific information. Afterward, the multi-omics self-attention mechanism is then utilized to adaptatively aggregate valuable correlations across modalities for representation learning and making the final prediction. We assess MORE’s performance on datasets characterized by message RNA (mRNA) expression, Deoxyribonucleic Acid (DNA) methylation, and microRNA (miRNA) expression for Alzheimer’s disease, invasive breast carcinoma, and glioblastoma. The results from three classification tasks highlight the competitive advantage of MORE in contrast with current state-of-the-art (SOTA) methods. Moreover, the results also show that MORE has the capability to identify a greater variety of disease-related biomarkers compared to existing methods, highlighting its advantages in biomedical data mining and interpretation. Overall, MORE can be investigated as a valuable tool for facilitating multi-omics analysis and novel biomarker discovery. Our code and data can be publicly accessed at https://github.com/Wangyuhanxx/MORE.
CryptoBench: cryptic protein–ligand binding sites dataset and benchmark
Authors: Škrhák Vít , Novotný Marian , Feidakis Christos P , Krivák Radoslav , Hoksza David
Published: December 2024

Motivation

Structure-based methods for detecting protein–ligand binding sites play a crucial role in various domains, from fundamental research to biomedical applications. However, current prediction methodologies often rely on holo (ligand-bound) protein conformations for training and evaluation, overlooking the significance of the apo (ligand-free) states. This oversight is particularly problematic in the case of cryptic binding sites (CBSs) where holo-based assessment yields unrealistic performance expectations.

Results

To advance the development in this domain, we introduce CryptoBench, a benchmark dataset tailored for training and evaluating novel CBS prediction methodologies. CryptoBench is constructed upon a large collection of apo–holo protein pairs, grouped by UniProtID, clustered by sequence identity, and filtered to contain only structures with substantial structural change in the binding site. CryptoBench comprises 1107 structures with predefined cross-validation splits, making it the most extensive CBS dataset to date. To establish a performance baseline, we measured the predictive power of sequence- and structure-based CBS residue prediction methods using the benchmark. We selected PocketMiner as the state-of-the-art representative of the structure-based methods for CBS detection, and P2Rank, a widely-used structure-based method for general binding site prediction that is not specifically tailored for cryptic sites. For sequence-based approaches, we trained a neural network to classify binding residues using protein language model embeddings. Our sequence-based approach outperformed PocketMiner and P2Rank across key metrics, including area under the curve, area under the precision-recall curve, Matthew’s correlation coefficient, and F1 scores. These results provide baseline benchmark results for future CBS and potentially also non-CBS prediction endeavors, leveraging CryptoBench as the foundational platform for further advancements in the field.

Availability and implementation

The CryptoBench dataset, including the benchmark model, is available on Open Science Framework—https://osf.io/pz4a9/. The code and tutorial are available at the GitHub repository—https://github.com/skrhakv/CryptoBench/.
Prevalence of two endosymbionts in range-expanding Zodarion spiders (Araneae: Zodariidae)
Authors: Viel Nathan , Wijacki Tamara , Pétillon Julien , Pekár Stano
Published: December 2024

Major changes in species geographical ranges are usually explained by climatic changes or human activities. Intrinsic causes, such as endosymbiotic agents, have not yet been considered thoroughly, despite their potential to affect profoundly the biology of organisms such as arthropods and their aim to maximize their own transmission, e.g. by altering the dispersal abilities of their host. Here, we describe on a large scale the prevalence of two widespread endosymbionts, Wolbachia and Cardinium, in the rapidly range-expanding spider Zodarion rubidumSimon, 1914. Using standard PCR, we screened for the presence of both endosymbionts in specimens collected from 40 populations across Europe. We interpolated the prevalence of the endosymbionts over the study area using ordinary kriging, looking for spatial patterns corresponding to the putative expansion pathway of Z. rubidum. We found that both endosymbionts are widely present throughout Z. rubidum populations, with Wolbachia showing low prevalences with a few patches of high incidence, and with Cardinium being almost at fixation across the study area. Furthermore, in seven additional Zodarion species we investigated the relationship between the prevalence of endosymbionts and spider geographical ranges. We failed to find any significant relationship between these two parameters. We discuss possible explanations for such wide endosymbiont distributions and question their potential impact on Zodarion populations.
Can brain network connectivity facilitate the clinical development of disease-modifying anti-Alzheimer drugs?
Authors: Pini Lorenzo , Lista Simone , Griffa Alessandra , Allali Gilles , Imbimbo Bruno P
Published: December 2024

The preclinical phase of Alzheimer’s disease represents a crucial time window for therapeutic intervention but requires the identification of clinically relevant biomarkers that are sensitive to the effects of disease-modifying drugs. Amyloid peptide and tau proteins, the main histological hallmarks of Alzheimer’s disease, have been widely used as biomarkers of anti-amyloid and anti-tau drugs. However, these biomarkers do not fully capture the multiple biological pathways of the brain. Indeed, robust amyloid-target engagement by anti-amyloid monoclonal antibodies has recently translated into modest cognitive and clinical benefits in Alzheimer’s disease patients, albeit with potentially life-threatening side effects. Moreover, targeting the tau pathway has yet to result in any positive clinical outcomes. Findings from computational neuroscience have demonstrated that brain regions do not work in isolation but are interconnected within complex network structures. Brain connectivity studies suggest that misfolded proteins can spread through these connections, leading to the hypothesis that Alzheimer’s disease is a pathology of network disconnectivity. Based on these assumptions, here we discuss how incorporating brain connectivity outcomes could better capture global brain functionality and, in conjunction with traditional Alzheimer’s disease biomarkers, could facilitate the clinical development of new disease-modifying anti-Alzheimer’s disease drugs.
Investigation of crack initiation during the burst test of hydrogen storage composite overwrapped pressure vessels
Authors: Liu Changchen , Ouyang Zhihui , Yu Jiexiang , Ma Li
Published: December 2024

Hydrogen storage composite overwrapped pressure vessels (COPVs), as a core component of fuel cells, are widely used in the new energy vehicles and other fields. However, the service performance of COPVs, especially the burst pressure, has a great dispersion, which may come from the microscopic defects inside the vessels. In this paper, the industrial computed tomography scan was carried out on a type III hydrogen storage COPV with an aluminum alloy liner and a carbon fiber wound layer, and it was found that many delamination defects with random sizes and locations exist inside the fiber wound layer. Among these defects, there are 164 delamination defects with an area of <500 mm2 (accounting for 87.7% of the total number of defects), but the area of the defects only comprises 19.14% of the entire defects area. Delamination defects were the predominant type of manufacturing defect in the fiber wound layer of COPVs. Then the burst test of the COPV was carried out, which showed that the aggregated area of large-sized delamination defects located in the composite layer of the cylindrical part triggered the crack initiation during the burst test. Thus, in turn, directly affected both the burst pressure and the post-burst morphology. Finally, a 3D equivalent model of the laminated structure is proposed to model the expansion of the composite cylinder. By carrying out a finite element simulation of the COPV, the most dangerous area during the loading process of the COPV is confirmed. The experimentally measured burst pressure of the cylinder is 115.5 MPa, which deviates by 18.6% from the pristine model prediction and by 9.09% from the model with delamination defects.
School Social Work and Mental Health Funding
Authors: Kelly Caroline H
Published: December 2024

School social workers provide mental health services to millions of students each year. However, few studies focus on how social workers generate funding and other support for school mental health. The purpose of this study is to identify the continuum of school mental health supports and how social workers advocate for and generate these supports. This study examines variation in school social worker experiences across three school types: Chicago neighborhood schools, Chicago charter schools, and Chicago-area suburban schools. This study uses the ecological systems framework to structure the interview guide and inform coding. This study finds three major themes: (1) schools improve student access to mental health services, (2) social workers advocate for mental health supports differently depending on their school type, and (3) schools sideline social workers through inadequate support of their positions. Findings suggest greater support for school social work positions and greater collaboration between administrators and school social workers to fully leverage available resources and meet student mental health needs.