bluuebunny/crossref_metadata_2025_split huggingface dataset:
On the ability of standard and brain-constrained deep neural networks to support cognitive superposition: a position paper
Authors: Garagnani Max 
Published: February 2024

AbstractThe ability to coactivate (or “superpose”) multiple conceptual representations is a fundamental function that we constantly rely upon; this is crucial in complex cognitive tasks requiring multi-item working memory, such as mental arithmetic, abstract reasoning, and language comprehension. As such, an artificial system aspiring to implement any of these aspects of general intelligence should be able to support this operation. I argue here that standard, feed-forward deep neural networks (DNNs) are unable to implement this function, whereas an alternative, fully brain-constrained class of neural architectures spontaneously exhibits it. On the basis of novel simulations, this proof-of-concept article shows that deep, brain-like networks trained with biologically realistic Hebbian learning mechanisms display the spontaneous emergence of internal circuits (cell assemblies) having features that make them natural candidates for supporting superposition. Building on previous computational modelling results, I also argue that, and offer an explanation as to why, in contrast, modern DNNs trained with gradient descent are generally unable to co-activate their internal representations. While deep brain-constrained neural architectures spontaneously develop the ability to support superposition as a result of (1) neurophysiologically accurate learning and (2) cortically realistic between-area connections, backpropagation-trained DNNs appear to be unsuited to implement this basic cognitive operation, arguably necessary for abstract thinking and general intelligence. The implications of this observation are briefly discussed in the larger context of existing and future artificial intelligence systems and neuro-realistic computational models.
Exploration of optimal control based surrogate modeling as a basis for fuel efficient 4D aircraft routing on graphs
Authors: Schweighofer Felix , Grüter Benedikt , Holzapfel Florian 
Published: February 2024

AbstractFuel efficient coordination of aircraft operations in the Terminal Maneuvering Area of large airports can contribute to the reduction of the environmental impact of air traffic. To exploit the full potential of the air traffic system, coordinated routing in the Terminal Maneuvering Area, runway assignment and scheduling need to be optimized considering detailed models of the aircraft dynamics and performance. Due to the inhomogeneous nature and level of detail of these combined discrete and continuous decision problems, the optimization of the overall operations poses significant challenges. As part of an integrated approach to the solution of this hybrid problem, this work explores the generation of surrogate models for the fuel consumption of individual aircraft using optimal control methods to exploit the physical capability of the aircraft within an operationally permissible envelope. The surrogate models approximate the predicted fuel consumption of a given point-mass aircraft model on short generic trajectory segments. The trade-off between flight duration and fuel consumption on such segments is analyzed, focusing on the influences of initial aircraft mass, altitude, distance, mean climb angle, along-track wind velocity and linear wind shear. An extensive description of the optimal control-based data generation and surrogate modeling methodology is followed by a discussion of the effects of parameter variation. Based on an illustrative case study, the applicability of the approach is critically analyzed.
Characterization of Chilean hot spring-origin Staphylococcus sp. BSP3 produced exopolysaccharide as biological additive
Authors: Banerjee Srijan , Cabrera-Barjas Gustavo , Tapia Jaime , Fabi João Paulo , Delattre Cedric , Banerjee Aparna 
Published: February 2024

AbstractA type of high molecular weight bioactive polymers called exopolysaccharides (EPS) are produced by thermophiles, the extremophilic microbes that thrive in acidic environmental conditions of hot springs with excessively warm temperatures. Over time, EPS became important as natural biotechnological additives because of their noncytotoxic, emulsifying, antioxidant, or immunostimulant activities. In this article, we unravelled a new EPS produced by Staphylococcus sp. BSP3 from an acidic (pH 6.03) San Pedro hot spring (38.1 °C) located in the central Andean mountains in Chile. Several physicochemical techniques were performed to characterize the EPS structure including Scanning electron microscopy–energy dispersive X-ray spectroscopy (SEM–EDS), Atomic Force Microscopy (AFM), High-Performance Liquid Chromatography (HPLC), Gel permeation chromatography (GPC), Fourier Transform Infrared Spectroscopy (FTIR), 1D Nuclear Magnetic Resonance (NMR), and Thermogravimetric analysis (TGA). It was confirmed that the amorphous surface of the BSP3 EPS, composed of rough pillar-like nanostructures, is evenly distributed. The main EPS monosaccharide constituents were mannose (72%), glucose (24%) and galactose (4%). Also, it is a medium molecular weight (43.7 kDa) heteropolysaccharide. NMR spectroscopy demonstrated the presence of a [→ 6)-⍺-d-Manp-(1 → 6)-⍺-d-Manp-(1 →] backbone 2-O substituted with 1-⍺-d-Manp. A high thermal stability of EPS (287 °C) was confirmed by TGA analysis. Emulsification, antioxidant, flocculation, water-holding (WHC), and oil-holding (OHC) capacities are   also studied for biotechnological industry applications. The results demonstrated that BSP3 EPS could be used as a biodegradable material for different purposes, like flocculation and natural additives in product formulation.
Graphical Abstract
Prediction of CBR by Deep Artificial Neural Networks with Hyperparameter Optimization by Simulated Annealing
Authors: Yabi Crespin Prudence , Agongbe Sètondji Wadoscky , Koto Tamou Bio Chéïssou , Noroozinejad Farsangi Ehsan , Alamou Eric , Gibigaye Mohamed 
Published: February 2024

AbstractThe construction of pavements requires the complete identification of the soils in place and of the added materials. This identification consists in determining the class of the soils and in evaluating their bearing capacity through the California bearing ratio (CBR) index. Obtaining the CBR index is very costly in terms of time and financial resources, especially when it is a large-scale project. It thus leaves prospects of obtaining it by simpler processes; hence, it arises the need to find simpler processes compared to classical processes. This study develops models for predicting the CBR index from physical properties that are less complex to obtain, based on deep neural networks. To achieve this, three databases were used. A first database consists of the proportion of fines, the Atterberg limits and the Proctor references of the soils. A second database uses the methylene blue value instead of the Atterberg limits, and a third database uses only the proportion of fines and the Proctor soil reference. On each of the databases, a deep neural network model was developed using dense layers, regularization layers, residual blocks and parallelization in TensorFlow to predict the CBR value. Each model was formed by combining several deep neural networks developed according to specific architectures. To expedite training, the simulated annealing method was employed to optimize hyperparameters and define the optimal configuration for each network. The predictions obtained are correlated with the true values from 83.6 to 96.5%. In terms of performance, the models have a mean deviation ranging from 3.74 to 5.96%, a maximum deviation ranging from 12.43 to 16.2% and a squared deviation ranging from 0.781 to 2.189. The results suggest that the variable VBS has a negative impact on the accuracy of the networks in predicting the CBR index. The developed models respect the confidence threshold (± 10%) and can be used to set up a local or regional geotechnical platform.
Valuing patient perspectives in the context of eating disorders
Authors: Jaiprakash Harshita H. , MacKinnon Amy , Arnaud Sarah , Neal Jacob P. 
Published: February 2024

Abstract
Purpose
This paper advocates for the inclusion of patient perspectives in the diagnosis and treatment of eating disorders (EDs) for ethical, epistemological, and pragmatic reasons. We build upon the ideas of a recent editorial published in this journal. Using EDs as their example, the authors argue against dominant DSM-oriented approaches in favor of an increased focus on understanding patients’ subjective experiences. We argue that their analysis stops too soon for the development of practical—and actionable—insights into how to effect the integration of first-person and third-person accounts of EDs.

Methods
Contextual analysis was used to make the case for patient perspectives.

Results
We use anorexia nervosa (AN) as an example to demonstrate how the integration of patient manifestations and voices offers a promising methodology to improve patient diagnosis and treatment. We suggest that Acceptance and Commitment Therapy (ACT) can support patients with AN by reconciling their values with the values that arise from a clinician’s duty of care.

Conclusions
We conclude that there are no good scientific reasons to exclude first-person perspectives of EDs in psychiatry.
Level of evidence: Level V: Opinions based on clinical experience.
A particle finite element method approach to model shear cutting of high-strength steel sheets
Authors: Sandin Olle , Rodríguez Juan Manuel , Larour Patrick , Parareda Sergi , Frómeta David , Hammarberg Samuel , Kajberg Jörgen , Casellas Daniel 
Published: February 2024

AbstractShear cutting introduces residual strains, notches and cracks, which negatively affects edge-formability. This is especially relevant for forming of high-strength sheets, where edge-cracking is a serious industrial problem. Numerical modelling of the shear cutting process can aid the understanding of the sheared edge damage and help preventing edge-cracking. However, modelling of the shear cutting process requires robust and accurate numerical tools that handle plasticity, large deformation and ductile failure. The use of conventional finite element methods (FEM) may give rise to distorted elements or loss of accuracy during re-meshing schemes, while mesh-free methods have tendencies of tensile instability or excessive computational cost. In this article, the authors propose the particle finite element method (PFEM) for modelling the shear cutting process of high-strength steel sheets, acquiring high accuracy results and overcoming the stated challenges associated with FEM. The article describe the implementation of a mixed axisymmetric formulation, with the novelty of adding a ductile damage- and failure model to account for material fracture in the shear-cutting process. The PFEM shear-cutting model was validated against experiments using varying process parameters to ensure the predictive capacity of the model. Likewise, a thorough sensitivity analysis of the numerical implementation was conducted. The results show that the PFEM model is able to predict the process forces and cut edge shapes over a wide range of cutting clearances, while efficiently handling the numerical challenges involved with large material deformation. It is thus concluded that the PFEM implementation is an accurate predictive tool for sheared edge damage assessment.
Different tumor growth pattern of clinically nonfunctioning pituitary neuroendocrine tumor according to sex and age: a longitudinal study
Authors: Park S. S. , Kang H. , Kim Y. H. , Kim J. H. 
Published: February 2024

Abstract
Purpose
Asymptomatic patients with clinically non-functional pituitary neuroendocrine tumors (CNF-PitNETs) are usually followed up. However, the natural course of CNF-PitNETs according to sex and age remains unclear. Therefore, this study assessed growth patterns of CNF-PitNETs according to sex and age.

Methods
In this longitudinal study, we enrolled 431 consecutive patients with CNF-PitNETs who were treated at Seoul National University Hospital from 1997 to 2021. The patients underwent hormone function testing and visual field testing, and were subsequently followed up with imaging over a median duration of 66 months.

Results
The median age of the patients was 53.0 years, and 37.1% (n = 160) were men. Men were older and harbored more macroadenomas than women. The annual tumor volume change was higher in men than in women (0.21 vs. 0.04 cm3/year, P < 0.001). The estimated cutoff value of age for significant tumor growth was 51 years. In men, the annual tumor volume change was similar across all age groups. In women, those aged ≤ 50 years showed significantly lower annual tumor volume change than those aged > 50 years (0.01, 0.11, and 0.17 cm3/year, P = 0.001). When comparing sexes within the same age group, the annual tumor volume changes was significantly lower for women than for men, only in patients aged ≤ 50 years (0.01 vs. 0.15 cm3/year, P < 0.001).

Conclusions
Among patients with CNF-PitNET, tumor growth was slower in women aged ≤ 50 years than in men and women aged > 50. These findings may guide the customization of surveillance strategies for CNF-PitNETs according to sex and age.
Muskuloskeletale Beschwerden und Lebensqualität bei Entsorgern von Sperrmüll
Authors: Velasco Garrido Marcial , Kraft Alexander , Harth Volker , Preisser Alexandra M. 
Published: February 2024

ZusammenfassungDie Tätigkeit der Sperrmüllentsorgung ist immer mit der manuellen Handhabung von Lasten verbunden, die mit einem hohen Risiko für Überbeanspruchung des muskuloskeletalen Systems einhergehen können. Ziel der vorliegenden Studie war, die Prävalenz von muskuloskeletalen Beschwerden sowie mögliche Zusammenhänge mit der Lebensqualität unter Sperrmüllentsorgern zu untersuchen. Es wurde zwischen Juni und Oktober 2018 eine Fragebogenerhebung durchgeführt. Die 12-Monats-Prävalenz von Rückenschmerzen und von weiteren muskuloskeletalen Beschwerden wurden mit Instrumenten des Robert Koch Instituts (RKI) (entsprechend des Gesundheitssurvey 2003, DEGS) erhoben. Die gesundheitsbezogene Lebensqualität wurde mit dem EQ-5D-Instrument der EuroQol-Gruppe erhoben. Die Gesamt-Lebensqualität wurde mit dem WHOQOL-Bref erfasst (Werte 0–100). Es nahmen 56 Männer an der Befragung teil (Rücklaufquote 53 %; Alter 46,2 ± 10,9 Jahre). Die 12-Monats-Prävalenz von Rückenschmerzen von jeder Dauer und Stärke lag bei 70,4 %, für Schulterbeschwerden bei 67,3 % und für Kniebeschwerden bei 63,6 %. Die 12-Monats-Prävalenz von chronischen Rückenschmerzen (Dauer ≥ 3 Monate) wurde mit 25 % ermittelt, die Lebenszeitprävalenz von chronischen Rückenschmerzen mit 29,6 %. Jeweils 20,3 % wiesen eine gesundheitsbezogene Lebensqualität ohne Einschränkungen oder mit leichten Einschränkungen in der Dimension „Schmerzen“ auf. In der visuellen Analogskala (VAS) wurde die gesundheitsbezogene Lebensqualität mit 75,4 ± 15,6 Punkten bewertet. Die globale Lebensqualität erreichte den Wert 60,5 ± 21,9. Die gesundheitsbezogene und die globale Lebensqualität der Sperrmüllentsorger mit chronischen Rückenschmerzen waren niedriger als im Durchschnitt. Im Vergleich zu den Ergebnissen von Bevölkerungssurveys (z. B. BURDEN-Studie) weisen die Sperrmüllentsorger höhere Prävalenzen von muskuloskeletalen Beschwerden sowie geringere Lebensqualitätsscores auf. Angesichts der hohen ergonomischen Belastungen der Tätigkeit besteht Interventionsbedarf zur Reduktion der muskuloskeletalen Beanspruchung.
Influence of water coupling coefficient on the blasting effect of red sandstone specimens
Authors: Li Yang , Yang Renshu , Wang Yanbing , Fu Dairui 
Published: February 2024

AbstractThis study investigates the impact of different water coupling coefficients on the blasting effect of red sandstone. The analysis is based on the theories of detonation wave and elastic wave, focusing on the variation in wall pressure of the blasting holes. Using DDNP explosive as the explosive load, blasting tests were conducted on red sandstone specimens with four different water coupling coefficients: 1.20, 1.33, 1.50, and 2.00. The study examines the morphologies of the rock specimens after blasting under these different water coupling coefficients. Additionally, the fractal dimensions of the surface cracks resulting from the blasting were calculated to provide a quantitative evaluation of the extent of rock damage. CT scanning and 3D reconstruction were performed on the post-blasting specimens to visually depict the extent of damage and fractures within the rock. Additionally, the volume fractal dimension and damage degree of the post-blasting specimens are calculated. The findings are then combined with numerical simulation to facilitate auxiliary analysis. The results demonstrate that an increase in the water coupling coefficient leads to a reduction in the peak pressure on the hole wall and the crushing zone, enabling more of the explosion energy to be utilized for crack propagation following the explosion. The specimens exhibited distinct failure patterns, resulting in corresponding changes in fractal dimensions. The simulated pore wall pressure–time curve validated the derived theoretical results, whereas the stress cloud map and explosion energy-time curve demonstrated the buffering effect of the water medium. As the water coupling coefficient increases, the buffering effect of the water medium becomes increasingly prominent.
4D time lapse tomography for monitoring cave propagation and stress distribution in Deep Mill Level Zone (DMLZ) PT Freeport Indonesia
Authors: Hidayat Wahyu , Sahara David P. , Widiyantoro Sri , Suharsono Suharsono , Riyanto Erwin , Nukman Mochamad , Wattimena Ridho Kresna , Melati Sari , Sitorus Eric , Nainggolan Turgod , Putra I. Putu Raditya Ambara 
Published: February 2024

AbstractCaving activity results in an increased induced seismicity which should be monitored to avoid massive and uncontrolled rock damage. This research was conducted at the Deep Mill Level Zone (DMLZ) underground mine, the deepest underground mine in Indonesia operated by PT Freeport Indonesia. This research aims to monitor cave propagation by using 4D tomography with a catalogue of microseismic for 57 days with a total of 14,821 events recorded by 84 stations consisting of 176,265 P phases and 133,472 S phases. The data is divided into four subsets to see the velocity evolution related to cave progress. Checkerboard Resolution Test (CRT) and Derivative Weight Sum (DWS) are used to assess the resolution of the inversion. 3D initial velocity model is constructed based on geological information and coring data. We have succeeded in identifying the interpreted cave propagation of a 60 m extension to the NW at around 100 m above undercut level based on 4D changes in velocity tomogram validate by Time Domain Reflectometry data. The decrease of Vp and Vs in subset 3 is interpreted due to the fracturing processes as the cave progresses. Furthermore, we observe a stress redistribution along with the progress of the cave, which is characterized by high velocities (Vp and Vs) due to compensation for changes in low velocity values ​​in the area in front of the cave, which is starting to collapse. We suggest that a considerable change in the velocity tomogram as an indicator of impending caving.
Exploring the welfare effects of RCEP—a quantitative analysis based on a structural model
Authors: Lin Faqin , Lv Yutong , Yang Haoming , Li Youqiang 
Published: February 2024

AbstractBased on Caliendo and Parro’s general equilibrium model, this study used the Regional Comprehensive Economic Partnership (RCEP) tariff reduction schedule to quantify the trade and welfare effects of the RCEP on its members at different points in time and calculated the welfare for the counterfactuals of India’s accession to the RCEP and tariff reductions in other parts of the world. Quantitative simulations showed that the RCEP brought welfare to most members, with South Korea receiving the greatest welfare, followed by Australia, Japan, New Zealand and the Association of Southeast Asian Nations as a whole, while China had the smallest improvement in trade and welfare effects. The RCEP mainly originated from the increase in the scale of trade, the terms of which tended to deteriorate. There were no significant welfare improvements for Singapore as a free trade port. Computers, electronic and optical products, and electrical equipment contributed most to the increase in the scale effect of China’s trade. In addition, this study found that the greater the tariff reductions among members, the stronger the welfare improvement effect, and that the welfare generated by the reduction of RCEP tariffs has an inverted “U” correlation with GDP. That is, when a country’s GDP falls below a certain threshold, there is a positive correlation between GDP and welfare. Beyond this threshold, there is a negative correlation between the two, which is consistent with trade theory, which states that large and small countries receive unequal benefits from opening up to trade.
Weakly supervised target detection based on spatial attention
Authors: Zhao Wenqing , Xu Lijiao 
Published: February 2024

AbstractDue to the lack of annotations in target bounding boxes, most methods for weakly supervised target detection transform the problem of object detection into a classification problem of candidate regions, making it easy for weakly supervised target detectors to locate significant and highly discriminative local areas of objects. We propose a weak monitoring method that combines attention and erasure mechanisms. The supervised target detection method uses attention maps to search for areas with higher discrimination within candidate regions, and then uses an erasure mechanism to erase the region, forcing the model to enhance its learning of features in areas with weaker discrimination. To improve the positioning ability of the detector, we cascade the weakly supervised target detection network and the fully supervised target detection network, and jointly train the weakly supervised target detection network and the fully supervised target detection network through multi-task learning. Based on the validation trials, the category mean average precision (mAP) and the correct localization (CorLoc) on the two datasets, i.e., VOC2007 and VOC2012, are 55.2% and 53.8%, respectively. In regard to the mAP and CorLoc, this approach significantly outperforms previous approaches, which creates opportunities for additional investigations into weakly supervised target identification algorithms.